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GBP/USD Outlook: Upward Trajectory Amid Economic ShiftsGBP/USD Outlook: Upward Trajectory Amid Economic Shifts The GBP/USD pair has shown resilience in recent sessions, climbing toward levels not seen since early October, currently hovering around 1.3435 after a rebound from lows near 1.3250. This movement reflects a broader weakening in the US Dollar, influenced by ongoing federal government shutdown impacts estimated at $15 billion weekly in lost economic output, alongside dovish signals from the Federal Reserve hinting at potential rate adjustments amid cooling job market data. On the UK side, the economy returned to modest growth with a 0.1% GDP increase in August, driven by a 0.4% rise in production despite flat services and a dip in construction. This data has bolstered the Pound, pushing it to its highest point in over a week against the Dollar. Technical indicators support a bullish bias in the short term. The pair has broken above a descending trendline, signaling a potential reversal, with key resistance eyed at 1.3470 to 1.3500. Support remains firm around 1.3250-1.3265, where recent bounces have occurred, and a bullish divergence on the 4-hour chart adds to the upside momentum. Market sentiment on platforms like X echoes this, with several analysts noting a shift toward bullish continuation if the pair holds above 1.3340, targeting 1.3480-1.3500. However, overbought conditions and resistance clusters near 1.3400 could prompt minor pullbacks before further gains. Broader factors tilting the scales include the International Monetary Fund's outlook on a subdued global expansion, which may weigh more heavily on the US amid trade tensions and shutdown effects, while the UK's return to growth provides a counterbalance. Bank analyses highlight potential USD strengthening from policy divergences and protectionist measures, but current dynamics favor GBP appreciation in the near term. Overall, the direction for GBP/USD today leans upward, with potential for extension toward 1.3500 if US pressures persist and no major reversals hit key supports. Traders should monitor upcoming US data releases and any UK budget updates for confirmation.
by DCAChampion
EURUSD Short: Approaches Supply - Pullback Short Setup in FocusHello traders! Here’s a clear technical breakdown of EURUSD (3H) based on the current chart structure. After a strong bullish impulse and a confirmed breakout from the descending channel, EURUSD has moved aggressively higher inside a newly formed ascending channel. This impulsive rally signals strong buyer dominance in the short term; however, price is now approaching a key Demand-to-Supply transition area around 1.1790–1.1830, which previously acted as a significant reaction zone. The sharp upside move has created a near-vertical leg, increasing the probability of a temporary pullback due to overextension and profit-taking. Currently, price is testing the upper portion of the ascending channel while simultaneously reacting to prior structure resistance. The rejection candles forming near this area suggest that bullish momentum is slowing, and buyers may be losing short-term control. This behavior often precedes a corrective retracement rather than a full trend reversal, especially after such an impulsive move. From a structural perspective, the zone around 1.1830–1.1870 aligns with a higher-timeframe Supply Zone, making it a logical area for sellers to step in. A bearish reaction from this region could trigger a pullback toward the mid or lower boundary of the ascending channel, where fresh demand may later re-enter. My scenario: In my opinion, after a strong impulse, a corrective pullback to the level of 1.1790 (TP!) will follow. This zone aligns with channel support and previous breakout structure, making it a natural target for a healthy retracement (TP1). This short idea is counter-trend and should be treated strictly as a pullback trade within a broader bullish structure. Strong acceptance and continuation above the supply zone would invalidate the short scenario and signal renewed bullish continuation. For now, price is at a critical reaction zone where sellers may attempt to force a correction before the next directional move. Manage your risk!
Short
by heniitrading
28
AUDCAD | Multi-TF | Rejection at High Momentum (VMS Context)AUDCAD has just printed a classic shooting star reversal, followed by a clean engulfing candle, indicating strong rejection at current levels. Context notes: Momentum: Extremely elevated near 96, now pointing down with bearish divergence Volume: 1H: 79 15M: 91 Both timeframes are showing strong participation Structure: Rejection is occurring after an extended move, suggesting potential exhaustion I currently have the position tool mapped on the chart to visualize: Logical stop placement (swing high plus ATR) Realistic profit targets (using the FIB retracement rule 50%-61%) Risk-to-reward feasibility (2:1) Due to the distance between current price and the required stop, any participation here would require a limit order to manage risk properly. This is about position efficiency, not chasing price. At this stage, this is documentation and observation, not a call to action. Execution only occurs if price behavior, structure, and volume continue to align within the VMS framework. Patience first. Process always. Not financial advice. Do your own research.
