Trading Divergences With Wedges in ForexTrading Divergences With Wedges in Forex
Divergence trading in forex is a powerful technique for analysing market movements, as is observing rising and falling wedges. This article explores the synergy between divergence trading and wedges in forex, offering insights into how traders can leverage these signals. From the basics to advanced strategies, learn how you could utilise this approach effectively, potentially enhancing your trading skills in the dynamic forex market.
Understanding Divergences
In forex trading, the concept of divergence plays a pivotal role in identifying potential market shifts. A divergence in forex, meaning a situation where price action and a technical indicator like the Relative Strength Index (RSI) or Moving Average Convergence Divergence (MACD) move in opposite directions, often signals a weakening trend. This discrepancy is a valuable tool in divergence chart trading, as it may indicate a possible reversal or continuation of the current trend.
There are two primary types of divergence in forex—regular and hidden. Regular divergence occurs when the price makes higher highs or lower lows while the indicator does the opposite, often signalling a reversal. Hidden divergence, on the other hand, happens when the price makes lower highs or higher lows while the indicator shows higher highs or lower lows, typically suggesting a continuation of the current trend.
Trading Rising and Falling Wedges
Rising and falling wedges are significant patterns in forex trading, often signalling potential trend reversals. A rising wedge, formed by converging upward trendlines, often indicates a bearish reversal if it appears in an uptrend. Conversely, a falling wedge, characterised by converging downward trendlines, typically reflects a bullish reversal if it occurs in a downtrend.
Traders often look for a breakout from these patterns as a signal to enter trades. For rising wedges, a downward breakout can be seen as a sell signal, while an upward breakout from a falling wedge is often interpreted as a buy signal. When combined with divergences, this chart pattern can add confirmation and precede strong movements.
Best Practices for Trading Divergences
Trading divergence patterns in forex requires a keen eye for detail and a disciplined, holistic approach. Here are key practices for effective trading:
- Comprehensive Analysis: Before trading on divergence and wedges, be sure to analyse overall market conditions.
- Selecting the Right Indicator: Choose a forex divergence indicator that suits your trading style. Common choices include RSI, MACD, and Stochastic.
- Confirmation Is Key: It’s best to watch for additional confirmation from price action or other technical tools before entering a trade.
- Risk Management: Traders always set stop-loss orders to manage risk effectively. Divergence trading isn't foolproof; protecting your capital is crucial.
- Patience in Entry and Exit: Be patient as the divergence develops and confirm with your chosen indicators before entering or exiting a trade.
Strategy 1: RSI and Wedge Divergence
Traders focus on regular divergence patterns when the RSI is above 70 (overbought) or below 30 (oversold), combined with a rising or falling wedge pattern. The strategy hinges on identifying highs or lows within these RSI extremes. It's not crucial if the RSI remains consistently overbought or oversold, or if it fluctuates in and out of these zones.
Entry
- Traders may observe a regular divergence where both the price highs/lows and RSI readings are above 70 or below 30.
- After the formation of a lower high (in an overbought zone) or a higher low (in an oversold zone) in the RSI, traders typically watch as the RSI crosses back below 70 or above 30. This is accompanied by a breakout from a rising or falling wedge, acting as a potential signal to enter.
Stop Loss
- Stop losses might be set just beyond the high or low of the wedge.
Take Profit
- Profit targets may be established at suitable support/resistance levels.
- Another potential approach is to exit when the RSI crosses back into the opposite overbought/oversold territory.
Strategy 2: MACD and Wedge Divergence
Regarded as one of the best divergence trading strategies, MACD divergence focuses on the discrepancy between price action and the MACD histogram. The strategy is particularly potent when combined with a rising or falling wedge pattern in price.
Entry
- Traders typically observe for the MACD histogram to diverge from the price. This divergence manifests as the price reaching new highs or lows while the MACD histogram fails to do the same.
- The strategy involves waiting for the MACD signal line to cross over the MACD line in the direction of the anticipated reversal. This crossover should coincide with a breakout from the rising or falling wedge.
- After these conditions are met, traders may consider entering a trade in anticipation of a trend reversal.
Stop Loss
- Stop losses may be set beyond the high or low of the wedge, which may help traders manage risk by identifying a clear exit point if the anticipated reversal does not materialise.
Take Profit
- Profit targets might be established at nearby support or resistance levels, allowing traders to capitalise on the expected move while managing potential downside.
Strategy 3: Stochastic and Wedge Divergence
Stochastic divergence is a key technique for divergence day trading in forex, especially useful for identifying potential trend reversals. This strategy typically employs the Stochastic Oscillator with settings of 14, 3, 3.
Entry
- Traders may look for divergence scenarios where the Stochastic readings are above 80 or below 20, mirroring the RSI approach.
- This divergence is observed in conjunction with price action, forming a rising or falling wedge.
- Entry may be considered following a breakout from the wedge, which signals a potential shift in market direction.
Stop Loss
- Setting stop losses just beyond the high or low of the wedge might be an effective approach.
Take Profit
- Profit targets may be set at key support/resistance levels.
The Bottom Line
Divergence trading, coupled with the analysis of rising and falling wedges, offers a comprehensive approach to navigating the forex market. By integrating the discussed strategies with sound risk management and market analysis, traders may potentially enhance their ability to make informed decisions in the dynamic world of forex.
This article represents the opinion of the Companies operating under the FXOpen brand only. It is not to be construed as an offer, solicitation, or recommendation with respect to products and services provided by the Companies operating under the FXOpen brand, nor is it to be considered financial advice.
Chart Patterns
Liquidity Sweep + FVG + RSIThis BCH/USDT 2H chart illustrates a textbook example of a liquidity sweep and reversal, backed by RSI confluence. Price repeatedly tested a horizontal resistance level, eventually triggering a breakout trap — enticing late buyers just before reversing.
The false breakout swept buy-side liquidity, trapping retail longs above resistance. Immediately after, price dropped back below the key level and formed a Fair Value Gap (FVG) — a common area where smart money re-enters positions. This signaled distribution rather than continuation.
Adding to the bearish confluence, RSI showed overbought conditions during the sweep, reinforcing that momentum was exhausted. Once liquidity was taken and RSI began dropping, a strong bearish move followed.
📉This setup combines multiple Smart Money Concepts:
🔁Liquidity engineering
🔁Breakout trap
🔁Fair Value Gap re-entry
🔁RSI confirmation
Your Technical Analysis Improved, But Your Account Didn't. Why?You're learning more. Your charts look cleaner.
But somehow... your losses just keep getting worse?
If that feels familiar, this breakdown might explain exactly why.
Hello✌️
Spend 3 minutes ⏰ reading this educational material.
🎯 Analytical Insight on Solana:
BINANCE:SOLUSDT is testing a key trendline and daily support that aligns with Fibonacci levels 🔍. A clear break above the psychological resistance at $210 could trigger at least a 16% rally, targeting $230 🚀.
Now, let's dive into the educational section,
🧬 The Precision Trap
The better your analysis gets the narrower your entries become.
You start avoiding trades unless every single box is ticked. But guess what Markets don’t tick boxes. They break them.
Overanalysis creates tighter stops smaller buffers and a mind that’s too afraid to pull the trigger.
💰 The Hidden Greed in Smart Trades
Better analysis often brings a false sense of confidence. You expect more precision more profit.
This turns into silent greed masked as logic. Suddenly you risk bigger positions because this one is obvious.
But pros don't risk more when they’re more confident. They risk consistently.
💭 The Mind That Blocks Your Profits
You didn’t lose because you didn’t know. You lost because you knew too much and became a slave to it.
When your brain seeks confirmation not clarity it sabotages trades that were ready to work.
Don't let analysis chain you to hesitation.
🔄 Analysis or Addiction
Ask yourself honestly
Are you using your analysis to take action or to avoid it
Charts should guide you not paralyze you. If you need six signals to feel safe you’re not analyzing you’re hiding.
🧃 Every Chart Has a Bias
What looks like a sell to you might be a buy to someone else.
Why Perspective. Some buy the bounce others short the breakdown.
So if your top-tier analysis still leads to losses maybe it's time to stop upgrading tools and start upgrading your lens.
🧨 The Overanalysis Spiral
Your brain can’t juggle thirty signals. But most traders try anyway.
This doesn’t make you smarter. It makes you slower more anxious and emotionally drained.
Good trading isn’t about more info. It’s about clearer action.
🧱 The Mind That Won’t Let You Win
The more you lean on your indicators the more you fear breaking their rules.
You skip solid trades just because one tool says maybe not yet.
At that point it’s not risk management. It’s dependency. Let tools guide not dominate you.
🛠️ TradingView Tools That Help Or Hurt Your Mindset
It’s not about what tools you use. It’s how you use them.
Here are a few tools that when used right can actually improve both your decision-making and emotional control:
Session Volume and VWAP
Don’t just chase setups blindly. Check price versus VWAP. Often entries you feel are great are just late reactions to intraday rebalancing.
RSI and Auto Divergence
Don’t focus on RSI values alone. Use divergence indicators that highlight hidden bullish or bearish signals. Many traders miss moves by ignoring the tension RSI reveals.
Long Short Position Tool
Try using this for mental reps. Plot fake trades. Watch how the market behaves without risking capital. Over time you’ll train your brain not just your account.
These tools won’t fix your psychology but they’ll mirror it. And that’s where real change begins
🎯 Final Thoughts
Great analysts don’t trade everything they understand.
They understand what not to trade.
If better charts aren't bringing better results stop upgrading your screen and start rewiring your mindset.
✨ Need a little love!
We pour love into every post your support keeps us inspired! 💛 Don’t be shy, we’d love to hear from you on comments. Big thanks , Mad Whale 🐋
📜Please make sure to do your own research before investing, and review the disclaimer provided at the end of each post.
