Get started

Futures market

Gold next move (weekly analysis)(30th Mar-3rd April-2026)Go through the analysis carefully, and do trade accordingly. Anup 'BIAS for the week (30th Mar-3rd April-2026) Current price- 4525 "if Price stays above 4410-20, then the next target is 4580, 4660 and 4760 and below it 4350 and 4300" Present scenario- 1. Wait for the perfect area for buying 2. we can also take aggressive entry towards bullish side using small time frame support and demand. What we expect 1. First move- we are expecting price to move around 4760-70 2. Second move- we are expecting huge selling after the first move -POSSIBILITY-1 Wait (as geopolitical situation are worsening ) -POSSIBILITY-2 Wait (as geopolitical situation are worsening) Best of luck Never risk more than 1% of principal to follow any position. Support us by liking and sharing the post.
OANDA:XAUUSDLong
by AnupZiddi
67
Gold 30Min Engaged ( Bearish Entry Detected )⚡Base : Hanzo Trading Alpha Algorithm The algorithm calculates volatility displacement vs liquidity recovery, identifying where probability meets imbalance. It trades only where precision, volume, and manipulation intersect —only logic. ✈️ Technical Reasons / Direction — SHORT / Reversal 4570 ☄️Bearish rejection confirmed through sharp candle body. ☄️Lower-high forming beneath resistance supply region. ☄️Volume decreasing confirms exhaustion in price rally. ☄️Sellers regained imbalance with heavy top rejection. ☄️Algorithm detects fading demand and shift to control. ⚙️ Hanzo Alpha Trading Protocol The Alpha Candle defines the day’s real control zone — the first battle of momentum. From this origin, the Volume Window reveals where the next precision strike begins. ⚙️ Hanzo Volume Window / Map Window tracked from 10:30 — mapping true market behavior. POC alignment exposes institutional bias and breakout potential zones. ⚙️ Hanzo Delta Window / Pulse Delta window monitors real buying vs. selling power behind each move. Tracks volume aggression to expose who controls the candle — buyers or sellers. When Delta aligns with Volume Map, momentum becomes undeniable.
CAPITALCOM:GOLDShort
by Path_Of_Hanzo
56
THIS IS NOT A REVERSAL, THIS IS HOW LIQUIDITY GETS TRAPPEDThe gold market enters the new week in a characteristic state of repricing after strong fluctuations, as the entire previous structure has been broken and capital is seeking a balance point. The macro context remains tug-of-war: growth shows signs of slowing but inflation has not truly cooled, making monetary policy expectations unpredictable. This is not a favorable environment for a sustainable upward trend, but an ideal condition for strong fluctuations – liquidity sweeps – and market psychology traps. On the D1 frame, after a strong breakdown breaking the long-term upward trendline, gold has rebounded but was quickly blocked at the confluence zones of Fibo 0.5–0.618 and FVG above. This indicates that the recent increase has not been accumulative, but mainly a pullback in a larger downtrend. The weekly close with a slight reclaim above the short-term demand zone is not enough to confirm a reversal, but is likely just a rebalancing act before continuing to move. This week, the important price zone to watch is 4750–4900, where the old demand, trendline, and medium-term Fibonacci levels converge. This will be the decisive area to see if the market continues to be rejected to maintain the downtrend, or can extend the rebound deeper. If the price cannot hold above this zone and shows signs of weakening, the main scenario remains a continuation down to the 4300–4100 area, where large liquidity is concentrated and has not been fully tested. Conversely, if the capital is strong enough to keep the price above the 4900 zone and create a higher low structure on D1, the market may extend the rebound to higher zones around 5100–5300. However, it should be emphasized that in the current context, such increases should still be viewed as recovery in a downtrend, until clear accumulation over time appears. Overall, gold is still in a phase where a long-term bottom has not formed. A real bottom does not come from a strong bounce, but from a long enough accumulation process to completely break market expectation psychology. Currently, that factor has not appeared, and capital still tends to take advantage of rebounds to distribute. Therefore, the week of 30/03–03/04 is likely to continue being a phase of liquidity testing and redefining the main direction, with a bias towards a downward scenario if important resistance zones are not conquered. LucasGrayTrading
OANDA:XAUUSDShort
by LucasGrayTrading
41
GOLD Price Update – Clean & Clear ExplanationGold is currently trading around 4,493, showing signs of short-term weakness after a strong bullish impulse. The market recently experienced a sharp upward move, pushing price into a key resistance zone near 4,540 – 4,580, where selling pressure has emerged. now price in a downward phase, with sellers in control—price making lower highs and lower lows. That bearish pressure eventually slowed, and the market began to base and accumulate, forming a gradual transition into an uptrend. Key zones to focus on Resistance: 4,530 – 4,580 Support / Demand: 4,460 – 4,480 The Gold strong rally, price is now pulling back and consolidating below resistance the structure shows lower highs forming, indicating temporary bearish pressure. “If you come across this post, please like, comment, and share. Thanks!”