Short
by darlwright
EURCAD H4 | Bullish Bounce Off Pullback SupportMomentum: Bullish Price is currently above the ichimoku cloud. Buy entry: 1.62026 - Pullback support - 78.6% Fib retracement Stop Loss: 1.61423 - Swing low support Take Profit: 1.62890 - Pullback resistance High Risk Investment Warning Stratos Markets Limited (fxcm.com/uk), Stratos Europe Ltd (fxcm.com/eu): CFDs are complex instruments and come with a high risk of losing money rapidly due to leverage. 69% of retail investor accounts lose money when trading CFDs with this provider. You should consider whether you understand how CFDs work and whether you can afford to take the high risk of losing your money. Stratos Global LLC (fxcm.com/en): Losses can exceed deposits. Please be advised that the information presented on TradingView is provided to FXCM (‘Company’, ‘we’) by a third-party provider (‘TFA Global Pte Ltd’). Please be reminded that you are solely responsible for the trading decisions on your account. Any information and/or content is intended entirely for research, educational and informational purposes only and does not constitute investment or consultation advice or investment strategy. The information is not tailored to the investment needs of any specific person and therefore does not involve a consideration of any of the investment objectives, financial situation or needs of any viewer that may receive it. Past performance is not a reliable indicator of future results. Actual results may differ materially from those anticipated in forward-looking or past performance statements. We assume no liability as to the accuracy or completeness of any of the information and/or content provided herein and the Company cannot be held responsible for any omission, mistake nor for any loss or damage including without limitation to any loss of profit which may arise from reliance on any information supplied by TFA Global Pte Ltd. Stratos Trading Pty. Limited (fxcm.com/au): Trading FX/CFDs carries significant risks. FXCM AU (AFSL 309763), please read the Financial Services Guide, Product Disclosure Statement, Target Market Determination and Terms of Business at fxcm.com/au
Long
by FXCM
Silver- to 80$?Silver reached a critical price level that may dictate its next directional move. The price reached the second high cycle and rejected from that area, a potential decline could materialize, signalling a sell scenario. Conversely, sustained acceptance above this zone may trigger a bullish breakout with upside potential toward $135. Disclaimer: This analysis is for informational purposes only and does not constitute financial advice. Trading carries significant risk, including the potential for substantial loss. Always exercise caution and trade responsibly.
TVC:SILVERShort
by Bilind-GeniusScalper
When a Stock Rises 78% in 30 Days, and You Don't Know What to DoHi, friends! This is Alexander Dlutsky, and today in my blog about investing in stocks, we'll talk about a situation that can happen to any of us. Imagine: you bought a stock, and it suddenly skyrocketed 78% in just a month. Joy? Of course! But also panic: sell? Hold? Buy more? I've gone through this many times myself, and I know how nerve-wracking it is. And even after many years, I know for sure that no one knows the exact answer to the question "What to do?" In this post, I'll break down three typical scenarios for what to do in such a situation. This is not financial advice — always consult with experts and study the market yourself. But these ideas will help you think logically and avoid impulsive mistakes. Let's figure it out! Scenario 1: "This is the Start of Big Growth" — Hold and Buy More If the stock rose so sharply, it might not be a coincidence. Pullbacks are inevitable, as one trader said, "even the road to hell wasn't built in a straight line." Check the fundamentals: did the company release a cool product, win a contract, or is the market overall on the rise? If you had the courage to buy, have the courage to hold. Personal advice: spend more time on things besides investments; the more you devote time to the outside world, the more unbiased your opinion becomes in investments, which helps a lot. You can always take your chips off the table. But still, what should you do? * Check the financial metrics, check your investment thesis, why you bought this company in the first place. * Analyze news and reports. * If in doubt, sell without thinking. * If confident, buy more on the pullback — but don't risk all your money. I remember how in 2020, Zoom stocks skyrocketed due to the pandemic. Many held and won. But remember: the market is unpredictable, so diversify your portfolio. ### Scenario 2: "The Bubble is Inflating" — Lock in Profits Partially 78% in 30 days — that's a lot. Maybe it's hype: meme stocks like GameStop or crypto in a boom. If the growth is based on emotions, without real fundamentals, better not to get greedy. What to do - Sell 30-50% of your position to lock in profits (for example, if you invested $1000 and it became $1780 — sell for $500-900). - Monitor the remaining part: watch the last 4 candles, they will tell you a lot about the near-term hype trend. In my experience, such "skyrockets" often end in a correction. Another saying from an experienced trader: "100% profit is very cool, anything above that is already greed." ### Scenario 3: "Not Sure, Waiting for Signals" — Observe and Learn If you don't know what's what — don't rush. The market gives you time to think. What to do: Set a stop and let the market decide what happens next. While waiting, look for confirmations for or against. Forums, blogs, anything you can find — information is the key to success. This is my favorite approach now. Investments are a marathon, not a sprint. Don't hurry, learn from mistakes. In conclusion: Emotions are the worst advisor. Choose a scenario based on your strategy, risk, and knowledge. If you're in a similar situation, share in the comments — let's discuss! If the post was useful, give it a like or share this post, it's valuable to me. I promise to share more honest stories from the world of stocks. Support me, friends — it motivates! 😊 #investments #stocks #stockmarket
NASDAQ:ASTSLong
by Strong_Holders
