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S&P 500ES1!
Nasdaq 100NQ1!
Bitcoin IndexXBT
U.S. Dollar IndexDX1!
Dow 30YM1!
Russell 2000RTY1!
AppleAAPL
Advanced Micro Devices IncAMD
Amazon Com IncAMZN
Tesla, IncTSLA
Netflix, IncNFLX
Meta Platforms, IncMETA
Crypto Market CapTOTAL
BitcoinBTCUSD
EthereumETHUSD
SOL/USDSOLUSD
UniswapUNIUSD
Luna / U.S. DollarLUNAUSD
EUR/USDEURUSD
GBP/USDGBPUSD
USD/JPYUSDJPY
AUD/USDAUDUSD
USD/CADUSDCAD
USD/CHFUSDCHF
GoldGC1!
SilverSI1!
Crude OilCL1!
Natural GasNG1!
CornZC1!
BitcoinBTC1!
US 10YUS10Y
Euro 10YEU10Y
Germany 10YDE10Y
Japan 10Y YieldJP10Y
UK 10YGB10Y
India 10YIN10Y

Editors' picks

DJIA daily are we ready for a major move?DJIA daily is still in its symmetrical triangle and just can't move up or down from it. 8, 20, and 50 days MA are coiling on the same levels and will produce a major move in the one direction. Breakout or down should be strong and fast. It is very close to the end of the triangle but it seems it is more bearish than bullish. Just the fact it can't move away from the lower line is bearish. Price is above r20, 50, and Big Red which is bullish, but if it drops, it will be right away below 20 and 50 days MA which will be bearish and fast. Yesterday's volume confirms huge indecision in the market which can be both bearish and bullish. RSI and MACD are for now neutral. Overall: DJIA is probably the only indices that didn't receive a buy or sell signal in our Daily morning brief and will stay like that until it chooses which side will go. Break from the triangle will very likely be very powerful and strong. With the move up even testing of ATH would be possible, but with a move below trend lines support at Big Red will for sure be tested and then likely lows from 2022. Overall same like SPY, Powell's speech could move the market.
Editors' picks
4
AI: Google challenges Microsoft and launches BardInvestment confirms how the Silicon Valley giants are ready to do battle over what is believed to be the new frontier of technology. Google (NASDAQ:{{6369|GOOGL}}) is challenging Microsoft (NASDAQ:{{252|MSFT}}) and launching Bard, the rival to ChatGPT, the OpenAI application on which the Redmond giant has bet billions of dollars. The introduction of Bard, the name seems to evoke William Shakespeare, the Bard par excellence of Anglo-Saxon culture, confirms how the race for artificial intelligence is accelerating, with Silicon Valley giants poised to do battle over what is believed to be the new frontier of technology. In recent days Mountain View had announced a $300 million investment in the start-up Anthropic, an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems. And now it is pushing further ahead with the introduction of Bard, which will initially be available for testing to trusted testers and then later be introduced to the general public, similar to how OpenAI did with ChatGPT. "Secure, quality responses" - The testers have been selected, they are a geographically diverse group that will help Google improve and understand users' use of artificial intelligence. "We will combine external feedback with our internal testing to make sure that Bard's responses are quality, secure, and grounded in the real world," explained Mountain View CEO Sundar Pichai, stressing that the testing phase will help Google "continue to learn and improve Bard's quality and speed." Bard aims to generate detailed answers to simple questions. Its operation is based on LaMDA, the Language Model for Dialogue Applications that made headlines last year for being called "sentient" by one of Google's engineers. ChatGPT's success - Microsoft has invested billions of dollars in OpenAI, the company behind the popular ChatGPT and believed to be one of the world's top three labs for artificial intelligence. OpenAI has recently become a household name for millions of people thanks to the success of ChatGPT, which, since its introduction in November, has seen a boom in users and opened a heated debate about the potential and application of artificial intelligence, forcing schools and universities, among others, to begin rethinking their teaching models. ChatGPT is indeed able to create text like a human being, using clear, defined prose and appropriate punctuation. For Microsoft therefore a huge chance to gain ground in the face of fierce rivals who, however, do not want to fall behind. As demonstrated by Google's Bard and Mark Zuckerberg's commitment to make meta one of the leaders in artificial intelligence.
Editors' picks
1
Big Four Macro Overview: EquitiesSPX Monthly Log Scale: -Despite last years 28% decline, the defining uptrends remain intact. In my view, the A1-B1 trendline best defines the bull market but decent arguments can also be made for C-D. A test of C-D would require that the market decline roughly 30% from the most recent close. - In the absence of overtly bearish behaviors and with the primary trendlines intact, I would be hard pressed to conclude that the macro trend has changed. The secular bull remains intact and it should be given the benefit of the doubt. -That said, my fundamental world view continues to suggest that equity remains vulnerable. I believe that the primary trend is in a transition between bull and bear (or at least bull to neutral). - While still willing to take bullish trades, I will monitor closely for opportunities to sell solid technical setups into weekly perspective strength. -Generally speaking, this position in the trend continues to be characterized by poor valuations and overly developed bullish sentiment. That was certainly true going into last year, but has been somewhat addressed (depending upon the sector). Despite last years decline, I see valuations and sentiment as more consistent with a market building a top as opposed to one basing for a fresh bull run. Triple Screen (MACD Momentum): Suggests that the current weekly perspective rally is corrective to last years monthly decline. The daily (far right) is setting up a significant divergence, suggesting that the current daily perspective uptrend is quickly aging. NYSE Composite Monthly (Log): -Despite last years decline, the technical trend remains intact. -Last years high to low decline covered 25%. Post "Greenspan Put" declines have covered -42%, -60% and -40% respectively. The 25% drawdown seems incomplete to me. Particularly against an environment in which the Fed is deemphasizing asset prices and concentrating on keeping inflaiton inbounds. Fundamentally: 1) Both policy vectors (Fiscal and Monetary) are negative and are unlikely to provide support. This may change if rising rates break the weakest financial link and forces the Fed to pivot to address a systemic issue or the building reccession threatens to become a hard landing. 2) Of the 19 bear markets since 1929, 15 have been accompanied by rising inflation. Rising inflation is by far the most consistent/reliable of the bear market factors. 3) I believe that the period of very low inflation created by globalization, good demographics, and several other factors has reversed. With higher underlying inflation rates, central banks won't have the luxury of combating weak asset prices with unlimited liquidity. And finally, many of the topics and techniques discussed in this post are part of the CMT Associations Chartered Market Technician’s curriculum. Good Trading: Stewart Taylor, CMT Chartered Market Technician Shared content and posted charts are intended to be used for informational and educational purposes only. The CMT Association does not offer, and this information shall not be understood or construed as, financial advice or investment recommendations. The information provided is not a substitute for advice from an investment professional. The CMT Association does not accept liability for any financial loss or damage our audience may incur.
Editors' picks
15
Bitcoin: Sell Setup Retrace 20K?Are you still waiting for 50K? While this kind of forecast is completely unrealistic and out of range, it is ESPECIALLY so in light of the new SELL SIGNAL that has appeared off of the 24K resistance following Friday's NFP outcome. As I wrote in my previous analysis, when 5 waves can be clearly counted, the move has likely run out of steam. While this is still a risky short, being long anywhere from 23 to 24K poses very high risk as well. This is a perfect example of when to avoid swing trades and mitigate risk by working with smaller time frames. The next swing trade idea that I am WAITING for is the retrace into the next relevant support AREA between 22K and 20K (see rectangle on chart). If this support manages to hold, it can offer an opportunity to capitalize on a retest of the 24K, and possibly a push into the 25K resistance. This type of move can take weeks to unfold, and is relevant only to the recent bullish momentum generated off the 17K area low. I mention this specifically because when observed from the weekly time frame, the broader trend is still arguably bearish. The recent move in Bitcoin may be nothing more than an over reaction (short squeeze) following the move in the Nasdaq and weakness in the Dollar. As long as 25K is not compromised, jumping to the conclusion of a new bullish trend is premature. This is NOT about profit, it is about accounting for RISK. It is important to understand that charts provide a very limited view of potential outcomes because of the assumption that current factors driving the market stay the same. Things CHANGE very quickly and a chart cannot account for unexpected news events in the future. This is why long term opinions are about as valuable as a pet rock. Many are extremely desperate for you to believe that they know something, when in fact that are only betting on the random nature of the market to make them look right. Okay you get it, but what about all this short term movement? You hate to wait, and want action. That is what smaller time frame strategies are all about. For Bitcoin that can mean working with 4 hour, 30 minute and even 5 minute time frames. When working on such time frames, your risk/reward expectations must also stay in proportion to the time frame. If you mix expectations here, you will simply lose, a LOT. For example, 5 minute expectations average around 80 to 100 points of risk, while 150 to 200 points of profit are within reason. IF you expect MORE, you will get stopped out often. Smaller time frames are where the random nature of the market is most prevalent. An open mind and strong decisiveness are major requirements (A LOT of experience also helps). Begin with 30 minute price structures, formulate expectations, identify your levels and wait for setups. I have streamed many examples of this. Keep in mind you ALWAYS have the option to WAIT for a higher probability opportunity. This is why I always emphasize learning to judge for yourself rather than listening to those who are incapable of controlling their emotions, or push some other hidden agenda. Learn to listen to PRICE not PEOPLE. A chart offers limited information but it pays to know which information on a chart carries the MOST actionable value, Thank you for considering my analysis and perspective. I hope you find it helpful.
