{"product_id":"micro-s-p-500-short-momentum-python-futures-strategy-source-code-mes","title":"Micro S\u0026P 500 Short Momentum – Python Futures Strategy Source Code (MES)","description":"\u003cdiv style=\"font-family:-apple-system,BlinkMacSystemFont,'Segoe UI',Roboto,Helvetica,Arial,sans-serif;color:#1f2937;line-height:1.6;max-width:860px;\"\u003e\n\n  \u003c!-- HEADER --\u003e\n  \u003cdiv style=\"background:#0f172a;color:#ffffff;padding:24px 28px;border-radius:10px;margin-bottom:24px;\"\u003e\n    \u003cp style=\"margin:0 0 4px;font-size:12px;letter-spacing:1.5px;text-transform:uppercase;color:#94a3b8;\"\u003ePython Strategy Source Code · Educational\u003c\/p\u003e\n    \u003ch2 style=\"margin:0 0 8px;font-size:26px;color:#ffffff;\"\u003eMicro S\u0026amp;P 500 Short Momentum\u003c\/h2\u003e\n    \u003cp style=\"margin:0;color:#cbd5e1;font-size:15px;\"\u003eA short-only Micro E-mini S\u0026amp;P 500 (MES) futures strategy built around NFP releases and hawkish Fed repricing. The code doesn't depend on any broker, uses only the Python standard library and has comments throughout.\u003c\/p\u003e\n    \u003cp style=\"margin:12px 0 0;font-size:13px;color:#94a3b8;\"\u003eBot ID: bot_mes_short_momentum  |  Exchange: CME  |  Bias: SHORT only  |  Max contracts: 2\u003c\/p\u003e\n  \u003c\/div\u003e\n\n  \u003c!-- OVERVIEW --\u003e\n  \u003ch3 style=\"font-size:20px;border-bottom:2px solid #e5e7eb;padding-bottom:6px;\"\u003eOverview\u003c\/h3\u003e\n  \u003cp\u003eYou get the complete, documented Python source code for a systematic short-momentum strategy on Micro E-mini S\u0026amp;P 500 futures. The strategy reads OHLCV bars and checks its entry and exit conditions at each bar close. It manages open positions with ATR-based stops and position sizing. Every decision is visible in the code, so you can trace why a trade was opened, how it was sized and why it was closed.\u003c\/p\u003e\n  \u003cp\u003eThe code doesn't depend on any broker. Market-data and order-execution hooks are marked with placeholder comments. You can feed it bars from any source and send its orders to any broker API or paper-trading adapter, and the signal, indicator and risk modules stay the same. It uses only the Python standard library (\u003ccode\u003easyncio\u003c\/code\u003e, \u003ccode\u003elogging\u003c\/code\u003e, \u003ccode\u003etyping\u003c\/code\u003e).\u003c\/p\u003e\n  \u003cp\u003eThis package is for:\u003c\/p\u003e\n  \u003cul\u003e\n    \u003cli\u003eDevelopers learning how systematic trading strategies are built\u003c\/li\u003e\n    \u003cli\u003eTraders who want a starting point to adapt and test on their own\u003c\/li\u003e\n    \u003cli\u003eQuants who want a clean, readable reference implementation\u003c\/li\u003e\n  \u003c\/ul\u003e\n  \u003cp style=\"background:#fff7ed;border-left:4px solid #f97316;padding:10px 14px;margin:16px 0;font-size:14px;\"\u003e\u003cstrong\u003ePlease note:\u003c\/strong\u003e This is source code for study and further development. It is not a finished, proven trading system. The backtest below has very few trades and low statistical confidence. Test it thoroughly yourself before you consider live use.\u003c\/p\u003e\n\n  \u003c!-- WHAT YOU RECEIVE --\u003e\n  \u003ch3 style=\"font-size:20px;border-bottom:2px solid #e5e7eb;padding-bottom:6px;\"\u003eWhat You Receive\u003c\/h3\u003e\n  \u003cul\u003e\n    \u003cli\u003e\n\u003cstrong\u003ebot_mes_short_momentum_portable.py\u003c\/strong\u003e: Python strategy file with all broker, data-feed and messaging code replaced by placeholder comments\u003c\/li\u003e\n    \u003cli\u003eThe full strategy logic, including indicators, signals, position sizing and risk controls\u003c\/li\u003e\n    \u003cli\u003eComments throughout the code, written for learning\u003c\/li\u003e\n    \u003cli\u003eWorks with any platform that delivers OHLCV bar data to Python\u003c\/li\u003e\n  \u003c\/ul\u003e\n\n  \u003c!