BITCOIN DAILY CHARTON WEEKLY TIMEFRAME THE PRICEACTION IS ABOVE THE WEEKLY SUPPORT FLOOR ,WAIT WEEKLY BREAK OF STRUCTURE AND LOOK FOR SELL..ON DAILY WE HAVE A DESCENDINGTRENDLINE ACTING AS DYNAMIC SUPPORT Bitcoin (BTC) is the world's first decentralized cryptocurrency, created in 2009 by an anonymous person or group using the pseudonym Satoshi Nakamoto. It operates on a peer-to-peer network without central banks or governments, using blockchain technology—a public ledger recording all transactions cryptographically across thousands of computers worldwide. Key Features: Decentralized: No single entity controls Bitcoin; miners validate transactions via proof-of-work. Limited Supply: Capped at 21 million coins (94% mined by 2026), creating scarcity like digital gold. Transactions: Users send/receive BTC via digital wallets; irreversible once confirmed (10-60 minutes). Security: Cryptographic keys ensure ownership; blockchain prevents double-spending. Uses: Store of Value: "Digital gold" hedge against inflation/currency devaluation. Payments: Accepted by merchants (e.g., Tesla briefly, El Salvador legal tender). Bitcoin hit ATH amid institutional adoption (ETFs, corporate treasuries), Trump pro-crypto policies, and halving cycle (April 2024 reduced rewards). Highly volatile; correlates with risk assets but increasingly viewed as macro hedge alongside your gold/silver interests. #BITCOIN #BTCUSD
Long
by Shavyfxhub
JD Approaching Buy Zone - Excellent Reward/Risk For A LongThis chart has a number of confluent signals that point to a good long setup. From both a trend & momentum perspective, I like it a lot. Everyone has to manage their emotions in trading. As this looks to be basing above the zone, I'm feeling a strong urge add to my original long. But I know patience is critical to risk/reward, and letting price come to the buy zone is the right decision. Emotionally, here's how I do it. I spread buy orders across the buy zone, with heavier orders near the bottom. So price action will determine the exact position size, with the maximum loss to my stop loss representing no more than 1-2% of my portfolio value. But what if we really want a position, and it never reaches our buy zone? Sometimes buying a single share before it hits the buy zone satiates that urge to participate. For me, it works. It's a tiny symbolic gesture that manages FOMO. Meanwhile, I sit on my hands with JD for my re-add. The orders are set.
NASDAQ:JDLong
by MicDrop5
01/27/2026 MSTR/MSTU LongHello traders, I’m neutral on Bitcoin for now, but I’m bullish on MSTR/MSTU. The hammer candle on the 4-hour timeframe suggests upside potential from here. After consolidating within a tight range for several days, MSTR appears ready for a breakout. My conservative Take Profit (TP) is the R1 trendline, though we may see further extension depending on Bitcoin’s performance. Stop Loss (SL) is set just below the previous wick. Conservative TP : $180-$183 SL : $155 May the trend be with you. GL all! AP
NASDAQ:MSTRLong
by aparkon
EURUSD is maintaining a strong bullish trendEURUSD – 1H Timeframe | Bullish Trend 📈 EURUSD is maintaining a strong bullish trend, with price holding above the EMA 200, acting as dynamic support 💪 🔹 Buy Zone: • 1.19500 – EMA 200 support & bullish reaction area ✅ 🎯 Technical Target: • 1.20400 As long as price respects EMA 200, bullish continuation remains likely. Wait for confirmation and manage entries wisely. ⚠️ Use proper risk management This is not financial advice. Trade with discipline and control your risk. 👍 Like | 💬 Comment | 🔁 Share | ➕ Follow for more updates
Long
by ExpertTraderASK
1
Falling towards pullback support?USTEC is falling towards the pivot and could bounce to the 1st resistance. Pivot: 25,801.30 1st Support: 25,361.85 1st Resistance: 26,481.54 Disclaimer: The opinions given above constitute general market commentary and do not constitute the opinion or advice of IC Markets or any form of personal or investment advice. Any opinions, news, research, analyses, prices, other information, or links to third-party sites contained on this website are provided on an "as-is" basis, are intended to be informative only, and are not advice, a recommendation, research, a record of our trading prices, an offer of, or solicitation for, a transaction in any financial instrument and thus should not be treated as such. The information provided does not involve any specific investment objectives, financial situation, or needs of any specific person who may receive it. Please be aware that past performance is not a reliable indicator of future performance and/or results. Past performance or forward-looking scenarios based upon the reasonable beliefs of the third-party provider are not a guarantee of future performance. Actual results may differ materially from those anticipated in forward-looking or past performance statements. IC Markets makes no representation or warranty and assumes no liability as to the accuracy or completeness of the information provided, nor any loss arising from any investment based on a recommendation, forecast, or any information supplied by any third party
ICMARKETS:USTECLong
by IC Markets
$SPY & $SPX — Market-Moving Headlines Thursday Jan 29, 2026🔮 AMEX:SPY & SP:SPX — Market-Moving Headlines Thursday Jan 29, 2026 🌍 Market-Moving Themes 🏦 Fed Head Fake Absorbed Markets shake off hawkish Powell comments as dip buyers step in late 🚗 Tesla Earnings Shock TSLA jumps after-hours on Model 2 timing and European FSD licensing headlines 🧠 AI Capex Split Reaction META slides on higher spending plans while suppliers stay in focus NVDA ANET ⚛️ AI Energy Undercurrent Uranium names firm as power constraints resurface CCJ OKLO VST 📊 Macro Sensitivity Day Labor and trade data test whether post-Fed stabilization holds 📊 Key U.S. Economic Data Thursday Jan 29 ET 8:30 AM - Initial Jobless Claims Jan 24: 205K - U.S. Trade Deficit Nov delayed: -42.9B - U.S. Productivity Q3 revised: 4.9% 10:00 AM - Wholesale Inventories Nov delayed: 0.2% - Factory Orders Nov delayed: 1.3% ⚠️ Disclaimer: For informational purposes only. Not financial advice. 📌 #SPY #SPX #Fed #Earnings #TSLA #META #AI #Energy #Macro #Markets #Stocks #Options
AMEX:SPYShort
by TrendTao