Editors' picks
43
Nasdaq: Short-term bull Long-term rangeWhy market is entering into short-term bullishness again and latter uncertainty or range? We will do both technical and fundamental analysis in this video tutorial, and we will see how both analyses can affirm each other. Refer to the related video link, I explained at greater length. Or you can always visit my YouTube channel. Content: . Why market is entering into a short-term bullishness? (Fundamental & Technical studies) . Subsequently the market will enter into a range (Fundamental & Technical studies) CME Micro Nasdaq Futures Minimum fluctuation 0.25 = $0.50 1 = $2 10 = $20 100 = $200 1000 = $2,000 Disclaimer: • What presented here is not a recommendation, please consult your licensed broker. • Our mission is to create lateral thinking skills for every investor and trader, knowing when to take a calculated risk with market uncertainty and a bolder risk when opportunity arises. CME Real-time Market Data help identify trading set-ups in real-time and express my market views. If you have futures in your trading portfolio, you can check out on CME Group data plans available that suit your trading needs www.tradingview.com
Editors' picks
Long
9
The yield curve has to un-invert eventually… right? (Part 2)This week, we thought it will be interesting to review the trade from last week given the reaction post-FOMC, as well as discuss an alternative way to set up this trade. Firstly, let’s review the post-FOMC/employment data reaction. - Nonfarm Payrolls surprised to the upside, as over half a million jobs were added way above the estimates of a sub 200K number. - Unemployment rate continues to fall further, reaching a 53-year low of 3.4% A clear re-pricing has occurred since last Friday’s better-than-expected jobs data and Wednesday’s Federal Reserve meeting. With markets now expecting 1 more rate hike in May, bringing the peak rate up from the 475 -500 bps range to the 500-525 bps range. Keeping this in mind, we go back to our analysis last week to understand this situation and historical precedence. While the time for a pause in rate hike seems to be pushed back, in the grand scheme of things, we think that this has only kept the window of opportunity for this trade open for longer and at a more attractive entry point now. Without repeating ourselves too much, we encourage readers to take a look at our idea last week which explores the historical correlation between the peaking of yield curve inversion and the pause in Fed rate hikes. Link to our last week’s idea: This week, let’s tap into a different instrument. Here, we aim to take a short position on the 2Y-10Y yield differential by creating a portfolio of Treasury futures to express this view. To do so, we would have to first select the 2 instruments, the 2-Yr Treasury futures is a straightforward choice for the short end. But for the 10-Yr leg, we have a choice of the '10-Yr Treasury Note Futures' vs the 'Ultra 10-Yr Treasury Note Futures'. Digging into the contract specification, the 'Ultra 10-Yr Treasury Note Futures' provide a better proxy for the true 10-year duration exposure as the delivery requirements are for Treasuries with maturities between 9year 5 months and 10 years. In comparison, the underlying of '10-Yr Treasury Note Futures' has a maturity between 6 year 6 months and 10 years. With contract selection out of the way, the next step is to calculate the Dollar Neutral spread. This requires us to identify the DV01 of the front and back legs of the spread and try to match them. This is to ensure that the entire position remains as close to dollar neutral as possible, so we can get a 'purer' exposure to the yield difference between the front and back legs, and parallel moves are negated. CME publishes articles on this topic to explain the setting up of a DV01 spread clearer than we can explain. You can find them attached in the reference section below. You can handily find the DV01 of the Cheapest To Deliver (CTD) securities on CME’s website. In this case, we are looking at the 2Yr and Ultra 10Yr Treasury Futures to set up the trade. With the DV01 of the 2Yr at 34.04 and the DV01 of the Ultra 10Yr at 96.26. The spread ratio can be calculated as 96.26/34.04 = 2.83. Rounding this to the nearest whole number, we would need 3 lots of2-Yr Treasury Future and 1 lot of Ultra 10-Yr Treasury Future, to keep the DV01 equal (neutral) for both legs of this portfolio. Given our view of the 2Yr-10Yr yield spread turning lower, we want to short the yield spread. Yield and prices move inversely, hence, to short the yield spread, we long the Treasury Futures spread as it is quoted in price. We can long 3 ZTH3 Futures (2Y Treasury Future) and short 1 TNH3 futures (Ultra 10Y Treasury Future) to complete 1 set of the spread. However, since the 2-Yr Treasury Futures has a notional value of 200,000 while the Ultra 10Y Treasury Futures a notional of $100,000, the price ratio will be 6:1 when the position/leg ratio in the spread trade is 3:1. As such the current level would provide us with an entry point of roughly 494 with a minimal move in Ultra 10yrs representing 15.625 USD and that in 2Y representing 7.8125 USD. While slightly more complex in setting up, this trade allows us another alternative to express the same view on the yield curve spread differential. Being able to execute the trade via different instruments allows you to pick the most liquid markets to trade or take advantage of mispricing in the markets. The charts above were generated using CME’s Real-Time data available on TradingView. Inspirante Trading Solutions is subscribed to both TradingView Premium and CME Real-time Market Data which allows us to identify trading set-ups in real-time and express our market opinions. If you have futures in your trading portfolio, you can check out on CME Group data plans available that suit your trading needs www.tradingview.com Disclaimer: The contents in this Idea are intended for information purpose only and do not constitute investment recommendation or advice. Nor are they used to promote any specific products or services. They serve as an integral part of a case study to demonstrate fundamental concepts in risk management under given market scenarios. A full version of the disclaimer is available in our profile description. Reference www.cmegroup.com www.cmegroup.com www.cmegroup.com www.cmegroup.com
Editors' picks
Long
6
Bitcoin's Correlation to Tech Stocks About to Change?The above chart shows the correlation between Bitcoin ( BTC ) and the Nasdaq 100 ETF ( QQQ ). The correlation between these two is the highest ever . See the chart below for a closer look. For the stats nerds out there, here are the current correlation values between BTC and QQQ (as measured by using monthly closing prices with a 20-period look back): r value is 0.936, r-squared is 0.7916, p value is 0. This extreme correlation between Bitcoin and the Nasdaq 100 is unlikely to last much longer. Correlations between assets tend to oscillate over time. Therefore, this extremely positive correlation is likely to oscillate down soon, which will have the effect of weakening the correlation between Bitcoin and Nasdaq 100, or in a more drastic scenario, turn the positive correlation into a negative one. If the correlation between BTC and QQQ does in fact weaken or turn negative, then it must also be true that both assets cannot continue their strong rallies at the same time. So we're left with an important question: Which asset will outperform the other if the perfect positive correlation ends? We can use a ratio chart to extrapolate the answer: the BTC/QQQ ratio chart. So let's look at that chart. In the chart above, we see the price of Bitcoin on the left and Bitcoin's performance relative to QQQ on the right. We can see that even though Bitcoin has been on a bull run, it has already rolled over to the downside relative to the performance of QQQ. When we look at the Stochastic RSI oscillator, as shown in the chart below, we see confirmation that Bitcoin is potentially beginning to oscillate back down relative to its performance to QQQ on the weekly chart. However, look at what happens when we examine the monthly chart. The exact opposite appears to be true. (See the chart below) In the monthly chart of BTC/QQQ, Bitcoin is just beginning a major oscillation up. What we're probably seeing is the monthly candle of BTC/QQQ creating a lower wick, which is why it appears that the weekly BTC/QQQ chart is oscillating down. If we zoom out even further -- to the quarterly (or 3-month) chart -- we see even further confirmation that Bitcoin is set to outperform the Nasdaq 100. (See the chart below) In the chart above we see a perfect log growth curve of Bitcoin relative to the Nasdaq 100, with bullish reversal candlesticks beginning to form on the quarterly timeframe. We also see the Stochastic RSI ready to oscillate back up, meaning Bitcoin is poised to begin a period of outperformance relative to tech stocks on the higher timeframes. Other charts lead us to a similar conclusion. In the yearly chart of QQQ/SPY, shown below, we see that the Nasdaq 100 is set to underperform the S&P 500 for the long term. This suggests that the current rally in the Nasdaq 100 stocks is potentially a bull trap or a lower timeframe counter-trend. As the Nasdaq 100 is set to begin to underperform the S&P 500, the S&P 500 itself is showing downward momentum on its yearly chart. If this downward momentum sustains to the close of 2023, it will mark an incredibly rare, and also quite bearish, signal for both indices. These, and other, higher timeframe charts are explained in more depth in my post below about the coming period of stagflation. In summary, virtually all of the higher timeframe charts indicate that the period of limitless monetary easing is over, and we've entered into a new supercycle wherein the price of money will remain some degree higher. So it seems that Bitcoin continues to win. As the stock market indices break out and create what time will likely prove to be another bull trap, Bitcoin is likely on a path toward more sustained bullishness than equities. In the face of stagflation, equities suffer from both a declining money supply (as the central banks fight inflation) and declining productivity. Although Bitcoin is not immune to similar declines, its perpetual scarcity may provide a unique tailwind during the coming period of stagflation.
Editors' picks
45
Fight or Flight?On February 1st, the Federal Reserve (Fed) announced a widely-expected 25bps rate hike. This was the rallying cry for the current market rally to continue. Is this confidence warranted? An interesting note is that the FOMC meeting minutes and the associated press conference appeared contradictory in nature because there was not a straightforward hawkish or dovish narrative across both. The statement was hawkish. Meanwhile, Fed Chairman Powell’s language in the press conference was remarkably dovish, describing the disinflation process as having started and as "encouraging and gratifying". This was the point that markets took as the signal to continue the recent rally. Precious metals, equities, and risk assets have all seen significant post-meeting relief. The first innings of a recession always appear to be somewhat of a soft landing in which inflation and growth begin to slow gradually. Yesterday’s meeting echoed the idea that recent indicators point to a modest increase in spending and that inflation has eased, precisely what the first innings of a recession would predict. As markets, potentially shortsightedly, adopt the soft landing narrative, the Fed’s lack of pushback against easier financial conditions added fuel to the fire. Given this, it is doubtful that markets will stop rallying until one of two cases occurs: First, if data comes in hot, it potentially frightens markets into thinking the Fed will turn back hawkish and raise rates more than the recently observed 25bps hike. The second scenario is the other extreme. Should data start coming in highly recessionary with lower inflation and weak growth, this will eliminate all believers in the soft landing narrative, thus halting the rally. However, at present, it looks like the market rally of 2023 could continue until either of these scenarios happen. An important thing to note is that whenever inflation has exceeded 5% in the past, it has never come back down without the Federal Funds Rate exceeding the rate of CPI inflation. Considering the Federal Funds Rate is currently between 4.5% and 4.75% whilst CPI inflation is at 6.5%, more rate hikes are on the horizon unless data comes in highly recessionary. CPI data on the 14th of February will provide significant insight into whether or not the Fed will follow the likes of the European Central Bank & Bank of England and go with a 50bps hike rather than a 25bps hike. Another important thing to note is that Apple , Amazon , and Alphabet (the parent company of Google ) all missed earnings last night. If three of the world's largest companies missed earnings, it does not breed confidence for economic hopes of avoiding a recession. One thing seems certain, the S&P500 is likely to take a hit when the NYSE opens later today.
Editors' picks
21
Earnings recession is becoming more apparentFollowing the FOMC’s rate hike, markets continued to rally yesterday until the closing bell when tech giants Alphabet, Amazon, and Apple reported their earnings. Bleak numbers poured cold water on a rally, and in after-market trading, Nasdaq 100 index fell more than 2.5%. However, this move quickly recovered, highlighting the market's growing fragility. With VIX near yearly lows and now evident earnings recession, we will seek a decline in volume accompanying the rising price to suggest a rally’s exhaustion. During the summer of 2022, we noted that declining corporate earnings and outlook downgrades in 3Q22 and 4Q22 would confirm our bearish thesis about the market progressing deeper into recession. With this being reflected in the data, we will pay very close attention to labor market data, which lags behind other indicators. To further confirm our bearish thesis, we want to see a pick-up in unemployment and small business bankruptcies, which will put the current mainstream narrative about “soft-landing” to the test (together with the FED not cutting rates). Alphabet - full-year 2022 results. Net income = $59.97 billion (vs. net income of $76.03 billion in 2021; -21.1% YoY) Operating income = $74.84 billion (vs. $78.71 billion in 2021; -4.9% YoY) Revenue = $282.83 billion (vs. $257.63 billion in 2021; +9.8% YoY) Alphabet disclosed that it expects to incur (in 1Q23) employee severance and related charges of $1.9 billion to $2.3 billion in relation to its layoffs of 12 000 people announced in January 2023. Additionally, it anticipates exit costs in regard to office space reductions of approximately $0.5 billion during that same quarter. Furthermore, the company expects a significant reduction in the depreciation of its equipment and servers throughout the entire year 2023. Amazon - full-year 2022 results. Net loss = $-2.7 billion (vs. net income of $33.4 billion in 2021; -108% YoY) Operating income = $12.2 billion (vs. $24.9 billion in 2021; -51% YoY) Net sales = $514 billion (vs. $469.8 billion in 2021; +9.4% YoY) Amazon saw a massive drop in net income (YoY) in 2022, from $33.4 billion to a net loss of $2.7 billion. The company expects its net sales to drop by more than 15% in 1Q23 (vs. the previous quarter) and suffer unfavorable impacts from exchange rates. Apple - 1st quarter FY2023 Net income = $29.98 billion (vs. $34.63 billion a year ago; -13.4%) Net sales = $117.2 billion (vs. $123.9 billion a year ago; -5.4% YoY) Operating income = $36.01 billion (vs. $41.48 billion a year ago; -13.2% YoY) Illustration 1.01 Illustration 1.01 shows the daily chart of NQ1!. At the moment, the price deviated too far from its 20-day and 50-day SMAs, making a case for the retracement. A breakout below Support 1 will bolster the bearish odds in the short term. Contrarily, a breakout above Resistance 1 will be bullish. Technical analysis Daily time frame = Bullish Weekly time frame = Bullish Illustration 1.02 Illustration 1.02 displays the daily chart of QQQ. The yellow arrow hints at bullish volume growth. A decline in volume accompanying the rising price will hint at declining momentum and potential trend reversal. Please feel free to express your ideas and thoughts in the comment section. DISCLAIMER: This analysis is not intended to encourage any buying or selling of any particular securities. Furthermore, it should not be a basis for taking any trade action by an individual investor. Therefore, your own due diligence is highly advised before entering a trade.