OANDA:XAUUSDLong
by Pintu_sahu01
21
XAUUSD Bullish at 4460 Ahead of NFP and Geopolitical Risks!Hey Traders, in today's trading session we are monitoring XAUUSD for a buying opportunity around the 4,460 zone. Gold is trading in an overall uptrend and currently is in a correction phase in which price is approaching the trendline support around the 4,460 support and resistance area. From the macro side, gold remains fundamentally supported by ongoing geopolitical tensions in the Middle East, which continue to keep safe-haven demand active across the market. At the same time, extreme volatility in oil prices is increasing inflation uncertainty, which keeps investors cautious and supportive of long-term gold demand. Although the US Dollar is still trading near multi-month highs and Treasury yields remain elevated, gold’s recent pullback appears more corrective than structural. The move into the 4,460 demand zone aligns with dip-buying interest, especially as traders begin positioning ahead of this week’s high-impact US data releases, including ISM and Nonfarm Payrolls, which could quickly weaken the dollar if data misses expectations. As long as price holds above the 4,460 support zone, the broader bullish structure remains intact, and we anticipate a continuation move toward higher resistance levels as safe-haven flows and macro uncertainty continue to support the upside. Trade safe Joe
PEPPERSTONE:XAUUSDLong
by JoeChampion
24
XAG/USD - Breakout Watch – Silver Ready for a Bullish Expansion?📊 Description & Setu p FX:XAGUSD XAGUSD is currently consolidating within a strong support zone after breaking out of a major descending trendline on the 1h chart. If we see a decisive bounce and sustained momentum from this base, it opens the door for a high-probability play toward our upper resistance targets. 🧭 Daily Bias: Bullish 🟢 🎯 Trade Intent: Looking for BUY setups 📈 🛠️ Technical Confluences: • Price reacting from strong demand zone (60.80 – 63.10) • Multiple rejections from descending trendline resistance (weakening sellers) • Consolidation structure indicating accumulation before expansion 📐🕯️ 🌍 Macro & Fundamental Catalyst: Precious metals are supported by safe-haven demand and shifting rate expectations. Any signs of USD weakness or dovish central bank tone could accelerate upside in silver. 🏦⚖️ 🟢 Targets / Resistance: R1: 77.124 (1st Resistance) R2: 81.223 - 81.252 (2nd Resistance) 🔴 Invalidation / Support: S1: 65.894 (Bottom of immediate accumulation zone) S2: 63.123 - 60.842 (Major Lower Support Zone) ⚠️ Disclaimer This analysis is for educational purposes only and not financial advice. Always manage your risk. #XAGUSD #ForexTrading #TechnicalAnalysis #PriceAction #TradingSetup #Silver #PreciousMetals If you find this analysis useful: 👍 Like the idea 💬 Comment your view — Are you taking the Buy or the Sell? ⭐️ Follow for daily high-probability setups Charts Don’t Lie — Traders Don’t Quit. 📈
FX:XAGUSDLong
by KABHI_TA_TRADING
31
GOLD: From Manipulated Drop to Bullish SetupGOLD: From Manipulated Drop to Bullish Setup From our old analysis, gold found a clear and strong support area near the red 4130 area after that huge -26% drop in a few days and all for no reason, as we all saw. Currently on the 4-hour charts, the price seems to be gathering for an upward move and forming an ascending triangle. Once the price moves above the triangle, a bigger move could happen. On the other hand, Trump is only making comments about reaching a peace agreement, but peace is the only thing Trump and Israel want, making geopolitical tension increase every day and supporting the rise in the price of gold. Key Targets: 4650 5000 5400 6000 You may find more details in the chart. Thank you and good luck! 🍀 ❤️ If this analysis helps your trading day, please support it with a like or comment ❤️ Previous analysis:
OANDA:XAUUSDLong
by KlejdiCuni
19
Selena | XAUUSD · 30M – Channel Correction Between Demand & SuppPEPPERSTONE:XAUUSD FOREXCOM:XAUUSD Structure | Trend | Key Reaction Zones Gold is currently trading inside a rising corrective channel after reacting from a key demand zone. Market Overview After a strong bearish move, price swept liquidity near 4200 and formed a solid base around the 4300–4400 demand zone. The market is now moving in a corrective bullish channel, indicating short-term recovery. However, price is approaching the 4600–4700 supply zone, which aligns with previous structure and could act as resistance. The reaction from this zone will determine whether the market continues higher or resumes the bearish trend. Key Scenarios ✅ Bullish Case 🚀 Continuation within channel. 🎯 Target 1: 4600 🎯 Target 2: 4700 🎯 Target 3: 4800 – 4900 Current Levels to Watch Resistance 🔴: 4600 – 4700 Support 🟢: 4300 – 4400 ⚠️ Disclaimer: This analysis is for educational purposes only. Not financial advice.
FOREXCOM:XAUUSDLong
by Gold-Thoughts-by-Selena
13
XAUUSDHello Traders! 👋 What are your thoughts on Gold? Following a strong bullish rally, Gold has entered a corrective phase. The breach of the ascending trendline provides a clear signal that the previous bullish structure is weakening. Currently, the price is performing a pullback toward a key confluence area, where the supply zone aligns with the broken trendline and the 0.5 Fibonacci retracement level. This convergence zone is expected to act as a significant resistance, potentially leading to a price rejection. Should the price react to this level and complete the pullback, it is anticipated to initiate a new bearish wave, targeting lower support levels. A convincing break and sustained consolidation above this resistance zone will invalidate the bearish outlook. Please don’t forget to like and share your thoughts in the comments! ❤️
FOREXCOM:XAUUSDShort
by HAMED_AZ
27
Gold 30M Bullish Structure Holding Above SupportGold has shifted into a short-term bullish structure after a CHoCH, with price holding above the rising trendline support. The market is consolidating near support while maintaining higher lows, suggesting potential continuation to the upside. Bullish continuation: if price holds the 4,485–4,465 support zone, it may continue higher toward the 4,600 weekly high resistance. Deeper pullback: a break below support could lead to a retracement into the 4,420 demand zone (order block + FVG) before a potential rebound. Key levels Resistance: 4,600 (weekly high Current resistance area: ~4,500 Support zone: 4,485–4,465 Lower demand zone: ~4,420 Short-term bullish while above 4,465, with upside targets in focus. This is a technical analysis idea for educational purposes, not financial advice.