Another 11 Million Tests, Still No Edge: The RSIPart II of the RSI Analysis: Testing the Momentum Hypothesis Preface: a reader's challenge This study exists because of a question from our community. Following the publication of our first RSI analysis, several readers asked whether we had tested the indicator incorrectly. The mean-reversion interpretation, they argued, represents retail misconception. Sophisticated traders use RSI as a momentum confirmation tool, buying strength rather than fading it. Would we test this alternative hypothesis? We welcome such challenges. Our research agenda is shaped by questions that meet one criterion: the hypothesis must be quantitatively testable. This requirement excludes many popular trading concepts. Elliott Wave theory, for instance, involves subjective wave counting that different analysts interpret differently. Fibonacci retracements require discretionary placement of anchor points. Support and resistance levels depend on the trader's eye. These approaches may or may not have merit, but they cannot be rigorously tested because two analysts examining the same chart will identify different signals. RSI momentum signals, by contrast, are precisely defined. When RSI crosses above 60, that crossing is objective and verifiable. This objectivity enables the comprehensive testing we conduct here. We encourage readers to continue suggesting testable hypotheses, as community engagement improves the relevance of our research. A necessary caveat before proceeding: our findings demonstrate that RSI signals lack statistical edge in aggregate across millions of parameter combinations. This does not prove that no individual trader has developed a profitable RSI-based approach. Markets are complex, and edge can emerge from sources our methodology does not capture: discretionary pattern recognition, combination with fundamental analysis, superior execution, or genuine skill in identifying context-dependent applications. However, traders claiming RSI profitability should exercise extreme caution regarding overfitting and data mining bias. When testing thousands of parameter combinations on historical data, some will appear profitable by chance alone. The human mind excels at constructing post-hoc narratives explaining why those specific parameters work, creating false confidence in strategies that will fail going forward. Our use of Bonferroni correction specifically guards against this trap by demanding evidence so strong that chance alone cannot explain it. Furthermore, while standalone RSI signals show no edge, the indicator may contribute value within broader systematic frameworks. RSI can serve as a volatility filter, identifying regimes of elevated or suppressed momentum where other strategies perform differently. It can function as a confirmation layer, requiring RSI alignment before executing signals from primary strategies based on moving averages, breakouts, or fundamental factors. Some quantitative funds incorporate RSI among dozens of inputs in machine learning models, where weak individual signals combine into stronger ensemble predictions. In mean-variance optimization, RSI readings might inform position sizing rather than entry timing. These applications differ fundamentally from the standalone signal testing we conduct here. They use RSI as one component among many rather than as a primary decision driver. Our study tests the specific claim that RSI signals alone identify profitable trading opportunities. That claim fails comprehensive examination. Whether RSI contributes marginal value within sophisticated multi-factor frameworks remains an open question we do not address. Readers should interpret our findings accordingly: RSI as a standalone trading tool is statistically worthless, but this does not preclude all possible uses of the indicator. Abstract Following our previous study that examined 15 million parameter combinations of RSI overbought/oversold signals, this continuation addresses the natural counterargument: perhaps RSI should be used as a momentum indicator rather than a mean-reversion tool. We conducted an additional 11 million statistical tests using RSI as a trend-following signal, buying when strength emerges and selling when weakness appears. The combined evidence from 26 million tests across both studies is unambiguous: RSI provides no statistically significant edge under any interpretation. Not a single test survived Bonferroni correction. The indicator that millions of retail traders rely upon is informationally worthless regardless of how it is applied. 1. Introduction: the counterargument In our previous study titled "15 Million Tests, Zero Edge: The RSI " we demonstrated that the popular mean-reversion interpretation of RSI produces no statistically significant trading edge. We tested over 15 million parameter combinations across 16 assets and five asset classes. The results were devastating: exactly zero tests survived Bonferroni correction for multiple comparisons. However, we anticipated a specific criticism. In Section 5.1 of that study, we noted that institutional traders who incorporate RSI typically use it as a momentum filter rather than a mean-reversion signal. The approach is precisely opposite to retail wisdom: they buy when RSI is above 50 indicating upward momentum and sell when RSI is below 50. We referenced Antonacci's (2014) research on dual momentum showing that trend-following approaches consistently outperform mean-reversion strategies. This raised an obvious question: if mean-reversion RSI fails, does momentum RSI succeed? Perhaps retail traders simply have the signal backwards. Perhaps RSI works, but only when used to confirm trends rather than fade them. This follow-up study directly addresses that hypothesis. We apply the same rigorous methodology to test RSI as a momentum indicator, generating buy signals when the oscillator demonstrates strength and sell signals when it shows weakness. The theoretical case for this approach is stronger than for mean-reversion, given the well-documented momentum anomaly in financial markets documented by Jegadeesh and Titman (1993). If RSI has any legitimate use in trading, momentum confirmation would be it. Our findings, however, extend the conclusions of our first study: RSI fails under both