Editors' picks
47
Please curb your enthusiasm in Bitcoin.At the moment there are a lot of internet "gurus" spouting nonsense. The guy in the picture is just one example. Over 500,000 subscribers being told that BITSTAMP:BTCUSD will be $50,000 in the next 3-4 months and to buy it up here after this rally. They are all telling you EXACTLY WHAT YOU WANT TO HEAR. When the price was $18,000 they were saying it was all over for Bitcoin. They are basically marketers not traders. They market for Buybit or Bitget or whoever. They make a lot of money when someone like you puts money into an exchange account. Now, turning to logic: Look at the chart, especially at the volume, which tells us a story, which I have marked. There is also the psychological story. Lots of you are nursing nasty red bags from the last consolidation around $30,000. You would love it to get there so you can get out. PSA: That's why it won't get there this time. Maybe next time, possibly after you have given up and sold your position after the next drop. All the price has done is pierce a succession of stop-loss levels to ping out the shorts who sold lower down, believing the negative press and the chat from exactly the same people who are now saying it is going up. I reckon one more pop up to the next level just north of $25,000, then a slow melting away, with you buying every dip. Patience is a virtue. It's hard to be patient I know. Hang on, this is a MONTHLY structure and this is still the beginning of the accumulation, not the end. We will tell you when we think it is the end.
Editors' picks
Long
100

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February 07February 07

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Has the time come for us to do away with search results pages and embrace the cutting edge technology of intelligent language models? Maybe. But the only thing known for certain is that all big tech companies are going to want a slice of the pie. And after Microsoft's major investment into ChatGPT, Google wasn't just going to sit around and watch its title as the king of search engines be threatened.

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Bitcoin - Prediction of the future! +20% this month. This is what I expect from BTC in the next few days / weeks. I think everyone is still very bearish, so it's time for a massive, mind-blowing pump! On the chart, you can see my prediction of the price action and how it could possibly look. Bitcoin is still pretty much consolidating in this parallel channel, and that's why we should see an explosive move very soon. If you want, you can wait for confirmation, which is a bull break of the local flag pattern. The aggressive entry was below the FOMC candle, which is where the majority of traders' stop losses are. Bitcoin is currently sitting in a very strong support zone, and it's hard to see a breakdown at this point. I don't want to short the support. Usually I want to long the support. This analysis is not a trade setup; there is no stop-loss, entry point, profit target, expected duration of the trade, risk-to-reward ratio, or timing. I post trade setups privately. The trendline from December can be your next profit target. You cannot see the start of the trendline, but it started on December 14. Sometimes it's better to take a look at ETH, because we can see a clearer chart. The price action on ETH is much more enjoyable, and to be honest, I see a big pump soon! Thank you, and for more ideas, hit "Like" and "Follow"!
Long
70
NZSDUSD H4: BULLS H*S pattern BUY LOW TP +250 pips (SL/TP)Why get subbed to me on Tradingview? -TOP author on TradingView -2500+ ideas published -15+ years experience in markets -Professional chart break downs -Supply/Demand Zones -TD9 counts / combo review -Key S/R levels -No junk on my charts -Frequent updates -Covering FX/crypto/US stocks -before/after analysis -24/7 uptime so constant updates 🎁Please hit the like button and 🎁Leave a comment to support our team! NZDUSD H4: BULLS H*S pattern BUY LOW TP +250 pips (SL/TP) IMPORTANT NOTE: speculative setup. do your own due dill. use STOP LOSS. don't overleverage. Tagged as LONG because I expect more gains after neckline reversal at 6220 🔸 Summary and potential trade setup ::: NZDUSD 4hour chart review outlook ::: H*S speculative setup ::: expecting NZD to outperform ::: after neckline re-test near 6220 ::: will boost NZD after pullback ::: expecting reversal after neckline bounce ::: after we complete throwback/pullback ::: 6220 BEARS targeting neckline of structure ::: BULLS stay out and buy low instead ::: recommended strategy: BUY LOW near 6220 ::: SL 50 pips TP1 +150 pips TP2 +250 pips ::: 6460/80 strong resistance overhead ::: BULLS will target re-test of LEFT/RIGHT structure ::: BULLS should BUY/HOLD 6220 exit +250 pips ::: BEARS wait until we max out near 6460-80 ::: and get ready to SHORT from S/R ::: SWING trade setup do not expect ::: fast/miracle overnights gains here ::: good luck traders 🔸 Supply/Demand Zones ::: N/A ::: 5680 fresh supply zone 🔸 Other noteworthy technicals/fundies ::: TD9 /Combo update: N/A ::: Sentiment short-term: BEARS/PULLBACK ::: Sentiment outlook mid-term: STRONG BULLS ::: Global Sentiment: neckline bounce / will boost NZD RISK DISCLAIMER: Trading Futures , Forex, CFDs and Stocks involves a risk of loss. Please consider carefully if such trading is appropriate for you. Past performance is not indicative of future results. Always limit your leverage and use tight stop loss.
Long
35
Lingrid | GOLD short term CORRECTIONThe gold market is developing a range zone at strong support level. Previouse resistance zone became a support which is a swing level. The market formed a double bottom I think its good area to go long for short term. Price action is ranging after impulse move down and it might go up from support and global trendline on the 4H timeframe. My short term target is resistance at 1890.000. My long term target: Traders, if you liked this idea or if you have your own opinion about it, write in the comments. I will be glad 👩‍💻
Long
19
Bitcoin: Sell Setup Retrace 20K?Are you still waiting for 50K? While this kind of forecast is completely unrealistic and out of range, it is ESPECIALLY so in light of the new SELL SIGNAL that has appeared off of the 24K resistance following Friday's NFP outcome. As I wrote in my previous analysis, when 5 waves can be clearly counted, the move has likely run out of steam. While this is still a risky short, being long anywhere from 23 to 24K poses very high risk as well. This is a perfect example of when to avoid swing trades and mitigate risk by working with smaller time frames. The next swing trade idea that I am WAITING for is the retrace into the next relevant support AREA between 22K and 20K (see rectangle on chart). If this support manages to hold, it can offer an opportunity to capitalize on a retest of the 24K, and possibly a push into the 25K resistance. This type of move can take weeks to unfold, and is relevant only to the recent bullish momentum generated off the 17K area low. I mention this specifically because when observed from the weekly time frame, the broader trend is still arguably bearish. The recent move in Bitcoin may be nothing more than an over reaction (short squeeze) following the move in the Nasdaq and weakness in the Dollar. As long as 25K is not compromised, jumping to the conclusion of a new bullish trend is premature. This is NOT about profit, it is about accounting for RISK. It is important to understand that charts provide a very limited view of potential outcomes because of the assumption that current factors driving the market stay the same. Things CHANGE very quickly and a chart cannot account for unexpected news events in the future. This is why long term opinions are about as valuable as a pet rock. Many are extremely desperate for you to believe that they know something, when in fact that are only betting on the random nature of the market to make them look right. Okay you get it, but what about all this short term movement? You hate to wait, and want action. That is what smaller time frame strategies are all about. For Bitcoin that can mean working with 4 hour, 30 minute and even 5 minute time frames. When working on such time frames, your risk/reward expectations must also stay in proportion to the time frame. If you mix expectations here, you will simply lose, a LOT. For example, 5 minute expectations average around 80 to 100 points of risk, while 150 to 200 points of profit are within reason. IF you expect MORE, you will get stopped out often. Smaller time frames are where the random nature of the market is most prevalent. An open mind and strong decisiveness are major requirements (A LOT of experience also helps). Begin with 30 minute price structures, formulate expectations, identify your levels and wait for setups. I have streamed many examples of this. Keep in mind you ALWAYS have the option to WAIT for a higher probability opportunity. This is why I always emphasize learning to judge for yourself rather than listening to those who are incapable of controlling their emotions, or push some other hidden agenda. Learn to listen to PRICE not PEOPLE. A chart offers limited information but it pays to know which information on a chart carries the MOST actionable value, Thank you for considering my analysis and perspective. I hope you find it helpful.
Editors' picks
43
BITCOIN Perfect structural repeat of the 2019 rally?On the previous analysis we talked about Bitcoin's (BTCUSD) emerging Golden Cross on the 1D time-frame and how it is clashing with the emerging Death Cross on the 1W time-frame. Well the 1D Golden Cross has been formed today and automatically draws our attention to the 1D Golden Cross of April 23 2019. This was formed just after the early 2019 rally begun. So the question that pops out is this: 'Is BTC repeating this rally?'. So far we can surely say that the structure since the November 21 2022 bottom resembles almost perfectly that from January 29 2019 to April 23 2019 and that 1D Golden Cross. As you see on the chart, both sequences started with a Channel Up on the 1D MA50 (blue trend-line), then consolidation before a hyper aggressive wave that broke above the 1D MA200 (orange trend-line) that later formed the Bullish Megaphone pattern that led us to the Golden Cross of today. RSI wise we are on the very same Bull Flag along the price's Megaphone. Following the Golden Cross, the 2019 structure rose another +150% from the day of the Cross to the June 26 2019 High. Obviously that rally isn't easy at all to be recreated as it was additionally fueled by the Libra fundamentals and a +150% rise from today's lows would put the peak of the rally at $57000. Unrealistic or not, it is yours to judge, so feel free to let us know of your opinion in the comments section below! Are we repeating the 2019 rally? ------------------------------------------------------------------------------- ** Please LIKE 👍, FOLLOW ✅, SHARE 🙌 and COMMENT ✍ if you enjoy this idea! Also share your ideas and charts in the comments section below! This is best way to keep it relevant, support us, keep the content here free and allow the idea to reach as many people as possible. ** ------------------------------------------------------------------------------- 💸💸💸💸💸💸 👇 👇 👇 👇 👇 👇
Long
15
Big Four Macro Overview: EquitiesSPX Monthly Log Scale: -Despite last years 28% decline, the defining uptrends remain intact. In my view, the A1-B1 trendline best defines the bull market but decent arguments can also be made for C-D. A test of C-D would require that the market decline roughly 30% from the most recent close. - In the absence of overtly bearish behaviors and with the primary trendlines intact, I would be hard pressed to conclude that the macro trend has changed. The secular bull remains intact and it should be given the benefit of the doubt. -That said, my fundamental world view continues to suggest that equity remains vulnerable. I believe that the primary trend is in a transition between bull and bear (or at least bull to neutral). - While still willing to take bullish trades, I will monitor closely for opportunities to sell solid technical setups into weekly perspective strength. -Generally speaking, this position in the trend continues to be characterized by poor valuations and overly developed bullish sentiment. That was certainly true going into last year, but has been somewhat addressed (depending upon the sector). Despite last years decline, I see valuations and sentiment as more consistent with a market building a top as opposed to one basing for a fresh bull run. Triple Screen (MACD Momentum): Suggests that the current weekly perspective rally is corrective to last years monthly decline. The daily (far right) is setting up a significant divergence, suggesting that the current daily perspective uptrend is quickly aging. NYSE Composite Monthly (Log): -Despite last years decline, the technical trend remains intact. -Last years high to low decline covered 25%. Post "Greenspan Put" declines have covered -42%, -60% and -40% respectively. The 25% drawdown seems incomplete to me. Particularly against an environment in which the Fed is deemphasizing asset prices and concentrating on keeping inflaiton inbounds. Fundamentally: 1) Both policy vectors (Fiscal and Monetary) are negative and are unlikely to provide support. This may change if rising rates break the weakest financial link and forces the Fed to pivot to address a systemic issue or the building reccession threatens to become a hard landing. 2) Of the 19 bear markets since 1929, 15 have been accompanied by rising inflation. Rising inflation is by far the most consistent/reliable of the bear market factors. 3) I believe that the period of very low inflation created by globalization, good demographics, and several other factors has reversed. With higher underlying inflation rates, central banks won't have the luxury of combating weak asset prices with unlimited liquidity. And finally, many of the topics and techniques discussed in this post are part of the CMT Associations Chartered Market Technician’s curriculum. Good Trading: Stewart Taylor, CMT Chartered Market Technician Shared content and posted charts are intended to be used for informational and educational purposes only. The CMT Association does not offer, and this information shall not be understood or construed as, financial advice or investment recommendations. The information provided is not a substitute for advice from an investment professional. The CMT Association does not accept liability for any financial loss or damage our audience may incur.