-- STRATEGY --\u003e\n  \u003ch3 style=\"font-size:20px;border-bottom:2px solid #e5e7eb;padding-bottom:6px;\"\u003eHow the Strategy Works\u003c\/h3\u003e\n  \u003ctable style=\"width:100%;border-collapse:collapse;font-size:14px;margin-bottom:16px;\"\u003e\n    \u003ctr\u003e\n      \u003ctd style=\"vertical-align:top;padding:10px;border:1px solid #e5e7eb;width:50%;\"\u003e\n        \u003cstrong\u003eIndicators\u003c\/strong\u003e\n        \u003cul style=\"margin:6px 0 0;padding-left:18px;\"\u003e\n          \u003cli\u003eRSI\u003c\/li\u003e\n          \u003cli\u003eMACD\u003c\/li\u003e\n          \u003cli\u003eEMA \/ SMA crossover\u003c\/li\u003e\n          \u003cli\u003eATR volatility\u003c\/li\u003e\n          \u003cli\u003eDonchian channel breakout\u003c\/li\u003e\n          \u003cli\u003eRealized-volatility regime filter\u003c\/li\u003e\n        \u003c\/ul\u003e\n      \u003c\/td\u003e\n      \u003ctd style=\"vertical-align:top;padding:10px;border:1px solid #e5e7eb;width:50%;\"\u003e\n        \u003cstrong\u003ePosition Sizing\u003c\/strong\u003e\n        \u003cul style=\"margin:6px 0 0;padding-left:18px;\"\u003e\n          \u003cli\u003eRisk-percent-of-capital sizing\u003c\/li\u003e\n          \u003cli\u003eMargin-utilization cap\u003c\/li\u003e\n          \u003cli\u003eInverse-volatility (ATR) scaling\u003c\/li\u003e\n          \u003cli\u003eVolatility-regime (VIX) scaling*\u003c\/li\u003e\n          \u003cli\u003eHard cap of 2 contracts\u003c\/li\u003e\n        \u003c\/ul\u003e\n      \u003c\/td\u003e\n    \u003c\/tr\u003e\n    \u003ctr\u003e\n      \u003ctd style=\"vertical-align:top;padding:10px;border:1px solid #e5e7eb;\"\u003e\n        \u003cstrong\u003eExits \u0026amp; Trade Management\u003c\/strong\u003e\n        \u003cul style=\"margin:6px 0 0;padding-left:18px;\"\u003e\n          \u003cli\u003eProfit-taking in stages at several R-multiple targets\u003c\/li\u003e\n          \u003cli\u003eTrailing stop that only moves in the trade's favor\u003c\/li\u003e\n          \u003cli\u003eHard stop (STOP_HIT) and trailing stop (TRAILING_STOP)\u003c\/li\u003e\n          \u003cli\u003eExit when the trend or momentum reverses (THESIS_INVALIDATED)\u003c\/li\u003e\n          \u003cli\u003eMaximum holding period (TIME_EXIT)\u003c\/li\u003e\n          \u003cli\u003eProfit target (PROFIT_TARGET)\u003c\/li\u003e\n        \u003c\/ul\u003e\n      \u003c\/td\u003e\n      \u003ctd style=\"vertical-align:top;padding:10px;border:1px solid #e5e7eb;\"\u003e\n        \u003cstrong\u003eRisk Controls\u003c\/strong\u003e\n        \u003cul style=\"margin:6px 0 0;padding-left:18px;\"\u003e\n          \u003cli\u003eStop after a set number of consecutive losses\u003c\/li\u003e\n          \u003cli\u003eLoss circuit breaker that halts trading\u003c\/li\u003e\n          \u003cli\u003eDynamic daily loss limit\u003c\/li\u003e\n          \u003cli\u003eWeekly loss limit\u003c\/li\u003e\n          \u003cli\u003eNo trading during the exchange maintenance window\u003c\/li\u003e\n          \u003cli\u003eProtection against stale data feeds\u003c\/li\u003e\n        \u003c\/ul\u003e\n      \u003c\/td\u003e\n    \u003c\/tr\u003e\n  \u003c\/table\u003e\n  \u003cp style=\"font-size:13px;color:#6b7280;\"\u003e*VIX-based scaling needs you to supply a VIX data feed. Execution model: an event-driven async loop with structured JSON event logs (entries, exits, diagnostics and metrics). All fills are simulated by default.\u003c\/p\u003e\n\n  \u003c!-- BACKTEST --\u003e\n  \u003ch3 style=\"font-size:20px;border-bottom:2px solid #e5e7eb;padding-bottom:6px;\"\u003eHypothetical Backtest Results\u003c\/h3\u003e\n  \u003cp style=\"font-size:14px;color:#4b5563;\"\u003eBacktest on 4-hour MES OHLCV bars (861 bars, about 4 months analyzed, May–Sep 2026) with $12,000 starting capital. Fills were approximated, not executed. \u003cstrong\u003eStatistical confidence: LOW (7 trades).