TVC:GOLDLong
by Gold_pro_traders
24
Gold Price Action – Key Support and Resistance Levels with TrendThis chart provides a detailed analysis of Gold (XAU/USD), focusing on crucial support and resistance levels. The Key Resistance at 5,389.438 USD marks a strong potential rejection point. Minor Resistance at 5,013.195 USD could signal a price reversal, while the Critical Support at 4,716.315 USD represents an important level to watch for price action. The Current Price at 4,542.445 USD is an active level to monitor closely for either a breakout or reversal. Strong Support at 4,427.393 USD is expected to hold the price, potentially leading to a bullish move. The Upward Trend Channel suggests overall bullish momentum, indicating that price may continue moving upward, with further opportunities at these key levels. Traders should monitor these levels to adjust their positions accordingly based on market behavior.
TVC:GOLDLong
by XauusdMarketNavigator
15
XAUUSD: Bullish Recovery from 4,440 - Price Targets 4,700 SupplyHello everyone, here is my breakdown of the current XAUUSD setup. Market Analysis Gold was previously trading inside a downward channel, showing consistent bearish pressure with lower highs and lower lows. After a strong drop, price found support around the 4,440 zone and formed a base, followed by a breakout above resistance, signaling a shift in momentum. Currently, price is trading inside an upward channel and holding above the 4,440 support zone, confirming it as a key demand area. At the same time, gold is approaching the 4,700 resistance zone, which aligns with a previous rejection level. My Scenario & Strategy As long as XAUUSD holds above the 4,440 support and respects the ascending channel, the bullish bias remains valid. A continuation higher could push price toward the 4,700 resistance, which is the main upside target. However, if price breaks below 4,440, the bullish scenario would weaken and a deeper pullback could follow. That’s the setup I’m tracking. Thank you for your attention, and always manage your risk.
FOREXCOM:XAUUSDLong
by Ratner
13
GOLD market is leaning slightly bearishGold is trapped in a range near resistance, and the market is leaning slightly bearish. Unless buyers can break above 4,550 with strength, the more probable move , Tecnically few sessions, gold has gone through a sharp sell-off followed by a steady recovery. After the deep drop (visible on the left side), buyers stepped in strongly, pushing price back up. However, that recovery lost momentum as price approached a major resistance zone around 4,550 Since then, the market has transitioned into a sideways consolidation phase, forming a range Inside this range, price action has become choppy, with lower highs forming near resistance, suggesting that buyers are struggling to push higher. At the same time, support has been tested multiple times, which weakens it over time. Resistance ; 4520 / 4600 Support ; 4400 / 4300 The most recent movement shows a failed attempt to push higher, followed by hesitation just below resistance a classic sign of distribution, where buying strength may be fading. You may find more details in the chart, Trade wisely best of luck buddies. Ps; Support with like and comments for better analysis Thanks for Supporting.
FOREXCOM:XAUUSDShort
by MR_GOLD_12
9
GOLD - A countertrend correction before a decline ICMARKETS:XAUUSD is under pressure again at the start of the week. A counter-trend retest of the 4555–4600 range is forming amid a strong dollar and rising oil prices. The conflict in the Middle East is escalating, and threats to global trade are mounting. Iran is preparing for a possible U.S. ground invasion of Kharg Island. With the risk of the Bab el-Mandeb Strait being blocked by Yemeni Houthis, such a blockade would further boost the dollar and oil prices, exerting enormous pressure on markets and driving up inflation. As the war expands to new fronts (the Red Sea, Lebanon) and the Fed shows no rush to ease policy, gold will remain under pressure. The bearish trend persists, with a key trigger at 4600 Resistance levels: 4550, 4600, 4735 Support levels: 4487, 4416, 4350 Technically, if bears hold the resistance of the current range, gold may remain within it and head toward the liquidity zone formed at 4416. I do not rule out the possibility of a rally to 4735 as part of market manipulation before a stronger decline. Best regards, R. Linda!
ICMARKETS:XAUUSDShort
by RLinda
13
XAUUSD Breakout Loading! Explosive Move Incoming?🚨 Market Situation TVC:GOLD Gold is currently trading inside a tight compression (triangle structure), with price approaching a key descending resistance trendline. After multiple higher lows, buyers are slowly building pressure — a classic sign of a potential breakout setup. 💡 Compression = Expansion coming soon 🎯 Key Levels (Must Watch) 🔴 Resistance Levels: → 4726 (First resistance) → 4805 (Second resistance / major target) 🟢 Support Zone: → 4387 (Key structural support) 🚀 Trade Idea 👉 Break above trendline → Expect bullish expansion toward 4726 & 4805 👉 Rejection from resistance → Possible short-term pullback ⏳ Wait for breakout confirmation — avoid false moves ⚠️ Disclaimer This is for educational purposes only. Not financial advice. Always manage your risk. #XAUUSD #GoldTrading #ForexTrading #PriceAction #TechnicalAnalysis #TradingView #BreakoutSetup 🔥 If this setup helped you: 👍 Like 💬 Comment your bias (Breakout or Rejection?) ⭐ Follow for more high-probability setups Charts Don’t Lie — Traders Don’t Quit. 📉🔥
FX:XAUUSDLong
by KABHI_TA_TRADING
16
Lingrid | GOLD Weekly Market Analysis: Rebound Under PressureOANDA:XAUUSD has staged a technical rebound from key support levels following a sharp correction, yet the broader market structure remains under significant pressure from rising real yields and a resurgent US dollar. While the recent escalation in US-Iran tensions initially sparked safe-haven flows, the precious metals complex has largely retreated. Technically, the chart reveals a price action is currently coiling within a potential rising wedge pattern situated inside the overarching major bearish channel. Following the decisive breakdown from the previous triangle, the recent bounce appears to be a corrective retracement rather than a trend reversal. The chart shows a possible bearish continuation from the apex of this current wedge formation, with a downside target near 4,230. Immediate resistance looms near the 4,700 level, where the pattern's upper trendline converges with previous support-turned-resistance, offering a high-probability zone for bearish entries. Fundamental catalysts this week align with this bearish technical outlook. The economic calendar features high-impact US data, including ADP Non-Farm Employment, Core Retail Sales, and ISM Manufacturing PMI. Strong readings in these reports would likely reinforce the Federal Reserve's hawkish stance, boosting the dollar and pressuring gold further. We should watch for a breakdown below as confirmation to target the 4,230 support zone, while a sustained move above 4,700 would be required to invalidate the immediate bearish thesis. Traders, if you like this idea, please leave your thoughts in the comments. I look forward to reading your ideas!