Editors' picks
15
BTCUSDT - ULTIMATE Support MUST HOLDHi Traders, Investors and Speculators of the Charts 📈📉 Bitcoin is about to retest an important support zone at $21800 . If BTC is unable to secure this support, the next support is only at $18400. A possibility exists to take a low leveraged long from the support, however this will be a high risk trade due to the nature of the cycle - it's unclear whether or not this is the first stages of a new bullrun or whether it's a bulltrap. I'd be more confident to claim the start of a new bull cycle IF we can maintain the current trading range and NOT CLOSE a candle UNDER this support zone. Can I interest you in an Altcoin? Check out this idea on BATUSDT: _______________________ 📢Follow us here on TradingView for daily updates and trade ideas on crypto , stocks and commodities 💎Hit like & Follow 👍 We thank you for your support ! CryptoCheck
Long
22

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Pine scripts

Machine Learning: Lorentzian Classification█ OVERVIEW A Lorentzian Distance Classifier (LDC) is a Machine Learning classification algorithm capable of categorizing historical data from a multi-dimensional feature space. This indicator demonstrates how Lorentzian Classification can also be used to predict the direction of future price movements when used as the distance metric for a novel implementation of an Approximate Nearest Neighbors (ANN) algorithm. █ BACKGROUND In physics, Lorentzian space is perhaps best known for its role in describing the curvature of space-time in Einstein's theory of General Relativity (2). Interestingly, however, this abstract concept from theoretical physics also has tangible real-world applications in trading. Recently, it was hypothesized that Lorentzian space was also well-suited for analyzing time-series data (4), (5). This hypothesis has been supported by several empirical studies that demonstrate that Lorentzian distance is more robust to outliers and noise than the more commonly used Euclidean distance (1), (3), (6). Furthermore, Lorentzian distance was also shown to outperform dozens of other highly regarded distance metrics, including Manhattan distance, Bhattacharyya similarity, and Cosine similarity (1), (3). Outside of Dynamic Time Warping based approaches, which are unfortunately too computationally intensive for PineScript at this time, the Lorentzian Distance metric consistently scores the highest mean accuracy over a wide variety of time series data sets (1). Euclidean distance is commonly used as the default distance metric for NN-based search algorithms, but it may not always be the best choice when dealing with financial market data. This is because financial market data can be significantly impacted by proximity to major world events such as FOMC Meetings and Black Swan events. This event-based distortion of market data can be framed as similar to the gravitational warping caused by a massive object on the space-time continuum. For financial markets, the analogous continuum that experiences warping can be referred to as "price-time". Below is a side-by-side comparison of how neighborhoods of similar historical points appear in three-dimensional Euclidean Space and Lorentzian Space: This figure demonstrates how Lorentzian space can better accommodate the warping of price-time since the Lorentzian distance function compresses the Euclidean neighborhood in such a way that the new neighborhood distribution in Lorentzian space tends to cluster around each of the major feature axes in addition to the origin itself. This means that, even though some nearest neighbors will be the same regardless of the distance metric used, Lorentzian space will also allow for the consideration of historical points that would otherwise never be considered with a Euclidean distance metric. Intuitively, the advantage inherent in the Lorentzian distance metric makes sense. For example, it is logical that the price action that occurs in the hours after Chairman Powell finishes delivering a speech would resemble at least some of the previous times when he finished delivering a speech. This may be true regardless of other factors, such as whether or not the market was overbought or oversold at the time or if the macro conditions were more bullish or bearish overall. These historical reference points are extremely valuable for predictive models, yet the Euclidean distance metric would miss these neighbors entirely, often in favor of irrelevant data points from the day before the event. By using Lorentzian distance as a metric, the ML model is instead able to consider the warping of price-time caused by the event and, ultimately, transcend the temporal bias imposed on it by the time series. For more information on the implementation details of the Approximate Nearest Neighbors (ANN) algorithm used in this indicator, please refer to the detailed comments in the source code. █ HOW TO USE Below is an explanatory breakdown of the different parts of this indicator as it appears in the interface: Below is an explanation of the different settings for this indicator: General Settings: Source - This has a default value of "hlc3" and is used to control the input data source. Neighbors Count - This has a default value of 8, a minimum value of 1, a maximum value of 100, and a step of 1. It is used to control the number of neighbors to consider. Max Bars Back - This has a default value of 2000. Feature Count - This has a default value of 5, a minimum value of 2, and a maximum value of 5. It controls the number of features to use for ML predictions. Color Compression - This has a default value of 1, a minimum value of 1, and a maximum value of 10. It is used to control the compression factor for adjusting the intensity of the color scale. Show Exits - This has a default value of false. It controls whether to show the exit threshold on the chart. Use Dynamic Exits - This has a default value of false. It is used to control whether to attempt to let profits ride by dynamically adjusting the exit threshold based on kernel regression. Feature Engineering Settings: Note: The Feature Engineering section is for fine-tuning the features used for ML predictions. The default values are optimized for the 4H to 12H timeframes for most charts, but they should also work reasonably well for other timeframes. By default, the model can support features that accept two parameters (Parameter A and Parameter B, respectively). Even though there are only 4 features provided by default, the same feature with different settings counts as two separate features. If the feature only accepts one parameter, then the second parameter will default to EMA-based smoothing with a default value of 1. These features represent the most effective combination I have encountered in my testing, but additional features may be added as additional options in the future. Feature 1 - This has a default value of "RSI" and options are: "RSI", "WT", "CCI", "ADX". Feature 2 - This has a default value of "WT" and options are: "RSI", "WT", "CCI", "ADX". Feature 3 - This has a default value of "CCI" and options are: "RSI", "WT", "CCI", "ADX". Feature 4 - This has a default value of "ADX" and options are: "RSI", "WT", "CCI", "ADX". Feature 5 - This has a default value of "RSI" and options are: "RSI", "WT", "CCI", "ADX". Filters Settings: Use Volatility Filter - This has a default value of true. It is used to control whether to use the volatility filter. Use Regime Filter - This has a default value of true. It is used to control whether to use the trend detection filter. Use ADX Filter - This has a default value of false. It is used to control whether to use the ADX filter. Regime Threshold - This has a default value of -0.1, a minimum value of -10, a maximum value of 10, and a step of 0.1. It is used to control the Regime Detection filter for detecting Trending/Ranging markets. ADX Threshold - This has a default value of 20, a minimum value of 0, a maximum value of 100, and a step of 1. It is used to control the threshold for detecting Trending/Ranging markets. Kernel Regression Settings: Trade with Kernel - This has a default value of true. It is used to control whether to trade with the kernel. Show Kernel Estimate - This has a default value of true. It is used to control whether to show the kernel estimate. Lookback Window - This has a default value of 8 and a minimum value of 3. It is used to control the number of bars used for the estimation. Recommended range: 3-50 Relative Weighting - This has a default value of 8 and a step size of 0.25. It is used to control the relative weighting of time frames. Recommended range: 0.25-25 Start Regression at Bar - This has a default value of 25. It is used to control the bar index on which to start regression. Recommended range: 0-25 Display Settings: Show Bar Colors - This has a default value of true. It is used to control whether to show the bar colors. Show Bar Prediction Values - This has a default value of true. It controls whether to show the ML model's evaluation of each bar as an integer. Use ATR Offset - This has a default value of false. It controls whether to use the ATR offset instead of the bar prediction offset. Bar Prediction Offset - This has a default value of 0 and a minimum value of 0. It is used to control the offset of the bar predictions as a percentage from the bar high or close. Backtesting Settings: Show Backtest Results - This has a default value of true. It is used to control whether to display the win rate of the given configuration. █ WORKS CITED (1) R. Giusti and G. E. A. P. A. Batista, "An Empirical Comparison of Dissimilarity Measures for Time Series Classification," 2013 Brazilian Conference on Intelligent Systems, Oct. 2013, DOI: 10.1109/bracis.2013.22. (2) Y. Kerimbekov, H. Ş. Bilge, and H. H. Uğurlu, "The use of Lorentzian distance metric in classification problems," Pattern Recognition Letters, vol. 84, 170–176, Dec. 2016, DOI: 10.1016/j.patrec.2016.09.006. (3) A. Bagnall, A. Bostrom, J. Large, and J. Lines, "The Great Time Series Classification Bake Off: An Experimental Evaluation of Recently Proposed Algorithms." ResearchGate, Feb. 04, 2016. (4) H. Ş. Bilge, Yerzhan Kerimbekov, and Hasan Hüseyin Uğurlu, "A new classification method by using Lorentzian distance metric," ResearchGate, Sep. 02, 2015. (5) Y. Kerimbekov and H. Şakir Bilge, "Lorentzian Distance Classifier for Multiple Features," Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods, 2017, DOI: 10.5220/0006197004930501. (6) V. Surya Prasath et al., "Effects of Distance Measure Choice on KNN Classifier Performance - A Review." . █ ACKNOWLEDGEMENTS @veryfid - For many invaluable insights, discussions, and advice that helped to shape this project. @capissimo - For open sourcing his interesting ideas regarding various KNN implementations in PineScript, several of which helped inspire my original undertaking of this project. @RikkiTavi - For many invaluable physics-related conversations and for his helping me develop a mechanism for visualizing various distance algorithms in 3D using JavaScript @jlaurel - For invaluable literature recommendations that helped me to understand the underlying subject matter of this project. @annutara - For help in beta-testing this indicator and for sharing many helpful ideas and insights early on in its development. @jasontaylor7 - For helping to beta-test this indicator and for many helpful conversations that helped to shape my backtesting workflow @meddymarkusvanhala - For helping to beta-test this indicator @dlbnext - For incredibly detailed backtesting testing of this indicator and for sharing numerous ideas on how the user experience could be improved.