interpretations. The indicator contains no exploitable information regardless of how traders choose to apply it. 2. Theoretical framework: why momentum RSI might work Before presenting our methodology and results, we must establish why the momentum interpretation of RSI has theoretical merit that the mean-reversion interpretation lacks. The momentum effect in financial markets has been documented extensively since Jegadeesh and Titman's seminal 1993 paper in the Journal of Finance. Their study demonstrated that buying past winners and selling past losers generated significant profits over three to twelve month horizons. This finding proved remarkably robust across markets, time periods, and asset classes. Carhart (1997) elevated momentum to the status of a fundamental risk factor, adding it to the Fama-French three-factor model. The behavioral explanation for momentum centers on investor underreaction. Daniel, Hirshleifer, and Subrahmanyam (1998) proposed that investors initially underreact to new information due to anchoring bias, leading prices to adjust gradually rather than immediately. Hong and Stein (1999) developed a model where information diffuses slowly across investor groups, creating predictable price trends. If these behavioral mechanisms generate momentum in asset prices, technical indicators that identify trend initiation should theoretically capture some of this effect. The RSI, by measuring the magnitude of recent gains relative to recent losses, appears suited to this task. When RSI crosses above a threshold, it signals that buying pressure has overcome selling pressure, potentially indicating the beginning of an upward trend. Antonacci (2014), whom we cited in our previous study, argued that combining absolute momentum with relative momentum produces superior risk-adjusted returns. His framework suggests that RSI above 50 could serve as an absolute momentum filter, confirming that an asset is in an uptrend before committing capital. This represents the most theoretically grounded case for RSI momentum trading. The contrast with mean-reversion theory is stark. Mean-reversion assumes that extreme RSI readings indicate exhaustion and impending reversal. But no compelling theoretical mechanism explains why oversold assets should rebound or overbought assets should decline. Markets can remain irrational longer than traders can remain solvent, as the saying attributed to Keynes reminds us. Momentum theory, by contrast, has both empirical support and behavioral explanations. If RSI is to work anywhere, it should work as a momentum indicator. This study tests whether it does. 3. Data and methodology 3.1 Asset universe and data sources We constructed a diversified asset universe spanning four major categories. United States equities were represented by SPY, QQQ, IWM, and DIA. International equities were represented by EFA and EEM. Commodities were represented by GLD, SLV, and USO. Fixed income was represented by TLT and IEF. Foreign exchange pairs were excluded from this analysis due to data availability constraints with the TwelveData API. This omission is unlikely to affect conclusions given that forex markets showed near-zero edge in our previous mean-reversion study, consistent with the efficient market hypothesis for currency markets. Daily price data covered approximately 5,000 trading days per asset, spanning from inception through January 2025. All prices for equity ETFs are adjusted for dividends and splits. 3.2 Parameter grid specification We designed the parameter grid to comprehensively test the RSI momentum hypothesis: RSI calculation periods ranged from 2 to 60 days in single-day increments, producing 59 distinct period lengths. This range encompasses the standard 14-day default as well as shorter periods favored by active traders and longer periods that might capture intermediate-term trends. Long entry thresholds ranged from 45 to 85, representing the level above which RSI must cross to generate a buy signal. Traditional momentum interpretation suggests buying when RSI exceeds 50, indicating positive momentum. We tested a wide range to ensure robustness. Short entry thresholds ranged from 15 to 55, representing the level below which RSI must cross to generate a sell signal. This captures the inverse momentum logic of selling when RSI demonstrates weakness. Holding periods included 1, 2, 3, 5, 7, 10, 15, 20, 30, 45, 60, and 90 days, identical to our previous study for comparability. This specification produced 1,190,148 unique parameter combinations per asset. Across 11 assets, the total parameter space encompassed 13,091,628 potential tests. After filtering for combinations generating at least 15 signals, 11,035,184 complete statistical tests were analyzed. 3.3 Signal definition: the opposite of mean-reversion The momentum signal definition differs fundamentally from the mean-reversion approach tested in our previous study. In that study, we defined buy signals when RSI crossed below oversold thresholds, expecting a rebound. Here, we define the opposite: a long signal occurs when RSI crosses above the upper threshold from below, indicating that buying pressure has strengthened sufficiently to push the oscillator into bullish territory. Similarly, a short signal occurs when RSI crosses below the lower threshold from above, indicating intensifying selling pressure. This is the opposite of the mean-reversion approach where crossing below thresholds generated buy signals. For each signal, we calculate the forward return over the specified holding period. The edge is computed as the difference between mean returns following signals and the baseline mean return. A positive edge indicates that momentum RSI signals identify periods of above-average returns. 3.4 Statistical framework We employ identical statistical methodology to our previous study to ensure direct comparability. Welch's t-test compares signal returns against baseline returns. The Bonferroni-corrected significance threshold for 11 million tests at alpha equals 0.05 is approximately 4.5 times ten to the negative ninth power. 