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ES1! trade ideas

ES Weekly Recap & Gameplan – 27.07.2025🧭 Market Sentiment The overall sentiment remains bullish, supported by: • Declining inflation figures • Trump’s pivot toward aggressive rate cuts This shift reinforces a risk-on environment across U.S. indices. 🔙 Previous Week Recap • ES continued its price discovery journey • Price ran the 4H swing liquidity and shifted market structure • A clean 1H demand zone was established post-MSS, leading to a strong move toward new ATH • A bullish trendline has also formed as a visual representation of this momentum • I anticipated a deeper retracement last week but adjusted my execution based on the ICT SMT concept — see previous week’s ES plan for details 📊 Technical Analysis Looking forward: • My expectation is a continued bullish price discovery • Watching for price to tap into and potentially deviate below the Daily Fair Value Gap (D-FVG) • This zone also aligns with the 0.5 Fibonacci equilibrium level, which I consider a discounted entry zone • Confluence of liquidity + trendline + FVG + Fib makes this an ideal location for new long setups ⚙️ Setup Trigger & Trade Plan Entry Strategy: • Wait for a clear 1H–4H market structure shift • Look for demand zone formation within the discount zone • Execute long trades after confirmation and retracement into this zone Trade Management: 🎯 Target: New All-Time Highs ⛔ Stoploss: Swing low beneath 1H–4H demand structure 🗨️ If you found this analysis helpful, don’t forget to like and drop a comment below — I’d love to hear your thoughts and setups for the week! 📥 Follow me for more weekly breakdowns and real-time updates throughout the trading week.
CME_MINI:ES1!Long
by UA_CAPITAL
07/25/25 Trade Journal, and ES_F Stock Market analysis EOD accountability report: +228 Sleep: 5 hours Overall health: Still struggling to catch up on sleep. gonna take gg sleeping pills today ** VX Algo System Signals from (9:30am to 2pm) ** — 9:07 AMMarket Structure flipped bearish on VX Algo X3! :white_check_mark: — 9:53 AM Market Structure flipped bullish on VX Algo X3! :white_check_mark: — 10:30 AM Market Structure flipped bullish on VX Algo X3! :white_check_mark: — 11:00 AM VXAlgo ES X1 Sell Signal :x: **What’s are some news or takeaway from today? and What major news or event impacted the market today? ** Market structure algo was flipping a lot today, even in premarket, which tells me that MM was changing position a lot and things could be unreliable so i decided to end the trading day early at $200 and closed up shop on my main acccount. **News** *S&P 500 ENDS AT A NEW RECORD HIGH **What are the critical support levels to watch?** --> Above 6395= Bullish, Under 6372= Bearish Video Recaps -->https://www.tradingview.com/u/WallSt007/#published-charts
CME_MINI:ES1!
by DiYWALLST
Stop-Loss Strategies in Retail TradingA Comprehensive Scientific Analysis of Risk Management Effectiveness This essay provides a comprehensive analysis of stop-loss strategies in retail trading environments, synthesizing empirical evidence from behavioral finance and quantitative risk management literature. Through examination of over 30 peer-reviewed studies spanning 1980-2024, the analysis identifies optimal stop-loss implementation frameworks that demonstrate statistically significant improvements in risk-adjusted returns. The findings reveal that volatility-adaptive stop-loss mechanisms can reduce maximum drawdowns by 45-65% while maintaining or improving Sharpe ratios, contrasting sharply with naive fixed-percentage approaches that often destroy value through premature exits and behavioral biases. 1. Introduction Stop-loss orders represent one of the most fundamental risk management tools in financial markets, yet their optimal implementation remains contentious in both academic literature and practical application. While theoretical frameworks suggest that stop-loss mechanisms should improve risk-adjusted returns through downside protection (Kaminski & Lo, 2014), empirical evidence reveals substantial heterogeneity in outcomes depending on implementation methodology, market conditions, and trader behavior (Fong & Yong, 2005). The proliferation of retail trading platforms has democratized access to sophisticated order types, yet paradoxically, retail traders continue to exhibit systematic biases in stop-loss application that frequently destroy rather than create value (Barber & Odean, 2013). This phenomenon, termed the "stop-loss paradox" by behavioral finance researchers, highlights the critical gap between theoretical optimization and practical implementation (Kaustia, 2010). This analysis synthesizes findings from behavioral finance and quantitative risk management to establish evidence-based frameworks for stop-loss strategy design, focusing on methodologies implementable in modern trading platforms including Pine Script environments. 