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Snaps

Your essential 20 second market digests.
BBBY
Cohen cuts the cord

Ah Mr Newton, your hypothesis has once again been proven correct as Bed Bath & Beyond’s gravity-defying rally comes to a thumping end, paving the way for a new star.

COIN
It ain’t about the gainz

Coinbase's CEO clarifies his stance on ETH staking, saying that he’s prepared to stand his ground on Ethereum regulation for the good of the network.

NG1!
Natural gas lets rip

Natural gas has been a standout in the commodities space in the last couple of weeks, as the world tries to shore up extra supplies.

APEUSD
The demise of NFTs?

The Apes are anything but Bored rn as a mass-liquidation event brews in the NFT space, with too much faith being placed in their ability to sell.

HTUSD
Huolding on for dear life

Yeah yeah we know these are getting repetitive, but yet another stablecoin has suffered a detachment from the US Dollar, the latest being a Huobi-issued coin.

DXY
“Little evidence” inflation is easing

The Fed is back at it again with the hawkish meeting minutes, this time clarifying its thoughts on the market’s hottest debate rn: whether inflation is cooling.

TOTALDEFI
The Genesis of a new CEO

Even the world’s largest crypto firms are still feeling the fallout of Terra/Luna, with crypto broker Genesis trying to mend its broken balance sheet by bringing on a new CEO.

TGT
Target reinforces the retail message

Most of the major US retailers have now reported earnings and while there’s been some mixed messaging going on, the core message of weariness is still clear.

DOGEUSD
Memecoin? How about a memechain

The newly launched Dogechain has the crypto community wondering once again – legitimate project, or yet another rugpull?

DNUT
Investors left glazed and confused

Krispy Kreme’s earnings have more holes in them than a classic dozen and investors are left with a bad taste in their mouth.

CROUSD
Fortune favors the Brits

Regulators have finally rolled over to allow Crypto.com to operate in the UK, but market downturns mean it still has some hurdles to jump.