4. Results 4.1 Aggregate findings Figure 1 presents the summary dashboard mirroring the format from our previous study. Panel A shows the distribution of edge values for both long and short momentum signals. The histogram is centered precisely at zero, indistinguishable from our mean-reversion results. Neither momentum buying nor momentum selling produces consistent outperformance. Panel B displays the percentage of tests achieving nominal significance by asset category. The rates range from 3.6 percent for bonds to 9.2 percent for US equities. While US equities exceed the five percent expected under the null hypothesis, this excess represents significance in the wrong direction, as we detail below. Panel C reveals how edge varies by holding period. No consistent pattern emerges across the twelve holding periods tested. Some show marginally positive average edge, others marginally negative, with magnitudes economically insignificant. Panel D presents the p-value distribution. The uniform spread between zero and one matches theoretical expectation under the null hypothesis of no effect. The aggregate statistics tell the same story as our previous study. Mean long signal edge equals positive 0.0091 percentage points with a median of exactly zero. Mean short signal edge equals positive 0.0011 percentage points with a median of exactly zero. These edges are economically meaningless: transaction costs alone would overwhelm any such edge by an order of magnitude. Most critically, after applying Bonferroni correction, exactly zero tests achieved statistical significance. Combined with our previous study, we have now conducted 26 million tests of RSI signals. Not a single one survives proper statistical scrutiny. 4.2 Results by asset category Figure 2 displays box plots of edge distribution for each asset category, allowing direct comparison with Figure 2 from our previous study. Commodities showed the most favorable results, with mean long edge of positive 0.35 percentage points and mean short edge of positive 0.50 percentage points. These figures might appear promising until one considers that no commodity tests survived Bonferroni correction. The variation is consistent with noise, not signal. Bonds displayed mean long edge of positive 0.07 percentage points and mean short edge of negative 0.02 percentage points. The negative short edge is particularly notable: selling bonds when RSI shows weakness actually underperforms random timing. International equities showed negative edges for both signal types, with long edge of negative 0.09 percentage points and short edge also negative 0.09 percentage points. RSI momentum signals actively harm performance in these markets. United States equities produced the most damaging results for momentum proponents. The long signal edge averaged negative 0.23 percentage points and the short signal edge averaged negative 0.33 percentage points. These are the largest magnitude edges in our study, and they are negative. RSI momentum signals in the world's most liquid equity market reliably identify periods of below-average returns. This finding requires careful interpretation to avoid a logical trap. The negative edge for momentum signals might suggest that RSI identifies trend exhaustion, which would seem to validate mean-reversion trading. If buying strength leads to below-average returns, should we not sell strength instead? This reasoning appears compelling but is fundamentally flawed, and understanding why illuminates the true nature of RSI failure. First, consider what the data actually shows. The momentum long signal in US equities produces returns of negative 0.23 percentage points relative to baseline. This does not mean buying strength produces losses; it means buying strength produces returns slightly below the average holding period return. The baseline return for US equities is positive due to the long-term upward drift of equity markets. A negative edge of 0.23 percentage points means momentum entries underperform random entries by less than a quarter of a percentage point, not that they produce absolute losses. Second, and more critically, our previous study already tested the mean-reversion hypothesis directly. If RSI truly identified trend exhaustion, then buying oversold conditions should produce positive edge, as exhausted downtrends reverse into uptrends. But we found mean oversold edge of negative 0.01 percentage points, statistically indistinguishable from zero. Selling overbought conditions, which would capitalize on exhausted uptrends, produced edge of exactly zero. The mean-reversion study provided no evidence that RSI identifies exploitable reversals. The apparent contradiction dissolves when we recognize what RSI actually measures: noise. The negative momentum edge in US equities and the zero mean-reversion edge are both consistent with a single explanation. RSI oscillations around price movements contain no predictive information whatsoever. The small negative momentum edge likely reflects regression to the mean in a noisy system rather than genuine trend exhaustion. Assets that have risen enough to push RSI above momentum thresholds are slightly more likely to experience smaller subsequent gains simply because extreme short-term movements are followed by more typical movements. This is not the same as mean reversion in the trading sense of predictable reversals. To illustrate concretely: suppose a stock rises five percent in a week, pushing RSI above 70. Our momentum study shows that buying at this point produces slightly below-average forward returns. But our mean-reversion study shows that selling at this point does not produce above-average returns either. The stock's future path is simply unpredictable from its RSI reading. It might continue higher, consolidate sideways, or decline, and RSI provides no information about which outcome will occur. The slight underperformance following momentum signals reflects the mathematics of bounded oscillators rather than actionable trading information. Furthermore, the academic literature on momentum and mean-reversion operates on different time horizons than RSI signals. Jegadeesh and Titman's momentum effect occurs over three to twelve month formation and holding periods. Mean-reversion in equity markets, to the extent it exists, manifests over multi-year horizons as documented by DeBondt and Thaler (1985) in their study of long-term reversals. RSI operates on a fourteen-day default period with our study testing holding periods up to ninety days. These horizons fall into what might be called the no-man's-land of predictability: too short for momentum effects, too long for microstructure-based patterns, and too short for long-term mean reversion. The bottom line is unambiguous: neither momentum nor mean-reversion RSI trading produces statistically significant edge. The slight negative momentum edge in US equities does not imply that mean-reversion works; we tested that directly and it does not. RSI readings are noise, and no interpretation of that noise yields profitable trading signals. 