OANDA:XAUUSDShort
by Lingrid
23
What 14 Million Tests Say About MACDThis paper is the fourth in a series. The first study tested RSI across 26 million configurations and found zero Bonferroni-significant results. The second documented a small but genuine Turn of the Month anomaly, with 21 significant results from 385 tests. The third examined VWAP and produced the strongest findings so far: 150,546 Bonferroni-significant results concentrated in mean reversion, with short signal edge of 0.89 percentage points, roughly six times transaction costs. MACD was always going to be next. The Moving Average Convergence Divergence indicator is the second-most popular technical analysis tool after RSI, present on virtually every charting platform, explained in every trading course, and defended with religious fervor. It has also been defended, occasionally, in the academic literature. Brock, Lakonishok and DeLoach (1992) found some evidence for moving average rules on the Dow Jones Industrial Average. That paper has been cited over three thousand times and forms the intellectual scaffolding for every MACD apologist who claims institutional backing. We tested MACD more thoroughly than it has been tested before. 14,310,400 parameter configurations across eight distinct strategies, 20 assets spanning six categories, 436 valid parameter pairs, eight signal periods, and 26 holding periods. The same Welch t-test framework with Bonferroni correction used for RSI, Turn of the Month, and VWAP. The results are unambiguous. MACD generates 3,235 Bonferroni-significant results from over 14 million tests, of which 2,844 concentrate in a single strategy type, histogram divergence, on the short side. The overall mean long edge is +0.054 percentage points and the mean short edge is +0.018 percentage points. Both are economically negligible, falling well below transaction costs. The standard 12/26/9 setup, the configuration taught in every introductory course, produces zero Bonferroni-significant results. The line crossover, the most commonly used MACD signal, also produces zero. MACD joins RSI in the category of indicators that fail systematic testing. Unlike RSI, which produced absolutely nothing, MACD shows a faint statistical pulse in divergence signals. That pulse is too weak and too concentrated to constitute a trading strategy, but it exists. Whether it constitutes a genuine edge or a statistical artifact at the boundary of detection is a question the data cannot definitively resolve. 1. Introduction Gerald Appel introduced the MACD indicator in 1979 as a tool for identifying changes in trend momentum (Appel, 1979). The calculation is straightforward: take the difference between a fast exponential moving average and a slow exponential moving average of price, then smooth that difference with a third exponential moving average called the signal line. The difference between the MACD line and the signal line forms the histogram. Appel recommended the 12/26/9 parameterization, meaning 12-period and 26-period EMAs with a 9-period signal smoothing. That combination has since become one of the most widely recognized parameter sets in all of technical analysis. The indicator spread quickly through the retail community. By the 1990s, MACD was included as a default indicator on nearly every charting platform. Murphy (1999) dedicated an entire chapter to it in his standard reference on technical analysis. Elder (1993) featured it prominently in his trading methodology. Pring (2002) described it as one of the most reliable momentum indicators available to traders. These endorsements were based on observation, pattern recognition, and discretionary experience, not systematic statistical testing. The academic treatment of MACD has been more cautious. Brock, Lakonishok and DeLoach (1992) tested simple moving average rules on the Dow Jones Industrial Average from 1897 to 1986 and found some evidence of predictive content in moving average signals. Their results applied to simple moving average crossovers, not specifically to MACD, but the paper became the most frequently cited academic justification for MACD-type strategies. Sullivan, Timmermann and White (1999) subsequently re-examined these results using the bootstrap reality check methodology and found that after correcting for data snooping, the evidence weakened substantially. Lo, Mamaysky and Wang (2000) applied computational pattern recognition to technical analysis and concluded that some technical patterns contain genuine information, while cautioning that the magnitude was economically small after costs. Park and Irwin (2007) surveyed 95 studies of technical analysis profitability and concluded that the evidence was mixed, with earlier studies tending to find profitability and later studies, using more rigorous methodology, finding less. The academic literature on MACD specifically, as distinct from simple moving average rules, is thin. Most quantitative studies lump MACD into broader examinations of moving average rules without testing its specific strategy variants independently. This gap leaves the retail community relying on decades-old endorsements from practitioners rather than on direct statistical evidence. The present study fills that gap with what we believe is the most comprehensive systematic test of MACD strategies in the available literature: 14,310,400 parameter configurations tested with Bonferroni correction across a diversified asset universe. 2. What MACD measures MACD is built from three exponential moving averages. The MACD line equals the fast EMA minus the slow EMA: MACD line = EMA(close, fast period) minus EMA(close, slow period) The signal line smooths the MACD line: Signal line = EMA(MACD line, signal period) The histogram equals the difference: Histogram = MACD line minus Signal line When the fast EMA exceeds the slow EMA, the MACD line is positive, indicating that recent prices are higher than prices over the longer lookback. When the MACD line exceeds the signal line, the histogram is positive, indicating that the trend is accelerating. Traders interpret these relationships as momentum signals. The standard 12/26/9 parameterization uses alpha equal to 2/(n+1) for each EMA, giving the fast EMA a smoothing factor of approximately 0.154, the slow EMA approximately 0.074, and the signal line approximately 0.20. These are not derived from any optimization or theoretical framework. Appel (1979) selected them based on his visual examination of stock charts. The combination stuck because it was published first, not because it was demonstrated to be optimal. At its core, MACD measures the difference between two lagged representations of the same price series. Both the fast and slow EMAs are functions of past closing prices, weighted by geometrically declining coefficients. The MACD line captures the difference in how quickly these two representations respond to recent price changes. When price moves sharply, the fast EMA reacts first, creating a gap that the MACD line registers. The signal line further smooths this gap. The critical question is whether this double-differenced, triple-smoothed transformation of price adds information that the original price series does not contain. Moving averages are linear combinations of past prices. Taking the difference of two moving averages produces another linear combination of past prices. Smoothing that difference with a third moving average produces yet another linear combination. At every step, the input is price, and the output is a weighted average of past prices. No new information enters the calculation at any stage. This is the same structural problem documented in our RSI study. RSI computes a ratio of recent up moves to recent down moves, which is a nonlinear transformation of price, and still produces zero Bonferroni-significant results. MACD performs a purely linear transformation, which is theoretically even less likely to extract latent information. The question is whether the empirical evidence agrees with this theoretical expectation. 