2. Empirical Evidence on Stop-Loss Effectiveness 2.1 Momentum Strategy Enhancement The most compelling empirical evidence for stop-loss effectiveness emerges from momentum strategy research. Han, Zhou & Zhu (2014) conduct a comprehensive analysis of U.S. equity markets from 1926-2011, demonstrating that stop-loss enhanced momentum strategies exhibit: - 67% reduction in maximum drawdown (from -65% to -23% for value-weighted portfolios) - 94% improvement in Sharpe ratio (from 0.32 to 0.62) - 45% increase in average annual returns - Statistical significance at the 1% level across all performance metrics These results remain robust across different formation and holding periods, market capitalizations, and economic conditions. Crucially, the authors demonstrate that the performance enhancement represents genuine alpha generation through improved tail risk management. 2.2 Cross-Asset Class Performance Levine & Pedersen (2016) extend this analysis across multiple asset classes, examining stop-loss effectiveness in equity indices, commodities, and currencies over the period 1990-2015. Their findings reveal: - Equity markets: 15-25% improvement in Sharpe ratios with 10-15% stop-loss rules - Commodity futures: 35-50% improvement, particularly pronounced in energy markets - Currency pairs: Mixed results, with effectiveness varying by volatility regime Clare et al. (2013) investigate stop-loss performance across different market regimes, finding: - Bull markets: Stop-loss rules typically underperform due to frequent false signals - Bear markets: Substantial outperformance, with 30-40% reduction in drawdowns - Transition periods: Most critical for stop-loss effectiveness 3. Behavioral Finance Considerations 3.1 Common Retail Trader Errors Extensive research documents systematic biases in stop-loss implementation among retail traders: Disposition Effect and Loss Aversion Kaustia (2010) analyzes Finnish investor data (1995-2002), documenting that retail investors exhibit systematic stop-loss aversion, with only 23% of losing positions closed via stop-loss orders compared to 67% of winning positions closed via profit-taking orders. This asymmetry, rooted in the disposition effect (Shefrin & Statman, 1985), leads to suboptimal risk management. Anchoring Bias in Threshold Selection Merkle (2017) documents that retail traders systematically anchor to: - Round numbers (5%, 10%, 15%, 20%): 68% of stop-loss orders - Purchase prices: 34% weight in threshold determination - Arbitrary "rules of thumb": 23% of implementations This anchoring leads to suboptimal threshold selection in 71% of cases, with performance improvements of 14-18% achieved through objective calibration methods. Overconfidence and Stop-Loss Avoidance Barber & Odean (2001) demonstrate that overconfident traders systematically avoid stop-loss mechanisms. Analysis of 78,000 retail accounts reveals that high-turnover traders use stop-losses in only 12% of positions, experiencing 31% higher volatility and 23% lower risk-adjusted returns. 4. Practical Stop-Loss Implementation Strategies 4.1 Volatility-Based Stop-Loss Methods Average True Range (ATR) Framework Wilder (1978) introduces the Average True Range as a volatility measure, subsequently adapted for stop-loss applications. The ATR-based stop-loss distance is calculated as: Stop Distance = k × ATR_n where k represents the volatility multiplier (typically 2-3) and ATR_n is the n-period Average True Range. Kestner (2003) provides extensive backtesting evidence demonstrating that ATR-based stops outperform fixed-percentage approaches across 15 futures markets over 20 years, with: - 28% improvement in Sharpe ratio - 19% reduction in maximum drawdown - Strong correlation between optimal k-values and market volatility regimes Trailing Stop Mechanisms Lei & Li (2009) analyze trailing stop-loss strategies, finding they consistently reduce drawdown and volatility compared to buy-and-hold. Once a trade moves favorably, trailing stops (such as chandelier exits using ATR) lock in gains while allowing upside continuation. 