Editors' picks
Pine Script™ indicator
143
Smart Money Concepts [LuxAlgo]This all-in-one indicator displays real-time market structure (internal & swing BOS / CHoCH), order blocks, premium & discount zones, equal highs & lows, and much more...allowing traders to automatically mark up their charts with widely used price action methodologies. Following the release of our Fair Value Gap script, we received numerous requests from our community to release more features in the same category. "Smart Money Concepts" (SMC) is a fairly new yet widely used term amongst price action traders looking to more accurately navigate liquidity & find more optimal points of interest in the market. Trying to determine where institutional market participants have orders placed (buy or sell side liquidity) can be a very reasonable approach to finding more practical entries & exits based on price action. The indicator includes alerts for the presence of swing structures and many other relevant conditions. Features This indicator includes many features relevant to SMC, these are highlighted below: Full internal & swing market structure labeling in real-time Break of Structure (BOS) Change of Character (CHoCH) Order Blocks (bullish & bearish) Equal Highs & Lows Fair Value Gap Detection Previous Highs & Lows Premium & Discount Zones as a range Options to style the indicator to more easily display these concepts Settings Mode: Allows the user to select Historical (default) or Present, which displays only recent data on the chart. Style: Allows the user to select different styling for the entire indicator between Colored (default) and Monochrome. Color Candles: Plots candles based on the internal & swing structures from within the indicator on the chart. Internal Structure: Displays the internal structure labels & dashed lines to represent them. (BOS & CHoCH). Confluence Filter: Filter non-significant internal structure breakouts. Swing Structure: Displays the swing structure labels & solid lines on the chart (larger BOS & CHoCH labels). Swing Points: Displays swing points labels on chart such as HH, HL, LH, LL. Internal Order Blocks: Enables Internal Order Blocks & allows the user to select how many most recent Internal Order Blocks appear on the chart. Swing Order Blocks: Enables Swing Order Blocks & allows the user to select how many most recent Swing Order Blocks appear on the chart. Equal Highs & Lows: Displays EQH/EQL labels on chart for detecting equal highs & lows. Bars Confirmation: Allows the user to select how many bars are needed to confirm an EQH/EQL symbol on chart. Fair Value Gaps: Displays boxes to highlight imbalance areas on the chart. Auto Threshold: Filter out non-significant fair value gaps. Timeframe: Allows the user to select the timeframe for the Fair Value Gap detection. Extend FVG: Allows the user to choose how many bars to extend the Fair Value Gap boxes on the chart. Highs & Lows MTF: Allows the user to display previous highs & lows from daily, weekly, & monthly timeframes as significant levels. Premium/Discount Zones: Allows the user to display Premium, Discount, and Equilibrium zones on the chart Usage Users can see automatic CHoCH and BOS labels to highlight breakouts of market structure, which allows to determine the market trend. In the chart below we can see the internal structure which displays more frequent labels within larger structures. We can also see equal highs & lows (EQH/EQL) labels plotted alongside the internal structure to frequently give indications of potential reversals. In the chart below we can see the swing market structure labels. These are also labeled as BOS and CHoCH but with a solid line & larger text to show larger market structure breakouts & trend reversals. Users can be mindful of these larger structure labels while trading internal structures as displayed in the previous chart. Order blocks highlight areas where institutional market participants open positions, one can use order blocks to determine confirmation entries or potential targets as we can expect there is a large amount of liquidity at these order blocks. In the chart below we can see 2 potential trade setups with confirmation entries. The path outlined in red would be a potential short entry targeting the blue order block below, and the path outlined in green would be a potential long entry, targeting the red order blocks above. As we can see in the chart below, the bullish confirmation entry played out in this scenario with the green path outlined in hindsight. As price breaks though the order blocks above, the indicator will consider them mitigated causing them to disappear, and as per the logic of these order blocks they will always display 5 (by default) on the chart so we can now see more actionable levels. The Smart Money Concepts indicator has many other features and here we can see how they can also help a user find potential levels for price action trading. In the screenshot below we can see a trade setup using the Previous Monthly High, Strong High, and a Swing Order Block as a stop loss. Accompanied by the Premium from the Discount/Premium zones feature being used as a potential entry. A potential take profit level for this trade setup that a user could easily identify would be the 50% mark labeled with the Fair Value Gap & the Equilibrium all displayed automatically by the indicator. Conclusion This indicator highlights all relevant components of Smart Money Concepts which can be a very useful interpretation of market structure, liquidity, & more simply put, price action. The term was coined & popularized primarily within the forex community & by ICT while making its way to become a part of many traders' analysis. These concepts, with or without this indicator do not guarantee a trader to be trading within the presence of institutional or "bank-level" liquidity, there is no supporting data regarding the validity of these teachings.
Pine Script™ indicator
436
Hurst Diamond Notation PivotsThis is a fairly simple indicator for diamond notation of past hi/lo pivot points, a common method in Hurst analysis. The diamonds mark the troughs/peaks of each cycle. They are offset by their lookback and thus will not 'paint' until after they happen so anticipate accordingly. Practically, traders can use the average length of past pivot periods to forecast future pivot periods in time🔮. For example, if the average/dominant number of bars in an 80-bar pivot point period/cycle is 76, then a trader might forecast that the next pivot could occur 76-ish bars after the last confirmed pivot. The numbers/labels on the y-axis display the cycle length used for pivot detection. This indicator doesn't repaint, but it has a lot of lag; Please use it for forecasting instead of entry signals. This indicator scans for new pivots in the form of a rainbow line and circle; once the hi/lo has happened and the lookback has passed then the pivot will be plotted. The rainbow color per wavelength theme seems to be authentic to Hurst (or modern Hurst software) and has been included as a default.
Editors' picks
Pine Script™ indicator
41
CVD - Cumulative Volume Delta (Chart)█   OVERVIEW This indicator displays cumulative ​volume delta (​CVD) as an on-chart oscillator. It uses intrabar analysis to obtain more precise ​volume delta information compared to methods that only use the chart's timeframe. The core concepts in this script come from our first ​ CVD indicator , which displays CVD​ values as plot candles in a separate indicator pane. In this script, CV​D values are scaled according to price ranges and represented on the main chart pane. █   CONCEPTS Bar polarity Bar polarity refers to the position of the close price relative to the open price. In other words, bar polarity is the direction of price change. Intrabars Intrabars are chart bars at a lower timeframe than the chart's. Each 1H chart bar of a 24x7 market will, for example, usually contain 60 bars at the lower timeframe of 1min, provided there was market activity during each minute of the hour. Mining information from intrabars can be useful in that it offers traders visibility on the activity inside a chart bar. Lower timeframes (LTFs) A lower timeframe is a timeframe that is smaller than the chart's timeframe. This script utilizes a LTF to analyze intrabars, or price changes within a chart bar. The lower the ​LTF, the more intrabars are analyzed, but the less chart bars can display information due to the limited number of intrabars that can be analyzed. Volume delta Volume delta is a measure that separates ​volume​ into "up" and "down" parts, then takes the difference to estimate the net demand for the asset. This approach gives traders a more detailed insight when analyzing volume​ and market sentiment. There are several methods for determining whether an asset's volume​ belongs in the "up" or "down" category. Some indicators, such as On Balance Volume​ and the Klinger Oscillator , use the change in price between bars to assign ​volume​ values to the appropriate category. Others, such as Chaikin Money Flow , make assumptions based on open, high, low, and close prices. The most accurate method involves using tick data to determine whether each transaction occurred at the bid or ask price and assigning the ​volume​ value to the appropriate category accordingly. However, this method requires a large amount of data on historical bars, which can limit the historical depth of charts and the number of symbols for which tick data is available. In the context where historical tick data is not yet available on TradingView, intrabar analysis is the most precise technique to calculate ​volume delta on historical bars on our charts. This indicator uses intrabar analysis to achieve a compromise between simplicity and accuracy in calculating ​volume delta on historical bars. Our Volume Profile indicators use it as well. Other ​volume delta indicators in our Community Scripts , such as the Realtime 5D Profile , use real-time chart updates to achieve more precise ​volume delta calculations. However, these indicators aren't suitable for analyzing historical bars since they only work for real-time analysis. This is the logic we use to assign intrabar ​volume to the "up" or "down" category:  • If the intrabar's open and close values are different, their relative position is used.  • If the intrabar's open and close values are the same, the difference between the intrabar's close and the previous intrabar's close is used.  • As a last resort, when there is no movement during an intrabar and it closes at the same price as the previous intrabar, the last known polarity is used. Once all intrabars comprising a chart bar are analyzed, we calculate the net difference between "up" and "down" intrabar volume​ to produce the volume​ delta for the chart bar. █   FEATURES CVD resets The "cumulative" part of the indicator's name stems from the fact that calculations accumulate during a period of time. By periodically resetting the volume​ delta accumulation, we can analyze the progression of ​volume delta across manageable chunks, which is often more useful than looking at ​volume delta accumulated from the beginning of a chart's history. You can configure the reset period using the "CVD Resets" input, which offers the following selections:  • None : Calculations do not reset.  • On a fixed higher timeframe : Calculations reset on the higher timeframe you select in the "Fixed higher timeframe" field.  • At a fixed time that you specify.  • At the beginning of the regular session .  • On trend changes : Calculations reset on the direction change of either the Aroon indicator, Parabolic SAR , or Supertrend .  • On a stepped higher timeframe : Calculations reset on a higher timeframe automatically stepped using the chart's timeframe and following these rules: Chart TF ​HTF < 1min 1H < 3H 1D <= 12H 1W < 1W 1M >= 1W 1Y Specifying intrabar precision Ten options are included in the script to control the number of intrabars used per chart bar for calculations. The greater the number of intrabars per chart bar, the fewer chart bars can be analyzed. The first five options allow users to specify the approximate amount of chart bars to be covered:  • Least Precise (Most chart bars) : Covers all chart bars by dividing the current timeframe by four.   This ensures the highest level of intrabar precision while achieving complete coverage for the dataset.  • Less Precise (Some chart bars) & More Precise (Less chart bars) : These options calculate a stepped ​LTF in relation to the current chart's timeframe.  • Very precise (2min intrabars) : Uses the second highest quantity of intrabars possible with the 2min ​LTF.  • Most precise (1min intrabars) : Uses the maximum quantity of intrabars possible with the 1min ​LTF. The stepped lower timeframe for "Less Precise" and "More Precise" options is calculated from the current chart's timeframe as follows: Chart Timeframe Lower Timeframe Less Precise More Precise < 1hr 1min 1min < 1D 15min 1min < 1W ​2hr​ 30min > 1W 1D 60min The last five options allow users to specify an approximate fixed number of intrabars to analyze per chart bar. The available choices are 12, 24, 50, 100, and 250. The script will calculate the LTF​ which most closely approximates the specified number of intrabars per chart bar. Keep in mind that due to factors such as the length of a ticker's sessions and rounding of the LTF​, it is not always possible to produce the exact number specified. However, the script will do its best to get as close to the value as possible. As there is a limit to the number of intrabars that can be analyzed by a script, a tradeoff occurs between the number of intrabars analyzed per chart bar and the chart bars for which calculations are possible. Display This script displays raw or cumulative volume​ delta values on the chart as either line or histogram oscillator zones scaled according to the price chart, allowing traders to visualize volume​ activity on each bar or cumulatively over time. The indicator's background shows where CVD​ resets occur, demarcating the beginning of new zones. The vertical axis of each oscillator zone is scaled relative to the one with the highest price range, and the oscillator values are scaled relative to the highest volume​ delta. A vertical offset is applied to each oscillator zone so that the highest oscillator value aligns with the lowest price. This method ensures an accurate, intuitive visual comparison of volume​ activity within zones, as the scale is consistent across the chart, and oscillator values sit below prices. The vertical scale of oscillator zones can be adjusted using the "Zone Height" input in the script settings. This script displays labels at the highest and lowest oscillator values in each zone, which can be enabled using the "Hi/Lo Labels" input in the "Visuals" section of the script settings. Additionally, the oscillator's value on a chart bar is displayed as a tooltip when a user hovers over the bar, which can be enabled using the "Value Tooltips" input. Divergences occur when the polarity of ​volume delta does not match that of the chart bar. The script displays divergences as bar colors and background colors that can be enabled using the "Color bars on divergences" and "Color background on divergences" inputs. An information box in the lower-left corner of the indicator displays the HTF used for resets, the ​LTF used for intrabars, the average quantity of intrabars per chart bar, and the number of chart bars for which there is LTF data. This is enabled using the "Show information box" input in the "Visuals" section of the script settings. FOR Pine Script™ CODERS  • This script utilizes `ltf()` and `ltfStats()` from the lower_tf library.   The `ltf()` function determines the appropriate lower timeframe from the selected calculation mode and chart timeframe, and returns it in a format that can be used with request.security_lower_tf() .   The `ltfStats()` function, on the other hand, is used to compute and display statistical information about the lower timeframe in an information box.  • The script utilizes display.data_window and display.status_line to restrict the display of certain plots.   These new built-ins allow coders to fine-tune where a script’s plot values are displayed.  • The newly added session.isfirstbar_regular built-in allows for resetting the ​CVD segments at the start of the regular session.  • The VisibleChart library developed by our resident PineCoders team leverages the chart.left_visible_bar_time and chart.right_visible_bar_time variables to optimize the performance of this script.   These variables identify the opening time of the leftmost and rightmost visible bars on the chart, allowing the script to recalculate and draw objects only within the range of visible bars as the user scrolls.   This functionality also enables the scaling of the oscillator zones.   These variables are just a couple of the many new built-ins available in the chart.* namespace.   For more information, check out this blog post or look them up by typing "chart." in the Pine Script™ Reference Manual .  • Our ta library has undergone significant updates recently, including the incorporation of the `aroon()` indicator used as a method for resetting ​CVD segments within this script.   Revisit the library to see more of the newly added content! Look first. Then leap.