3. Common MACD strategies Retail MACD education centers on eight interpretive frameworks. Some are taught in every introductory course. Others appear in more advanced material. All eight are represented in our test battery. The line crossover interprets the MACD line crossing above the signal line as a buy signal and crossing below as a sell signal. This is the canonical MACD trade and the first strategy every tutorial teaches. The zero-line cross interprets the MACD line crossing above zero as bullish, meaning the fast EMA has overtaken the slow EMA, and crossing below zero as bearish. The histogram direction change interprets the histogram crossing from negative to positive as a buy signal and positive to negative as a sell signal. Because the histogram equals MACD line minus signal line, this is equivalent to the line crossover with one bar less lag. The histogram divergence compares price action with histogram behavior over a lookback window. When price makes a new low but the histogram does not, this is interpreted as bullish divergence. When price makes a new high but the histogram does not, bearish divergence. The price-MACD divergence is similar but compares price against the MACD line itself rather than the histogram. Price making a new low while the MACD line does not suggests weakening downward momentum. The histogram momentum strategy looks for three or more consecutive bars of increasing or decreasing histogram value, interpreting sustained directional movement in the histogram as acceleration in the underlying trend. The above-zero filtered crossover restricts the standard line crossover to signals occurring when the MACD line is above zero for longs and below zero for shorts. The logic is that a crossover above the zero line represents a stronger confirmation because it occurs within an established trend rather than against one. The histogram peak-trough reversal identifies local extrema in the histogram and enters when the histogram reverses from a peak or trough. A trough followed by a rising bar generates a long signal. A peak followed by a falling bar generates a short signal. None of these strategies has a theoretical derivation. They are all interpretive frameworks applied to a derived indicator, based on the assumption that various patterns in the MACD-signal-histogram relationship predict future price direction. The divergence strategies have the weakest theoretical basis of all, requiring price and momentum to disagree in a specific way and treating the disagreement as predictive. Whether any of them contain information is an empirical question. 4. Data and methodology 4.1 Asset universe We constructed a universe of 20 ETFs across six categories covering the major liquid segments of global financial markets. US large cap equities comprised SPY, QQQ, IWM, DIA, and VTI, providing exposure from the S&P 500 to the total market. Sector ETFs included XLF, XLK, XLE, XLV, and XLU, spanning financials, technology, energy, healthcare, and utilities. International equities included EFA and EEM, covering developed and emerging markets. Fixed income comprised TLT, IEF, and AGG, spanning long-duration treasuries, intermediate treasuries, and the aggregate bond market. Commodities included GLD, SLV, and USO, covering gold, silver, and oil. Real assets comprised VNQ and DJP, covering REITs and a broad commodity index. All data is daily, sourced from TwelveData with Tiingo as fallback, covering approximately 5,000 trading days per asset. 4.2 Parameter grid We tested the full practical range of MACD parameters: Fast period: 2 through 20 in steps of 1, giving 19 values. Slow period: 10 through 60 in steps of 2, giving 26 values. Valid parameter pairs require the slow period to exceed the fast period by at least 5, producing 436 valid combinations. Signal period: 3, 5, 7, 9, 12, 15, 18, and 21, giving 8 values. Holding period: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 14, 16, 18, 20, 25, 30, 40, 50, 60, 75, 90, 120, 150, 180, and 252 trading days, giving 26 values from one day to one full year. The total configuration space is 8 strategies multiplied by 20 assets multiplied by 436 parameter pairs multiplied by 8 signal periods multiplied by 26 holding periods, equalling 14,510,080 target tests. After filtering for minimum data length and minimum signal counts, 14,310,400 valid test results remained. 4.3 Strategy implementation For each asset and parameter combination, MACD is calculated once using pandas ewm with adjust=False, which produces the standard exponential moving average with alpha equal to 2/(n+1). All eight strategies generate their signals from this single MACD calculation. Forward returns are computed as close-to-close returns over the specified holding period. This avoids look-ahead bias: the signal fires at bar t, and the return is measured from the close of bar t to the close of bar t plus the holding period. 4.4 Statistical framework Edge equals the mean forward return following a signal minus the mean forward return over all bars in the same asset sample. This baseline-adjusted approach ensures that a strategy in a rising market does not receive credit for beta. Significance is assessed using Welch's t-test for unequal variances. A minimum of 10 signals per configuration is required. Given 14,310,400 valid tests, the Bonferroni-corrected significance threshold at alpha equal to 0.05 is 3.49 times ten to the negative ninth power. Surviving this threshold requires a result so extreme that it would occur by chance fewer than once in 300 million tries under the null hypothesis. 