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Ideas

China's Economy Crisis: What You Need To Know‍China is the world’s second-largest economy. If that doesn’t impress you, consider this: It has grown from a ragtag collection of state-owned firms to the world’s second-largest economy in just 35 years. China is now the world’s largest producer of goods, from smartphones to steel, autos to aircraft carriers. In 2017 alone, China produced almost as much output as the U.S., Japan, Germany, France and Britain combined. However, there are signs that China is heading for a recession. The country’s stock market has crashed twice (in July 2015 and again in January 2016), and Chinese investors have lost a lot of money as a result. There are many reasons that explain why an impending economic crash in China is imminent... China Has a Debt Problem China’s debt-to-GDP ratio (Private Sector) is now over 250%, which is extremely alarming. China’s debt problem is a ticking time bomb that could go off at any moment. As interest rates rise in the U.S., the cost of servicing the debt will become more expensive for Chinese issuers. If China continues to grow its debt at its current pace, it could easily become the next Greece or Argentina, where economic collapse is imminent. The Chinese government has tried to curb the rise in debt by tightening its domestic monetary policy. That caused the country’s stock market to plummet and its currency to depreciate. China’s aggressive money-printing has helped to fuel an emerging debt crisis that could trigger a global economic slowdown. In fact, the Bank for International Settlements (BIS) says that China’s debt-to-GDP ratio has jumped from 150% in 2008 to more than 250% today. The Chinese Yuan Is Dropping Like a Rock China’s controlled currency is starting to depreciate. And that usually occurs before an economic crash. The Chinese yuan (also known as the renminbi) has fallen more than 7.7% against the U.S. dollar since March 2022. The yuan’s decline is partly due to the trade war with the U.S. China’s central bank has been intervening in the markets to prevent the yuan from declining too quickly. That’s caused the dollar to rise against other currencies. It’s also helped to fuel a rise in Treasury yields. A strong U.S. dollar is bad for American exports. But it’s also bad for China, since a strong dollar makes it more difficult for Chinese companies to compete abroad. China’s controlled currency is starting to depreciate. And that usually occurs before an economic crash. CNH1! Manufacturing Is Slowing Down China’s manufacturing PMI has been falling for months. In July 2018, it was 48.3, which is below the 50 mark that separates growth from contraction. A number below 50 is also considered to be “bad”, while a number above 50 is “good”. The PMI reading for July 2019 was 49.7. This may sound like good news for those employed in the U.S. However, it’s not. A slowdown in the manufacturing sector usually leads to a fall in consumer spending and a slowdown in the economy. That’s because reduced consumer spending leads to fewer sales and an excess of inventory or unsold goods. That often leads to a drop in GDP. China is Producing a Lot of Empty Buildings As an economic crash approaches, developers start to build a lot of empty buildings. That’s because people start to slow down their spending and are not prepared to make the necessary financial commitments. China’s ghost cities are the canary in the coal mine. These are cities where 90% of the buildings are either vacant or incomplete. Now, it’s interesting to note that China’s ghost cities were entirely vacant as recently as 2010. At that time, few people would have predicted that China would build an entire city and have no one living in it. China's shadow banking problem is a major concern for the Chinese economy. Shadow banking refers to financial services provided outside of the traditional banking sector. These include weaker institutions such as peer-to-peer lending, pawnshops and informal lending networks. Shadow banking is often used to circumvent government restrictions on the traditional banking system, which can make it harder for the government to monitor and control the overall economy. Shadow banks are also more likely to lend to high-risk borrowers, fueling asset bubbles and economic instability. As a result, shadow banking has become increasingly important in China as the country's economic growth has slowed. Despite its importance, understanding shadow banking in China is difficult due to its complexity and lack of transparency. It is best to keep an eye on developments in this area as they could have a significant impact on the Chinese economy in coming years. China Consumer Confidence Index China Unemployment Rate Conclusion In the final analysis, there are many signs that indicate that a looming economic crash in China is imminent. Indeed, analysts expect that the country could be poised for a major economic slowdown in the near future. If this happens, it will have a negative impact on global economic growth. Investors should be careful about which companies they invest in and may want to avoid companies that are heavily reliant on the Chinese economy.
Editors' picks
9
Market Impacts of the US Mid-term ElectionsCME: S&P 500 CME_MINI:ES1! ; NYMEX: WTI NYMEX:CL1! and Henry Hub NYMEX:NG1! ; COMEX: Copper COMEX:HG1! and Aluminum COMEX:ALI1! The 2020 U.S. presidential election put Democrats in control of the White House and both branches of the Congress. In the upcoming mid-term elections, if Democrats retain their majority, Joe Biden will become the most powerful U.S. president in the 21st century. Donald Trump, his predecessor, enjoyed a Republican-led Congress in the first two years. However, after Democrats took back the House in 2018, Mr. Trump found himself fighting with Speaker Nancy Pelosi daily, all the way to a presidential impeachment in 2020. President Obama faced a divided Congress in six of eight years. The only lasting impact of his presidency may be Obamacare, besides his own legacy as the first African American president in U.S. history. United We Act, Divided We Fight Looking back on the 90 years since Franklin D. Roosevelt first became president: • We had Party Government for 44 years. The term refers to where the president, the house and the senate are controlled by the same political party. • For 14 years, we had a Divided Government , where only one branch of the Congress aligned with the president. • The remaining 32 years were Opposing Government , where the president and the Congress came from opposing parties. A divided or an opposing government tends to spend too much time on political infight. It’s difficult to reach a consensus to do big things. Major bills usually got approved in a unified government, and their impact extends far beyond the four-year presidency. For proof, we only need to look at how government spends money. In 2022, Medicare is the biggest expense item in the $6 trillion federal budget. Medicare Act was introduced in 1965 under President Johnson and a Democrat-led Congress. More than half a century later, it now costs $1.44 trillion or 24% of government spending. Social Security is the second largest expense item. The program was enacted in 1935 by a Democrat-led Congress as part of President Roosevelt’s New Deal. Social Security costs $1.13 trillion in 2022, or 19% of federal budget. Biden Administration’s Achievements What did the Biden Administration accomplish? One may point out the embarrassing retreat from Afghanistan in 2021 and the runaway inflation in 2022. However, Mr. Biden has been very effective in pushing legislative agenda. In just 1-1/2 years, four major bills with a $4 trillion total budget have been signed into law. A month after Biden took office, Congress passed a $1.9 trillion American Rescue Act on March 11, 2021. Most Americans received a $1,400 check from the Treasury Department. Millions of small businesses got approved for much needed loans. Government bailout prevented the economy from going into recession in the depths of a pandemic, even though it might have paved the groundwork for hyperinflation we are experiencing now. On November 15, 2021, Congress passed a $1.2 trillion Infrastructure Investment and Jobs Act. Among the biggest items, $110 billion are allocated to upgrade the country’s roads and bridges, $66 billion to renovate passenger and freight railways, and $65 billion to revamp the electric grid. U.S. unemployment rate stays very low this year, thanks in part to the new jobs created from government funded programs. On August 9th, Biden signed into law the U.S. Chip and Science Act, which has a $280 billion price tag for ten years. Just a week later, He approved the $737 billion Inflation Reduction Act. Most economists agree that bill has little chance of reducing inflation. The real purpose is to fund climate programs. To be budget-neutral, high-income earners will see a tax hike. Investment carry interest will be taxed. And there is a 15% minimum corporate tax. Mid-term Outcomes and their Implications to Financial Market The 2022 mid-term elections consist of 36 senate races, 435 house races, and 36 gubernatorial elections. There are thousands more at state and local government levels. Depending on their political leanings, different polling agencies have very different mid-term predictions. Here, I would like to explore the impact of the mid-term elections on financial markets based on the three states of governing: • A one-party government • A divided government • A lame duck government One-Party Government The Democrats currently control the Presidency, the House of Representatives, and the Senate. A united government could do big things and spend big money. If Biden’s party win in the midterm, the Administration would continue its path to "Build Back Better ". The Winners: • The stock market: My chart shows correlation of market turning and passage of big bills. Government investment creates jobs and supports business expansion. If you expect Democrats to win, you could express this view by a bullish equity index trade. Suggested strategy: Long CME E-Mini S&P 500 Futures. • Base Metals: Massive infrastructure programs call for more use of industrial materials. This is Bullish for NYMEX Copper and Aluminum. • Climate programs will provide more subsidies to clean energy, electric car, and new investment to support an ambitious carbon reduction goal. The Losers: • Fossil energy: Traditional oil and gas industry would face more government restrictions. This is bad for stocks in the energy sector, but Bullish for NYMEX WTI crude oil and Henry Hub natural gas. Less domestic drilling means less energy supply. • High net-worth investors: Higher tax rate on people earning $400,000 or more. New taxes on investment carry interest. This will be bad for hedge funds, private equity, and venture capital funds. • The 15% minimum corporate tax will affect multinational corporations and high-tech companies which frequently use offshore tax haven. • While government spending may help pop up the S&P, the Tech-heavy NASDAQ 100 may be a loser with the higher corporate tax rates. I am concerned about the long-term ramifications of the new taxes on innovations. Government investment could not replace the role of venture capital. The former tends to be risk-adverse and the latter has more risk appetite to fund early-stage companies. They may find ten losers before running into a blockbuster. If you cut off the incentive by taxing the winner, venture capitalists will no longer fund the Apple or Google of tomorrow. Divided Government If Republican retakes either the House or the Senate, but not both, the Administration would face challenges mainly in government spending and taxes. New legislation may be stalled at a Republican-led House or Senate. I don’t see any clear winners or losers in this scenario. The Administration would turn its focus on implementing the bills already passed, such as the CHIP Act and the Inflation Reduction Act. Fewer new legislations are on the horizon. Lame Duck Government If Democrats lose control of both the House and the Senate, we may well expect a lame duck government in the next two years. A Republican-led Congress would launch attack on “Build Back Better” and roll back progressive policies enacted by the Democrats. The Winners: • Oil and gas. Domestic drilling will resume in full speed. • The rich. New taxes will be rolled back. The Losers: • Climate programs. Funding will be stripped out or watered down. • New energy and electric car. Subsidies will be reduced and restricted. Voters have short memory. What happened in 2020 and 2021 will be ancient history. What will happen in the next two months – the economy, jobs, inflation, gas price – will dominate voters’ mode when they come out to vote on November 8th. So, it’s fair to say it is still too early to predict which state of government would prevail in the next two years. Financial market is extremely volatile this year. Getting an information edge increases your odds of success. I suggest my readers subscribe to CME market data. Tradingview users already have access to delayed data. A Pro user could upgrade to real-time CME market data for only $4 a month, a huge discount at the time of high inflation. Happy Trading. Disclaimers *Trade ideas cited above are for illustration only, as an integral part of a case study to demonstrate the fundamental concepts in risk management under the market scenarios being discussed. They shall not be construed as investment recommendations or advice. Nor are they used to promote any specific products, or services.
Editors' picks
Long
4
Bear Market Bottoms ExaminedSo many bulls and bears are stating their cases on social media as to whether or not a bottom is in so I thought I'd take some time today to examine what a daily bottoming process looks like using SPX. Standard & Poor's 500 was created in 1957 and since then it has gone through 9 bear markets (Defined as a GREATER THAN 20% decline on a CLOSING basis). 2022 will make 10 but at this point we do not know whether or not we have a bottom in place until we can break above the all time high of 4818.62 As you can see from the below charts, with the exception of Oct 1987; all the bottoms have large & steady "thrusts" IMMEDIATELY after the lows were made that held the following re-tracements IMMEDIATELY: .382 - 67% (6 out 9 bottoms- 2009, 2002, 1982, 1974,1966, 1962) .50 - 11% (1 out 9 bottoms-2020) .618 - 11% (1 out 9 bottoms- 1970) < .618 - 11% (1 out 9 bottoms-1987) Our current bottom could NOT hold the .618 immediately after the low was made therefore it falls into the category of the 1987 exception/rare case. The strongest bull cases show a thrust and then hold of a .382 re-tracement. I'm using a very basic bar chart with black bars to cut down the noise of everything, inserting a Fib Re-tracement, drawing the immediate thrust and adding the number of trading days it took to get above the last lower high. June 1962 (Approx decline: 27%) Oct 1966 (Approx decline: 22%) May 1970 (Approx decline: 33%) Oct 1974 (Approx decline: 48%) Aug 1982 (Approx decline: 27%) Oct 1987 (Approx decline: 33%) Oct 2002 (Approx decline: 47%) March 2009 (Approx decline: 56%) March 2020 (Approx decline: 32%) After looking over all these bottoms I must say the bears do present a strong case that the bottom is not yet in place. IMO, the only similar chart from a bulls perspective is the May 1970 case as it does resemble the "look" of our current bottom however look at how long it took to get above the last lower high. I hope you enjoyed this post...at a minimum it gives me one post that goes back in time to look at the daily charts of all 9 SPX bear market bottoms to analyze the look and feel of a bear market bottom since they happen so infrequently!
Editors' picks
43
What is really moving markets this summer?Want to know what I think caused this latest bear rally? This chart of SPX is broken into quarters that represent when the very large JHEQX hedge that rolls over the funds put credit spread. The funds put options netted most of the funds profit in q2 fuelled by sell offs in technology. In Q1 I thought a market wide sell off would net the fund 2B but Vanna Flows pulled the market out of a steep dive for a march rally. But high volatility in MAR from news and inflation fears forced short vol liquidations. google “When did VXX stop issuing”… march 15. I was not charting much in Q2 and didn’t do the PNL for the funds hedge but if I had to guess the put options profit was est of ~1.5B Seeing that VOL was not as high during Q2 compared to Q1, one would assume less VOL selling. This allowed markets to decline with out strong reflexive support from VOL selling (everyone buying VOL). Now that VOL is compressing and SPX has its bucket of shares volatility should return. My novice understanding of these mechanics are limited here, but my conjecture is that the price will be drawn to between 4005 - 3580. For reference, the Contract Values and costs on June 30th Sell 46,000 contracts for 3020P at -28.25 on June 30th +1.3M Buy 46,000 contracts for 3580P at +119.80 on June 30th -5.5M Sell 46,000 contracts for 4005C at -93.41 on June 30th +4.3M This is just one fund. JPM has 2 other similar funds (not as big) that roll over each quarter spaced apart by month. OI contract sizes are not as large in the other funds (10k-15k) for sequential months, but their effects on liquidity play a role at the end. Don't take this as investment advice. Do some research and draw your own conclusion.