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Pine Script™ indicator
16
Fair value bands (Dynamic risk levels, fair value metrics)— Overview Fair value bands, like other band tools, depict dynamic points in price where price behaviour is normal or abnormal, i.e. trading at/around mean (price at fair value) or deviating from mean (price outside fair value). Unlike constantly readjusting standard deviation based bands, fair value bands are designed to be smooth and constant, based on typical historical deviations. The script calculates pivots that take place above/below fair value basis and forms median deviation bands based on this information. These points are then multiplied up to 3, representing more extreme deviations. By default, the script uses OHLC4 and SMA 20 as basis for the bands. Users can form their preferred fair value basis using following options: Price source - Standard OHLC values - HL2 (High + low / 2) - OHLC4 (Open + high + low + close / 4) - HLC3 (High + low + close / 3) - HLCC4 (High + low + close + close / 4) Smoothing - SMA - EMA - HMA - RMA - WMA - VWMA - Median Once fair value basis is established, some additional customization options can be employed: Trend mode Direction based Cross based Trend modes affect fair value basis color that indicates trend direction. Direction based trend considers only the direction of the defined fair value basis, i.e. pointing up is considered an uptrend, vice versa for downtrend. Cross based trends activate when selected source (same options as price source) crosses fair value basis. These sources can be set individually for uptrend/downtrend cross conditions. By default, the script uses cross based trend mode with low and high as sources. Cross based (downtrend not triggered) vs. direction based (downtrend triggered): Threshold band Threshold band is calculated using typical deviations when price is trading at fair value basis. In other words, a little bit of "wiggle room" is added around the mean based on expected deviation. This feature is useful for cross based trends, as it allows filtering insignificant crosses that are more likely just noise. By default, threshold band is calculated based on 1x median deviation from mean. Users can increase/decrease threshold band width via input menu for more/less noise filtering, e.g. 2x threshold band width would require price to cross wiggle room that is 2x wider than typical, 0x erases threshold band altogether. Deviation bands Width of deviation bands by default is based on 1x median deviations and can be increased/decreased in a similar manner to threshold bands. Each combination of customization options produces varying behaviour in the bands. To measure the behaviour and finding fairest representation of fair and unfair value, some data is gathered. — Fair value metrics Space between each band is considered a lot, named +3, +2, +1, -1, -2, -3. For each lot, time spent and volume relative to volume moving average (SMA 20) is recorded each time price is trading in a given lot: Depending on the asset, timeframe and chosen fair value basis, shape of the distributions vary. However, practically always time is distributed in a normal bell curve shape, being highest at lots +1 to -1, gradually decreasing the further price is from the mean. This is hardly surprising, but it allows accurately determining dynamic areas of normal and abnormal price behaviour (i.e. low risk area between +1 and -1, high risk area between +-2 to +-3). Volume on the other hand is typically distributed the other way around, being lowest at lots +1 to -1 and highest at +-2 to +-3. When time and volume are distributed like so, we can conclude that 1) price being outside fair value is a rare event and 2) the more price is outside fair value, the more anomaly behaviour in volume we tend to find. Viewing metric calculations Metric calculation highlights can be enabled from the input menu, resulting in a lot based coloring and visibility of each lot counter (time, cumulative relative volume and average relative volume) in data window: — Alerts Available alerts are the following: Individual - High crossing deviation band (bands +1 to +3 ) - Low crossing deviation band (bands -1 to -3 ) - Low at threshold band in an uptrend - High at threshold band in a downtrend - New uptrend - New downtrend Grouped - New uptrend or downtrend - Deviation band cross (+1 or -1) - Deviation band cross (+2 or -2) - Deviation band cross (+3 or -3) — Practical guide Example #1 : Risk on/risk off trend following Ideal trend stays inside fair value and provides sufficient cool offs between the moves. When this is the case, fair value bands can be used for sensible entry/exit levels within the trend. Example #2 : Mean reversions When price shows exuberance into an extreme deviation, followed by a stall and signs of exhaustion (wicks), an opportunity for mean reversion emerges. The higher the deviation, the more volatility in the move, the more signalling of exhaustion, the better. Example #3 : Tweaking bands for desired behaviour The faster the length of fair value basis, the more momentum price needs to hit extreme deviation levels, as bands too are moving faster alongside price. Decreasing fair value basis length typically leads to more quick and aggressive deviations and less steady trends outside fair value.
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Pine Script™ indicator
18
Harmonic Patterns Based Trend FollowerEarlier this week, published an idea on how harmonic patterns can be used for trend following. This script is an attempt to implement the same. 🎲 Process 🎯 Derive Zigzag and scan harmonic patterns for last 5 confirmed pivots 🎯 If a pattern is found, highest point of pattern will become the bullish zone and lower point of the pattern will become bearish zone. 🎯 Since it is trend following method, when price reaches bullish zone, then the trend is considered as bullish and when price reaches bearish zone, the trend is considered as bearish. 🎯 If price does not touch both regions, then trend remains unchanged. 🎯 Bullish and bearish zone will change as and when new patterns are formed. 🎲 Note Patterns are not created on latest pivot as last pivot will be unconfirmed and moving. Due to this, patterns appear after certain delay - patterns will not be real time. But, this is expected and does not impact the overall process. When new pattern formed When price breaks over the zones 🎲 Output 🎯 Patterns formed are drawn in blue coloured lines. Due to pine limitation of max 500 lines, older patterns automatically get deleted when new ones come. 🎯 Bullish Zone and Bearish Zone are plotted in green and red colours and the zone will change whenever new pattern comes along. 🎯 Bar colors are changed according to calculated trend. Trend value can be 1 or -1 based on the current trend. You can also find the value in data window. 🎯 For simplicity purpose, input option for selection of specific patterns are not provided and also pattern names are not displayed on the chart.
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Pine Script™ indicator
32
[@btc_charlie] Trader XO Macro Trend ScannerWhat is this script? This script has two main functions focusing on EMAs (Exponential Moving Average) and Stochastic RSI. EMAs EMAs are typically used to give a view of bullish / bearish momentum. When the shorter EMA (calculated off more recent price action) crosses, or is above, the slower moving EMA (calculated off a longer period of price action), it suggests that the market is in an uptrend. This can be an indication to either go long on said asset, or that it is more preferable to take long setups over short setups. Invalidation on long setups is usually found via price action (e.g. previous lows) or simply waiting for an EMA cross in the opposite direction (i.e. shorter EMA crosses under longer term EMA). This is not a perfect system for trade entry or exit, but it does give a good indication of market trends. The settings for the EMAs can be changed based on user inputs, and by default the candles are coloured based on the crosses to make it more visual. The default settings are based on “Trader XO’s” settings who is an exceptional swing trader. RSI Stochastic RSI is a separate indicator that has been added to this script. RSI measures Relative Strength (RSI = Relative Strength Index). When RSI is <20 it is considered oversold, and when >80 it is overbought. These conditions suggests that momentum is very strong in the direction of the trend. If there is a divergence between the price (e.g. price is creating higher highs, and stoch RSI is creating lower highs) it suggests the strength of the trend is weakening. Whilst this script does not highlight divergences, what it does highlight is when the shorter term RSI (K) crosses over D (the average of last 3 periods). This can give an indication that the trend is losing strength. Combination The EMAs indicate when trend shifts (bullish or bearish). The RSI indicates when the trend is losing momentum. The combination of the two can be used to suggest when to prefer a directional bias, and subsequently shift in anticipation of a trend reversal. Note that no signal is 100% accurate and an interpretation of market conditions and price action will need to be overlayed to Why is it different to others? I have not found other scripts that are available in this way visually including alerts when Stoch RSI crosses over/under the extremes; or the mid points. Whilst these indicators are default, the combination of them and how they are presented is not and makes use of the TradingView colouring functionalities. What are the features? Customise the variables (averages) used in the script. Display as one EMA or two EMAs (the crossing ones). Alerts on EMA crosses. Alerts on Stoch RSI crosses - slow/fast, upper, lower areas. - Currently set on the chart to show alerts when Stoch RSI is above 80, then falls below 80 (and colours it red). Customisable colours. What are the best conditions for this? It is designed for high timeframe charts and analysis in crypto, since crypto tends to trend. It can however be used for lower timeframes. Disclaimer/Notes: I have noticed several videos appearing suggesting that this is a "100% win rate indicator" . NO indicator has 100% win rate. An indicator is an *indicator* that is all. Please use responsibly and let me know if there are any mods or updates you would like to see.
Pine Script™ indicator
7
True Trend Average BandsThis is the indicator I am most proud of. After reading Glenn Neely's book "Mastering Eliott Waves" / "Neowave" and chatting with @timwest who got acknowledged by Neely, we came up with the idea of an moving average which does calculate the real average price since a trend started. Addionally I adapted a method from Neely Neowave and Tim Wests TimeAtMode to not force a timeframe on a chart but instead let the charts data decide which timeframe to use, to then calculate the real average price since the trend started. It took me a while to get this right and coded, so take a moment and dive deeper and you might learn something new. We assume that the price is in multiple trends on multiple timeframes, this is caused by short term traders, long term traders and investors who trade on different timeframes. To find out in which timeframe the important trends are, we have to look out for significant lows and highs. Then we change the timeframe in the chart to a value so that we have 10 to 20 bars since the significant low/high. While new bars are printed, and we reach more than 20 bars, we have to switch to a higher timeframe so we have 10 to 20 bars again. In the chart you see two significant trends: a downtrend on the 3 week timeframe and an uptrend from the 2 month timeframe. Based on the logic I have described, these are the two important timeframes to watch right now for the spx (there is another uptrend in the yearly chart, which is not shown here). Now that we understand how to find the important timeframes, let's look what the magic in this script is that tells us the real average price since a trend started. I developed a new type of moving average, which includes only the prices since a trend started. The difference to the regular sma is that it will not include prices which happened before the significant low or high happened. For example, if a top happened in a market 10 days ago, the regular sma20 would be calculated by 10 bars which happened before the top and 10 bars which happened after the top. If we want to know the average price of the last 10 bars we manually have to change the ma20 to the ma10 which is annoying manual work, additionally even if we use the ma10 in this case, and we look at yesterday's bar the ma10 will include 9 bars from after the top and one bar before the top, so the ma10 would only show the real average price for the current bar which is not what we want. To come up with a solution to this problem, the True Trend Average searches for the lowest/highest bar in a given period (20 bars). Then starts to calculate the average value since the low/high. For example: if the price reaches a new 20 day high and then trades below it, the day of the high will be the sma1, the day after it's the sma2, ... up to the maximum look back length. This way, we always know what the average price would have been if someone sold/bought a little bit every bar of his investment since the high/low. Why is this even important? Let's assume we missed selling the top or buying the low, and think it would have been at least better to buy/sell a little bit since the new trend started. Once the price reaches the true trend average again, we can buy/sell, and it would be as good as selling/buying a little bit every day. We find prices to buy the dip and sell the bounce, which are as good as scaling in/out. There is a lot more we can learn from these price levels but I think it is better to let you figure out yourself what you can learn from the information given by this indicator. Think about how market participants who accumulate or distribute feel when prices are above or below certain levels. Now that we understand this new type of moving average, let's look into the lines we see in the chart: The upper red band line shows the true trend average high price since the last significant top within 20 bars. The lower red band line shows the true trend average hl2 price since the last significant top within 20 bars. The lower green band line shows the true trend average low price since the last significant low within 20 bars. The upper green band line shows the true trend average hl2 price since the last significant low within 20 bars. The centerline is the average between the upper red band and the lower green band. The teal lines show 1 standard deviation from the outer bands. Before today only a few people had access to this indicator, now that it is public and open source, I am curious if you will find it useful and what you will do with it. Please share your findings. /edit: The chart only shows the 3week timeframe so here are the other two trends from the 2month and 1year timeframe
Pine Script™ indicator
13
NET BSP NET BSP derived from Buying & Selling Pressure which is a volatility indicator that monitors average metrics of green and red candles separately. We could navigate more confidently through market with projected market balance. BSP allowed us to track and analyze the ongoing performance of bullish and bearish impulsive waves and their corrections. Due to unintuitive way of measuring decline with SP going up, I decided to remake it into more intuitive version with better precision. When we encounter the fall it's better to have declining values of tool to be able to cover it visually with ease. One of the solutions was to create a sense of balance of Buying Pressure against Selling Pressure. Since we are oriented by growth, it'd be more logical to summarize the market balance with BP - SP Comparison: When Buying and Selling Pressure are equal, NET BSP would be at 0. NETBSP > 0 and NETBSP > NETBSP = 🟢 NETBSP > 0 and NETBSP < NETBSP = 🟡 NETBSP < 0 and NETBSP < NETBSP = 🔴 NETBSP < 0 and NETBSP > NETBSP = 🟡 Hence, we get visualized stages of uptrends and downtrends which allows to evaluate chances and estimations of upcoming counter-waves. Also, it is worth to note that output clearly shows how one wave is derived from another in terms of sizing. Feel free to adjust NET BSP arguments to adapt sensitivity to the timeframe you're working on.