What does the future hold for Pi Network?Pi Network Coin (PI) is the native cryptocurrency of the Pi Network, a decentralized blockchain project designed to make cryptocurrency mining and usage accessible to everyday people via mobile devices. Unlike traditional cryptocurrencies like Bitcoin that rely on energy-intensive mining hardware, Pi Network allows users to mine PI coins on their smartphones using a lightweight, mobile-friendly process that does not drain battery life or require costly equipment.
What Could make Pi Network Grow (Factors affecting price)
Short-term price is highly volatile, influenced by token unlock schedules, exchange trading volumes, and speculative sentiment.
Medium-to-long term potential depends on the speed and success of Mainnet open trading launch, exchange listings on major platforms, and real-world PI ecosystem adoption including DeFi and decentralized applications.
Risks stem from regulatory uncertainties, possible high selling pressure from early miners, and slow token utility development.
Positive catalysts include expanding app ecosystem, mainstream exchange listings, and growing merchant/payment acceptance.
As of late July 2025, the PI price is subject to these dynamic factors, with market price hovering around $0.0006–$0.73 depending on exchange and trading pair, showing both significant upside if adoption accelerates and downside from current bearish technical pressures.
People don't like the truth! Let's be honest, people don't like honesty. They prefer ideas that affirm their own beliefs.
When I read articles and posts from newer traders, it's often from a place of "all in" diamond hands and the notion that things go up forever.
I've been a trader for over 25 years now, and the game isn't about making a quick buck, it's about making money over and over again. This got me thinking, the issue is when you deal with a small account you require leverage, small timeframes and of course the "shit" or bust mindset. If you lose a thousand dollars, $10,000 even $100,000 - what does it matter? That's no different than a game of poker in Vegas.
The idea of being 80% in drawdown, is alien to me. The idea of one trade and one win is also a crazy notion.
Instead of playing with the future, there is an easier way to work. This isn't about slow and boring, it's about psychology and discipline. 10% returns on a million-dollar account isn't all that difficult. Instead of aiming for 300x returns on an alt coin (due to the account size being tiny) You can make less of a percentage gain with a larger account size.
In terms of psychology - the word " HOPE " is used, way too often, it's used when you hope a stock or the price of Bitcoin goes up, it's used when you hope the position comes back in your favour, it's used when you want your 10,000 bucks to double.
This isn't trading, it's gambling.
The truth is, it's not the winners that make you a good trader. It's the way you deal with the losses.
Once you learn proper risk management, a downtrend in a market move is a 1-2% loss coupled with a new opportunity to reverse the bias.
As a disciplined trader, the game is played differently.
Let's assume you don't have $100k spare - prop firms are a great option, OPM = other people's money.
Remove the risk and increase the leverage, all whilst trading with discipline.
The market goes through many phases, cycles and crashes.
You don't always need something as catastrophic to take place, but if you are all in on a position. You need to understand that losses can be severe and long-lasting.
When everyone sees an oasis in the desert, it's often a mirage.
You only have to look at the Japanese lesson in 1989, when the Nikkei was unstoppable-until it wasn't. For that short space in time, everyone was a day trader, housewives to taxi drivers.
Everyone's a genius in a Bull market.
Then comes the crash. The recovery time on that crash?
34-years!!!
I have covered several aspects of psychology here on TradingView;
When it comes to trading, if you are able to keep playing. It's a worthwhile game. If you are gambling, it's a game whereby the house often wins.
Right now, stocks are worth more than their earnings. Gold is up near all-time highs, crypto, indices the same.
All I am saying is if you are all in. Be careful!
Disclaimer
This idea does not constitute as financial advice. It is for educational purposes only, our principal trader has over 25 years' experience in stocks, ETF's, and Forex. Hence each trade setup might have different hold times, entry or exit conditions, and will vary from the post/idea shared here. You can use the information from this post to make your own trading plan for the instrument discussed. Trading carries a risk; a high percentage of retail traders lose money. Please keep this in mind when entering any trade. Stay safe.
Market Travel: An Adaptive Framework for Tracking Structure🧭 Understanding Market Travel: An Adaptive Framework for Tracking Structure Manually
Market structure can be one of the most challenging patterns to read. There are tools and methods to help interpret it, but none are absolute. As market speed and volatility shift, so does its behavior. That’s why it’s important to move beyond rigid definitions and start understanding how price travels through the market.
What Is Travel?
“Travel” is a concept I developed through personal study and chart work. As price moves, it naturally forms pullbacks—temporary dips toward the weak side—and breaks—moves that close beyond the strong side. These are the two critical phases that form the backbone of market structure.
While most people focus on static patterns, I’ve found more value in learning how price travels through its pullbacks and breaks. These movements aren’t random—they follow clear behavioral patterns. Once you learn to identify these, structure becomes easier to read across timeframes.
The Three Modes of Travel
I've observed three types of travel that occur between the dip and the break:
1. Pure Sentiment Travel
This is the cleanest and most decisive form of travel. Price moves in one dominant direction with little to no opposing candles. For example, in a daily uptrend, the pullback might consist entirely of bearish 4H candles. As soon as a strong bullish candle appears, that typically signals the return toward the trend’s strong high.
2. Stacking Travel
Stacking is more nuanced. Price moves with alternating bullish and bearish candles, but the dominant sentiment stays in control.
Let’s say price is dipping in a daily uptrend. On the 1H chart, you may see a bearish sequence that includes a few bullish candles. These bullish candles don’t invalidate the bearish structure because they fail to close above the pivot high formed between the last bullish leg and the beginning of the bearish move. As long as that high is respected, the bearish stacking is valid.
Once price breaks that high (or, in a bullish stacking case, breaks the pivot low), the stacking order is broken, and that signals a reversal back toward the dominant direction.
3. Shifting Travel
Shifting travel looks similar to stacking but is constantly flipping between bullish and bearish stacking. Each shift creates a new high or low within the shifting structure. These micro-structures form lower lows or higher highs as sentiment switches back and forth.
Once price breaks its own shifting structure (e.g., breaks a bearish sequence with a bullish close), this typically signals the end of that leg of travel and a reversal toward the dominant higher timeframe trend.
How to Apply Travel Across Timeframes
These three types of travel operate in a hierarchy:
- Shifting travel (LTF) respects stacking travel (MTF)
- Stacking travel (MTF) respects pure travel (HTF)
- Pure sentiment travel (HTF) is the master mode that resets the others
When you identify a new pure sentiment shift on the higher timeframe, that becomes your reset point. From that candle forward, you should begin fresh stacking and shifting analysis on your lower timeframes.
Workflow example:
1. Spot a pure sentiment shift on the HTF (e.g., bullish daily candle after a clean bearish pullback)
2. From that pivot low, begin tracking stacking travel on the MTF
3. Use shifting travel on the LTF to navigate inside the stacking structure
If stacking or shifting behavior breaks unexpectedly, that usually means market speed is changing—and you may need to reassign which timeframes serve as HTF, MTF, and LTF.
Why This Works
This framework gives you a fixed point of structure—the dip and the break—but allows you to adapt to the behavior in between. Instead of just reacting to breakouts, you're learning how price moves to get there.
That’s what gives you the edge: not just reading where price is, but how it’s traveling to get there.
Final Thoughts
This adaptive travel model helps break down market structure into something both trackable and flexible. Try observing these travel types in real time and let me know how it works for you.
Tools & Resources
If you’d like to access my Pure Order Flow indicator and more exclusive tools, visit my TradingView profile:
@The_Forex_Steward
I’ve built an arsenal of indicators designed to support this framework across different markets and styles. If this breakdown helped, don’t forget to boost the post so others can benefit from it too!
The Empirical Validity of Technical Indicators and StrategiesThis article critically examines the empirical evidence concerning the effectiveness of technical indicators and trading strategies. While traditional finance theory, notably the Efficient Market Hypothesis (EMH), has long argued that technical analysis should be futile, a large body of academic research both historical and contemporary presents a more nuanced view. We explore key findings, address methodological limitations, assess institutional use cases, and discuss the impact of transaction costs, market efficiency, and adaptive behavior in financial markets.
1. Introduction
Technical analysis (TA) remains one of the most controversial subjects in financial economics. Defined as the study of past market prices and volumes to forecast future price movements, TA is used by a wide spectrum of market participants, from individual retail traders to institutional investors. According to the EMH (Fama, 1970), asset prices reflect all available information, and hence, any predictable pattern should be arbitraged away instantly. Nonetheless, technical analysis remains in widespread use, and empirical evidence suggests that it may offer predictive value under certain conditions.
2. Early Empirical Evidence
The foundational work by Brock, Lakonishok, and LeBaron (1992) demonstrated that simple trading rules such as moving average crossovers could yield statistically significant profits using historical DJIA data spanning from 1897 to 1986. Importantly, the authors employed bootstrapping methods to validate their findings against the null of no serial correlation, thus countering the argument of data mining.
Gencay (1998) employed non-linear models to analyze the forecasting power of technical rules and confirmed that short-term predictive signals exist, particularly in high-frequency data. However, these early works often omitted transaction costs, thus overestimating potential returns.
3. Momentum and Mean Reversion Strategies
Momentum strategies, as formalized by Jegadeesh and Titman (1993), have shown persistent profitability across time and geographies. Their approach—buying stocks that have outperformed in the past 3–12 months and shorting underperformers—challenges the EMH by exploiting behavioral biases and investor herding. Rouwenhorst (1998) confirmed that momentum exists even in emerging markets, suggesting a global phenomenon.
Conversely, mean reversion strategies, including RSI-based systems and Bollinger Bands, often exploit temporary price dislocations. Short-horizon contrarian strategies have been analyzed by Chan et al. (1996), but their profitability is inconsistent and highly sensitive to costs, timing, and liquidity.