Editors' picks
11
(8/17/22) S&P 500 Update - End of the rally soon? The S&P 500 has been rallying for over a month now. This rally was not unforeseen. The market had fallen very deep and a correction was overdue. However, we are currently approaching the 200-Day Moving Average and a key Resistance Zone. This is likely where we will start to see things slow down and likely where this rally ends. If buyers hold up, then it is likely to stay SIDEWAYS in a range between 4200 - 4400. If not, then it will likely begin the next move DOWN to a new low. *** 2022 is a BEAR market. I don't believe we've seen the bottom yet. Every rally will likely end in a bull trap and push back down further. When conditions change, then we will know that a bottom is in. Conditions have not changed yet. I will update when they do. *** In 2021, we had an insane market rally. This was largely due to money printing, Stimulus checks, not having to pay rent/mortgage, PPP loans, Student Loan forbearance, low-interest rates, etc. These were all unsustainable situations. This year, we are in a total opposite scenario. 2021's major theme was "To The Moon"... but 2022's major theme will be "Back To Earth". Safe trading & safe investing!
Editors' picks
22
Observations on Technical Verses Fundamental Analysis:Trend Following and Growth Investing In Technical Analysis (TA), trend following is the equivalent of growth investing in Fundamental Analysis (FA). Further, in TA, mean reversion analysis ("overbought" and "oversold") is the equivalent of valuation ("overvalued" & "undervalued") in FA. In both trend following and growth investing, the focus is on finding the best trends (price in TA, revenues in FA), without regard to "value". Therefore, a trend follower will hold onto a trending stock, regardless of how "overbought" it gets, much like a growth investor will hold onto a growth stock, regardless of how "overvalued" it gets. Conversely, a mean reversion investor will buy stocks that are very "oversold" relative to some anchor, such as the 200-day average or 52-week high, regardless of the direction of the trend, while a value manager will buy stocks that are "undervalued" relative to some anchor, such as earnings or book value, regardless of current fundamental performance. In other words, both mean reversion and value investors are making the case that the trends (price or earnings) have simply gone too far and are unjustified. Understandably, we can see why trend following and mean reversion don't "work" at the same time, just as growth and value don't "work" at the same time. In the end, the line in the sand between TA and FA is ego. A pure TA investor accepts the verdict of the market in terms of what it deems fundamentally "attractive" visa vie the existence of either a positive price trend in a timeframe that is driven by fundamental trends (as opposed to short term trends and noise) or a magnitude of "oversold" momentum that overlaps with historical valuation measures. A FA investor, on the other hand, invests perhaps hundreds of hours developing a personal opinion of what is "attractive", and often finds him/herself at odds with the market's verdict. Since we can never make money until the market agrees with us, we can see then how a more holistic investor who has the wisdom to unite the strengths of trend following with growth investing (or mean reversion with value investing) is better off than those who use only one of those inputs. By leaning on trend, a growth investor will know when the market agrees with his/her painstakingly curated fundamental view, particularly when things are changing, most importantly from good to bad. Behavioral bias may prevent a growth investor from seeing the change in fundamentals that is being depicted by the change in price trend. Indeed, it is in this very moment (former highflying, expensive growth stock that breaks price trend in a meaningful timeframe) when "overbought and overvalued" conditions finally start to matter. David Lundgren, CMT CFA Chief Market Strategist Co-Host "Fill the Gap" podcast 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
Education
13
Chinese Real Estate Large Cap IndexThis is an updated version of my previous "Evergrande + others" chart of Chinese real estate. Instead of including some smaller companies with longer price history, this focuses on large market cap companies. I weighted the prices against each other equally by their 42 day average, and then weighted that by the market cap: 1. Sun Hung Kai Properties (0016) HKD 268.5 billion -2.06% Sun Hung Kai Properties Limited develops and invests in properties for sale and rent in Hong Kong, Mainland China, and internationally. It...See Company Profile HKD 2. China Overseas Land & Investment (0688) HKD 252.28 billion 24.86% China Overseas Land & Investment Limited, an investment holding company, engages in the property development and investment, and treasury...See Company Profile HKD 3. China Resources Land (1109) HKD 245.3 billion 4.88% China Resources Land Limited, an investment holding company, invests, develops, manages, and sells properties in the Peoples Republic of China....See Company Profile HKD 4. China Vanke Co. (2202) HKD 235.54 billion -11.14% China Vanke Co., Ltd., a real-estate company, develops and sells properties in the Peoples Republic of China. The company operates through...See Company Profile HKD 5. CK Asset (1113) HKD 202.95 billion 13.53% CK Asset Holdings Limited operates as a property developer in Hong Kong, the Mainland, Singapore, the United Kingdom, continental Europe,...See Company Profile HKD 6. Longfor (0960) HKD 177.07 billion -20.57% Longfor Group Holdings Limited, an investment holding company, engages in property development, investment, and management businesses in China....See Company Profile HKD 7. Sino Land Co. (0083) HKD 91.07 billion 21.52% Sino Land Company Limited, an investment holding company, invests in, develops, manages, and trades in properties. It operates through six...See Company Profile HKD 8. Country Garden Co. (2007) HKD 80.22 billion -49.28% Country Garden Holdings Company Limited, an investment holding company, invests, develops, and constructs real estae properties primarily in...See Company Profile HKD 9. Greentown China (3900) HKD 40.51 billion 28.98% Greentown China Holdings Limited, an investment holding company, engages in the property development and related business in China. It operates...See Company Profile HKD 10. Yuexiu Property Co. (0123) HKD 29.82 billion 40 .17% Yuexiu Property Company Limited, together with its subsidiaries, develops, sells, and manages properties primarily in Mainland China and Hong...See Company Profile HKD source: fknol.com (Unfortunately they no longer sort by market cap by default. To view it you'll have to sign up for fknol's terrible website.) Here was the logic I used: 'a' = 42 day price average. 'b' = adjust b based on the market cap. if the market cap is larger, c gets smaller, market cap smaller, c larger. Market....a=42D_AVG.....b=a/Market_Cap_Billions --------------------------------------------------------------------------------------------- 0016.......94.14................0.3506 0688.......21.49................0.08518 1109.......35.14................0.1433 2202.......18.51................0.07858 1113.......51.73................0.2549 0960.......37.36................0.211 0083.......0.3542..............0.003889 2007.......5.662................0.07058 3900.......13.34................0.3293 0123.......0.09548............0.003202 (I had to fill in the table with dots so it would show correctly.) Now, for each row, take each market and divide by 'b': 'market1'/b1 + 'market2'/b2 + ... : '0016'/0.3506+'0688'/0.08518+'1109'/0.1433+'2202'/0.07858+'1113'/0.2549+'0960'/0.211+'0083'/0.003889+'2007'/0.07058+'3900'/0.3293+'0123'/0.003202 You can also exclude the second column, skip computing 'b', and instead divide the price by 'a' and you would have a 42 day average price weighted index. Dividing a price by an average would normalize it near 1, weighting each price equally. Does it make sense? Thanks for taking a look! Misc. Analysis: Total valuation, going by the info, is roughly 1623.26 billion HKD , which is ~200 billion USD. This is not an unusually large amount, but the importance of these companies is far beyond their numerical market cap. Chinese citizens and companies purchase properties around the world, so I think this price action goes hand in hand with global real estate, possibly with this index as a leading indicator. A large global surplus of buyers in the last few decades has pushed real estate prices everywhere to unreasonable levels and now there is a deficit of buyers. Any serious bailout will distort prices and at some point it's possible that the price action becomes useless. The CCP owns a piece of every company already so I think this would be the more probable route. Good luck and don't forget to hedge your bets!
Editors' picks
Education
8
#2 Bullish Pattern: Ascending Triangle#2 Ascending Triangle The 2nd most bullish pattern is the Ascending Triangle. The Ascending Triangle is formed after an initial trend higher and is typically a consolidation before price continues higher. The price oscillation during consolidation consists of at least 2 swing highs and 2 swing lows. Eventually price meets at the top of the triangle and a breakout occurs. It’s common for ascending triangles to have one or more false breakouts before a final price direction is achieved. Price target is determined from taking the height of the thickest end triangle. Interested in more bullish patterns? See #1 Double Bottom.
Editors' picks
15
How to improve your trading by looking at interest rates: Part 2Hey everyone! 👋 This month, we wanted to explore the topic of interest rates; what they are, why they are important, and how you can use interest rate information in your trading. This is a topic that new traders typically gloss over when starting out, so we hope this is a helpful and actionable series for new people looking to learn more about macroeconomics and fundamental analysis! Last week we took a look at how to find bond prices on our platform, as well as a few quick tips for understanding how and why interest rates move. If you'd like a quick refresher, click the link at the bottom of this post. This week, let's take a look at why understanding interest rates is important to your trading, and how you can use this info to your advantage. You can think of rates markets in three dimensions. 1.) Absolute 2.) Relative 3.) Through Time In other words; 1.) How are rates traded on an absolute basis? AKA, do they offer an attractive risk/reward for investors? 2.) How are rates traded on a relative basis? AKA, what separates bond prices between different countries? 3.) How are rates traded through time? AKA, what is the "Yield Curve"? It's worth taking a little bit of a deeper look at each of these dimensions and how they work. This week we will begin by looking at interest rates from an 'Absolute' standpoint . 🏦 When it comes to looking at bonds as an investment vehicle on this straightforward basis, investors in the broader market will typically look at how attractive bonds are from a yield / total return perspective vs. other asset classes, like equities, commodities, and cryptocurrencies. When it comes to gauging this total return question, the three main risks are important to know about: 1.) Central Bank Funds Rate risk 2.) Inflation Risk 3.) Credit Risk In other words; 1.) Will the central bank rate move in such a way that makes the interest rate I'm receiving on a bond uncompetitive? 2.) Bonds are loans with timers. Will inflation eat away at my principal in terms of buying power faster than I'm being compensated? 3.) Can my counterparty make me whole when the bond comes due? For the United States, the third question is typically "ignored" as lending money to the U.S. government is oftentimes viewed as "risk free", but in all scenarios understanding the attractiveness of bond yields over given time horizons vs. interest rates and inflation is a huge question. In addition to that, absolute risk/reward for rates needs to be compared to other asset classes. If the S&P 500 is yielding 2%, paid out from the earnings of the biggest companies in the country, then how does the risk of holding equities compare to the risks of holding bonds? Understanding how institutions are judging this decision can often be gauged by looking at the movement of interest rates in the open market. When stocks are outperforming bonds, institutional demand for stocks is higher, indicating that people are feeling good and want to take risk. When bonds are outperforming stocks, it can be indicative that people would prefer to hold 'risk free' interest payment vehicles as opposed to equity in companies with worsening economic prospects. This is the most straightforward way of looking at interest rates - how do they compare to the absolute risks in the market, and how do they compare to other "yield" streams? Do they make sense from a risk/reward perspective? One final thing - If interest rates are rising, then the amount of return needed to "compensate" for taking risk needs to get higher and higher, or other assets like equities begin to look uncompetitive. Additionally, higher interest rates mean that future cashflows are worth less, given that most valuation calculations rely on the "risk free rate". As an example, this implosion happened late last year, as people began selling bonds and interest rates began to rise. As interest rates rose, stocks that had a good chunk of their "value" priced into the future got hit the hardest, as the value of those cash flows in real terms dropped. Interest rates can help a lot for putting the big moves in the market into perspective. 😀 That's all for this week! Next week, we will take a look at how credit risk and FX risk plays into relative bond pricing, and how different sovereign bonds may or may not appear attractive to one another on a relative basis. Our final week will look at the yield curve, and how risk over time affects demand for rates. Cheers! -Team TradingView Here's last week's post if you're not caught up:
Editors' picks
Education
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Will lean hog catch up?The commodities market is a close-knit one, with the price hike in one commodity often affecting another. Such correlation is evident in agricultural products such as soybean meals, corn, and lean hogs. Lean hog prices are highly correlated with Soybean Meal and Corn as young feeder pigs are fed a diet of roughly 70% corn and 30% soybean meal. As such when corn and soybean prices rise, lean hog prices often follow suit. As spelt out in some of our previous ideas , we think agricultural commodities are due for a rally amid the backdrop of supply chain constraints arising from the Russian-Ukraine crisis, and high fertilizer costs (due to surging natural gas prices) which in turn feed into crop planting cost. Over the past 3 weeks, most agricultural products staged a rebound with Soybean Meal and Corn getting in on the action as well. The rally resulted in Corn prices up 15% and Soybean Meal prices up 10% from 3 weeks ago while lean hog prices lagged, moving only 4.4%. Thus, we think that lean hog prices have room for more upside. Looking at the chart of HEZ2022, we see the lean hog December 2022 futures breaking out of the range established from the start of the year and coming back to retest the range-high. We see this as support for lean hog prices to break up. Should agricultural commodities continue their rally, higher feed cost would be translated into high lean hog prices. Spread Entry at 90.250, stops at 87.850. Targets at 95. 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 Reference: www.cmegroup.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.
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Educational ideas