Pine Script™ indicator
20
Pivot and Price DiscoveryA Population Sampled linear regression model that provides additional detail about the distribution moments (skew, kurtosis, variance and mean) as well as providing indicators that track when a pivot has enough momentum to trade on as well as expected ranges of future price action based on Std Devs. For the momentum lines -- red indicates that there has been a reducing pivot with momentum, this continues as a grey line for continuation, and will be cancelled when an increasing pivot with momentum is encountered. Forward looking trend triangle captures the +/- stated standard deviation from the latest bar_index over 2 periods. Movements that trace outside of this can be considered a precursor to an upcoming pivot, and by analyzing skewness and kurtosis, the probability of an upcoming pivot should be better understood. I have really only looked at this for timescales greater than 5 minutes. Adjust the lookback length accordingly when moving to different timescales: For example, 1 hr at 10m timescale will be a lookback length of 6 which is too low for accurate analysis, so keep the lookback length appropriate for the timescales being used. Also realize that trade volume will skew the deviations and regression if you are including data outside of regular trading hours (futures are different, but also experience volume sensitivity -- I maylook into accounting for this in future versions.) © TheGeeBee
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Pine Script™ indicator
6

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Educational ideas

What I've learned after backtesting So, I love backtesting. Recently I've found my self in a 3% drawdown and needed to figure out what the cause of it was and trading at this moment won't give me that answer. So, I decided to backtest. Here is what I found: 1. I'm overtrading my system I am a proud swing trader who got back into scalping the market in December 2022. It was mot my idea, but I thought I could handle it. I started out great, but then the market reminded me why I left the lower timeframes. 2. I'm not holding my trades long enough. Thanks Prop Firms! Since joining a prop firm my mind has been changed to holding trades for less time than I normally would. I don't mind holding trades for weeks or months, but prop firms give you time limits during evaluation periods. That was and still is a huge adjustment for me. Being a swing trader means I have to let my profits run. So, now, I've found a prop firm that will allow me to hold my trades with no time limits. 3. Not holding trades to my weekly and monthly targets. I need to see past my daily targets. Normally my daily risk to rewards are between 1:1 and 1:2. I'm in drawdown because I'm not recovering from my losses with these risk to rewards. So now, I'm only taking trades with RR over 1:2 and better. This way I'm trading less, holding longer(sometimes), and getting the best bank for my buck. Backtesting helped me see my mistakes and how to correct them. This is called fixing your strategy. Notice how I'm not changing my strategy. I'm tweaking my strategy to fit my mental capacity and trading style. If you find you're in a drawdown and can't see, stop trading and backtest what you're currently doing and find a way to stop the behavior thats causing your drawdown. Then, stop doing that particular thing so you can see better results. I pray this has helped you. Let me know your key takeaway by commenting below.
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Education
9
Learn Why Most of the Traders Fail The evidence suggests that only a very small proportion of day traders makes money year over year. There are certain patterns which may separate profitable traders from those who ultimately lose money. And indeed, there is one particular mistake that in our experience gets repeated time and time again. What is the single most important mistake that led to traders losing money? Here is a hint – it has to do with how we as humans relate to winning and losing. Our own human psychology makes it difficult to navigate financial markets, which are filled with uncertainty and risk, and as a result the most common mistakes traders make have to do with poor risk management strategies. Traders are often correct on the direction of a market, but where the problem lies is in how much profit is made when they are right versus how much they lose when wrong. Bottom line, traders tend to make less on winning trades than they lose on losing trades. Humans aren’t machines, and working against our natural biases requires effort. Once you have a trading plan that uses a proper reward/risk ratio, the next challenge is to stick to the plan. Remember, it is natural for humans to want to hold on to losses and take profits early, but it makes for bad trading. We must overcome this natural tendency and remove our emotions from trading. That will help you to be a consistently profitable trader. ✅LIKE AND COMMENT MY IDEAS✅ Please, like this post and subscribe to our tradingview page!👍
Education
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FOREX MARKET PLAYERSWhen it comes to the forex market, there are a number of different players that play a role in its overall functioning. From central banks and commercial banks to individual investors and brokers, each one plays a part in keeping the market ticking. In this article, we take a closer look at each of these groups and their role in the forex market. Central banks Central banks play a vital role in the foreign exchange market. They are responsible for setting monetary policy, which can have a big impact on the banking system and the economy as a whole. When it comes to setting monetary policy, central banks have two main objectives: ensuring price stability and achieving full employment. In order to achieve these objectives, central banks use a variety of tools, such as interest rates, quantitative easing, and open market operations. The monetary policy set by central banks can have a big impact on the banking system. For example, if central banks raise interest rates, it will become more expensive for banks to borrow money. This can lead to higher lending rates and reduced lending activity, which can in turn slow down economic growth. The economy is also affected by the monetary policy set by central banks. For instance, if interest rates are lowered, it can encourage spending and boost economic growth. On the other hand, if interest rates are raised, it can lead to slower economic growth. Institutional investors Institutional investors are usually large organizations, such as hedge funds or insurance companies, that don't trade frequently. Instead, they have a long-term orientation and are concerned about the overall health of the market. For these investors, the foreign exchange market provides an opportunity to make profits by buying and selling currencies. Most institutional investors use a professional currency trader to buy and sell currencies on their behalf. These traders have access to information and resources that individual investors don't have. They also have the experience and expertise to make informed decisions about when to buy and sell currencies. When institutional investors buy a currency, they are betting that it will appreciate in value relative to other currencies. If their bet pays off, they will make a profit. On the other hand, if the currency depreciates in value, they will incur a loss. The foreign exchange market is risky, but it can be profitable for those who know what they're doing. Institutional investors often have an advantage over individual investors because they have access to more information and resources. They also tend to be more experienced and knowledgeable about the market. Individual investors Individual investors play an important role in the foreign exchange market. They provide the market with much-needed liquidity and can profit from currency movements. Most individual investors are small-scale investors, but there are also large-scale investors, such as hedge funds and insurance companies. The different investment strategies used by individual investors may include buying and holding currencies, day trading, and carrying out technical analysis. Some individual investors choose to buy and hold currencies for the long term. They believe that over time, the currency will appreciate in value. This strategy requires patience and a willingness to accept gradual gains. Other individual investors opt for a more active approach, day trading currencies. This involves buying and selling currencies within the same day in order to take advantage of short-term price movements. Day trading can be a risky strategy, but it can also lead to quick profits. Many individual investors carry out technical analysis when making decisions about when to buy and sell currencies. Technical analysis is a method of predicting future price movements based on past price data. Commercial banks Commercial banks are an important part of the economy. They are responsible for taking deposits from individuals and companies and lending money to borrowers. Commercial banks play a vital role in the economy by acting as a conduit for funds between savers and borrowers. The largest commercial banks in the world are Citigroup, JPMorgan Chase, HSBC, Bank of America and Wells Fargo. These banks have a significant impact on the forex market. They buy and sell currencies on a daily basis in order to facilitate transactions between businesses and consumers. Most commercial banks use professional currency traders to buy and sell currencies on their behalf. These traders have access to information and resources that individual investors don't have. They also have the experience and expertise to make informed decisions about when to buy and sell currencies. When commercial banks buy a currency, they are betting that it will appreciate in value relative to other currencies. If their bet pays off, they will make a profit. On the other hand, if the currency depreciates in value, they will incur a loss. Brokers Most retail brokers in the foreign exchange market are what is called market makers. This means that they essentially act as a middleman between the buyer and seller of a currency pair. For example, if you wanted to buy Euros using US dollars, the broker would find someone who wanted to sell Euros and match you up with them. The broker would then charge a commission on the transaction. Market makers make money by charging a spread, which is the difference between the bid price and the ask price of a currency pair. For example, if the bid price of EUR/USD is 1.20 and the ask price is 1.21, the spread would be 1 pip. Market makers typically add 3-5 pips to the spread in order to make a profit. Another way that some brokers make money is through what is called slippage. Slippage occurs when an order is filled at a worse price than expected due to market conditions. For example, if you placed an order to buy EUR/USD at 1.20 and the market was very volatile, your order might be filled at 1.19 instead. In this case, the broker would keep the 1 pip difference as profit. Some brokers also charge fees for making deposits or withdrawals from your account. These fees can vary depending on the method used (e.g., wire transfer, credit card) and can add up over time if you're frequently making deposits or withdrawals Companies When it comes to foreign exchange, companies have a few different options available to them. They can use foreign exchange to hedge currency risk, speculate on currency movements, or invest in currency as an asset class. Currency ETFs are also an option for companies looking for active currency management. Hedging currency risk is important for companies that have exposure to foreign currencies. For example, a company that exports goods to Europe might want to hedge against the risk of a decline in the value of the Euro. To do this, the company would enter into a currency forward contract. This contract locks in the exchange rate between two currencies for a future date. So, if the value of the Euro does decline, the company's export revenue will not be affected. Speculating on currency movements can be a risky proposition, but it can also be profitable. Companies that speculate on currencies typically use financial instruments like futures contracts or options. These contracts allow them to bet on the direction of a currency's movements without actually having to buy or sell any currency. Of course, if they guess wrong about which way the market will move, they can lose money. Investing in currency as an asset class is another option for companies. This can be done by buying foreign currencies with the intention of holding them for investment purposes. For example, a company might buy Japanese Yen because it expects the Yen to appreciate in value relative to other currencies. If this happens and the company sells its Yen at a higher price than it bought them for, it will make a profit. Currency ETFs are another tool that companies can use for active currency management. These funds trade on exchanges just like stocks and can be bought and sold through brokers. Currency ETFs track baskets of currencies or individualcurrency pairs and can be used to gain exposure to foreign exchange markets without having to trade directly in those markets. Traders, if you liked this idea or if you have your own opinion about it, write in the comments. I will be glad 👩‍💻
Education
11
A trifling observation.Is it possible to provide an indication that pre-empts the classic "death cross"? Traders use different systems to judge the market outlook on patterns, as well as an important indication for them. It is perfectly normal that someone can be wrong, and someone will be lucky to read the market correctly. This post is about anticipatory indication and prejudice. If you open the articles on moving averages, you can read that the exponential Moving averages (EMAs) are preferable on low timeframes up to a minute chart, but they are not but it's recommended for the weekly chart. Whereas it is recommended to use SMAs on longer timeframes. OK, I thought. But why? Who has checked it? A price is a price, in itself it only says that someone has offered an asset at a certain price, and someone bought at that price. But the market trend requires more confirmation of transactions through volumes. The price alone cannot tell you what the market has decided. And that is why I made this comparison. MA 50/200 (white and blue line) versus EMA 50/200 (orange and purple) + VFI LF (volume flow indicator). Hypothesis: EMAs are valid for 1 week timeframe, the exponent is not suitable for this timeframe is a preconception. MA lags in indicating the signal, but you need to know the trend of the volume, for which you need an indicator like VFI LF. In the case of unidirectional signals EMA 50/200 and VFI LF you can make a deal without waiting for the signal MA 50/200. Assertion:
 Bitcoin is in a bear market and no reversal has occurred. The bounce at the beginning of the year was intended to test crossed possible area of the weekly SMA moving averages. But because of death cross on EMAs already on the 9th of January, it also puts selling pressure. And here the Volume Flow Indication is an important aid. See, the VFI has two pale lines besides the volume flow line itself, it's a fast and slow MA of volume (but it's MA of volume, not of price!), and on these lines you can also see golden and death crosses. Look closely, in the history of Bitstamp trading (the longest trading history of Bitcoin) there have been exactly 3 such crosses by volume indication on weekly chart. Two bearish and one bullish. The last bearish cross on the MA of volume flow occurred about a month before the cross at EMA 50/200 price. December 12... As a result: Two bearish pre-emptive signals versus one classic "textbook" one. My bet is that there will not be a upbounce. There will be an 85% retracement level from the peak and a consolidation at the bottom. Waiting for a reality check in this race. My bet is that we are in a bear market.