4. Institutional Use of Technical Analysis
Contrary to the belief that TA is primarily a retail tool, it is also utilized—though selectively—by institutional investors:
Hedge Funds: Many quantitative hedge funds incorporate technical indicators within multi-factor models or machine learning algorithms. According to research by Neely et al. (2014), trend-following strategies remain a staple among CTAs (Commodity Trading Advisors), particularly in futures markets. These strategies often rely on moving averages, breakout signals, and momentum filters.
Market Makers: Although market makers are primarily driven by order flow and arbitrage opportunities, they may use TA to model liquidity zones and anticipate stop-hunting behavior. Order book analytics and technical levels (e.g., pivot points, Fibonacci retracements) can inform automated liquidity provision.
Pension Funds and Asset Managers: While these institutions rarely rely on TA alone, they may use it as part of tactical asset allocation. For instance, TA may serve as a signal overlay in timing equity exposure or in identifying risk-off regimes. According to a CFA Institute survey (2016), over 20% of institutional investors incorporate some form of technical analysis in their decision-making process.
5. Adaptive Markets and Conditional Validity
Lo (2004) introduced the Adaptive Markets Hypothesis (AMH), arguing that market efficiency is not a binary state but evolves with the learning behavior of market participants. In this framework, technical strategies may work intermittently, depending on the ecological dynamics of the market. Neely, Weller, and Ulrich (2009) found technical rules in the FX market to be periodically profitable, especially during central bank interventions or volatility spikes—conditions under which behavioral biases and structural inefficiencies tend to rise.
More recent studies (e.g., Moskowitz et al., 2012; Baltas & Kosowski, 2020) show that momentum and trend-following strategies continue to deliver long-term Sharpe ratios above 1 in diversified portfolios, particularly when combined with risk-adjusted scaling techniques.
6. The Role of Transaction Costs
Transaction costs represent a critical variable that substantially alters the net profitability of technical strategies. These include:
Explicit Costs: Commissions, fees, and spreads.
Implicit Costs: Market impact, slippage, and opportunity cost.
While early studies often neglected these elements, modern research integrates them through realistic backtesting frameworks. For example, De Prado (2018) emphasizes that naive backtesting without cost modeling and slippage assumptions leads to a high incidence of false positives.
Baltas and Kosowski (2020) show that even after accounting for bid-ask spreads and market impact models, trend-following strategies remain profitable, particularly in futures and FX markets where costs are lower. Conversely, high-frequency mean-reversion strategies often become unprofitable once these frictions are accounted for.
The impact of transaction costs also differs by asset class:
Equities: Higher costs due to wider spreads, especially in small caps.
Futures: Lower costs and higher leverage make them more suitable for technical strategies.
FX: Extremely low spreads, but high competition and adverse selection risks.
7. Meta-Analyses and Recent Surveys
Park and Irwin’s (2007) meta-analysis of 95 studies found that 56% reported significant profitability from technical analysis. However, profitability rates dropped when transaction costs were included. More recent work by Han, Yang, and Zhou (2021) extended this review with data up to 2020 and found that profitability was regime-dependent: TA performed better in volatile or trending environments and worse in stable, low-volatility markets.
Other contributions include behavioral explanations. Barberis and Thaler (2003) suggest that TA may capture collective investor behavior, such as overreaction and underreaction, thereby acting as a proxy for sentiment.
8. Limitations and Challenges
Several methodological issues plague empirical research in technical analysis:
Overfitting: Using too many parameters increases the likelihood of in-sample success but out-of-sample failure.
Survivorship Bias: Excluding delisted or bankrupt stocks leads to inflated backtest performance.
Look-Ahead Bias: Using information not available at the time of trade leads to unrealistic results.
Robust strategy development now mandates walk-forward testing, Monte Carlo simulations, and realistic assumptions on order execution. The growing field of machine learning in finance has heightened these risks, as complex models are more prone to fitting noise rather than signal (Bailey et al., 2014).
9. Conclusion
Technical analysis occupies a contested but persistent role in finance. The empirical evidence is mixed but suggests that technical strategies can be profitable under certain market conditions and when costs are minimized. Institutional investors have increasingly integrated TA within quantitative and hybrid frameworks, reflecting its conditional usefulness.
While TA does not provide a universal arbitrage opportunity, it can serve as a valuable tool when applied adaptively, with sound risk management and rigorous testing. Its success ultimately depends on context, execution discipline, and integration within a broader investment philosophy.
References
Bailey, D. H., Borwein, J. M., Lopez de Prado, M., & Zhu, Q. J. (2014). "The Probability of Backtest Overfitting." *Journal of Computational Finance*, 20(4), 39–69.
Baltas, N., & Kosowski, R. (2020). "Trend-Following, Risk-Parity and the Influence of Correlations." *Journal of Financial Economics*, 138(2), 349–368.
Barberis, N., & Thaler, R. (2003). "A Survey of Behavioral Finance." *Handbook of the Economics of Finance*, 1, 1053–1128.
Brock, W., Lakonishok, J., & LeBaron, B. (1992). "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns." Journal of Finance, 47(5), 1731–1764.
Chan, L. K. C., Jegadeesh, N., & Lakonishok, J. (1996). "Momentum Strategies." Journal of Finance, 51(5), 1681–1713.
De Prado, M. L. (2018). Advances in Financial Machine Learning, Wiley.
Fama, E. F. (1970). "Efficient Capital Markets: A Review of Theory and Empirical Work." Journal of Finance, 25(2), 383–417.
Gencay, R. (1998). "The Predictability of Security Returns with Simple Technical Trading Rules." Journal of Empirical Finance, 5(4), 347–359.
Han, Y., Yang, K., & Zhou, G. (2021). "Technical Analysis in the Era of Big Data." *Review of Financial Studies*, 34(9), 4354–4397.
Jegadeesh, N., & 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: Market Efficiency from an Evolutionary Perspective." *Journal of Portfolio Management*, 30(5), 15–29.
Moskowitz, T. J., Ooi, Y. H., & Pedersen, L. H. (2012). "Time Series Momentum." *Journal of Financial Economics*, 104(2), 228–250.
Neely, C. J., Weller, P. A., & Ulrich, J. M. (2009). "The Adaptive Markets Hypothesis: Evidence from the Foreign Exchange Market." *Journal of Financial and Quantitative Analysis*, 44(2), 467–488.
Neely, C. J., Rapach, D. E., Tu, J., & Zhou, G. (2014). "Forecasting the Equity Risk Premium: The Role of Technical Indicators." *Management Science*, 60(7), 1772–1791.
Park, C. H., & Irwin, S. H. (2007). "What Do We Know About the Profitability of Technical Analysis?" *Journal of Economic Surveys*, 21(4), 786–826.
Rouwenhorst, K. G. (1998). "International Momentum Strategies." *Journal of Finance*, 53(1), 267–284.
Zhu, Y., & Zhou, G. (2009). "Technical Analysis: An Asset Allocation Perspective on the Use of Moving Averages." *Journal of Financial Economics*, 92(3), 519–544.
80% Of Time - A Trading Edge You Don't Want To MissDo you want to know why trading with median lines, also known as pitchforks, can be so successful? It’s simple:
Prices swing from one extreme back to the middle.
From the middle, they often swing to the other extreme.
What do we see on the chart?
- The upper extreme
- The center
- The lower extreme
So far, so good.
Now let’s follow the price and learn a few important rules that belong to the rulebook of median lines/pitchforks, and with which you can make great trades.
Point 1
The price starts and is sold off down to…
Point 2
...and from there starts to rise again, up to…
Point 3
...which is the center. And here we have a rule that is very important and one that you need to be aware of in trading to be successful:
THE PRICE RETURNS TO THE CENTER IN ABOUT 80% OF ALL CASES
If we know this, then we can stay in a trade with confidence.
Point 4
The price climbed even higher but missed the upper extreme.
This is the “Hagopian Rule” (named after the man who discovered it).
And the rule goes: If the price does not reach the next line (upper extreme, lower extreme, or center), then the price will continue moving in the opposite direction from where it originally came.
Phew...that’s a mouthful ;-)
But yes, we actually see that the price does exactly this.
From point 4, where the price missed the upper extreme, the price not only goes back to the center but continues and almost reaches the lower extreme!
Now if that isn’t cool, I don’t know what is!
And what do we have at point 5?
A "HAGOPIAN"!
What did we just learn?
The price should go higher than the center line.
Does it do that?
Oh yes!
But wait!
Not only does the Hagopian Rule apply. Remember?
"The price returns to the center line in about 80% of the cases."
HA!
Interesting or interesting?
So, that’s it.
That’s enough for now.
Now follow the price yourself and always consider which rule applies and whether it’s being followed.
How exactly do you trade all this, and what are the setups?
...one step at a time.
Don’t miss the next lesson and follow me here on TradingView.
Wishing you lots of success and fun!
Altcoin Season:It All Comes Down to One Thing—Liquidity RotationHello Traders 🐺
Let’s be real—everything about “altcoin season” comes back to one key concept: liquidity rotation. You’ve probably heard that term thrown around, but what does it actually mean ? And more importantly, how do we use it?
No matter what market cycle we’re in—bullish or bearish—each cycle is made up of several internal phases. And during those phases, tracking where smart money is flowing becomes crucial. But let’s break it down even further.
Take a look at the chart. Before the last altcoin season kicked off, something interesting happened: the Bitcoin Dominance Index (BTC.D) had a significant rally. As the name suggests, this index tracks Bitcoin’s share of the overall crypto market cap. So when CRYPTOCAP:BTC.D is rising, that means Bitcoin is sucking up a larger share of the liquidity—smart money is flowing into BTC first.