🔥Does Bitcoin follow the script? Elon Musk's manipulations?Greetings to all readers. As has been repeatedly noted, most people are not used to paying attention to the little things. However, it is this action that distinguishes them from those who strive for a much greater understanding of the market. I am publishing this idea so that you can all realize that sometimes original, non-classical methods of analysis can bring very good results. Gradually, more and more people are delving into the issue of market manipulation in one way or another. For those who are interested in how this is all determined, I will say a few words below, the rest may skip this information. each date must be viewed from all sides and find clues in the form of numerical patterns that belong to the "red" group. In this case, I determined this date as a correction date based on the connection with the manipulative number (see gematria in the screenshot). Remember these numbers. I want to say that this has nothing to do with "numerology" as you are used to seeing it. And the correction is not happening because "the numbers wanted it that way." There are deeper processes, and this is just the tip...
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7
Finding your optimal performance 🏃‍♂️Most traders spend a good bit of time looking at charts. Well here is a chart we traders should all take a look at. The chart shown is the Yerkes-Dodson Law. The Yerkes-Dodson law is a proposition that people perform best at intermediate levels of arousal, and that performance is lower at high or low levels of arousal. The theory behind this is visually represented by the graphic in this idea. No arousal levels or a bored/laidback approach to life will mean no stress but no real performance in what you are trying to achieve or do. However when arousal and stress gets too high by pushing to hard, performance starts to decrease. It's about finding the right balance to achieve an optimal performance. A certain level of stress about what you are trying to achieve motivates you to study, learn or train in order to do your best. A sportsperson has to get bumped up before an event as well as train hard, But getting to worked up and training to hard could cause a decrease in performance when it comes to the event. Pushing not hard enough to pass an exam will lead to a fail as you haven't studied or don't care, But also pushing to hard could lead to a fail as you've let stress and anxiety take over forgetting everything you studied. Moderate levels of arousal is best for overall performance. This theory can be applied to your trading. Take a non interested approach or bored approach and you performance in this area will be affected. Less potential profits etc. Get to focused on your trading or trade to hard could lead to poor performance along with a load of stress in your life. You as an individual will have to self reflect and determine where you fit on the curve in the idea graphic. If you fell more success, achievement and happiness can be had, by all means crack on and go for it! However, if you are getting to a point where you feel you might have reached your limit, it could well be time to dial it back a bit. Don’t push to hard for it that you go down the opposite side of the curve. This theory can be applied to every aspect in your life by using it to balance all aspects of your life will also help your trading as well as work, relationships and everything else we all go through day to day. Thanks for taking time to read this. Darren 🙌
Education
GoldViewFX - EXAMPLE OF EMA5 CROSS AND LOCK STRATEGYHey Everyone, As you all know we generate two types of levels the Goldturn levels (weekly), which we share to all our members and also our VIP intraday levels (daily) for premier. We then use our EMA5 cross and lock to identify targets. Please see example of our 1H chart setup and how EMA5 cross and lock confirmed the lower targets. We can see EMA5 cross 1769 Goldturn followed with another 1H candle body close below that level. This then left a gap below to the next Goldturn 1761, which was HIT perfectly. As long as we keep the levels updated our members are able to then apply this strategy to identify open targets. We use this alongside our algo setups to strengthen our signals and direction. Please don't forget to like, comment and follow to support us, we really appreciate it! GoldViewFX XAUUSD TOP AUTHOR
Education
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Wyckoff Schematics broken downBack last year I posted an educational post on the Wyckoff Distribution schematic I was seeing on Bitcoin. This was the logic behind the "Rocket Call" back last March. It was knowing where to search for an accumulation (which it was not) or a distribution. There are a couple of tell tail signs outside of Wyckoff literature that can assist in knowing which is which for various reasons (not for this post). So at the 60k marker first time around, I could see the logic for a Distribution and it revealed it's hand very early on. I wrote this educational post around the topic. Knowing Wyckoff - it's more to do with human psychology than technical analysis - many people said at the time, oh it's 100 years old, can't work in crypto etc, etc. Unfortunately as the human race, we are getting dumber and dumber, making these schematics almost more valuable in today's markets. After we had our move "Rocket" post. I covered another educational post hinting at the accumulation phase - naturally, the price drops and rises as the waves. In this post I covered the key for the terminology used in these schematics. Below you will see some info on the phases of an accumulation schematic. Accumulation Schematic Phase A The selling force decreases, and the downtrend starts to slow down. This phase is usually marked by an increase in trading volume. The Preliminary Support (PS) indicates that some buyers are showing up, but still not enough to stop the downward move. The Selling Climax (SC) is formed by an intense selling activity as investors capitulate. This is often a point of high volatility, where panic selling creates big candlesticks and wicks. The strong drop quickly reverts into a bounce or Automatic Rally (AR), as the excessive supply is absorbed by the buyers. In general, the trading range (TR) of an Accumulation Schematic is defined by the space between the SC low and the AR high. As the name suggests, the Secondary Test (ST) happens when the market drops near the SC region, testing whether the downtrend is really over or not. At this point, the trading volume and market volatility tend to be lower. While the ST often forms a higher low in relation to the SC, that may not always be the case. Phase B Based on Wyckoff’s Law of Cause and Effect, Phase B may be seen as the Cause that leads to an Effect. Essentially, Phase B is the consolidation stage, in which the Composite Man accumulates the highest number of assets. During this stage, the market tends to test both resistance and support levels of the trading range. There may be numerous Secondary Tests (ST) during Phase B. In some cases, they may produce higher highs (bull traps) and lower lows (bear traps) in relation to the SC and AR of the Phase A. Phase C A typical Accumulation Phase C contains what is called a Spring. It often acts as the last bear trap before the market starts making higher lows. During Phase C, the Composite Man ensures that there is little supply left in the market, i.e., the ones that were to sell already did. The Spring often breaks the support levels to stop out traders and mislead investors. We may describe it as a final attempt to buy shares at a lower price before the uptrend starts. The bear trap induces retail investors to give up their holdings. In some cases, however, the support levels manage to hold, and the Spring simply does not occur. In other words, there may be Accumulation Schematics that present all other elements but not the Spring. Still, the overall scheme continues to be valid. Phase D The Phase D represents the transition between the Cause and Effect. It stands between the Accumulation zone (Phase C) and the breakout of the trading range (Phase E). Typically, the Phase D shows a significant increase in trading volume and volatility. It usually has a Last Point Support (LPS), making a higher low before the market moves higher. The LPS often precedes a breakout of the resistance levels, which in turn creates higher highs. This indicates Signs of Strength (SOS), as previous resistances become brand new supports. Despite the somewhat confusing terminology, there may be more than one LPS during Phase D. They often have increased trading volume while testing the new support lines. In some cases, the price may create a small consolidation zone before effectively breaking the bigger trading range and moving to Phase E. Phase E The Phase E is the last stage of an Accumulation Schematic. It is marked by an evident breakout of the trading range, caused by increased market demand. This is when the trading range is effectively broken, and the uptrend starts. There is an awful lot more when it comes to understanding Wyckoff - such as volume, but it is too much to put in a handful of posts. These posts are done to give you an insight into trading Wyckoff. Another useful post on this topic is this below; People tend to look at Wyckoff on a Tick chart, a 1min or 15 minute chart - the same rules apply and are potentially more beneficial and applicable on the higher timeframes, seeing a weekly move play out in terms of a schematic could take several months. It's all about knowing what to look for. Disclaimer This idea does not constitute as financial advice. It is for educational purposes only, our principle trader has over 20 years’ experience in stocks, ETF’s, and Forex. Hence each trade setup might have different hold times, entry or exit conditions, and will vary from the post/idea shared here. You can use the information from this post to make your own trading plan for the instrument discussed. Trading carries a risk; a high percentage of retail traders lose money. Please keep this in mind when entering any trade. Stay safe.
Education
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Simple trading setup from swing range- Determine directional bias from HTF - Find high/low trading range from previous day - Drawn in fib level to see premium/discount zone for entry - Spot CHoCH in different direction of HTF (Potential to grab liquidity) - Wait and see Price action with HTF bias (In this case is bearish) - Price entered premium zone for open short position - Wait for lower time frame BOS before entry - Target imbalance zone/ Previous key level low/ Fair value gap (RR 2.65, not bad, since we get entry outside premium zone but more confirmation)
Education
CSC-HARSI with Alerts for GO long or Short and when to BUYWelcome to the coffee shop everybody I am highly highly highly excited about the new developments taking place with the CoffeeShop Crypto HARSI 2022 Don't let the name of the indicator fool you it can be used on more than just crypto you can use it on all markets or any markets that you choose to use it on. As you know the indicator was released sometime ago and I really want to give a big thank you to all the people who come through Boost the script as well as use it on their charts it's really nice to see you guys doing that and I want to let you know that I get information I get indications of that taking place and I do make sure to follow you because I want to know what it is that you're up to and I want you to see what I'm up to. okay now that we're done with the introductions and all the salutations and make you feel good about yourselfes let's get into what's happening with the CSC-HARSI. Make sure to take a look at the attached video above because you're going to see and hear me discussing the new implementation of 2 types of alerts and indications that show up on the indicator itself. One indication is when it is going to be telling you to Bi-Lo another indication is going to be when it tells you to go long. That is related to people who want to go bullet in the market and Buy Low sell High. "Bi-Lo" Means that the trend is about to reverse or that if you're in a ranging Market you can buy at this very low price. Shortly after that you'll end up getting another indication saying "Go long". This means that you've already bought at the lowest possible price in a safe place and now when it says go long you can set your trade and take profit levels. So "Buy Lo" does not mean enter into the market and set your take profit it simply means that you buy shares at a low price. The other indications that will show up will be simply the reverse of that. One would say "Buy Hi" which means you just accumulate shares or coins or what have you so that you can short them later on. A little while after that you'll get another Indication that says "go Short". This means that you've already accumulated shares at a high value and now you're going to "short" them. In the attached video you'll be able to see how to use the coffee shop crypto and when and how do you use these two separate alerts for example "Bi-Lo" and "Go-Long" or "Buy-Hi" and "Go-Short" As of the recording of this video in the publication of this idea do not look for the information related to that in the coffee shop crypto heart see this is simply an idea to let you know what's coming up next. So in the meantime go ahead add to your favorites from this link and add it to your chart and when I published the new version of the code which will be with somewhere in the next 24 hours I hope you'll get an indication from tradingview and it'll say hey has been an update to this script go and get the new one. At which point you would simply delete the coffee shop crypto from your trading chart, then you would end up going to the Community Scripts and typing in CoffeeShop Crypto 2022 And re-add it to your chart. So again make sure you watch the video that's attached and if you have any questions go ahead and drop them below if you just simply excited about it go ahead link a comment about that below as well.