5. Results 5.1 Aggregate findings Figure 1 presents the overall picture, and it is a quiet one. Mean edges cluster near zero for most strategies. No strategy produces mean edge exceeding 0.35 percentage points on either side. Histogram divergence and price-MACD divergence are the only strategies with visible positive bars on the long side. The annotations beneath each strategy name show Bonferroni-significant test counts, and most read zero. Across all 14,310,400 tests, mean long edge is +0.054 percentage points and mean short edge is +0.018 percentage points. Both figures are below the 0.10 to 0.15 percentage points required to cover round-trip transaction costs for liquid ETFs. Even if these edges were statistically robust, they would not survive implementation. Figure 2 decomposes by asset category and shows that the weak aggregate results are not masking strong effects in subgroups. US equities show the most positive numbers: long edge +0.209 percentage points and short edge +0.128 percentage points. But even these figures are marginal relative to transaction costs and do not achieve significance after Bonferroni correction in the vast majority of configurations. 5.2 Statistical significance Figure 3 maps the parameter space. The heatmap is dominated by colors near zero, with no clearly defined region of strong positive or negative edge. The standard 12/26 position sits in an unremarkable part of the landscape, neither at a local optimum nor at a local minimum. There is no hidden sweet spot that traders are missing. The parameter space is uniformly mediocre. Figure 4 examines whether edge develops at longer holding horizons, as it did for VWAP mean reversion. The answer is no. Long and short edges show no consistent monotonic pattern across holding periods. Some strategies show mild positive edge at very long holding periods above 120 days, but the effects are small, inconsistent across strategies, and could plausibly reflect equity risk premium rather than MACD signal content. Figure 5 shows the p-value distribution. Under the null hypothesis, p-values distribute uniformly. The observed distribution is close to uniform, with a mild excess at low values that is much less pronounced than the sharp spike documented in the VWAP study. The excess represents the 391 long-side and 2,844 short-side Bonferroni-significant results. These are not zero, which distinguishes MACD from RSI, but they are not the kind of departure from uniformity that characterizes a robust indicator. 5.3 Results by strategy Histogram divergence is the only strategy with a meaningful number of significant results. Of 1,788,800 histogram divergence tests, 255 long signals and 2,844 short signals survive Bonferroni correction. Mean long edge is +0.323 percentage points, mean short edge is +0.102 percentage points. The long edge is above transaction costs. The short edge is not. The mechanism behind histogram divergence is that price makes a new low over a lookback window while the MACD histogram does not. This is interpreted as weakening selling pressure. The data suggests this interpretation has some validity: when selling pressure weakens as measured by the histogram failing to confirm a price low, subsequent long returns are modestly above baseline. The effect is real in the statistical sense of surviving strict correction. Whether it is robust enough to build a strategy around is another question: 255 Bonferroni-significant long results from 1.79 million tests is a survival rate of 0.014 percent. Price-MACD divergence produces 136 Bonferroni-significant long results with mean long edge of +0.347 percentage points. This is structurally similar to histogram divergence but uses the MACD line itself rather than the histogram. The slightly higher mean edge and lower survival count suggest a less consistent but occasionally stronger signal. Line crossover produces zero Bonferroni-significant results from 1,788,800 tests. The canonical MACD trade, the one drawn first on every tutorial chart, has no statistical support. Zero-line cross produces zero Bonferroni-significant results. The idea that the fast EMA overtaking the slow EMA predicts future returns is not supported. Histogram direction change produces zero Bonferroni-significant results. This is equivalent to the line crossover with slightly different timing, and the data treats them identically: both fail. Histogram momentum produces zero Bonferroni-significant results. Three consecutive bars of histogram acceleration predict nothing. Above-zero filtered crossover produces zero Bonferroni-significant results. Adding a trend filter to a crossover that does not work does not produce a crossover that works. Histogram peak-trough reversal produces zero Bonferroni-significant results. Identifying local extrema in the histogram and trading the reversal generates random outcomes. Figure 7 presents the complete numerical summary. Six of eight strategies produce zero Bonferroni-significant results. The two that produce significant results, histogram divergence and price-MACD divergence, account for a total of 3,235 significant tests from 14.3 million, a rate of 0.023 percent. For comparison, VWAP mean reversion alone produced 100,765 significant results from 1.68 million tests, a rate of 6.0 percent. 5.4 Results by asset category US equities show the strongest effects: long edge of +0.209 percentage points and short edge of +0.128 percentage points. This is consistent with US equities being the most liquid, most traded, and most studied market, where any residual signal is most likely to appear. International equities show modest long edge of +0.028 percentage points but more interesting short edge of +0.193 percentage points. Sector ETFs show positive long edge of +0.134 percentage points with short edge near zero. Commodities show negative edge on both sides: long negative 0.175 percentage points and short negative 0.180 percentage points. This means MACD signals applied to commodity ETFs actively destroy value on both the long and the short side. The commodity result is consistent with the lack of volume-based microstructure dynamics in commodity ETFs, where price movements are driven by supply-demand fundamentals rather than by institutional execution patterns. Fixed income shows mildly negative edge on both sides. Real assets show negligible edge in both directions. 5.5 The standard 12/26/9 setup Figure 8 isolates the question every MACD user wants answered: is the standard setup at least better than the average parameter combination? From 4,160 tests using exactly the 12/26/9 parameterization, mean long edge is +0.060 percentage points and mean short edge is negative 0.012 percentage points. Bonferroni-significant results: zero on both sides. The violin plots show the 12/26/9 distribution sitting squarely in the middle of the full parameter distribution. It is not worse than average. It is not better than average. Appel's original recommendation, selected from visual chart examination in 1979, performs almost exactly at the median of the parameter space. There is no hidden better combination waiting to be discovered either: the best mean long edge across all parameter combinations is +0.656 percentage points (price-MACD divergence, fast=20, slow=26, signal=3), which sounds like progress until you realize it is a mean across 20 assets and 26 holding periods and that the best-looking aggregate can easily emerge from random variation when 3,488 parameter triplets are evaluated. 