This is critical to understand, because Bitcoin Dominance is one of the clearest indicators to tell you which phase of the cycle we're in and where the money is heading next.
Now here’s the key question:
Why do we associate a drop in BTC Dominance with the start of altcoin season?
It all goes back to the literal meaning of Bitcoin Dominance. If BTC.D is approaching 100%, nearly all the money is concentrated in Bitcoin alone. But when this dominance starts dropping, it signals that capital is beginning to rotate out of BTC and into altcoins.
And here's where it gets spicy:
When BTC.D approaches a key resistance level—like it's doing right now—and at the same time we see bearish divergences across multiple timeframes... that’s our cue. Combine that with technical analysis, and suddenly you've got yourself a roadmap most beginners are completely blind to.
That’s why 80% of traders end up feeding the profits of the other 20%. The harsh truth? Markets are wealth transfer mechanisms—from the impatient to the patient. Every bad entry, every panic sell, ends up padding the wallet of someone who planned the rotation in advance.
Let’s not complicate things too much though. Just look at what’s happening right now:
BTC Dominance hit a major resistance level, showed strong bearish divergences (as I mentioned in earlier posts), and what happened next? Boom—altcoins started pumping hard this past week.
To everyone who stayed with me through this phase and positioned themselves early—congrats. You earned this.
But here’s the bigger picture:
We're still at the beginning of the altcoin cycle. Like I explained before, it all happens in phases:
Bitcoin Season – Smart money enters Bitcoin first.
Ethereum Season – Then liquidity flows into ETH.
Large-Cap Altcoins – After that, big-name altcoins start moving.
Altcoin Season (Full Risk-On) – Finally, capital floods into low-cap alts—the wild phase.
And that last phase? That’s when things get crazy. That’s where irrational exuberance lives. That’s where dreams are made—or broken—depending on your timing and plan.
So yeah, buckle up. We're not done yet.
And as always remember :
🐺 Discipline is rarely enjoyable , but almost always profitable. 🐺
🐺 KIU_COIN 🐺
HOW-TO: Auto Harmonic Screener - UltimateXHello Everyone,
In this video, we have discussed on how to use our new Auto Harmonic Screener - UltimateX. We have covered the following topics.
Difference between Auto Harmonic Screener - UltimateX (Current script) and Auto Harmonic Pattern - UltimateX and how to use both the scripts together
Difference between Auto Harmonic Screener - UltimateX (Current script) and the existing screener Auto Harmonic Pattern - Screener which is built on request.security calls. We have discussed how the limitations of old script and how using the new script with Pine screener utility will help overcome those problems.
We have gone through the indicator settings (which are almost similar to that of Auto Harmonic Pattern UltimateX
Short demo on how to use the script with Pine Screener
Also check our existing video on How to use the new Pine Screener Utility.
SYM Trade Breakdown – Robotics Meets Smart Technical's🧪 Company: Symbotic Inc. ( NASDAQ:SYM )
🗓️ Entry: April–May 2025
🧠 Trade Type: Swing / Breakout Reversal
🎯 Entry Zone: $16.28–$17.09
⛔ Stop Loss: Below $14.00
🎯 Target Zone: $50–$64+
📈 Status: Strong Rally in Motion
📊 Why This Trade Setup Stood Out
✅ Macro Falling Wedge Reversal
After nearly two years of compression inside a falling wedge, price finally tapped multi-year structural support and fired off with strength. This wasn’t just a bottom — it was a structural inflection point.
✅ Triple Tap at Demand Zone
Symbotic tapped the ~$17 area multiple times, signaling strong accumulation. Volume and momentum picked up with each successive test, showing institutional interest.
✅ Clean Break of Trendline
Price broke through the falling resistance trendline decisively, confirming the bullish reversal and unleashing stored energy from months of sideways structure.
🔍 Company Narrative Backdrop
Symbotic Inc. isn't just any tech stock. It’s at the forefront of automation and AI-powered supply chain solutions, with real-world robotics deployed in major retail warehouses. That kind of secular growth narrative adds rocket fuel to technical setups like this — especially during AI adoption surges.
Founded in 2020, Symbotic has quickly become a rising name in logistics and warehouse automation, serving the U.S. and Canadian markets. With robotics in demand and investors chasing future-ready tech, the price action aligned perfectly with the macro theme.
🧠 Lessons from the Trade
⚡ Compression = Expansion: Wedges like this build pressure. When they break, the moves are violent.
🧱 Structure Never Lies: The $17 zone was no accident — it was respected over and over.
🤖 Tech Narrative Boosts Confidence: Trading is easier when the fundamentals align with the technicals.
💬 What’s Next for SYM?
If price holds above the wedge and clears the $64 resistance, we could be looking at new all-time highs in the next cycle. Watching for consolidation and retests as opportunity zones.
#SYM #Symbotic #Robotics #Automation #AIStocks #BreakoutTrade #FallingWedge #SwingTrade #TechnicalAnalysis #TradingView #TradeRecap #SupplyChainTech
Angle of Ascent: what it means, how to use it.Angle of Ascent is a visual pattern that forms on a chart when stocks are running with momentum or velocity. Drawing a line along an up trending price action helps you see the Angle of ascent. Also Chaikins Osc and EMA MFI indicators are extremely helpful in warning a day ahead of time that the Angle of Ascent is too steep to sustain.
This is an exit signal for profit taking at or near the highest high of a swing style run.
Angle of Ascent is also used on Weekly Charts to determine how far a stock can run before resistance from previous highs will stall that stock and cause a minor to intermediate correction.
Recognizing when an angle of ascent has become too steep to sustain and using these indicators will help you hold a swing run but also help you exit before a retracement or correction starts.
The professional side of the market uses penny spreads, millisecond routing to the ques of the market, and can easily front run retail traders orders.
Reminder: retail brokers are required to light your order before sending to the PFOF Payment for Order Flow Market Maker of their choice.
The Digital Stock Market moves at a much faster pace with subtle nuances such as Angle of Ascent. As you become an advanced level trader to a semi-professional trader, or potentially a full time professional trader, these details matter more than when you are just learning stock trading.
Trade Wisely
Martha Stokes CMT
Blueprint to Becoming a Successful Gold Trader in 2025🚀 Blueprint to Becoming a Successful Gold Trader in 2025
A strategic, step-by-step plan to master gold trading by combining institutional concepts, cutting-edge automation, and the best prop funding opportunities for XAUUSD.
________________________________________
🏦 Broker Selection (Gold-Specific)
• 🔍 Choose Brokers Offering Raw Spread XAUUSD Accounts:
Seek brokers with raw/zero spread gold trading or tight gold spreads (0.10-0.30 average) with deep liquidity.
• ⚡ Prioritize Ultra-Fast Execution for Metals:
Confirm broker servers are in NY4/LD4 and latency is optimized for gold volatility spikes.
• 🛡️ Verify Regulation & Execution:
ASIC, FCA, FSCA preferred; check for proof of XAUUSD execution quality (Myfxbook/FXBlue verified).
• 📊 MetaTrader 4/5 Gold Support:
Ensure MT4/5 platform offers tick-chart precision for gold and supports custom EAs/indicators.
• 💳 Flexible Withdrawals/Payouts:
Crypto, Wise, and Revolut compatibility for fast, secure funding.
________________________________________
🎯 Gold Trading Strategy (ICT + Supply/Demand Zones)
• 🧠 Master Gold-Adapted ICT Concepts:
o Liquidity runs and stops at London/NY session highs/lows
o XAUUSD-specific Order Blocks (OBs), FVGs, and Market Structure Breaks (MSB)
• 📍 Map Institutional Supply-Demand Zones:
Gold reacts violently to these—align SD zones with ICT Order Blocks for best confluence.
• 📐 Precision Entries:
Only enter after liquidity sweeps at key XAUUSD levels (H4/D1), avoiding choppy retail entries.
• 📈 Time & Price for XAUUSD:
Focus exclusively on London Open (8:00 GMT) and NY Open/Gold Fixing (13:20 GMT)—peak volatility windows.
• 📆 Weekly Preparation:
Annotate D1/H4 gold charts every Sunday with clear OBs, liquidity points, and SD zones for the week.
________________________________________
💰 Prop Funding for Gold Trading
• 🥇 Select Firms Offering XAUUSD with Tight Rules:
Choose FTMO, The Funded Trader, MyFundedFX, or similar with high leverage and XAUUSD trading enabled.
• 📑 Pass Evaluation with Gold-Only Strategy:
Use high-probability, low-frequency XAUUSD trades—1-3 setups per week, strict risk parameters.
• 🎯 Risk Management:
Max 1% risk/trade, stop trading after 2 consecutive losses—protect account and pass evaluations.
• 📊 Analytics Monitoring:
Use prop dashboards (FTMO Metrics, FundedNext stats) to review XAUUSD trade stats and adjust.
• 📚 Diversify Funded Accounts:
Split funded capital among multiple firms to hedge against firm-specific risk and maximize payouts.
________________________________________
⚙️ Automating Gold Trading (MT4/5 EAs & Bots)
• 🛠️ Hire MQL4/5 Developers for XAUUSD EAs:
Code bots focused on gold-specific ICT (OBs, FVGs, London/NY volatility).
• 🤖 Develop EAs for Gold:
o OB/FVG/Market Structure detection on XAUUSD
o Supply/Demand zone algo entries
o Gold breakout EAs for session openings
• 📌 Trade Management Automation:
o Entry, stop loss, partial TP, BE, trailing for gold’s high volatility
o Dynamic lot-sizing by daily ATR
• 📡 VPS Hosting Near Broker’s Gold Server:
Use NY4/LD4 VPS for lowest latency (ForexVPS, Beeks).