4.3 Parameter sensitivity Figure 3 presents heatmaps showing how edge varies across the parameter space, directly comparable to Figure 3 in our previous study. The upper panels display long signal edge against RSI period and threshold on the left, and against threshold and holding period on the right. The lower panels show corresponding short signal results. If RSI momentum signals possessed genuine predictive power, we would expect consistent regions of positive edge across the parameter space. Instead, the patterns appear random. Small positive regions sit adjacent to equally sized negative regions with no systematic structure. Comparing these heatmaps to those from our mean-reversion study reveals striking similarity: both show noise without signal. Neither mean-reversion nor momentum interpretation identifies parameter combinations with reliable predictive power. 4.4 Multiple testing correction Figure 4 shows the distribution of p-values for long and short momentum signals separately, formatted identically to Figure 4 from our previous study. The percentage of tests achieving nominal significance at p less than 0.05 equals 6.48 percent for long signals and 5.63 percent for short signals. These rates are only slightly elevated above the five percent expected under the null hypothesis, and entirely consistent with correlation among tests rather than genuine predictive power. After Bonferroni correction, zero tests remain significant. This matches exactly the result from our mean-reversion study. Whether testing 15 million mean-reversion combinations or 11 million momentum combinations, the conclusion is identical: no evidence of edge. 5. Combined analysis: 26 million tests, zero edge The primary contribution of this study is completing the comprehensive examination of RSI utility. Table 1 presents the combined results across both studies. Table 1 displays the combined results from approximately 26 million RSI tests conducted across both studies. The mean-reversion study from Part I tested roughly 15 million parameter combinations, finding a mean oversold edge of negative 0.01 percentage points and a mean overbought edge of zero. The momentum study in Part II tested approximately 11 million combinations, finding a mean long edge of positive 0.01 percentage points and a mean short edge of zero. Nominal significance rates hovered between 5.6 and 8.8 percent across all signal types, only marginally exceeding the five percent expected under the null hypothesis. Most importantly, not a single test from either study survived Bonferroni correction. The symmetry is remarkable. Mean-reversion produces a tiny negative edge for buy signals; momentum produces a tiny positive edge. The magnitudes are indistinguishable from zero in both cases. The nominal significance rates hover around five percent as expected under the null hypothesis. No tests survive correction in either study. These are not marginal findings subject to interpretation. The evidence is overwhelming: RSI signals contain no exploitable information. The indicator fails whether used for mean-reversion or momentum, across all asset classes tested, across all parameter combinations examined, and across all holding periods from one day to three months. 6. Why RSI fails despite valid momentum theory The failure of RSI momentum signals despite the well-documented existence of momentum in asset returns requires explanation. Several factors contribute to this disconnect. 6.1 Information transformation destroys the signal The RSI transforms raw price data through Wilder's specific mathematical operation. This transformation may destroy the momentum signal present in returns. Academic momentum research by Jegadeesh and Titman (1993) and subsequent studies use simple past returns over formation periods of three to twelve months. The RSI uses a smoothed ratio of gains to losses over much shorter periods, typically 14 days. Moskowitz, Ooi, and Pedersen (2012) documented time-series momentum in the Journal of Financial Economics using raw returns, not oscillator transformations. Novy-Marx (2012) demonstrated that intermediate-term momentum in raw returns outperforms more complex momentum measures. Adding mathematical transformations to price data does not create new information; it can only preserve or destroy existing information. RSI appears to destroy it. 6.2 Signal timing occurs at trend exhaustion Academic momentum strategies buy assets after strong performance over three to twelve months and hold for similar horizons. RSI generates signals based on short-term oscillator movements that may not align with these horizons. When RSI crosses above 70, it indicates that recent buying pressure has been intense. However, this intensification may occur late in a momentum cycle after the bulk of gains have been realized. Our finding that US equity long signals precede below-average returns supports this interpretation. RSI momentum signals may identify trend exhaustion rather than trend initiation. 6.3 Forty-five years of arbitrage The RSI has been publicly available since 1978. Any simple trading rule based on its signals has been known for nearly five decades. Lo (2004) argued in his adaptive markets hypothesis that profitable trading strategies become arbitraged away as they become widely known. If RSI signals ever contained useful information, that information has likely been incorporated into prices by the countless traders who have tested the same ideas before us. The remaining edge after forty-five years of scrutiny is indistinguishable from zero. 7. Implications for traders The combined findings of our two studies have direct practical implications that we summarize here. 7.1 Abandon all RSI-based strategies In our previous study, we recommended that traders stop using RSI overbought/oversold levels as signals. We now extend this recommendation: traders should stop using RSI entirely as a mechanical trading signal. Neither mean-reversion nor momentum interpretation produces edge. The indicator is informationally empty. 