Education
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📉Bollinger Bands-RSI Strategy⚔Hello Dear Friends How can we use Bollinger Bands and RSI (Relative Strength Index) together? Bollinger Bands I shared an article about Bollinger Bands, you can check it out. The logic of Bollinger Bands is simple, there are two bands at the top and bottom where the standard deviation of the price is added and subtracted. In the middle is a moving average. *A rising price usually moves between the moving average and the upper line of the band. *A falling price usually moves between the moving average and the lower line of the band. *When the price touches the upper line of the band, it is expected to decrease to the moving average in the middle. *When the price touches the lower line of the band, it is expected to rise up to the moving average in the middle. RSI(Relative Strength Index) It is the graphed version of the acceleration of the price movement. *Above 70 means overbought. *Below 30 means oversold. *A value cut below 50 is a sell signal. *50 value cut upwards is a buy signal. If you are using the RSI in conjunction with a moving average. *Closing the moving average downwards is a sell signal. *It is a buy signal when the moving average crosses upwards. Now if we examine the EUR/USD chart; In general, candlesticks and train lines are more important to me. After the price came to the train resistance, a pinbar candle was formed; The next day created a red falling candle. The price made the candle formation when it touched the upper line of the Bollinger Band. The RSI has crossed the 50 level downwards and sagged below the moving average. Besides, there is discord in the RSI. Price is below the previous high while the RSI is above the previous high. ***In order for the formations in the indicators and indicators to work, the price trend must return. Otherwise, all signals may be traps.
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What is liquidity gap? Why there is always pump?🚀 When the bull market start with a good news? It`s always bad news at the beginning of the uptrend: in 2015, 2019, 2020. Always the same situation. And now we a here in 2022 and bad news at the bottom of the market. Push 🚀 if it looks similar to other cycles. In this idea i explain you what is liquidity gap and global situation on BTC. You can identify it using the Volume Profile which is default tool at TradingView. 📊Liquidity gap is an area where the price not stay for the long time and don`t create any levels or order flows. So as you understand there are areas without any liquidity where the traders can set a sl or tp. We can compare it with empty space where is no life or it`s really rare thing. The price break this areas so easy because there are no liquidity and the price: 🔥 have no support if it falls (as it was when BTC fall in a week from $29k to 17k few month ago) 🔥 have no resistance if it growth (as it was at any bull market when the price nreak the ATH and scyrocketing) Now the price of BTC consolidating below such liquidity gap of $24500-29500 and going to break it up after some accumulation. As a rule, the liquidity gap breaking with a pumps because nothing stop them inside this gaps. The top of this gap is a bottom of a huge consolidation channel $29500-69000, so the price can make a pullback after $29500 test. In final, price break this level and continue it`s growth to the previous ATH. Thanks in large part to consolidation at the bottom, where the bulls were able to accumulate enough Bitcoins and are ready to sell them higher and higher. Consolidation is always good for the bulls especially for the biggest one 🐳 📊Why are these white circles marked? It's a bonus for my subscribers. Remember that before the very PUMP you will think everything will fall to zero, and many analysts on the trading view will say that the price has created a bear flag or a wedge etc. At that point, you may be disappointed and afraid to open a trade or sell all your crypto, but that will only be an emotion you should not succumb to. Only if your strategy says so. Keep these words in mind. 🔥 I will open a trade if I will see the large whales orders on DOM and Footprint. These are usually the most profitable trades with a short stop loss and excellent risk to reward. 💻Friends, press the "boost"🚀 button, write comments and share with your friends - it will be the best THANK YOU. P.S. Personally, I open an entry if the price shows it according to my strategy. Always do your analysis before making a trade.
Education
2
How to manage Capital in an Economic DownturnThe Great Recession is not the first time that the economy has experienced downturn or recession. The last one occurred during the early 1980s, and it caused unemployment to spike and home prices to drop. However, that doesn’t mean that a similar situation cannot happen again. The effects of a recession have lasting implications for consumers and businesses. When consumers have less money to spend on goods and services, businesses must make adjustments in order to remain profitable. In fact, recessions can lead to innovation in industries like technology where creative minds come up with cheaper solutions for everyday problems. Here’s a look at how consumers are affected by recessions, what they’re doing about it, as well as how you can manage your money in these challenging times. What Happens When the Economy Recovers? When the economy recovers from a recession, there are typically two ways that consumers spend their money. One way is that consumers continue to spend on the same products and services that they bought before the recession. The other spending trend that occurs during a recovery is that consumers change the products and services that they spend money on. The reason for this change in spending habits is that consumers have changed their priorities during the recession. When a recession has caused consumers to have less disposable income, they tend to make their money go further. When consumers have less disposable income, they can no longer afford to spend money on certain products and services. The Impact of a Recession on Consumers A recession can have a lasting impact on consumers. Consumers who experience a recession tend to have less confidence in their ability to manage their money. This can cause lasting damage to their credit scores as they seek out lower interest loans or take out a repayment plan. A recession can also impact a consumer’s career and ability to earn a living wage. When a recession occurs, businesses have to make changes to remain profitable. This might include laying off employees or reducing the hours that part-time workers are scheduled for. A recession can impact consumers’ ability to buy a home as well. Mortgage rates tend to be higher during a recession as investors seek out higher returns because of the increased risk of default. Consumer Responses During a Recession When a recession occurs, consumers are likely to make changes to their spending habits in order to save money. The first thing that consumers are likely to do is reduce discretionary spending. Discretionary spending is the money that is spent on entertainment activities, eating out at restaurants, shopping for luxury items, and on travel. Another common response of consumers during a recession is to change how they get their services. When a recession occurs, consumers are likely to change how they get their banking, insurance , and healthcare services as well as how they pay their bills. How Consumers Can Manage Their Money in a Recession The best way for consumers to manage their money during a recession is to make a budget. A budget for spending should include all of the money that goes out of your bank account each month as well as how much money comes into your account. When making a budget, it is important to consider your expenses and income to see if there is any room in your budget to make changes. This can include looking at your monthly expenses and trying to reduce the amount that you spend on certain items. When you are making a budget, it is important to keep in mind that you will have to change it as time goes on. As your income changes, you may have more or less money available to spend each month. Likewise, you may also have more or less expenses to pay each month. Investing in the Stock Market: The stock market is one of the riskiest investments you can make. It’s also one of the most profitable when things go right. The stock market has its ups and downs, but it always rebounds in the long run. Even during a recession, savvy investors know how to make money in the stock market by investing in stocks and other types of securities. Investing in the stock market may seem intimidating at first, but it’s not as complicated as you think! In this Educational article, we’ll show you how to invest in the stock market if you have less than $5,000 to invest. With these tips and tricks to invest in a recession, you’ll be on your way to becoming a successful investor with an impressive portfolio sooner than you think! How to invest in the stock market with $5,000 Before you dive head first into the stock market, it’s important to know how much you have to invest. While the stock market can be rewarding, it’s also one of the riskiest investments you can make. Investing in the stock market is all about risk and reward — the more risk you take, the bigger your reward can be. Investing in the stock market requires at least $5,000 in order to diversify your portfolio. Diversification is key to long-term success in the stock market. Rather than putting all of your eggs in one basket, diversification allows you to spread your funds across many different investments. Diversification is key When you’re investing in the stock market, it’s important to diversify your portfolio. Diversification allows you to spread your funds across many different investments for two reasons: risk reduction and opportunity enhancement. Risk reduction is accomplished by not putting all of your funds into one investment. Instead, you’re spreading the funds across different types of investments. Opportunity enhancement allows you to take advantage of different types of growth opportunities. Understand why you’re investing Before you invest in the stock market, it’s important to understand why you’re investing in the first place. If you’re investing for growth, you’re looking for stocks that are currently undervalued to increase in value over time. If you’re investing for income, you’re looking for stocks that pay dividends. Take advantage of no-fee investments When you invest in the stock market, you pay fees for the management of your portfolio. Mutual funds and exchange-traded funds (ETFs) are mutual funds that are pre-packaged and purchased as a single unit. Mutual funds are professionally managed funds that are offered by financial institutions, whereas ETFs are professionally managed funds that are traded on a stock exchange. If you’re investing a small amount of money in the stock market, you’re better off choosing mutual funds or ETFs that have no or low management fees. Mutual funds and ETFs with no or low management fees are often referred to as no-load funds. Shorting ETFs can be profitable (This strategy is best suitable for Professional Traders) Shorting ETFs can be profitable if you’re investing a large amount of money in the stock market. Shorting ETFs allows you to profit from a declining market. Shorting ETFs is a very risky investment strategy and is not recommended for beginners. If you’re interested in shorting ETFs, be sure to talk to a financial advisor before making any investments. Additional Note: When the global economy is on the verge of recession, investors are scared and their first thought is to run towards things that are safe. In recent years, markets have grown to distrust risky investments such as stocks and other volatile assets. When the global economy is about to go into recession, commodities like gold and oil usually become hot properties for investors wanting to preserve their capital. There are a number of asset classes that thrive during a recession: real estate, bonds, and value stocks—or anything with a low correlation to the stock market. However, at the same time there are also some that suffer: high-beta stocks; growth stocks; growth real estate; luxury goods; emerging market equities; and anything else with a high correlation to the stock market. In our next article we will analyze Gold and Silver as an hedge against inflation and their performance in an economic downturn. Conclusion The recession that took place in the early 2000s is a great example of how a recession can change the way consumers spend their money. During this recession, consumers were likely to spend more money on food and clothing since those were necessities that consumers could not do without. When the next recession occurs, consumers may change their spending habits once again. However, it is important to remember that a recession is a natural part of the business cycle. It is likely that consumers will continue to spend their money in the future even in the face of a recession. Investing in the stock market is a smart way to diversify your investment portfolio. It’s also a great way to earn passive income through dividends. The best way to invest in the stock market if you have less than $5,000 to invest is through mutual funds or ETFs with no or low management fees. Shorting ETFs can also be a great way to make money in a recession if you have a large amount of funds to invest. Even though the technical definition of a recession has been changed/modified it is important to know that unemployment rate determines the condition of a recession.
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Pine Scripts