• 📈 Quarterly Forward-Testing:
Optimize EAs in demo before live trading, retest on every major gold volatility shift (FOMC, CPI).
________________________________________
📲 Leveraging Bots & AI in 2025
• 📊 Integrate with MT4/5 Analytics Tools:
Use myfxbook, QuantAnalyzer for detailed gold trade breakdowns.
• 🔮 AI-Based Gold Forecasting:
Layer in machine learning models (e.g., TensorTrade, TradingView AI) to anticipate session volatility and direction.
• 🔔 Real-Time Alert Bots:
Set up Telegram/Discord bots for instant notification of ICT-based XAUUSD signals.
• 🧑💻 Manual Oversight:
Always review high-impact news (NFP, CPI, FOMC) and override automation when macro risk spikes.
• 🔄 Continuous Bot Updates:
Retrain your EAs monthly on latest XAUUSD price action to maintain edge.
________________________________________
🗓️ Daily Gold Trader Routine
• 🌅 Pre-Session (30 mins):
Review annotated gold charts, key session highs/lows, OB/FVG/SD levels, and upcoming news.
• 💻 During Session:
Monitor bot execution, validate setups manually, manage risk during NY/London overlap.
• 📝 Post-Session (15 mins):
Journal gold trades, note reasoning for entry/exit, emotional state, and lessons learned.
• 📆 Weekly Review:
Assess overall gold trading stats and EA performance, adjust strategy as needed.
• 📚 Continuous Learning:
Stay updated on ICT, gold market fundamentals, and new trading tech.
________________________________________
📌 Final Success Advice for 2025
• 🔍 Specialize in XAUUSD/Gold—Don’t Diversify Randomly:
Depth > Breadth—become a true gold trading expert.
• 🚩 Keep Adapting Your Gold Trading EAs:
Markets change—so must your bots and playbooks.
• 🧘 Stay Patient, Disciplined, and Selective:
Gold rewards precision and patience, not overtrading.
• 💡 Embrace AI & Automation:
Leverage every tool: AI, analytics, and custom EAs for a real 2025 trading edge.
Volume Gaps and Liquidity Zones: Finding Where Price Wants to GoDifficulty: 🐳🐳🐳🐋🐋 (Intermediate+)
This article is best suited for traders familiar with volume profile, liquidity concepts, and price structure. It blends practical trading setups with deeper insights into how price seeks inefficiency and liquidity.
🔵 INTRODUCTION
Ever wonder why price suddenly accelerates toward a level — like it's being magnetized? It’s not magic. It’s liquidity . Markets move toward areas where orders are easiest to fill, and they often avoid areas with little interest.
In this article, you’ll learn how to identify volume gaps and liquidity zones using volume profiles and price action. These tools help you anticipate where price wants to go next — before it gets there.
🔵 WHAT ARE VOLUME GAPS?
A volume gap is a price region with unusually low traded volume . When price enters these areas, it often moves quickly — there’s less resistance.
Think of a volume gap as a thin patch of ice on a frozen lake. Once the market steps on it, it slides across rapidly.
Volume gaps usually show up on:
Volume Profile
Fixed Range Volume tools
Session or custom volume zones
They’re often created during impulsive moves or news events — when price skips levels without building interest.
🔵 WHAT ARE LIQUIDITY ZONES?
Liquidity zones are price areas where a large number of orders are likely to be sitting — stop losses, limit entries, or liquidation levels.
These zones often form around:
Swing highs and lows
Order blocks or fair value gaps
Consolidation breakouts
Psychological round numbers
When price approaches these areas, volume often spikes as those orders get filled — causing sharp rejections or breakouts.
🔵 WHY THIS MATTERS TO TRADERS
Markets are driven by liquidity.
Price doesn’t just move randomly — it hunts liquidity, clears inefficiencies, and fills orders.
Your edge: By combining volume gaps (low resistance) with liquidity zones (target areas), you can forecast where price wants to go .
Volume gap = acceleration path
Liquidity zone = destination / reversal point
🔵 HOW TO TRADE THIS CONCEPT
1️⃣ Identify Volume Gaps
Use a visible range volume profile or session volume. Look for tall bars (high interest) and valleys (low interest).
2️⃣ Mark Liquidity Zones
Use swing highs/lows, OBs, or EQH/EQL (equal highs/lows). These are magnet areas for price.
3️⃣ Watch for Reactions
When price enters a gap, expect speed.
When it nears a liquidity zone, watch for:
Volume spike
Wick rejections
S/R flip or OB retest
🔵 EXAMPLE SCENARIO
A strong bearish move creates a volume gap between 103 000 – 96 000
Below 96 000 sits bullish order blocks — clear liquidity
Price enters the gap and slides fast toward 96 000
A wick forms as buyers step in, volume spikes — the reversal begins
That’s price filling inefficiency and tapping liquidity .
🔵 TIPS FOR ADVANCED TRADERS
Use higher timeframes (4H/1D) to define major gaps
Look for overlapping gaps across sessions (Asia → London → NY)
Align your trades with trend: gap-fills against trend are riskier
Add OB or VWAP as confirmation near liquidity zones
🔵 CONCLUSION
Understanding volume gaps and liquidity zones is like reading the market’s intention map . Instead of reacting, you start predicting. Instead of chasing, you’re waiting for price to come to your zone — with a plan.
Price always seeks balance and liquidity . Your job is to spot where those forces are hiding.
Have you ever traded a volume gap into liquidity? Share your setup below
Fibonacci Retracement: The Hidden Key to Better EntriesIf you’ve ever wondered how professional traders predict where price might pull back before continuing... the secret lies in Fibonacci Retracement.
In this post, you’ll learn:
What Fibonacci retracement is
Why it works
How to use it on your charts (step-by-step)
Pro tips to increase accuracy in the market
🧠 What Is Fibonacci Retracement?:
Fibonacci Retracement is a technical analysis tool that helps traders identify potential support or resistance zones where price is likely to pause or reverse during a pullback.
It’s based on a mathematical sequence called the Fibonacci Sequence, found everywhere in nature — from galaxies to sunflowers — and yes, even in the markets.
The Fibonacci sequence is a series of numbers where each number is the sum of the two preceding ones, starting with 0 and 1. The sequence typically begins with 0, 1, 1, 2, 3, 5, 8, 13, and so on. This pattern can be expressed as a formula: F(n) = F(n-1) + F(n-2), where F(n) is the nth Fibonacci number.
The key Fibonacci levels traders use are:
23.6%
38.2%
50%
61.8%
78.6%
These levels represent percentages of a previous price move, and they give us reference points for where price might pull back before resuming its trend and where we can anticipate price to move before showing support or resistance to the trend you are following.
💡Breakdown of Each Fib Level:
💎 0.236 (23.6%) – Shallow Pullback
What it indicates:
Weak retracement, often signals strong trend momentum.
Buyers/sellers are aggressively holding the trend.
Best action:
Aggressive entry zone for continuation traders.
Look for momentum signals (break of minor structure, bullish/bearish candles). Stay out of the market until you see more confirmation.
💎 0.382 (38.2%) – First Strong Area of Interest
What it indicates:
Healthy pullback in a trending market.
Seen as a key area for trend followers to step in.
Best action:
Look for entry confirmation: bullish/bearish engulfing, pin bars, Elliott Waves, or break/retest setups.
Ideal for setting up trend continuation trades.
Stop Loss 0.618 Level
💎 0.500 (50.0%) – Neutral Ground
What it indicates:
Often marks the midpoint of a significant price move.
Market is undecided, can go either way.
Best action:
Wait for additional confirmation before entering.
Combine with support/resistance or a confluence zone.
Useful for re-entry on strong trends with good risk/reward.
Stop Loss 1.1 Fib Levels
💎 0.618 (61.8%) – The “Golden Ratio”
What it indicates:
Deep pullback, often seen as the last line of defense before trend reversal.
High-probability area for big players to enter or add to positions.
Best action:
Look for strong reversal patterns (double bottoms/tops, engulfing candles).
Excellent area for entering swing trades with tight risk and high reward.
Use confluence (structure zones, moving averages, psychological levels, Elliott Waves).
Wait for close above or below depending on the momentum of the market.
Stop Loss 1.1 Fib Level
💎 0.786 (78.6%) – Deep Correction Zone
What it indicates:
Very deep retracement. Often a final “trap” zone before price reverses.
Risk of trend failure is higher.
Best action:
Only trade if there's strong reversal evidence.
Use smaller position size or avoid unless other confluences are aligned.
Can act as an entry for counter-trend trades in weaker markets.
Stop Loss around 1.1 and 1.2 Fib Levels
⏱️Best Timeframe to Use Fibs for Day Traders and Swing Traders:
Day trading:
Day traders, focused on capturing short-term price movements and making quick decisions within a single day, typically utilize shorter timeframes for Fibonacci retracement analysis, such as 15-minute through hourly charts.
They may also use tighter Fibonacci levels (like 23.6%, 38.2%, and 50%) to identify more frequent signals and exploit short-term fluctuations.
Combining Fibonacci levels with other indicators such as moving averages, RSI, or MACD, and focusing on shorter timeframes (e.g., 5-minute or 15-minute charts) can enhance signal confirmation for day traders.
However, relying on very short timeframes for Fibonacci can lead to less reliable retracement levels due to increased volatility and potential for false signals.
Swing trading:
Swing traders aim to capture intermediate trends, which necessitates giving trades more room to fluctuate over several days or weeks.
They typically prefer utilizing broader Fibonacci levels (like 38.2%, 50%, and 61.8%) to identify significant retracement points for entering and exiting trades.
Swing traders often focus on 4-hour and daily charts for their analysis, and may even consult weekly charts for a broader market perspective.