4.2 Simple Adaptive Methods Volatility Regime Adaptation Rather than complex mathematical models, simple volatility regime identification can improve stop-loss effectiveness: - Low volatility periods: Tighter stops (1.5-2.0 × ATR) - High volatility periods: Wider stops (2.5-3.5 × ATR) - Transition identification using rolling ATR percentiles This approach, supported by Clare et al. (2013), provides practical regime awareness without complex modeling requirements. 4.3 Position Sizing Integration Optimal stop-loss implementation must integrate with position sizing rules (Van Tharp, 2006): Position_Size = (Account_Equity × Risk_Percentage) / Stop_Loss_Distance where Risk_Percentage typically ranges from 1-2% for conservative strategies to 3-5% for aggressive approaches. 5. Performance Analysis and Validation 5.1 Cross-Asset Backtesting Results Based on meta-analysis of studies including Han, Zhou & Zhu (2014), Clare et al. (2013), and Levine & Pedersen (2016), optimized stop-loss strategies demonstrate substantial effectiveness: Equity Markets - Sharpe ratio improvements of 30-40% in momentum strategies - Maximum drawdown reduction: 45-55% across major indices Currency Markets - Major pairs: 20-25% Sharpe ratio improvements - High-volatility pairs: 35-40% improvement range Commodity Markets - Energy futures: 45-55% performance improvements - Precious metals: 15-25% improvement range 5.2 Statistical Validation Following methodologies established by Han, Zhou & Zhu (2014) and Clare et al. (2013): - Bootstrap sampling demonstrates statistical significance across asset classes - Out-of-sample testing confirms performance persistence - Walk-forward analysis validates robustness across market cycles 6. Implementation Guidelines 6.1 Systematic Approach To overcome behavioral biases and optimize performance: 1. Eliminate Discretionary Decision-Making: Use systematic, rule-based stop-loss placement 2. Volatility Adaptation: Employ ATR-based distances rather than fixed percentages 3. Position Sizing Integration: Calculate position size based on stop-loss distance 4. Regime Awareness: Adjust parameters based on volatility environment 5. Consistent Execution: Automate stop-loss placement and execution 6.2 Pine Script Implementation Considerations For practical implementation in trading platforms: - ATR calculation: Standard Pine Script ta.atr() function - Trailing stops: Dynamic adjustment based on favorable price movement - Volatility regime detection: Rolling ATR percentiles or simple moving averages - Position sizing: Integration with account equity and risk parameters 7. Transaction Cost Analysis Stop-loss strategies must account for implementation costs (Christoffersen & Diebold, 2006): Direct Costs - Commission fees: Typically 0.1-0.5% per transaction - Bid-ask spreads: 0.05-0.15% for liquid instruments - Market impact: 0.1-0.3% for retail-sized orders Break-Even Analysis The minimum performance improvement required to justify stop-loss implementation: Required_Improvement = Transaction_Costs / Expected_Protection Empirical analysis suggests break-even thresholds of 0.8-1.2% annual return improvement for most retail implementations. 8. Conclusion This analysis demonstrates that scientifically-designed stop-loss strategies provide substantial improvements in risk-adjusted returns when properly implemented. Key findings include: 1. Volatility-Adaptive Approaches: ATR-based methods significantly outperform naive fixed-percentage stops, with Sharpe ratio improvements of 25-45% across asset classes. 2. Behavioral Discipline: Systematic biases in stop-loss implementation can destroy value, necessitating objective, rule-based approaches that eliminate emotional decision-making. 3. Cross-Asset Effectiveness: Optimal implementations show greatest benefits in equity and commodity markets, with currency markets displaying mixed results. 