7.2 Use raw returns for momentum For traders seeking momentum exposure, academic research supports using simple past returns rather than oscillator transformations. Jegadeesh and Titman's original methodology of ranking assets by three to twelve month trailing returns remains robust. No indicator improvement is necessary or beneficial. 7.3 Accept fundamental unpredictability Our 26 million tests represent an exhaustive search for RSI edge that does not exist. Rather than searching for the next indicator or parameter combination, traders would benefit from accepting that short-term price movements are fundamentally unpredictable. This acceptance redirects attention toward controllable factors: position sizing, diversification, cost minimization, and behavioral discipline. 8. Limitations This study has limitations consistent with those noted in our previous work. We examined only daily data. Transaction costs were not explicitly modeled. Combination strategies incorporating multiple indicators were not tested. Future research might examine whether RSI contains conditional information given specific market regimes. However, such conditional approaches face severe data mining risks, and the complete absence of unconditional effect provides little reason for optimism. References Antonacci, G. (2014). Dual Momentum Investing: An Innovative Strategy for Higher Returns with Lower Risk. New York: McGraw-Hill Education. Carhart, M.M. (1997). On persistence in mutual fund performance. Journal of Finance, 52(1), 57-82. Daniel, K., Hirshleifer, D. and Subrahmanyam, A. (1998). Investor psychology and security market under and overreactions. Journal of Finance, 53(6), 1839-1885. Hong, H. and Stein, J.C. (1999). A unified theory of underreaction, momentum trading, and overreaction in asset markets. Journal of Finance, 54(6), 2143-2184. Jegadeesh, N. and Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. Journal of Finance, 48(1), 65-91. Lo, A.W. (2004). The adaptive markets hypothesis. Journal of Portfolio Management, 30(5), 15-29. Moskowitz, T.J., Ooi, Y.H. and Pedersen, L.H. (2012). Time series momentum. Journal of Financial Economics, 104(2), 228-250. Novy-Marx, R. (2012). Is momentum really momentum? Journal of Financial Economics, 103(3), 429-453. Wilder, J.W. (1978). New Concepts in Technical Trading Systems. Greensboro, NC: Trend Research.
CME_MINI:NQ1!Education
by EdgeTools
Falling towards 50% Fib support?EUR/USD is falling towards the support level, which is a pullback support slightly below the 50% Fibonacci retracement and could bounce from this level to our take profit. Entry: 1.1806 Why we like it: There is a pullback support that is slightly below the 50% Fibonacci retracement. Stop loss: 1.1701 Why we like it: There is an overlap support that aligns with the 78.6% Fibonacci retracement. Take profit: 1.2037 Why we like it: There is a pullback resistance level. Enjoying your TradingView experience? Review us! TradingView (www.tradingview.com) Please be advised that the information presented on TradingView is provided to Vantage (‘Vantage Global Limited’, ‘we’) by a third-party provider (‘Everest Fortune Group’). Please be reminded that you are solely responsible for the trading decisions on your account. There is a very high degree of risk involved in trading. Any information and/or content is intended entirely for research, educational and informational purposes only and does not constitute investment or consultation advice or investment strategy. The information is not tailored to the investment needs of any specific person and therefore does not involve a consideration of any of the investment objectives, financial situation or needs of any viewer that may receive it. Kindly also note that past performance is not a reliable indicator of future results. Actual results may differ materially from those anticipated in forward-looking or past performance statements. We assume no liability as to the accuracy or completeness of any of the information and/or content provided herein and the Company cannot be held responsible for any omission, mistake nor for any loss or damage including without limitation to any loss of profit which may arise from reliance on any information supplied by Everest Fortune Group.
Long
by Vantage
GBPUSD Bearish Continuation | Target 1.3735 – 1.3716 | Bearish BThe British Pound (GBPUSD) is showing clear intraday weakness as the downside momentum prevails. The price has rejected resistance and is currently trading below its key pivot level and moving averages. As long as the price remains capped below 1.3819, the sellers are expected to maintain control, pushing the pair toward lower support zones. Trade Plan: Bias: Bearish Entry Zone: Sell on rallies while the price stays below the 1.3819 resistance. Targets: First target: 1.3735 | Second target: 1.3716 (in extension). Risk Condition: Bearish only if price stays below 1.3819. Market Logic: The price is trading below the pivot level of 1.3819, which now acts as a ceiling. RSI is below its neutrality area at 50, confirming weak momentum. MACD is below its signal line and negative, supporting further downside pressure. The structure aligns with SMC (Smart Money Concepts) bearish mitigation, as the price stands below its 20 and 50-period moving averages. Invalidation: This bearish view is valid only below 1.3819. A strong break and hold above this level cancels the bearish thesis and may lead to a test of 1.3851. Disclaimer: This idea is for educational purposes only, not financial advice. Currency markets are highly volatile. Trade at your own risk and always use proper risk management. FX:GBPUSD CRYPTOCAP:FOREX AAII:BEARISH $INTRADAY NYSE:SMC $SUPPLYDEMAND $PRICEACTION NYSE:RSI $MACD $TREND $GU
Short
by Market_Pulse6