🎯 Why Does Fibonacci Work?:
Fibonacci levels work because of:
Mass psychology – many traders use them
Natural rhythm – markets move in waves, not straight lines
Institutional footprint – smart money often scales in around key retracement zones
It's not magic — it's structure, and it's surprisingly reliable when used correctly.
🛠 How to Draw Fibonacci Retracement (Step-by-Step):
Let’s say you want to trade XAU/USD (Gold), and price just had a strong bullish run.
✏️ Follow These Steps:
Identify the swing low (start of move)
Identify the swing high (end of move)
Use your Fibonacci tool to draw from low to high (for a bullish move)
The tool will automatically mark levels like 38.2%, 50%, 61.8%, etc.
These levels act as pullback zones, and your job is to look for entry confirmation around them.
🔁 For bearish moves, draw from high to low. (I will show a bearish example later)
Now let’s throw some examples and pictures into play to get a better understanding.
📈 XAU/USD BULLISH Example:
1.First we Identify the direction of the market:
2.Now we set our fibs by looking for confirmations to get possible entry point:
Lets zoom in a bit:
Now that we have a break of the trendline we wait for confirmation and look for confluence:
Now we set our fibs from the last low to the last high:
This will act as our entry point for the trade.
3. Now we can look for our stop loss and take profit levels:
Stop Loss:
For the stop loss I like to use the fib levels 1.1 and 1.2 when I make an entry based upon the 0.618 level. These levels to me typically indicate that the trade idea is invalid once crossed because it will usually violate the prior confirmations
Take Profit:
For the take profit I like to use the Fib levels 0.236, 0, -0.27, and -0.618. This is based upon your personal risk tolerance and overall analysis. You can use 0.236 and 0 level as areas to take partial profits.
Re-Entry Point Using Elliott Waves as Confluence Example:
This is an example of how I used Elliott Waves to enter the trade again from the prior entry point. If you don’t know what Elliott Waves are I will link my other educational post so you can read up on it and have a better understanding my explanation to follow.
After seeing all of our prior confirmations I am now confident that our trend is still strongly bullish so I will mark my Waves and look for an entry point.
As we can see price dipped into the 0.38-0.5 Fib level and rejected it nicely which is also in confluence with the Elliott Wave Theory for the creation of wave 5 which is the last impulse leg before correction.
🔻 In a downtrend:
Same steps, but reverse the direction — draw from high to low and look to short the pullback.
XAU/USD Example:
As you can see the same basic principles applied for bearish movement as well.
⚠️ Pro Tips for Accuracy:
✅ Always use Fib in confluence with:
Market structure (higher highs/lows or lower highs/lows)
Key support/resistance zones
Volume or momentum indicators
Candle Patterns
Elliott Waves, etc.
❌ Don’t trade Fib levels blindly — they are zones, not guarantees.
📊 Use higher timeframes for cleaner levels (4H, Daily)
💡 Final Thought
Fibonacci retracement doesn’t predict the future — it reveals probability zones where price is likely to react.
When combined with structure and confirmation, it becomes one of the most reliable tools for new and experienced traders alike.
🔥 Drop a comment if this helped — or if you want a Part 2 where I break down Fibonacci Extensions and how to use them for take-profit targets.
💬 Tag or share with a beginner who needs to see this!
Mastering supply and demand zones - how to use it in trading?Supply and demand zones are key concepts in technical analysis used by traders to identify potential price reversal areas on a chart. They are based on the idea that prices move due to an imbalance between buyers (demand) and sellers (supply).
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What will be discussed?
- What are supply and demand zones?
- How to detect supply and demand zones?
- Examples from supply and demand zones?
- How to trade using supply and demand zones?
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What are supply and demand zones?
Supply and demand zones are areas on a price chart where the forces of buying and selling are strongly concentrated, causing significant movements in price. In simple terms, a supply zone is an area where selling pressure exceeds buying pressure, often leading to a drop in price. It usually forms when price moves upward into a region where sellers begin to outnumber buyers, pushing the price back down. On the other hand, a demand zone is a region where buying pressure exceeds selling pressure, typically resulting in a rise in price. This occurs when price moves downward into a region where buyers see value and begin to outnumber sellers, causing the price to increase again.
These zones reflect areas of imbalance in the market. In a supply zone, sellers are more eager to sell than buyers are to buy, often due to overbought conditions, news, or fundamental changes. In a demand zone, buyers are more eager to buy than sellers are to sell, often because the price has become attractive or undervalued. Traders look for these zones because they provide clues about where price may reverse or stall, offering potential entries or exits for trades.
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How to detect supply and demand zones?
Identifying supply and demand zones involves analyzing price action on a chart, typically using candlestick patterns. A common way to detect a supply zone is to look for a sharp upward move followed by a sudden reversal or strong drop in price. The area where the price stalled before falling sharply is likely to be a supply zone. This zone includes the highest candle body or wick before the drop, and a few candles before it that mark where the selling pressure began.
To identify a demand zone, you would look for a sharp drop in price followed by a strong rally upward. The area where the price paused before rising significantly can be considered a demand zone. Like with supply zones, the demand zone includes the lowest candle before the price reversed and a few candles leading up to it.
These zones are not exact price levels but rather ranges. Price does not have to touch an exact line to react; it often moves within the general area. For more accuracy, traders often refine their zones by identifying them on higher time frames such as the 4-hour or daily chart, then adjusting them slightly on lower time frames like the 1-hour or 15-minute chart.
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Examples from supply and demand zones:
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How to trade using supply and demand zones?
Trading supply and demand zones involves anticipating how price is likely to behave when it returns to one of these key areas. A common method is to wait for price to enter a zone and then watch for confirmation that it is going to reverse. For example, if price rises into a supply zone, you might look for signs like a bearish candlestick pattern, a drop in volume, or a rejection wick to signal that sellers are stepping in again. This would be an opportunity to enter a short trade with the expectation that price will fall.
Conversely, if price falls into a demand zone, you would wait for bullish signals—such as a strong bullish candle, a double bottom pattern, or clear rejection of lower prices—to confirm that buyers are returning. This would be a potential setup for a long trade, expecting the price to move up from the zone.
Traders often place stop losses just beyond the zone to limit risk in case the level fails. For a supply zone, the stop loss would go just above the zone, while for a demand zone, it would go just below. Targets can be set at recent support or resistance levels, or by using risk-reward ratios like 1:2 or 1:3 depending on the trader’s strategy.
Patience and discipline are important when trading these zones. Not every zone will lead to a reversal, and false breakouts can occur. Therefore, combining supply and demand analysis with other tools such as trendlines, moving averages, or indicators can improve the chances of a successful trade.
In summary, supply and demand zones help traders understand where large buying or selling forces are likely to influence price. By learning to identify these zones and waiting for confirmation signals, traders can enter high-probability trades with clear risk and reward levels.
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Disclosure: I am part of Trade Nation's Influencer program and receive a monthly fee for using their TradingView charts in my analysis.
Thanks for your support. If you enjoyed this analysis, make sure to follow me so you don't miss the next one. And if you found it helpful, feel free to drop a like and leave a comment, I’d love to hear your thoughts!
The only key levels you need - DITCH THE INDICATORS- Previous day high/Low
- Weekly high/low
- Session high/low
- Closing Price
In this specific example on OANDA:AUDUSD we have a day 3 Tuesday breakout fail reversal setup on the backside of a previous weeks expansion.
Fridays closing price was plotted going into Monday day 2 on the backside of a new week. Once the initial high low was set on day 2 below the previous weeks high and closing price we than look for short opportunities going into day 3 Tuesday.
In this case day 2 Ny session high acted as the reversal point staying below Friday closing price below the high of the previous week. The Asia/London session printed a beautiful high/low range reversing at near the midpoint of the previous days range (50% retrace.)
A great opportunity for a projected range expansion presented with confluence at a previous days low giving a solid set and forget trade with little to no stress or heat. This parabolic opportunity took place in the NY session below Fridays closing price to a previous weeks LOD level.
- Mondays High (Stop)
- NY session High, Fridays Close (Entry)
- Wed Low, Range expansion (Target)
KEY NOTES:
It is very important to keep your trading simple. As a newer trader I filled my chart with as many indicators as possible trying to find a "signal" because I lacked the patience for the market to give me a setup over multiple days. Now as a more experienced trader I sit back on higher time frames (1H/15M) TO WAIT FOR THE DAILY LEVELS TO PRINT. Avoiding trading inside a range on a low time frame. Lower time frames are only to decrease risk and increase position accuracy already derived from higher time frames. It is key to understand when higher time frame traders are triggered into a market and to understand there are only two main plays from key levels. Keep it simple, find the scalable setups, AND PUT THE SIZE ON WITH CONFIDENCE.
Earnings HFT gapsThe gaps that form during earnings season on or the next day after the CEO reports the revenues and income for that past quarter are always HFT driven. The concern over the past 2 previous quarters was the fact that the High Frequency Trading Firms were incorporating Artificial Intelligence into their Algos to make automated trading decisions on the millisecond scale. These small lot orders fill the ques milliseconds ahead of the market open in the US and any huge quantity of ORDERS (not lot size) causes the computers of the public exchanges and market to gap up or gap down, often a huge gap.
This can be problematic for those of you who use Pre Earnings Runs to enter a stock in anticipation of a positive to excellent earnings report for this upcoming quarter.
The HFT algos had several major flaws in the programming that did the opposite: The AI triggered sell orders rather than buy order causing the stock price to gap down hugely on good earnings news.
Be mindful that normal gaps due to a corporate event are far more reliable and consistent.
When you trade during earnings season, be aware that there is still added risk of an AI making a mistake and causing the stock to gap and run down on good news.
It is important to calculate the risk factors until it is evident by the end of this earnings season that the errors within the AI programming have been corrected and that the AI will gap appropriately to the actual facts rather than misinterpreted information.