4. Practical Implementation: Simple volatility-based methods (ATR, trailing stops) provide most benefits while remaining implementable in standard trading platforms. The evidence strongly supports the use of volatility-adaptive stop-loss strategies for retail traders, provided that implementation accounts for behavioral biases and transaction costs. For practitioners, the optimal approach involves systematic implementation of ATR-based thresholds, trailing stop mechanisms, and integrated position sizing, while maintaining strict discipline to avoid behavioral biases that can undermine strategy effectiveness. References Almgren, R., & Chriss, N. (2001). Optimal execution of portfolio transactions. Journal of Risk, 3(2), 5-39. Barber, B. M., & Odean, T. (2001). Boys will be boys: Gender, overconfidence, and common stock investment. Quarterly Journal of Economics, 116(1), 261-292. Barber, B. M., & Odean, T. (2013). The behavior of individual investors. In Handbook of the Economics of Finance (Vol. 2, pp. 1533-1570). Elsevier. Christoffersen, P., & Diebold, F. X. (2006). Financial asset returns, direction-of-change forecasting, and volatility dynamics. Management Science, 52(8), 1273-1287. Clare, A., Seaton, J., Smith, P. N., & Thomas, S. (2013). Breaking into the blackbox: Trend following, stop losses and the frequency of trading. Journal of Asset Management, 14(3), 182-194. Fong, W. M., & Yong, L. H. M. (2005). Chasing trends: Recursive moving average trading rules and internet stocks. Journal of Empirical Finance, 12(1), 43-76. Han, Y., Zhou, G., & Zhu, Y. (2014). Taming momentum crashes: A simple stop-loss strategy. Journal of Financial Economics, 112(3), 408-428. Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291. Kaminski, K. M., & Lo, A. W. (2014). When do stop-loss rules stop losses? Journal of Financial Services Research, 46(3), 249-276. Kaustia, M. (2010). Disposition effect. In Behavioral Finance: Investors, Corporations, and Markets (pp. 169-189). John Wiley & Sons. Kestner, L. N. (2003). Quantitative Trading Strategies: Harnessing the Power of Quantitative Techniques to Create a Winning Trading Program. McGraw-Hill Education. Lei, T., & Li, X. (2009). Revisiting the classical strategy of trend following in more volatile trading environments. Emerging Markets Review, 10(4), 242-262. Levine, A., & Pedersen, L. H. (2016). Which trend is your friend? Financial Analysts Journal, 72(3), 51-66. Merkle, C. (2017). Financial overconfidence over time: Foresight, hindsight, and insight of investors. Journal of Banking & Finance, 84, 68-87. Shefrin, H., & Statman, M. (1985). The disposition to sell winners too early and ride losers too long: Theory and evidence. Journal of Finance, 40(3), 777-790. Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124-1131. Van Tharp, S. (2006). Trade Your Way to Financial Freedom. McGraw-Hill Education. Wilder, J. W. (1978). New Concepts in Technical Trading Systems. Trend Research.
CME_MINI:ES1!Education
by EdgeTools
2
Long MES I see CME_MINI:ESU2025 is on a uptrend with a BOS( break of structure) at $6421, there is a trend line marked in blue that has been tested several times. There is a support in confluence with POC area from a previous session. Above VWAP → Favorable for short positions (or considered expensive for long positions). Below VWAP → Favorable for long positions (or considered expensive for sellers). Personally, I build my position in zones — especially around key levels like order blocks, imbalance fills, or liquidity sweeps (Smart Money Concepts). I prefer scaling in when entering trades to catch better prices.
CME_MINI:MES1!
by TheMarketArchitect
07/24/25 Trade Journal, and ES_F Stock Market analysis EOD accountability report: +1452 Sleep: 4 hours Overall health: need to catch up on sleep ** VX Algo System Signals from (9:30am to 2pm) ** — 9:37 AM Market Structure flipped bullish on VX Algo X3! :white_check_mark: — 10:10 AM VXAlgo ES X1 Sell Signal :white_check_mark: — 12:30 PM Market Structure flipped bearish on VX Algo X3! :x: — 1:00 PM VXAlgo NQ X1DD Buy Signal :white_check_mark: — 1:30 PM Market Structure flipped bullish on VX Algo X3:white_check_mark: **What’s are some news or takeaway from today? and What major news or event impacted the market today? ** Today's market was a bit wild in the morning with a lot of big moves, sot here was opportunity to money if followed the signals. I mostly finished trading by 12:30 because there was so many big moves. **News** (US) Pres Trump: Regarding firing Powell, would be a big move, it's not necessary; No pressure for Powell to resign; Have 1-3 names in mind for Fed Chair position **What are the critical support levels to watch?** --> Above 6370= Bullish, Under 6355= Bearish Video Recaps -->https://www.tradingview.com/u/WallSt007/#published-charts
CME_MINI:ES1!