Education
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Leading Indicators To Improve Decision Making in Oil TradingHello Traders! As you know, trading is a game of probabilities and navigating the financial markets is not always easy. Different strategies that we use, such as Elliott wave analysis and pattern trading, can provide different scenarios for market movements. However, market conditions are often uncertain and can extend beyond what is predicted by these strategies. In such cases, it is useful to have access to scientifically proven tools that can help us better assess the probabilities of different scenarios. One such tool is the use of leading indicators. In this educational idea, we will explore the use of a leading indicator for Wti prices that embodies information from futures term spread and Relative Inventories. Correlation with Relative Inventories is due to the basic supply and demand dynamics of the market. When inventories are high, there is an oversupply of oil which puts downward pressure on prices. Conversely, when inventories are low, there is a shortage of oil which puts upward pressure on prices. Another useful metric for predicting oil prices is the term spread. The term spread refers to the difference between the prices of two oil contracts with different delivery dates. Researchers have found that changes in the term spread can be a leading indicator of future prices. The relationship between the term spread and oil prices comes from the fact that the term spread reflects changes in market expectations about future supply and demand for oil. Studies have confirmed the predictive power of both relative inventories and the term spread. Starting in a seminar paper by Hamilton (1983), it was demonstrated that changes in inventories had a significant impact on future oil prices. Similarly, other research has shown that changes in the term spread have a strong correlation with future oil price movements (e.g., Kilian and Murphy, 2009), and now there are a vastity of academic paper that explores that correlations and the predictive possibilities. Here another couple of references: www.sciencedirect.com gupea.ub.gu.se Now, I want to bring you an example of how these empirical result can be exploited and used in trading. In the main chart indeed I show an indicator constructed to reproduce the forecasting model proposed in the last article that I linked (Larsson, 2018). This Forecasting Model is a time series ARIMA model that uses both relative inventories and term spread between 3-months ahead contract and the 40-months ahead contract, together with squared relative inventories to capture non linearities in the relation between inventories and wti price. You can see the forecasted model in the red line, while the blue line is the weekly oil closing price. I will report again here the chart for clarity: After the uptrend ended, in which the forecasting model overshooted before crossing back, we can see that every time the red line (forecasting model) retested the blue line (actual price) the retest was followed by a strong decrease in price. This was use for us as confirmation for our bearish scenario on oil, that we are still trading. I hope you can find this post useful! If you have any comment, please share, we will be happy! Cheers, GMR
Education
Funds and money in cryptoFunds and money in crypto First, let's determine why money are required for the project. Money . The first and most evident thought that occurs to mind. A startup exchanges a portion of its stock or tokens (often a soul) for digital evergreen paper. Is it feasible to grow your business without these funds? Certainly, you can, but why? When a team has operational cash flow, it can stop pursuing profits from day one and instead focus on developing a high-quality product that will bring a lot more profit for everyone in the long run. Expertise . Every big VC has a whole team of specialists that can assist a new or not-so-young startup with a variety of difficulties, including business model development, tokenomics, marketing, and cost reduction. Even if a developer is a talented coder, this does not guarantee that he or she can create a lucrative firm. Connections . The fact that funds invest in dozens of initiatives necessitates communication with hundreds of thousands of professionals worldwide. There may be an intriguing project in the investor's portfolio with which one might form a relationship or attract customers. Quality rating . When a cool fund invests in a firm, the rest of the market receives a signal to keep an eye on them. If stock experts who evaluate hundreds of companies every month opt to invest in the team, then the startup's concept and potential are rather strong. While this does not alter the fact that even market experts occasionally miss the mark. We have therefore determined why we require a financial investment and will proceed. The following important question is how much was invested in the project. It would appear that more is better. However, this is not always the case, at least not in our experience as bold speculators. When 100-200 million dollars are invested in a token, this indicates that the minimum FDV is already trying for a billion dollars, making it considerably more difficult for early investors to obtain Xs with sensible prices on the listing. Therefore, purchasing such enormous items at the beginning of the market is a mediocre idea, however participation in their activities is an excellent idea. On the other hand, if they invest too little ($100-$300k), this may indicate that they don't trust much in the progress just yet; other funds invested three kopecks just in case. With this alternative, however, there is a substantial potential for X, as was the case with My Neighbor Alice, who, after privately accumulating two lyams, moved to binance and made their early investors and players wealthy. I should emphasize, however, that this is a relatively unusual occurrence, which occurred owing to the bull market's enthusiasm. Ideally, we are interested in anything that falls between the preceding two criteria. A $5-$20k investment gives ample room for X's on the listing, and is sufficient to form a really cool team and develop the product.
Education
Probability theory for trading signalsThere is a standard mathematical task. Let’s assume that six guns fired simultaneously at one target. The probability of hitting one target with one shot from one gun is 0.35 (35%); for the rest of the guns separately, the probability of hitting the target is also 0.35 (35%). We need to find the probability of at least one hit in one salvo from all guns. I believe that solution of this task can be used to find the correct moment for buy or sell signals. Let's say we have six indicators of different natures (stochastic, trend, chart pattern, volume profile, Fibonacci levels, candlestick patterns etc.) and each indicator has a relatively low win rate %, let's assume conservatively, that each indicator has 35% of win rate. If all indicators simultaneously show a buy signal, then the probability that at least one signal will be correct is calculated as follows: The probability that each signal separately is true: p1 = 35%, p2 = 35%, p3 = 35%, p4 = 35%, p5 = 35%, p6 = 35% The probability that each signal separately is false: q1 = 65%, q2 = 65%, q3 = 65%, q4 = 65%, q5 = 65%, q6 = 65% The probability that all signals will be false at the same time: P_(A) = q1 x q2 x q3 x q4 x q5 x q6 = 8% The probability that at least one signal will be true: P(A) = 1 - P_(A) = 1 – 0,08 = 0,92 (92%) So, we just confirmed obvious thing that if many indicators show the same signal simultaneously that we have higher chance to win as compared with signal of only one technical indicator. But you must be careful. - This methodology doesn’t work good in a flat market - Big players can easily steal your stop-losses because they also see these cumulative signals. - Close to 90% win-rate is not 100% win-rate, thus risk management is a must anyway - this method is quite heavy due to big volume of manual work. Important note: in order to avoid receiving too optimistic results, it’s necessary to use different types of indicators by their nature. Don’t use, for example three stochastics and five trend indicators. Correct example of indicators: 1 Fibonacci levels, 1 stochastics, 1 candlestick pattern, 1 chart pattern, 1 volume profile, 1 trend indicator. Anyway, I just made a test of this methodology for Crypto, Equity and Forex and the win-rate was about 80-90% with 80% profit after three weeks, I think that it really works.
Education
The 5 Outcomes Of a Trade | How not to blow your account Successful traders know there are 5 outcomes that can come out of a trading position. When managed well these outcomes can lead to great success. However, when manage badly can cause disaster to a trader’s account. Below I’ll highlight and discuss the possible 5 outcomes of a trade and how you can manage them. 1. Small Profit This is when a position ends in a very small profit, for trend traders, this is usually the case. However, in this situation, there is no loss. 2. Small Loss This is when you lose a small amount at the close of your position. This is part of normal and good trading. In fact, you should cut your losses early. Taking small losses or cutting your losses early will help you stay in this business long term. 3. Breakeven This is a position where you really didn’t make or lose any money. They’ll come too, they are not necessarily bad trades. These types of trades may just mean you should find re-entry to the position or may just be a quick exit without a loss or profit. 4. Big Profit This is when a position ends in a very big profit. This type of trade does not come too often but when they do come they are the trades that move your general account return for the period to the next level. As a trader, these are the type of trades you should look forward to. 5. Big Loss This is when a position ends up closing at a very big loss. This type of trade should never happen on your trading account as a pro-trader. This is the type of trade that can blow your trading account. It’s why you should know how to cut your losses quickly and take a small loss. I’m glad I’ve been able to share with you the possible outcomes of a trade and how you can manage them properly. A simple knowledge like this can suddenly turn your trading account to become profitable. Dear followers, let me know, what topic interests you for new educational posts?
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Tesla -> The Bulls Are Pushing HigherHello Traders, welcome to this free and educational multi-timeframe technical analysis . Just a couple of weeks ago Tesla stock perfectly tested and rejected a quite strong previous support zone towards the upside. However this bullish move of about 80% is still not over yet in my opinion, since we still have some room towards the upside until we retest the next resistance area. From a daily perspective I am now just waiting for a short term retracement back to the previous resistance zone which is now turned support, then I will wait for some bullish confirmation and then there is a high chance that we will see the next weekly push towards the upside. Thank you for watching and I will see you tomorrow! You can also check out my previous analysis of this asset:
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What I've learned after backtesting So, I love backtesting. Recently I've found my self in a 3% drawdown and needed to figure out what the cause of it was and trading at this moment won't give me that answer. So, I decided to backtest. Here is what I found: 1. I'm overtrading my system I am a proud swing trader who got back into scalping the market in December 2022. It was mot my idea, but I thought I could handle it. I started out great, but then the market reminded me why I left the lower timeframes. 2. I'm not holding my trades long enough. Thanks Prop Firms! Since joining a prop firm my mind has been changed to holding trades for less time than I normally would. I don't mind holding trades for weeks or months, but prop firms give you time limits during evaluation periods. That was and still is a huge adjustment for me. Being a swing trader means I have to let my profits run. So, now, I've found a prop firm that will allow me to hold my trades with no time limits. 3. Not holding trades to my weekly and monthly targets. I need to see past my daily targets. Normally my daily risk to rewards are between 1:1 and 1:2. I'm in drawdown because I'm not recovering from my losses with these risk to rewards. So now, I'm only taking trades with RR over 1:2 and better. This way I'm trading less, holding longer(sometimes), and getting the best bank for my buck. Backtesting helped me see my mistakes and how to correct them. This is called fixing your strategy. Notice how I'm not changing my strategy. I'm tweaking my strategy to fit my mental capacity and trading style. If you find you're in a drawdown and can't see, stop trading and backtest what you're currently doing and find a way to stop the behavior thats causing your drawdown. Then, stop doing that particular thing so you can see better results. I pray this has helped you. Let me know your key takeaway by commenting below.
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SPY: Trade Recap and Thoughts/Concerns Hey everyone, Today has been rushed, just got back home. Messy trade day for me and my trades were kind of disorganized but I wanted to share a brief recap and also talk about some concerns I have regarding the current PA and targets. Also sorry for the manic laughing at the beginning, I guess there was a snow storm and in the middle of recording, a huge chuck of snow fell past my window and made a huge banging sound and scared the shit out of me. I found it quite amusing afterwards. :P As always, let me know your comments/questions below! Safe trades everyone!
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