Deep Dive Part III – The Next BIG Whale Play UnfoldsDeep Dive Part III – The Next BIG Whale Play Unfolds
📍In Parts I & II of this Deep Dive, we broke down the psychology of whale behavior — from “Buy the Rumors, Sell the News” to the critical breakout zones that echoed historical patterns.
🐋 Back then, we spotted the whales' playbook early. The strategy was simple:
Buy the Rumors – Sell the News.
🧠 But now, the script has changed.
“The trap is where you’re most bored… 🌴📵
Their exit — on your liquidity — comes when you’re least ready. 💰🏄♂️💼”
Let’s break this moment down into what’s really unfolding.
We are officially entering the next stage of the cycle — not just in price, but in psychology.
This is no longer just about charts.
This is about human behavior on autopilot.
Here’s what I see happening right now — broken into three truths:
1️⃣ People Are On Holiday 🌞
From my community to the broader market, the energy is low.
People are either sunbathing on a beach or mentally checked out.
The focus is not there. The reflex to take action is dulled.
📉 The trap is where you’re most bored… 🌴📵
💰 Their exit — on your liquidity — comes when you’re least ready. 🏄♂️💼🚀
We’re seeing it unfold now:
1. Set the Bear Trap
2. Trigger the FOMO (will be down the road, yes)
3. Exit on Liquidity (the closing act of the play)
🕶️ But when everyone is away or asleep, that’s when the trap is laid.
It’s during these quiet, lazy days that the big moves get built.
2️⃣ This is a Disbelief Rally 🎢
The market trained everyone with a rhythm:
pump ➝ dump, pump ➝ dump, pump ➝ dump…
So what happens now?
People don’t trust the breakout. They’re frozen.
“We’ll dump again,” they say.
Except… what if this time, we don’t?
That disbelief becomes fuel.
It becomes hesitation — and hesitation becomes missed opportunity.
3️⃣ Bears Are Shorting Into Strength 🧨
This is key. While retail is confused, the bears are pressing in hard.
Their shorts are adding fuel to the pump they don’t see coming.
That’s why I posted recently:
“Shorting isn’t the problem. Being a psycho bear is.”
It’s not about being bullish or bearish —
It’s about timing , discipline , and narrative awareness .
Whales love this moment.
They lure in shorts, set the trap, then ignite the breakout straight into FOMO.
🧠 The Game:
Set the Trap → Trigger the FOMO → Exit on Liquidity 💥
This is what you’re seeing on the chart.
Not just price action — psychological choreography.
🕰️ In 2020–2021, we saw the exact same structure.
Part I warned about early accumulation and baiting behavior.
Part II showed how whales manipulated expectations with layered waves of doubt.
Now in Part III — the explosion few are ready for.
Zoom into the chart and it’s all there:
The curve, the trap, the trigger… and yes — the Final Boss.
🎯 The Final Boss: 6.51T
That’s the ultimate liquidity zone.
If this cycle plays out, we’re headed toward it.
“Sell the Rate Cuts” will be the new “Sell the News.”
It’s not the headlines that matter — it’s who’s left holding the bag.
🔚 Final Thought
The real exit — the one that traps most of retail — will come not when you’re euphoric,
but when you’re still saying:
“Surely we must dump now…”
So stay sharp.
Trade the chart — but don’t forget to read the behavior.
One Love,
The FXPROFESSOR 💙
Part1:
Part2:https://www.tradingview.com/chart/idea/VgMBPsp3/
The Bear Trap:
Disclosure: I am happy to be part of the Trade Nation's Influencer program and receive a monthly fee for using their TradingView charts in my analysis. Awesome broker, where the trader really comes first! 🌟🤝📈
Soybeans and Rain: Moisture’s Market Impact on the Bean Trade1. Introduction: Moisture & Market Momentum
Soybeans, often referred to as “the oilseed king,” are a cornerstone of global agriculture. As a leading source of protein for both humans and animals, their price fluctuations affect industries ranging from food production to biofuels. One key variable traders often monitor? Rainfall. 🌧️
Moisture plays a critical role in soybean development, influencing yield and quality from the moment the seed is sown. It’s no surprise that many market participants assume a strong correlation between rainfall and price behavior. But is that assumption truly supported by data?
In this article, we analyze how varying precipitation levels impact weekly soybean futures returns. As you'll see, the results might not be as clear-cut as you’d expect—but they still offer meaningful insights.
2. Biological Realities: Soybeans’ Water Needs
Soybeans thrive under specific conditions. While they’re generally resilient, rainfall—or the lack thereof—can tip the balance between bumper harvests and disappointing yields.
During early vegetative stages, sufficient moisture ensures healthy root development. Later, during the pod-fill phase, rainfall becomes even more essential. Too little water at this point leads to incomplete pods or aborted seeds. On the flip side, too much rain can invite fungal diseases and delay harvests, especially in lower-lying regions.
In countries like Brazil and Argentina, soybean fields often face seasonal extremes, while the U.S. Midwest typically enjoys more consistent conditions—though droughts and floods have both hit the Corn Belt in recent years. These environmental realities create natural volatility in both yield and pricing expectations.
3. Methodology: How We Analyzed Weather vs. Futures
To explore the potential connection between rainfall and soybean futures prices, we collected weekly weather data for major soybean-growing cities across the globe. Each week’s precipitation was categorized using a normalized percentile system:
Low Rainfall: below the 25th percentile
Normal Rainfall: between the 25th and 75th percentiles
High Rainfall: above the 75th percentile
We then matched this data against weekly returns of standard soybean futures (ZS) and micro soybean futures (MZS), both traded on the CME Group.
This allowed us to compare average price behavior in different rainfall scenarios—and test whether there was any statistically significant difference between dry and wet weeks.
4. Statistical Findings: Is There a Signal in the Noise?
When examining the data, the initial visual impression from boxplots was underwhelming—return distributions across rainfall categories looked surprisingly similar. However, a deeper dive showed that the difference in mean returns between low and high precipitation weeks was statistically significant, with a p-value around 0.0013.
What does that mean for traders? While the signal may not be obvious to the naked eye, statistically, rainfall extremes do impact market behavior. However, the magnitude of impact remains modest—enough to be part of your strategy but not enough to drive decisions in isolation.
Soybean prices appear to be influenced by a mosaic of factors, with precipitation being just one tile in that complex picture.
5. Charting the Relationship: Visual Evidence
While statistical tests gave us the green light on significance, we know traders love to “see” the story too. Boxplots of weekly soybean futures returns segmented by rainfall categories offered a subtle narrative:
Low-precipitation weeks showed slightly higher average returns and tighter interquartile ranges.
High-precipitation weeks had broader return distributions and more frequent downside outliers.
Normal weeks exhibited relatively stable behavior, reinforcing the idea that the market reacts most during extremes.
This kind of visualization may not scream alpha at first glance, but it reinforces the idea that precipitation events—particularly dry spells—tend to nudge prices upward, possibly as market participants price in production risk.
6. Trading Implications: Positioning Around Weather
Here’s where things get practical. While weather alone won’t dictate every trading decision, it can be a key filter in a broader strategy. For soybean traders, rainfall data can help inform:
Bias assessment: Low-precipitation weeks may suggest bullish tendencies.
Risk control: Expect wider return distributions in high-precip weeks—adjust stops or contract sizing accordingly.
Event trading: Pair weather anomalies with technical signals like trendline breaks or volume surges for potential setups.
It’s also worth noting that weekly weather forecasts from reputable sources can serve as a forward-looking indicator, giving traders a head start before the market fully reacts.
7. Margin Efficiency with Micro Soybeans
For traders looking to scale into soybean exposure without the capital intensity of full contracts, the CME Group’s micro-sized futures offer a compelling alternative.
📌 Contract Specs for Soybean Futures (ZS):
Symbol: ZS
Contract size: 5,000 bushels
Tick size: 1/4 of one cent (0.0025) per bushel = $12.50
Initial margin: ~$2,100 (varies by broker and volatility)
📌 Micro Soybean Futures (MZS):
Symbol: MZS
Contract size: 500 bushels
Tick size: 0.0050 per bushel = $2.50
Initial margin: ~$210
These smaller contracts are perfect for strategy testing, risk scaling, or layering exposure around key macro events like WASDE reports or weather disruptions. For traders aiming to build weather-aligned positions, MZS is a powerful tool to balance conviction with capital efficiency.
8. Wrapping It All Together
Rain matters. Not just in fields, but in futures prices too. While soybean markets may not overreact to every drizzle or downpour, extreme rainfall conditions—especially drought—can leave noticeable footprints on price action.
For traders, this means opportunity. By incorporating precipitation metrics into your workflow, you unlock a new layer of context. One that doesn’t replace technical or fundamental analysis, but enhances both.
And remember: this article is just one piece of a larger exploration into how weather affects the commodity markets. Make sure you also read prior installments.
When charting futures, the data provided could be delayed. Traders working with the ticker symbols discussed in this idea may prefer to use CME Group real-time data plan on TradingView: www.tradingview.com - This consideration is particularly important for shorter-term traders, whereas it may be less critical for those focused on longer-term trading strategies.
General Disclaimer:
The trade ideas presented herein are solely for illustrative purposes forming a part of a case study intended to demonstrate key principles in risk management within the context of the specific market scenarios discussed. These ideas are not to be interpreted as investment recommendations or financial advice. They do not endorse or promote any specific trading strategies, financial products, or services. The information provided is based on data believed to be reliable; however, its accuracy or completeness cannot be guaranteed. Trading in financial markets involves risks, including the potential loss of principal. Each individual should conduct their own research and consult with professional financial advisors before making any investment decisions. The author or publisher of this content bears no responsibility for any actions taken based on the information provided or for any resultant financial or other losses.