6. Comparison with previous studies Four indicators, 46 million tests, one consistent framework. The scoreboard: RSI: zero Bonferroni-significant results from 26 million tests. The most popular technical indicator generates random output. Turn of the Month: 21 Bonferroni-significant results from 385 tests. A small test universe with a real effect driven by identifiable institutional flow cycles. VWAP: 150,546 Bonferroni-significant results from 5.8 million tests. Mean reversion short signals deliver 0.89 percentage points of edge, roughly six times transaction costs. A genuine, economically meaningful finding with a clear microstructure mechanism. MACD: 3,235 Bonferroni-significant results from 14.3 million tests. Concentrated in histogram divergence with mean long edge of +0.323 percentage points. Marginal relative to transaction costs. No strategy variant approaches the economic significance of VWAP mean reversion. The pattern that emerges across these four studies is now well established. Price-only transformations, RSI and MACD, fail. Both indicators take closing prices, apply mathematical operations, and return a derived series that contains no information beyond what the original price series already carried. The EMAs in MACD are linear weighted averages of past prices. Their differences are linear combinations of linear combinations. No transformation in this chain can create information that the input did not contain. Volume-incorporating indicators, specifically VWAP, succeed. VWAP integrates volume with price and thereby accesses information about market participation that price alone does not capture. The institutional execution patterns around VWAP create genuine supply-demand dynamics that a price-only indicator cannot detect. Calendar effects, Turn of the Month, succeed because they proxy for institutional flow patterns anchored to economic payment cycles. The information comes from the calendar, not from price. The lesson is consistent: indicators predict when they access information beyond the price series. Indicators that merely transform price cannot create information the price did not already contain. This is not a philosophical position. It is a consistent empirical finding across 46 million tests. 7. Why MACD fails and why divergence partially survives 7.1 The mathematical constraint MACD is a linear function of past prices. The fast EMA, the slow EMA, the MACD line, the signal line, and the histogram are all linear combinations of the same closing price series with different weighting schemes. In the framework of Lo, Mamaysky and Wang (2000), the question is whether the specific weighting scheme applied by MACD isolates information that raw price data obscures. For linear filters applied to the same underlying series, the answer is generally no. A linear filter can redistribute information across frequencies but cannot create it. The EMA emphasizes recent prices relative to older prices. The MACD line computes the difference between two such emphases. The result is a signal that is correlated with recent price momentum but carries no independent information about future returns. This is different from VWAP, which multiplies price by volume before averaging. That multiplication introduces a genuinely new data dimension. MACD multiplies price by nothing except predetermined decay weights that are functions of the chosen period parameters. 7.2 Why divergence is different Histogram divergence and price-MACD divergence are structurally different from the other six strategies because they compare two separate quantities: price level and an oscillator derived from price. When price makes a new low but the histogram does not confirm that low, the signal is detecting a nonlinear discrepancy between raw price and the smoothed momentum measure. This is a second-order relationship that goes beyond the simple linear filtering of the crossover strategies. The divergence detection involves comparing local extrema in two different series, a comparison that introduces a nonlinearity the other MACD strategies lack. Price can make new lows while smoothed momentum improves because the rate of decline is slowing even as the level continues to fall. This is economically interpretable: weakening selling pressure before a price reversal. The divergence signals survive Bonferroni correction, but barely. 255 long and 2,844 short results from 3.58 million divergence tests is a survival rate of 0.087 percent. For context, VWAP mean reversion produces a survival rate of 6.0 percent, roughly 70 times higher. The divergence effect is real in the statistical sense but sits at the edge of what can be confidently distinguished from multiple testing artifacts at this scale. 7.3 What Brock, Lakonishok and DeLoach actually found The most cited academic defense of MACD-type strategies is Brock, Lakonishok and DeLoach (1992), who tested simple moving average crossover rules on the DJIA from 1897 to 1986. Their results showed buy signals following moving average crossovers generated higher returns than sell signals. Three qualifications limit the applicability of those results to modern MACD trading. First, the study tested simple moving averages, not exponential moving averages with a signal line. MACD's triple-EMA structure is a more complex filter than anything Brock and colleagues examined. Second, the study used a single asset, the DJIA, over a single period. Sullivan, Timmermann and White (1999) applied the bootstrap reality check to an expanded set of technical trading rules and found that after correcting for the full universe of rules that could have been tested, the significance of the best-performing rule was substantially reduced. Third, the study period ended in 1986. Markets in 1986 were structurally different from markets in 2026: spreads were wider, execution was slower, algorithmic trading was non-existent, and information dissemination operated on fundamentally different timescales. A moving average rule that exploited slow information diffusion in 1960 would face a radically different environment today. Our results on 14.3 million tests across 20 assets and 40 years of more recent data find no support for MACD crossover strategies. This is not inconsistent with Brock and colleagues finding weak support for simple moving average rules on one asset ending in 1986. It simply means that any signal that may have existed has been arbitraged away, or that it was specific to the asset, period, and methodology of the original study. 