R:R Trading System FrameworkFirst off, huge thanks to @fikira! He was able to adapt what I built to work much more efficiently, allowing for more strategies to be used simultaneously. Simply put, I could not have gotten to this point without you. Thanks for what you do for the TV community. Second, I am fairly new to pinescript writing, so I welcome criticism, thoughtful input and improvement suggestions. I would love to grow this concept into something even better, if possible. So please let me know if you have any ideas for improvement. However I do juggle a lot of different things outside of TV, so implementations may be delayed. I have decided, at this time, not to add alerts. First, because I feel most people looking to adapt this framework can add their own pretty easily. Also, given how customized the framework is currently, while also attempting to account for all the possible ways in which people may want alerts to function after they customize it, it seems best to leave them out as it doesn't exactly fit the idea of a framework. For best viewing, I recommend hovering over the script's name > ... > Visual order > Bring to front. Also I found hollow candles with mono-toned colors (like pictured) are more visually appealing for me personally. I HIGHLY RECOMMEND USING WITH BAR REPLAY TO BETTER UNDERSTAND THE FRAMEWORK'S FUNCTIONALITY. ▶️ WHAT THIS FRAMEWORK IS - A huge collection of concepts and capabilities for those trying to better understand, learn, or teach pinescript. - A system designed to showcase Risk:Reward concepts more holistically by providing all of the most popular components of retail trading to include backtesting, trade visual plotting, position tracking, market condition shifts, and useful info while positioned to help highlight changes in your risk:reward based decision-making processes. - A system that can showcase individual strategies regardless of trade direction, allowing you to develop hedging strategies without having multiple indicators that do not correlate with each other. - Designed around the idea that you trade less numbers of assets but manage your positions and risk based on multiple concurrently running strategies to manage your risk exposure and reward potential. - An attempt to combine all the things you need to execute with an active trading management style. - A framework that uses backtested results (in this case the number of averaged bars it takes to hit key levels) in real-time to inform your risk:reward decision-making while in-trade (in this case in your Trade Tracking Table using dynamic color to show how you might be early, on-time, or late compared to the average amount of backtested time it normally takes to hit that specific key level). ▶️ WHAT THIS FRAMEWORK IS NOT - A complete trading product. DO NOT USE as-is. It is a FRAMEWORK for you to generate ideas of your own and fairly easily implement your own triggering conditions in the appropriate sections of the script. ▶️ USE CASES - If you decide you like the Stop, Target, Trailing Stop, and Risk:Reward components as-is, then just understanding how to plug in your Entry and Bullish / Bearish conditions (Triangles) and adjust the input texts to match your custom naming will be all you need to make it your own! - If you want to adapt certain components, then this system gives you a great starting point to adapt your different concepts and ideas from. ▶️ SYSTEM COMPONENTS - Each of the system's components are described via tooltips both in the input menu and in the tables' cells. - Each label on the chart displays the corresponding price at those triggered conditions on hover with tooltips. - The Trailing Stop only becomes active once it is above the Entry Price for that trade, and brightens to show it is active. The STOP line (right of price) moves once it takes over for the Entry Stop representing the level of the Trailing Stop at that time for that trade. - The Lines / Labels to the right of price will brighten once price is above for Longs or below for Shorts. The Trade Tracking Table cells will add ☑️ once price is above for Longs or below for Shorts. - The brighter boxes on the chart show the trades that occurred based on your criteria and are color coded for all components of each trade type to ensure your references are consistent. (Defaults are TV built-in strategies) - The lighter boxes on the chart show the highest and lowest price levels reached during those trades, to highlight areas where improvements can be made or additional considerations can be accounted for by either adjusting Entry triggers or Bullish / Bearish triggers. - Default Green and Red Triangles (Bullish / Bearish) default to having the same triggering condition as the Entry it corresponds to. This is to highlight either a pyramiding concept, early exit, or you can change to account for other things occurring during your trades which could help you with Stop and Target management/considerations. TradingView and many of its community members have done a lot for me, so this is my attempt to give back.
Editors' picks
Pine Script™ indicator
21
Bjorgum Double Tap█   OVERVIEW Double Tap is a pattern recognition script aimed at detecting Double Tops and Double Bottoms. Double Tap can be applied to the broker emulator to observe historical results, run as a trading bot for live trade alerts in real time with entry signals, take profit, and stop orders, or to simply detect patterns. █   CONCEPTS How Is A Pattern Defined? Doubles are technical formations that are both reversal patterns and breakout patterns. These formations typically have a distinctive “M” or a “W” shape with price action breaking beyond the neckline formed by the center of the pattern. They can be recognized when a ​pivot fails to break when tested for a second time and the retracement that follows breaks beyond the key level opposite. This can trap entrants that were playing in the direction of the prior trend. Entries are made on the breakout with a target projected beyond the neckline equal to the height of the pattern. Pattern Recognition Patterns are recognized through the use of ​zig-zag; a method of filtering price action by connecting swing highs and lows in an alternating fashion to establish trend, ​support and resistance, or derive shapes from price action. The script looks for the highest or lowest point in a given number of bars and updates a list with the values as they form. If the levels are exceeded, the values are updated. If the direction changes and a new significant point is made, a new point is added to the list and the process starts again. Meanwhile, we scan the list of values looking for the distinctive shape to form as previously described. █   STRATEGY RESULTS Back Testing Historical back testing is the most common method to test a strategy due in part to the general ease of gathering quick results. The underlying theory is that any strategy that worked well in the past is likely to work well in the future, and conversely, any strategy that performed poorly in the past is likely to perform poorly in the future. It is easy to poke holes in this theory, however, as for one to accept it as gospel, one would have to assume that future results will match what has come to pass. The randomness of markets may see to it otherwise, so it is important to scrutinize results. Some commonly used methods are to compare to other markets or benchmarks, perform statistical analysis on the results over many iterations and on differing datasets, walk-forward testing, out-of-sample analysis, or a variety of other techniques. There are many ways to interpret the results, so it is important to do research and gain knowledge in the field prior to taking meaningful conclusions from them. 👉  In short, it would be naive to place trust in one good backtest and expect positive results to continue. For this reason, results have been omitted from this publication. Repainting Repainting is simply the difference in behaviour of a strategy in real time vs the results calculated on the historical dataset. The strategy, by default, will wait for confirmed signals and is thus designed to not repaint. Waiting for bar close for entires aligns results in the real time data feed to those calculated on historical bars, which contain far less data. By doing this we align the behaviour of the strategy on the 2 data types, which brings significance to the calculated results. To override this behaviour and introduce repainting one can select "Recalculate on every tick" from the properties tab. It is important to note that by doing this alerts may not align with results seen in the strategy tester when the chart is reloaded, and thus to do so is to forgo backtesting and restricts a strategy to forward testing only. 👉  It is possible to use this script as an indicator as opposed to a full strategy by disabling "Use Strategy" in the "Inputs" tab. Basic alerts for detection will be sent when patterns are detected as opposed to complex order syntax. For alerts mid-bar enable "Recalculate on every tick" , and for confirmed signals ensure it is disabled. █   EXIT ORDERS Limit and Stop Orders By default, the strategy will place a stop loss at the invalidation point of the pattern. This point is beyond the pattern high in the case of Double Tops, or beneath the pattern low in the case of Double Bottoms. The target or take profit point is an equal-legs measurement, or 100% of the pattern height in the direction of the pattern bias. Both the stop and the limit level can be adjusted from the user menu as a percentage of the pattern height. Trailing Stops Optional from the menu is the implementation of an ATR based trailing stop. The trailing stop is designed to begin when the target projection is reached. From there, the script looks back a user-defined number of bars for the highest or lowest point +/- the ATR value. For tighter stops the user can look back a lesser number of bars, or decrease the ATR multiple. When using either Alertatron or Trading Connector, each change in the trail value will trigger an alert to update the stop order on the exchange to reflect the new trail price. This reduces latency and slippage that can occur when relying on alerts only as real exchange orders fill faster and remain in place in the event of a disruption in communication between your strategy and the exchange, which ensures a higher level of safety. 👉  It is important to note that in the case the trailing stop is enabled, limit orders are excluded from the exit criteria. Rather, the point in time that the limit value is exceeded is the point that the trail begins. As such, this method will exit by stop loss only. █   ALERTS Five Built-in 3rd Party Destinations The following are five options for delivering alerts from Double Tap to live trade execution via third party ​API solutions or chat bots to share your trades on social media. These destinations can be selected from the input menu and alert syntax will automatically configure in alerts appropriately to manage trades. Custom JSON JSON, or JavaScript Object Notation, is a readable format for structuring data. It is used primarily to transmit data between a server and a web application. In regards to this script, this may be a custom intermediary web application designed to catch alerts and interface with an exchange ​API. The JSON message is a trade map for an application to read equipped with where its been, where its going, targets, stops, quantity; a full diagnostic of the current state and its previous state. A web application could be configured to follow the messages sent in this format and conduct trades in sync with alerts running on the TV server. Below is an example of a rendered JSON alert: { "passphrase": "1234", "time": "2022-05-01T17:50:05Z", "ticker": "ETHUSDTPERP", "plot": { "stop_price": 2600.15, "limit_price": 3100.45 }, "strategy": { "position_size": 0.1, "order_action": "buy", "market_position": "long", "market_position_size": 0, "prev_market_position": "flat", "prev_market_position_size": 0 } } Trading Connector Trading Connector is a third party fully autonomous Chrome extension designed to catch alert webhooks from TradingView and interface with MT4/MT5 to execute live trades from your machine. Alerts to Trading Connector are simple; just select the destination from the input drop down menu, set your ticker in the "TC Ticker" box in the "Alert Strings" section and enter your URL in the alert window when configuring your alert. Alertatron Alertatron is an automated algo platform for cryptocurrency trading that is designed to automate your trading strategies. Although the platform is currently restricted to crypto, it offers a versatile interface with high flexibility syntax for complex market orders and conditions. To direct alerts to Alertatron, select the platform from the 3rd party drop down, configure your ​API key in the ”Alertatron Key” box and add your URL in the alert message box when making alerts. 3 Commas 3 Commas is an easy and quick to use click-and-go third party crypto ​API solution. Alerts are simple without overly complex syntax. Messages are simply pasted into alerts and executed as alerts are triggered. There are 4 boxes at the bottom of the "Inputs" tab where the appropriate messages to be placed. These messages can be copied from 3 Commas after the bots are set up and pasted directly into the settings menu. Remember to select 3 Commas as a destination from the third party drop down and place the appropriate URL in the alert message window. Discord Some may wish to share their trades with their friends in a Discord chat via webhook chat bot. Messages are configured to notify of the pattern type with targets and stop values. A bot can be configured through the integration menu in a Discord chat to which you have appropriate access. Select Discord from the 3rd party drop down menu and place your chat bot URL in the alert message window when configuring alerts. 