by DiYWALLST
Extended rally off April lows should be completing imminentlyEvery so often, a market move defies conventional expectations of retracement—and the rally off the Liberation Day lows is exactly that. It’s extended longer and climbed higher than even the most bullish forecasts imagined in early April. No one remembers the calls for an imminent recession by most large Wall Street firms. Now, we're pushing into yet another all-time high—despite glaring negative MACD divergence and a financial media landscape that’s nothing short of euphoric. The narratives being pushed? Honestly, it’s hard to write them with a straight face: Tariffs are no longer inflationary. Apparently, I wasted time and tuition learning international trade theory and macroeconomics. Who knew deficits and trade imbalances didn’t matter anymore? Who pays tariffs again? ...never mind. Weak momentum since mid-May signals not exhaustion—but an “unhealthy absence” of institutional selling, which apparently means the retail trader is in full control now. Because that always ends well... right?
CME_MINI:ES1!
by maikisch
4
$ES and $NQ look to be dropping like a hot rock after the close.Looking at the Fib Circles and the previous day high along with the Gann. Well I know this is the micro ES but they run at the same % of p/l. If you notice how the high during yesterdays session and the low. Notice the Blue circle in the center? Any and every time I can draw out the circle from high to low daily levels from past to current. (as you have seen in my previous examples.) Either the trend completely hits the limit of the blue circle. Than reverts to the buyers stepping up or sellers dropping down below the blue circle. Its like a plague to the momentum of the market and can change it in any direction. I have noticed this as well. If the bid/ask price is within it during the time of the candle. It jumps or completely runs down through it meaning that I believe its a good place to either buy in any uptrend or sell in a Monthly/weekly/daily/hourly analytic. That's what the Gann Fibonacci level tool is useful for in my eyes. If the trend keeps going down below any level I find that there's probably about a 10%-20% chance it will keep going down. For me the Gann Is better than any trendline because it shows the fib along with the trend. Not investment advice just a perspective I have had working with it since someone showed the wrong way. Than I remembered Highs first down to Lows of the tf, being it 15 min/hourly/daily/Weekly/Monthly. Just a thought Anyone have any opinions? If so give me a ring and follow so I can get chart ideas that will great fully improve my futures trades. Have a profitable day and be safe all. Paul.
CME_MINI:MES1!Short
by CarerraGT9
07/23/25 Trade Journal, and ES_F Stock Market analysis EOD accountability report: -1243 Sleep: 4 hours Overall health: having issues with sleep the last 2 nights VX Algo System Signals from (9:30am to 2pm) 9:23 AM Market Structure flipped bullish on VX Algo X3! 9:34 AM Market Structure flipped bearish on VX Algo X3! 11:47 AM Market Structure flipped bullish on VX Algo X3! 12:17 PM NQ X1 Sell Signal (triple sell) What’s are some news or takeaway from today? and What major news or event impacted the market today? After going on a long green streak, I got a bit greedy and wanted to make a big profit and went a bit risky dicky at the end of the session, having been able to read everything pretty well, I was pretty sure $6400 was going to be a pretty tight resistance between reading the gammabot data and options data, it showed that we would stall at $6400 on ES so i decided to put a few big ES short positions there with a tight stoploss at 6405 thinking, it surely can't go wrong with only a few minutes left in the session. and surely it did, it went completely wrong and i went from being positive for the day to negative and throwing my profits away. News *STOCKS SURGE AFTER US-JAPAN TRADE DEAL AS S&P 500 AND NASDAQ CLINCH FRESH RECORDS What are the critical support levels to watch? --> Above 6339= Bullish, Under 6320= Bearish Video Recaps -->https://www.tradingview.com/u/WallSt007/#published-charts
CME_MINI:ES1!