8. Implications For traders using MACD crossover: 1,788,800 configurations tested. Zero Bonferroni-significant results. This is the same outcome as VWAP crossover and the same outcome as RSI in general. Crossover strategies applied to momentum oscillators do not predict future returns. The consistency of this null result across three independent indicators tested in three separate studies suggests that the finding is not specific to any one indicator. It is a property of crossover signals derived from price transformations. For traders using MACD divergence: the data shows a statistically real but economically marginal effect. Histogram divergence long signals average +0.323 percentage points, which exceeds transaction costs but only modestly. The effect concentrates in specific assets and parameter combinations rather than being broadly available across the universe. A trader who restricts MACD usage exclusively to divergence signals on US equities with carefully selected parameters might extract a small positive edge. Whether that edge justifies the complexity of implementation relative to alternatives such as VWAP mean reversion, which delivers nearly three times the edge with 70 times the significant configurations, is a question of opportunity cost. For systematic strategy developers: MACD does not belong in the toolbox as a primary signal generator. The 14.3 million tests produce no evidence of consistent, economically meaningful prediction from any MACD strategy variant. This does not preclude MACD as a filter or auxiliary input in a broader system, but the data does not support building a strategy around MACD signals. Resources allocated to MACD-based strategy development would generate substantially higher expected returns if redirected to VWAP mean reversion or calendar-based approaches. For trading educators: the standard MACD curriculum, centered on line crossovers and the 12/26/9 setup, teaches strategies that have been tested across 14 million configurations and produce nothing. If MACD must remain in curricula for completeness, the honest presentation would acknowledge that crossover signals have no statistical support, that the 12/26/9 setup is no better than the median parameter combination, and that the only variant with any empirical basis is divergence, which even then produces marginal edge. Teaching the standard MACD crossover as a viable trading strategy is, at this point, not supported by the evidence. 9. Limitations Several constraints bound the conclusions. First, this study tests daily data only. MACD behavior on intraday timeframes was not examined. The VWAP study showed that timeframe matters substantially, and it is possible that MACD performs differently on 4-hour or weekly data, though there is no theoretical reason to expect it would. Second, we tested MACD in isolation. Some practitioners combine MACD with other indicators, support and resistance levels, or fundamental filters. These combinations were not evaluated. It is possible that MACD contributes useful information as one component of a multi-factor system even though it fails as a standalone signal, though the same could be said of any random variable. Third, the divergence lookback was fixed at 14 bars. Variable lookback periods for divergence detection might produce different results. Fourth, execution was assumed at bar close. Real execution involves slippage that would further reduce the already-marginal edge values. Fifth, this study does not test whether MACD had predictive value in earlier historical periods that has since been arbitraged away. It is possible that MACD signals were informative in the 1980s and 1990s when markets were less efficient and algorithmic trading did not exist. That hypothesis is not testable with the data horizon available. References Appel, G. (1979). The Moving Average Convergence-Divergence Trading Method. Signalert Corporation, Great Neck, NY. Appel, G. (2005). Technical Analysis: Power Tools for Active Investors. Financial Times/Prentice Hall, Upper Saddle River, NJ. Brock, W., Lakonishok, J. and DeLoach, S. (1992). Simple technical trading rules and the stochastic properties of stock returns. Journal of Finance, 47(5), pp. 1731-1764. Elder, A. (1993). Trading for a Living: Psychology, Trading Tactics, Money Management. John Wiley and Sons, New York. Lo, A.W., Mamaysky, H. and Wang, J. (2000). Foundations of technical analysis: Computational algorithms, statistical inference, and empirical implementation. Journal of Finance, 55(4), pp. 1705-1765. Murphy, J.J. (1999). Technical Analysis of the Financial Markets. New York Institute of Finance, New York. Park, C.H. and Irwin, S.H. (2007). What do we know about the profitability of technical analysis? Journal of Economic Surveys, 21(4), pp. 786-826. Pring, M.J. (2002). Technical Analysis Explained. 4th edn. McGraw-Hill, New York. Sullivan, R., Timmermann, A. and White, H. (1999). Data-snooping, technical trading rule performance, and the bootstrap. Journal of Finance, 54(5), pp. 1647-1691.
CME_MINI:ES1!Education
by EdgeTools
31
SILVER(XAGUSD): Intraday Smart Trading Setup, Risky But Worth It✴️ Silver has recently reached levels of 74. Additionally, an analysis of the DXY suggests a possible bearish reversal after the index touched the 101 mark. This DXY movement is a significant factor supporting a sustained bullish trend for Silver. ✴️ However, given our intraday trading strategy, only a slight depreciation of the USD is required to propel silver prices towards our target. Other fundamental economic indicators, such as Non-Farm Payrolls (NFP) and additional data releases, could also influence the metals market. ✴️We encourage you to like, comment, and follow our work to support the continued sharing of such analyses. We wish you successful and secure trading. Sincerely, Team Setupsfx #xagusd #xag #silver #silvertrading #xagtrading #xagusdtrade #smartmoneyconcept #smc #smctrading #smcstrategy #icttrading #ict #daydtrading #forex #forexmarket #intradaytrading #smartsystem #metalmarket #silvermarket #goldmarket
OANDA:XAGUSDLong
by Setupsfx_
19
XAUUSD Rejection at 4,550 Signals Downside Risk To 4,390Hello traders! Here’s my technical outlook based on the current XAUUSD (4H) chart structure. Price moved inside an ascending channel before a rejection at the top signaled a shift. A break below channel support confirmed bearish structure. Currently, gold is trading below the 4,550 resistance (seller zone) and near the 4,390 support (buyer zone), forming a triangle compression. As long as price remains below the 4,550 resistance, the bearish bias stays valid. A rejection from this area could push price toward the 4,390 support (TP1) as the next downside target. Please share this idea with your friends and click Boost 🚀
FOREXCOM:XAUUSDShort
by LegionQ8
30
WTI Oil Preparing for Next Big Direction MoveThe chart illustrates WTI crude oil trading in a consolidation phase following a strong bullish rally 📊. Price has repeatedly tested the resistance zone around 101, forming multiple rejection wicks that highlight strong selling pressure at this level. Despite this, the ascending trendline continues to act as dynamic support, maintaining the overall bullish structure. Currently, price is approaching a key breakout zone, making the next move crucial 👀. A successful breakout above resistance could trigger strong bullish momentum, pushing price toward the target of 111.71 🚀. However, if price breaks below the trendline, it would signal weakness, leading to a decline toward the first bearish target at 91.95, with further downside potential extending to 86.52 if selling pressure intensifies. If you found this XAUUSD analysis helpful, don’t forget to LIKE 👍 and COMMENT 💬!
TVC:USOIL
by Dynamic_Trade_Strategies
4