👉  For further information regarding alert setup, refer to the platform specific instructions given by the chosen third party provider. █   IMPORTANT NOTES Setting Alerts For alert messages to be properly delivered on order fills it is necessary to place the following placeholder in the alert message box when creating an alert. {{strategy.order.alert_message}} This placeholder will auto-populate the alert message with the appropriate syntax that is designated for the 3rd party selected in the user menu. Order Sizing and Commissions The values that are sent in alert messages are populated from live metrics calculated by the strategy. This means that the actual values in the "Properties" tab are used and must be set by the user. The initial capital, order size, commission, etc. are all used in the calculations, so it is important to set these prior to executing live trades. Be sure to set the commission to the values used by the exchange as well. 👉  It is important to understand that the calculations on the account size take place from the beginning of the price history of the strategy. This means that if historical results have inflated or depleted the account size from the beginning of trade history until now, the values sent in alerts will reflect the calculated size based on the inputs in the "Properties" tab. To start fresh, the user must set the date in the "Inputs" tab to the current date as to remove trades from the trade history. Failure to follow this instruction can result in an unexpected order size being sent in the alert. █   FOR PINECODERS  • With the recent introduction of matrices in Pine, the script utilizes a matrix to track ​pivot points with the bars they occurred on, while tracking if that ​pivot has been traded against to prevent duplicate detections after a trade is exited.  • Alert messages are populated with placeholders ; capability that previously was only possible in alertcondition() , but has recently been extended to `strategy.*()` functions for use in the `alert_message` argument. This allows delivery of live trade values to populate in strategy alert messages.  • New arguments have been added to strategy.exit() , which allow differentiated messages to be sent based on whether the exit occurred at the stop or the limit. The new arguments used in this script are `alert_profit` and `alert_loss` to send messages to Discord
Editors' picks
Pine Script™ strategy
39
Fourier Extrapolator of Price w/ Projection Forecast [Loxx]Due to popular demand, I'm pusblishing Fourier Extrapolator of Price w/ Projection Forecast.. As stated in it's twin indicator, this one is also multi-harmonic (or multi-tone) trigonometric model of a price series xi, i=1..n, is given by: xi = m + Sum( a*Cos(w*i) + b*Sin(w*i), h=1..H ) Where: xi - past price at i-th bar, total n past prices; m - bias; a and b - scaling coefficients of harmonics; w - frequency of a harmonic ; h - harmonic number; H - total number of fitted harmonics. Fitting this model means finding m, a, b, and w that make the modeled values to be close to real values. Finding the harmonic frequencies w is the most difficult part of fitting a trigonometric model. In the case of a Fourier series, these frequencies are set at 2*pi*h/n. But, the Fourier series extrapolation means simply repeating the n past prices into the future. This indicator uses the Quinn-Fernandes algorithm to find the harmonic frequencies. It fits harmonics of the trigonometric series one by one until the specified total number of harmonics H is reached. After fitting a new harmonic , the coded algorithm computes the residue between the updated model and the real values and fits a new harmonic to the residue. see here: A Fast Efficient Technique for the Estimation of Frequency , B. G. Quinn and J. M. Fernandes, Biometrika, Vol. 78, No. 3 (Sep., 1991), pp . 489-497 (9 pages) Published By: Oxford University Press The indicator has the following input parameters: src - input source npast - number of past bars, to which trigonometric series is fitted; Nfut - number of predicted future bars; nharm - total number of harmonics in model; frqtol - tolerance of frequency calculations. The indicator plots two curves: the green/red curve indicates modeled past values and the yellow/fuchsia curve indicates the modeled future values. The purpose of this indicator is to showcase the Fourier Extrapolator method to be used in future indicators.
Editors' picks
Pine Script™ indicator
31
VisibleChart█   OVERVIEW This library is a Pine programmer’s tool containing functions that return values calculated from the range of visible bars on the chart. This is now possible in Pine Script™ thanks to the recently-released chart.left_visible_bar_time and chart.right_visible_bar_time built-ins, which return the opening time of the leftmost and rightmost bars on the chart. These values update as traders scroll or zoom their charts, which gives way to a class of indicators that can dynamically recalculate and draw visuals on visible bars only, as users scroll or zoom their charts. We hope this library's functions help you make the most of the world of possibilities these new built-ins provide for Pine scripts. For an example of a script using this library, have a look at the Chart ​VWAP indicator. █   CONCEPTS Chart properties The new chart.left_visible_bar_time and chart.right_visible_bar_time variables return the opening time of the leftmost and rightmost bars on the chart. They are only two of many new built-ins in the `chart.*` namespace. See this blog post for more information, or look up them up by typing "chart." in the Pine Script™ Reference Manual . Dynamic recalculation of scripts on visible bars Any script using chart.left_visible_bar_time or chart.right_visible_bar_time acquires a unique property, which triggers its recalculation when traders scroll or zoom their charts in such a way that the range of visible bars on the chart changes. This library's functions use the two recent built-ins to derive various values from the range of visible bars. Designing your scripts for dynamic recalculation For the library's functions to work correctly, they must be called on every bar. For reliable results, assign their results to global variables and then use the variables locally where needed — not the raw function calls. Some functions like `barIsVisible()` or `open()` will return a value starting on the leftmost visible bar. Others such as `high()` or `low()` will also return a value starting on the leftmost visible bar, but their correct value can only be known on the rightmost visible bar, after all visible bars have been analyzed by the script. You can plot values as the script executes on visible bars, but efficient code will, when possible, create resource-intensive labels, lines or tables only once in the global ​scope using var , and then use the setter functions to modify their properties on the last bar only. The example code included in this library uses this method. Keep in mind that when your script uses chart.left_visible_bar_time or chart.right_visible_bar_time , your script will recalculate on all bars each time the user scrolls or zooms their chart. To provide script users with the best experience you should strive to keep calculations to a minimum and use efficient code so that traders are not always waiting for your script to recalculate every time they scroll or zoom their chart. Another aspect to consider is the fact that the rightmost visible bar will not always be the last bar in the dataset. When script users scroll back in time, a large portion of the time series the script calculates on may be situated after the rightmost visible bar. We can never assume the rightmost visible bar is also the last bar of the time series. Use `barIsVisible()` to restrict calculations to visible bars, but also consider that your script can continue to execute past them. █   FUNCTIONS The library contains the following functions: barIsVisible()   Condition to determine if a given bar is within the users visible time range.   Returns: (bool) True if the the calling bar is between the `chart.left_visible_bar_time` and the `chart.right_visible_bar_time`. high()   Determines the value of the highest `high` in visible bars.   Returns: (float) The maximum high value of visible chart bars. highBarIndex()   Determines the `bar_index` of the highest `high` in visible bars.   Returns: (int) The `bar_index` of the `high()`. highBarTime()   Determines the bar time of the highest `high` in visible bars.   Returns: (int) The `time` of the `high()`. low()   Determines the value of the lowest `low` in visible bars.   Returns: (float) The minimum low value of visible chart bars. lowBarIndex()   Determines the `bar_index` of the lowest `low` in visible bars.   Returns: (int) The `bar_index` of the `low()`. lowBarTime()   Determines the bar time of the lowest `low` in visible bars.   Returns: (int) The `time` of the `low()`. open()   Determines the value of the opening price in the visible chart time range.   Returns: (float) The `open` of the leftmost visible chart bar. close()   Determines the value of the closing price in the visible chart time range.   Returns: (float) The `close` of the rightmost visible chart bar. leftBarIndex()   Determines the `bar_index` of the leftmost visible chart bar.   Returns: (int) A `bar_index`. rightBarIndex()   Determines the `bar_index` of the rightmost visible chart bar.   Returns: (int) A `bar_index` bars()   Determines the number of visible chart bars.   Returns: (int) The number of bars. volume()   Determines the sum of volume of all visible chart bars.   Returns: (float) The cumulative sum of volume. ohlcv()   Determines the open, high, low, close, and volume sum of the visible bar time range.   Returns: ( ) A tuple of the OHLCV values for the visible chart bars. Example: open is chart left, high is the highest visible high, etc. chartYPct(​pct)   Determines a price level as a percentage of the visible bar price range, which depends on the chart's top/bottom margins in "Settings/Appearance".   Parameters:      pct : (series float) Percentage of the visible price range (50 is 50%). Negative values are allowed.   Returns: (float) A price level equal to the `pct` of the price range between the high and low of visible chart bars. Example: 50 is halfway between the visible high and low. chartXTimePct(​pct)   Determines a time as a percentage of the visible bar time range.   Parameters:      pct : (series float) Percentage of the visible time range (50 is 50%). Negative values are allowed.   Returns: (float) A time in UNIX format equal to the `pct` of the time range from the `chart.left_visible_bar_time` to the `chart.right_visible_bar_time`. Example: 50 is halfway from the leftmost visible bar to the rightmost. chartXIndexPct(​pct)   Determines a `bar_index` as a percentage of the visible bar time range.   Parameters:      pct : (series float) Percentage of the visible time range (50 is 50%). Negative values are allowed.   Returns: (float) A time in UNIX format equal to the `pct` of the time range from the `chart.left_visible_bar_time` to the `chart.right_visible_bar_time`. Example: 50 is halfway from the leftmost visible bar to the rightmost. whenVisible(​src, whenCond, length)   Creates an array containing the `length` last `src` values where `whenCond` is true for visible chart bars.   Parameters:      src : (series int/float) The source of the values to be included.      whenCond : (series bool) The condition determining which values are included. Optional. The default is `true`.      length : (simple int) The number of last values to return. Optional. The default is all values.   Returns: (float ) The array ID of the accumulated `src` values. avg(​src)   Gathers values of the source over visible chart bars and averages them.   Parameters:      src : (series int/float) The source of the values to be averaged. Optional. Default is `close`.   Returns: (float) A cumulative average of values for the visible time range. median(​src)   Calculates the median of a source over visible chart bars.   Parameters:      src : (series int/float) The source of the values. Optional. Default is `close`.   Returns: (float) The median of the `src` for the visible time range. vVwap(​src)   Calculates a volume-weighted average for visible chart bars.   Parameters:      src : (series int/float) Source used for the ​VWAP calculation. Optional. Default is `hlc3`.   Returns: (float) The ​VWAP for the visible time range.
Editors' picks
Pine Script™ library
25