Full Breakdown of My Trading Strategy Dow Futures DaytradingI will be detailing my strategy to both help others and to help myself fine tune my strategy.
My strategy is one of market maker cycles. The end goal: to trade off of the Daily chart by drilling down to the 15 minutes for entries. Everything revolves around the Daily chart. The only indicator I use is ATR, other than that, pure price action. I use opening prices a lot in my trading.
Starting with the MONTHLY chart:
Every month has the following-
An opening price
A first trading day
A last trading day
These are things that ALL traders see and can't misinterpret.
I will use June as the basis for my examples.
I try to figure out what kind of monthly candle is likely to form. Bullish, Bearish or Doji. I use ATR to try to figure out the likely size also. For Dow Futures, a typical Monthly candle is around 3000 ticks +/-
Going to the Daily chart, I mark the beginning of the month and the end of the month.
The meat of the strategy, and the one quite frankly is the most difficult and the most discretionary, is reading price action on the Daily chart to determine what the next daily candle is likely to do and where it opens at. No strategy is 100% accurate and I do take losses from being wrong. With proper risk management ( I will detail my personal risk management later ) you can still make tons of money being 50% right.
Not everyday is meant to be traded and quite frankly, most days are pure trash. Over 55% of all Daily candles are small, resting Doji days. You are looking for the expansion daily candles.
Starting with the first trading of June:
1. May 29th, Large Doji day and and formed a mother bar
2. May 30th, another doji day and still inside the previous bar
3. June 2nd, opened up in middle of inside bar, Bias for day is Long. Buy near the bottom of the inside bar and a break of Yesterday's Low.
This is an actual trade I took. Once I saw the Doji candle on the 15 minute break below yesterday's low I entered in Long. I will go over stops and targets later. For now, I am explaining how I find my bias and locations.
The next day: start the process over again. Look at the Daily and the context of the bars. Look for swing points, Daily highs and lows. Key Daily bars as signals. I usually like to do this 5 minutes after Asia opens just to see where price opens at. I then mark the daily open with a cyan blue line. If I am Long bias then I want to buy under the open at key levels. I use SP as swing point, a daily high or low that has not been broken yet.
Tuesday, I would have a Long bias again. Because we opened still inside of the mother bar and I see highs not broken, I want to trade in that direction. What is a key level on this Tuesday? I see the monthly open right underneath. The big question I would ask myself on this Tuesday is where in that move can I get in on a pullback for the Long trade?
The market gives you an entry here.
I did not take that trade, I WILL show you the trade I did take on this day. After NY opened, I saw the spike into the monthly open and a doji right ON the open. I slammed Long. Especially, the three swing points to be used as the direction.
Now on to trade management. Stops, Targets. I have the same bracket for every trade, so the only variable is my entry. Once I enter, I set my ATM strategy.
I use the 15 minute ATR to determine my stop loss. This part is also up to the individual trader and is discretionary. I will show you MY strategy.
Take a zoomed-out view of the 15-minute chart with the 14 period ATR, mark the clusters of the peak ATR readings from NY sessions. In this case it is between 70-90. I tend to go towards the upper limit, this case 90. I then use 1.25-1.5 times of this reading based on my account and position sizing. In June AND in July, I am using 120 tick stops.
My targets are all strictly 2.5 risk to reward of what my stop is plus or minus a few ticks for commissions. Since I am using 120 tick stops, my targets are therefore, 300-310 ticks. Going back to my Tuesday trade, the trade management would be a set 2.5R all or nothing. Enter the trade and walk away. Go read a book or play PS5. Go to gym. It will either hit stop, target or close out at 4pm NY close.
2 Winning trades wipes away 5 losers. I have losers all the time with a 50% win rate. I can expect 8 losing trades in a row at any given time. Something I have experienced multiple times.
Now on to my money management strategy. The holy grail of this entire system. Quite frankly, how you enter and your strategy at the end of the day doesn't amount to much. How you manage your money is where professionalism is achieved.
Take your starting account balance, divide it in fours. I will use a 10,000 account as simple math.
10,000
2500 Level 1 14.5R
2500 Level 2 11.5R
2500 Level 3 9.5R
2500 Level 4 8.5R
I risk 1.75% per trade and each level will stay fixed until the next level is reached. In this example, Level 1 will be using $175 risk per trade and a 2.5 risk to reward, $440 reward. You will keep risking $175 per trade until you hit your $2500 profit goal to advance to Level 2. In this case this will take you 14.5R
Now you are on Level 2, you find your new account balance is now $12,500. Find 1.75% of this = $220. Keep using $220 risk until you hit another $2500 in profits. This will take you 11.5R.
Keep repeating these steps until you have hit all 4 profit levels and your account has doubled. Your new account balance is now $20,000. You will start this process over again. To double your account you will need a total of 44-45R. At a conservative approach of 5-7% monthly gain, you can expect to double your account in 8 months +/- depending on how good you can get.
The number one major key to ALL OF THIS IS
One trade per Daily candle. You lose on that day, move on and come again tomorrow
All profit targets need to be hit or close out at 4pm depending on price
Sector Rotation Strategy🌐 Sector Rotation Strategy: A Smart Way to Stay Ahead in the Stock Market
What Is Sector Rotation?
Imagine you're playing cricket. Some players shine in certain conditions — like a fast bowler on a bouncy pitch or a spinner on a turning track. The same idea applies to stock market sectors.
Sector Rotation is the process of shifting your money from one sector to another based on the market cycle, economic trends, or changing investor sentiment.
In simple words:
"You’re moving your money where the action is."
First, What Are Sectors?
The stock market is divided into different sectors, like:
Banking/Financials – HDFC Bank, Kotak Bank, SBI
IT– Infosys, TCS, Wipro
FMCG – HUL, Nestle, Dabur
Auto – Maruti, Tata Motors
Pharma – Sun Pharma, Cipla
Capital Goods/Infra – L&T, Siemens
PSU – BEL, BHEL, HAL
Real Estate, Metals, Energy, Telecom, etc.
Each sector behaves differently at various stages of the economy.
Why Is Sector Rotation Important?
Because all sectors don’t perform well all the time.
For example:
In a bull market, sectors like Auto, Capital Goods, and Infra usually lead.
During slowdowns, investors run to safe havens like FMCG and Pharma.
When inflation or crude oil rises, energy stocks tend to do better.
When interest rates drop, banking and real estate might shine.
So, instead of holding poor-performing sectors, smart investors rotate into the hot ones.
How Does Sector Rotation Work?
Let’s say you are an investor or trader.
Step-by-step guide:
Track the economy and markets
Is GDP growing fast? = Economy expanding
Are interest rates high? = Tight liquidity
Is inflation cooling down? = Growth opportunity
Observe sectoral indices
Check Nifty IT, Nifty Bank, Nifty FMCG, Nifty Pharma, etc.
See which are outperforming or lagging.
Watch for news flow
Budget announcements, RBI policy, global cues, crude oil prices, etc.
E.g., Defence orders boost PSU stocks like BEL or HAL.
Move your capital accordingly
If Infra and Capital Goods are breaking out, reduce exposure in IT or FMCG and rotate into Infra-heavy stocks.
Real Example (India, 2024–2025)
Example: Rotation from IT to PSU & Infra
In late 2023, IT stocks underperformed due to global slowdown and US recession fears.
Meanwhile, PSU and Infra stocks rallied big time because:
Government increased capital expenditure.
Defence contracts awarded.
Railway budget saw record allocations.
So, many smart investors rotated out of IT and into:
PSU Stocks: RVNL, BEL, HAL, BHEL
Capital Goods/Infra: L&T, Siemens, ABB
Railway Stocks: IRFC, IRCTC, Titagarh Wagons
This sector rotation gave 30%–100% returns in a few months for many stocks.
Tools You Can Use
Sectoral Charts on TradingView / Chartink / NSE
Use indicators like RSI, MACD, EMA crossover.
Compare sectors using “Relative Strength” vs Nifty.
Economic Calendar
Track RBI policy, inflation data, IIP, GDP, etc.
News Portals
Moneycontrol, Bloomberg, ET Markets, CNBC.
FIIs/DII Activity
Where the big money is going – this matters!
Sector Rotation Heatmaps
Some platforms show weekly/monthly performance of sectors.
📈 Sector Rotation Strategy for Traders
For short-term traders (swing/intraday):
Rotate into sectors showing strength in volumes, price action, breakouts.
Use tools like Open Interest (OI) for sector-based option strategies.
Example:
On expiry weeks, if Bank Nifty is showing strength with rising OI and volume, rotate capital into banking-related trades (Axis, ICICI, SBI).
Sector Rotation for Long-Term Investors
For investors, sector rotation can be used:
To reduce drawdowns.
To book profits and re-enter at better levels.
To ride economic trends.
Example:
If you had exited IT in late 2022 after a rally, and entered PSU stocks in early 2023, your portfolio would’ve seen better growth.
Pros of Sector Rotation
Better returns compared to static investing
Helps avoid underperforming sectors
Takes advantage of macro trends
Works in both bull and bear markets
Cons or Risks
Requires monitoring and active management
Timing the rotation is difficult
Wrong rotation = underperformance
May incur tax if frequent buying/selling (for investors)
Pro Tips
Don't rotate too fast; let the trend confirm.
Use SIPs or staggered entry in new sectors.
Avoid “hot tips”; follow actual price and volume.
Blend sector rotation with strong stock selection (don’t just chase sector).
Conclusion
The Sector Rotation Strategy is one of the smartest, most practical tools used by both traders and investors. You don’t need to be a pro to use it — just stay alert to the market mood, economic cycles, and where the money is moving.
Think of it as dancing with the market:
“When the music changes, you change your steps.”
Keep rotating. Keep growing.