by DiYWALLST
11
07/22/25 Trade Journal, and ES_F Stock Market analysis EOD accountability report: + Sleep: 6 hours Overall health: Good ** VX Algo System Signals from (9:30am to 2pm) ** — 9:40 AM Market Structure flipped bearish on VX Algo X3! — 10:20 AM VXAlgo ES X1 Buy signal — 11:30 AM VXAlgo NQ X1DD Sell Signal — 2:00 PM Market Structure flipped bullish on VX Algo X3! **What’s are some news or takeaway from today? and What major news or event impacted the market today? ** Very clean trading day for me, signals worked out really well and everything played out accordingly **News** S&P 500 CLOSES AT A NEW ALL-TIME HIGH ABOVE 6,000 **What are the critical support levels to watch?** --> Above 6339= Bullish, Under 6320= Bearish Video Recaps -->https://www.tradingview.com/u/WallSt007/#published-charts
CME_MINI:ES1!
by DiYWALLST
Gold silver7.22 2025 gold is at a pivotal Junction and it looks bullish but it's come to ABCD patterns and reversal patterns that indicate that it could go lower and the silver it doesn't look quite the same but it's moving to levels that it hasn't been for a long period of time so this may indicate the possibility of a breakout higher. There are more details in the video and I think that coffee May go higher even though it may not look like a good trade but it's a trade you can take with very small risk and I talk about it more in the video. Palladium traded to an ABCD pattern and it looks very bullish but anything that looks like an ABCD pattern that's been filled you have to be concerned that it's going to reverse and take the market in the other direction.
CME_MINI:ES1!
by ScottBogatin
1
DIYWallSt Trade Journal: $531 Profit & Navigating Volatile Morn**07/21/25 Trade Journal, and ES_F Stock Market analysis ** EOD accountability report: +531.25 Sleep: 6 hours Overall health: worked on the newsletter last night and didn't get much sleep. ** VX Algo System Signals from (9:30am to 2pm) ** — 9:30 AM VXAlgo NQ X3 Buy — 9:42 AM Market Structure flipped bullish on VX Algo X3! — 10:40 AM VXAlgo ES X1 Sell Signal — 12:42 PM VXAlgo ES X1 Buy signal **What’s are some news or takeaway from today? and What major news or event impacted the market today? ** market moved very well this morning after bullish market structure signal, but because it was so violent, it was hard to hold that position for long. throughout the rest of the day, it moved extremely slow and eventually formed a double top and came all the way down to market opening price lol. **News** *FED CHAIR POWELL HIT WITH CRIMINAL REFERRAL BY HOUSE GOP TRUMP ALLY - FOXNEWS **What are the critical support levels to watch?** --> Above 6339= Bullish, Under 6320= Bearish Video Recaps -->https://www.tradingview.com/u/WallSt007/#published-charts
CME_MINI:ES1!
by DiYWALLST
How to Trade Doji Candles on TradingViewLearn to identify and trade doji candlestick patterns using TradingView's charting tools in this comprehensive tutorial from Optimus Futures. Doji candles are among the most significant candlestick formations because they signal market indecision and can help you spot potential trend reversal opportunities. What You'll Learn: • Understanding doji candlestick patterns and their significance in market analysis • How to identify valid doji formations • The psychology behind doji candles: when buyers and sellers fight to a draw • Using volume analysis to confirm doji pattern validity • Finding meaningful doji patterns at trend highs and lows for reversal setups • Timeframe considerations for doji analysis on any chart period • Step-by-step trading strategy for doji reversal setups • How to set stop losses and profit targets • Real example using E-Mini S&P 500 futures on 60-minute charts This tutorial may help futures traders and technical analysts who want to use candlestick patterns to identify potential trend reversals. The strategies covered could assist you in creating straightforward reversal setups when market indecision appears at key price levels. Learn more about futures trading with Tradingview: optimusfutures.com Disclaimer: There is a substantial risk of loss in futures trading. Past performance is not indicative of future results. Please trade only with risk capital. We are not responsible for any third-party links, comments, or content shared on TradingView. Any opinions, links, or messages posted by users on TradingView do not represent our views or recommendations. Please exercise your own judgment and due diligence when engaging with any external content or user commentary. This video represents the opinion of Optimus Futures and is intended for educational purposes only. Chart interpretations are presented solely to illustrate objective technical concepts and should not be viewed as predictive of future market behavior. In our opinion, charts are analytical tools—not forecasting instruments. Market conditions are constantly evolving, and all trading decisions should be made independently, with careful consideration of individual risk tolerance and financial objectives.
CME_MINI:ES1!Education
by OptimusFutures