Time█   OVERVIEW This library is a Pine Script™ programmer’s tool containing a variety of time related functions to calculate or measure time, or format time into string variables. █   CONCEPTS `formattedTime()`, `formattedDate()` and `formattedDay()` Pine Script™, like many other programming languages, uses timestamps in UNIX format, expressed as the number of milliseconds elapsed since 00:00:00 UTC, 1 January 1970. These three functions convert a UNIX timestamp to a formatted string for human consumption. These are examples of ways you can call the functions, and the ensuing results: CODE RESULT formattedTime(timenow) >>> "00:40:35" formattedTime(timenow, "short") >>> "12:40 AM" formattedTime(timenow, "full") >>> "12:40:35 AM ​UTC​" formattedTime(1000 * 60 * 60 * 3.5, "HH:mm") >>> "03:30" formattedDate(timenow, "short") >>> "4/30/22" formattedDate(timenow, "medium") >>> ​"Apr​ 30, 2022" formattedDate(timenow, "full") >>> "Saturday, April 30, 2022" formattedDay(timenow, "E") >>> "Sat" formattedDay(timenow, "dd.MM.yy") >>> "30.04.22" formattedDay(timenow, "yyyy.MM.dd G 'at' hh:mm:ss z") >>> "2022.04.30 AD at 12:40:35 UTC" These functions use str.format() and some of the special formatting codes it allows for. Pine Script™ documentation does not yet contain complete specifications on these codes, but in the meantime you can find some information in the The Java™ Tutorials and in Java documentation of its MessageFormat class . Note that str.format() implements only a subset of the MessageFormat features in Java. `secondsSince()` The introduction of varip variables in Pine Script™ has made it possible to track the time for which a condition is true when a script is executing on a realtime bar. One obvious use case that comes to mind is to enable trades to exit only when the exit condition has been true for a period of time, whether that period is shorter that the chart's timeframe, or spans across multiple realtime bars. For more information on this function and varip please see our Using `varip` variables publication. `timeFrom( )` When plotting lines , boxes , and labels one often needs to calculate an offset for past or future end points relative to the time a condition or point occurs in history. Using xloc.bar_index is often the easiest solution, but some situations require the use of xloc.bar_time . We introduce `timeFrom()` to assist in calculating time-based offsets. The function calculates a timestamp using a negative (into the past) or positive (into the future) offset from the current bar's starting or closing time, or from the current time of day. The offset can be expressed in units of chart timeframe, or in seconds, minutes, hours, days, months or years. This function was ported from our Time Offset Calculation Framework . `formattedNoOfPeriods()` and `secondsToTfString()` Our final two offerings aim to confront two remaining issues: How much time is represented in a given timestamp? How can I produce a "simple string" timeframe usable with request.security() from a timeframe expressed in seconds? `formattedNoOfPeriods()` converts a time value in ​ms to a quantity of time units. This is useful for calculating a difference in time between 2 points and converting to a desired number of units of time. If no unit is supplied, the function automatically chooses a unit based on a predetermined time step. `secondsToTfString()` converts an input time in seconds to a target timeframe string in timeframe.period string format. This is useful for implementing stepped timeframes relative to the chart time, or calculating multiples of a given chart timeframe. Results from this function are in simple form, which means they are useable as `timeframe` arguments in functions like request.security() . █   NOTES Although the example code is commented in detail, the size of the library justifies some further explanation as many concepts are demonstrated. Key points are as follows:  • ​Pivot points are used to draw lines from. `timeFrom( )` calculates the length of the lines in the specified unit of time.   By default the script uses 20 units of the charts timeframe. Example: a 1hr chart has arrows 20 hours in length.  • At the point of the arrows `formattedNoOfPeriods()` calculates the line length in the specified unit of time from the input menu.   If “Use Input Time” is disabled, a unit of time is automatically assigned.  • At each ​pivot point a label with a formatted date or time is placed with one of the three formatting helper functions to display the time or date the ​pivot occurred.  • A label on the last bar showcases `secondsSince()` . The label goes through three stages of detection for a timed alert.   If the difference between the high and the open in ticks exceeds the input value, a timer starts and will turn the label red once the input time is exceeded to simulate a time-delayed alert.  • In the bottom right of the screen `secondsToTfString()` posts the chart timeframe in a table. This can be multiplied from the input menu. █   FUNCTIONS formattedTime(timeInMs, format)   Converts a UNIX timestamp (in milliseconds) to a formatted time string.   Parameters:      timeInMs : (series float) Timestamp to be formatted.      format : (series string) Format for the time. Optional. The default value is "HH:mm:ss".   Returns: (string) A string containing the formatted time. formattedDate(timeInMs, format)   Converts a UNIX timestamp (in milliseconds) to a formatted date string.   Parameters:      timeInMs : (series float) Timestamp to be formatted.      format : (series string) Format for the date. Optional. The default value is "yyyy-MM-dd".   Returns: (string) A string containing the formatted date. formattedDay(timeInMs, format)   Converts a UNIX timestamp (in milliseconds) to the name of the day of the week.   Parameters:      timeInMs : (series float) Timestamp to be formatted.      format : (series string) Format for the day of the week. Optional. The default value is "EEEE" (complete day name).   Returns: (string) A string containing the day of the week. secondsSince(cond, resetCond)   The duration in milliseconds that a condition has been true.   Parameters:      cond : (series bool) Condition to time.      resetCond : (series bool) When `true`, the duration resets.   Returns: The duration in seconds for which `cond` is continuously true. timeFrom(from, qty, units)   Calculates a +/- time offset in variable units from the current bar's time or from the current time.   Parameters:      from : (series string) Starting time from where the offset is calculated: "bar" to start from the bar's starting time, "close" to start from the bar's closing time, "now" to start from the current time.      qty : (series int) The +/- qty of units of offset required. A "series float" can be used but it will be cast to a "series int".      units : (series string) String containing one of the seven allowed time units: "chart" (chart's timeframe), "seconds", "minutes", "hours", "days", "months", "years".   Returns: (int) The resultant time offset `from` the `qty` of time in the specified `units`. formattedNoOfPeriods(​ms, unit)   Converts a time value in ​ms to a quantity of time units.   Parameters:      ms : (series int) Value of time to be formatted.      unit : (series string) The target unit of time measurement. Options are "seconds", "minutes", "hours", "days", "weeks", "months". If not used one will be automatically assigned.   Returns: (string) A formatted string from the number of `ms` in the specified `unit` of time measurement secondsToTfString(tfInSeconds, mult)   Convert an input time in seconds to target string TF in `timeframe.period` string format.   Parameters:      tfInSeconds : (simple int) a timeframe in seconds to convert to a string.      mult : (simple float) Multiple of `tfInSeconds` to be calculated. Optional. 1 (no multiplier) is default.   Returns: (string) The `tfInSeconds` in `timeframe.period` format usable with `request.security()`.
Editors' picks
Pine Script™ library
25
Relative Bandwidth FilterThis is a very simple script which can be used as measure to define your trading zones based on volatility. Concept This script tries to identify the area of low and high volatility based on comparison between Bandwidth of higher length and ATR of lower length. Relative Bandwidth = Bandwidth / ATR Bandwidth can be based on either Bollinger Band, Keltner Channel or Donchian Channel. Length of the bandwidth need to be ideally higher. ATR is calculated using built in ATR method and ATR length need to be ideally lower than that used for calculating Bandwidth. Once we got Relative Bandwidth, the next step is to apply Bollinger Band on this to measure how relatively high/low this value is. Overall - If relative bandwidth is higher, then volatility is comparatively low. If relative bandwidth is lower, then volatility is comparatively high. Usage This can be used with your own strategy to filter out your non-trading zones based on volatility. Script plots a variable called "Signal" - which is not shown on chart pane. But, it is available in the data window. This can be used in another script as external input and apply logic. Signal values can be 1 : Allow only Long -1 : Allow only short 0 : Do not allow any trades 2 : Allow both Long and Short
Editors' picks
Pine Script™ indicator
18
Breakout Probability (Expo)█ Overview Breakout Probability is a valuable indicator that calculates the probability of a new high or low and displays it as a level with its percentage. The probability of a new high and low is backtested, and the results are shown in a table— a simple way to understand the next candle's likelihood of a new high or low. In addition, the indicator displays an additional four levels above and under the candle with the probability of hitting these levels. The indicator helps traders to understand the likelihood of the next candle's direction, which can be used to set your trading bias. █ Calculations The algorithm calculates all the green and red candles separately depending on whether the previous candle was red or green and assigns scores if one or more lines were reached. The algorithm then calculates how many candles reached those levels in history and displays it as a percentage value on each line. █ Example In this example, the previous candlestick was green; we can see that a new high has been hit 72.82% of the time and the low only 28.29%. In this case, a new high was made. █ Settings Percentage Step The space between the levels can be adjusted with a percentage step. 1% means that each level is located 1% above/under the previous one. Disable 0.00% values If a level got a 0% likelihood of being hit, the level is not displayed as default. Enable the option if you want to see all levels regardless of their values. Number of Lines Set the number of levels you want to display. Show Statistic Panel Enable this option if you want to display the backtest statistics for that a new high or low is made. (Only if the first levels have been reached or not) █ Any Alert function call An alert is sent on candle open, and you can select what should be included in the alert. You can enable the following options: Ticker ID Bias Probability percentage The first level high and low price █ How to use This indicator is a perfect tool for anyone that wants to understand the probability of a breakout and the likelihood that set levels are hit. The indicator can be used for setting a stop loss based on where the price is most likely not to reach. The indicator can help traders to set their bias based on probability. For example, look at the daily or a higher timeframe to get your trading bias, then go to a lower timeframe and look for setups in that direction. ----------------- Disclaimer The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information. All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs. My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Editors' picks
Pine Script™ indicator
65
Point of Control V2 The genesis of this project was to create a POC library that would be available to deliver volume profile information via pine to other scripts of indicators and strategies. This is a republish of an invite only script to open access This is the indicator version of the library function. A few points of significance: - Allows the choice of reset of the study period, day/week or bars. This is simple enough to expand to other conditions - Bar count resets starting from the beginning of the data set (bar index =0) vs bars back from the end of the data set - A 'period' in this context is the time between resets - the start of the POC (eg. start of Day or Week) until it resets (for example at the beginning of a next day or week) - Automates the determination of the increment level rather than the user specifying ticks or price brackets - Does not allow for setting the # of rows and then calculating the implied price increment levels - When a period is complete it is often useful to look back at the POCs of historical periods, or extend them forward. - This script will find the historical POCs around the current price and display them rather than extend all the historical POC lines to the right - This script also looks across all the period POCs and identifies the master POC or what I call the Grand POC, and also the next 3 runner up POCs This indicator is also available as a library. BINANCE:BTCUSDT NSE:NIFTY OANDA:XAUUSD NASDAQ:AAPL TVC:USOIL
Editors' picks
Pine Script™ indicator
8

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TRADEWITHTRAVIS 8/19

GOOD MORNING EVERYONE WE RE GOING LIVE THIS MORNING TO TALK ABOUT SOME OF THE BEST TRADING PAIRS OF THIS WEEK. HAVE YOUR IDEAS READY WE HAVE MADE 4500 THIS MORNING KET ME SHOW YOU HOW

by CarterKyleCapital
Flip Flop Friday

Good morning and welcome to episode 670 of ‘Talking Bull’. In this video/podcast we cover the main headlines and what to expect from the day ahead. 

by Signal_Centre

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