\u003c\/strong\u003e\u003c\/p\u003e\n\n  \u003ctable style=\"width:100%;border-collapse:collapse;font-size:14px;margin-bottom:16px;\"\u003e\n    \u003ctr style=\"background:#f1f5f9;\"\u003e\n      \u003cth style=\"text-align:left;padding:8px 10px;border:1px solid #e5e7eb;\"\u003eMetric\u003c\/th\u003e\n      \u003cth style=\"text-align:right;padding:8px 10px;border:1px solid #e5e7eb;\"\u003eValue\u003c\/th\u003e\n    \u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd style=\"padding:8px 10px;border:1px solid #e5e7eb;\"\u003eNet P\u0026amp;L (hypothetical)\u003c\/td\u003e\n\u003ctd style=\"text-align:right;padding:8px 10px;border:1px solid #e5e7eb;\"\u003e$773.86\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd style=\"padding:8px 10px;border:1px solid #e5e7eb;\"\u003eTotal trades\u003c\/td\u003e\n\u003ctd style=\"text-align:right;padding:8px 10px;border:1px solid #e5e7eb;\"\u003e7 (4 winners \/ 3 losers)\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd style=\"padding:8px 10px;border:1px solid #e5e7eb;\"\u003eWin rate\u003c\/td\u003e\n\u003ctd style=\"text-align:right;padding:8px 10px;border:1px solid #e5e7eb;\"\u003e57.1%\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd style=\"padding:8px 10px;border:1px solid #e5e7eb;\"\u003eSharpe ratio\u003c\/td\u003e\n\u003ctd style=\"text-align:right;padding:8px 10px;border:1px solid #e5e7eb;\"\u003e1.68\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd style=\"padding:8px 10px;border:1px solid #e5e7eb;\"\u003eMaximum drawdown\u003c\/td\u003e\n\u003ctd style=\"text-align:right;padding:8px 10px;border:1px solid #e5e7eb;\"\u003e$76.79 (0.64%)\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd style=\"padding:8px 10px;border:1px solid #e5e7eb;\"\u003eMax consecutive wins \/ losses\u003c\/td\u003e\n\u003ctd style=\"text-align:right;padding:8px 10px;border:1px solid #e5e7eb;\"\u003e2 \/ 2\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd style=\"padding:8px 10px;border:1px solid #e5e7eb;\"\u003eProfitable months\u003c\/td\u003e\n\u003ctd style=\"text-align:right;padding:8px 10px;border:1px solid #e5e7eb;\"\u003e2 of 4 (50%)\u003c\/td\u003e\n\u003c\/tr\u003e\n  \u003c\/table\u003e\n\n  \u003cp style=\"font-size:14px;margin-bottom:6px;\"\u003e\u003cstrong\u003eMonthly results (hypothetical, % of $12,000)\u003c\/strong\u003e\u003c\/p\u003e\n  \u003ctable style=\"width:100%;border-collapse:collapse;font-size:14px;margin-bottom:16px;text-align:center;\"\u003e\n    \u003ctr style=\"background:#f1f5f9;\"\u003e\n      \u003cth style=\"padding:8px;border:1px solid #e5e7eb;\"\u003eMay 2026\u003c\/th\u003e\n      \u003cth style=\"padding:8px;border:1px solid #e5e7eb;\"\u003eJun 2026\u003c\/th\u003e\n      \u003cth style=\"padding:8px;border:1px solid #e5e7eb;\"\u003eJul 2026\u003c\/th\u003e\n      \u003cth style=\"padding:8px;border:1px solid #e5e7eb;\"\u003eAug 2026\u003c\/th\u003e\n      \u003cth style=\"padding:8px;border:1px solid #e5e7eb;\"\u003eSep 2026\u003c\/th\u003e\n    \u003c\/tr\u003e\n    \u003ctr\u003e\n      \u003ctd style=\"padding:8px;border:1px solid #e5e7eb;color:#15803d;\"\u003e+$794.87\u003cbr\u003e\u003csmall\u003e+6.6%\u003c\/small\u003e\n\u003c\/td\u003e\n      \u003ctd style=\"padding:8px;border:1px solid #e5e7eb;color:#6b7280;\"\u003eNo trades\u003c\/td\u003e\n      \u003ctd style=\"padding:8px;border:1px solid #e5e7eb;color:#b91c1c;\"\u003e−$7.02\u003cbr\u003e\u003csmall\u003e−0.06%\u003c\/small\u003e\n\u003c\/td\u003e\n      \u003ctd style=\"padding:8px;border:1px solid #e5e7eb;color:#15803d;\"\u003e+$3.27\u003cbr\u003e\u003csmall\u003e+0.03%\u003c\/small\u003e\n\u003c\/td\u003e\n      \u003ctd style=\"padding:8px;border:1px solid #e5e7eb;color:#b91c1c;\"\u003e−$16.80\u003cbr\u003e\u003csmall\u003e−0.14%\u003c\/small\u003e\n\u003c\/td\u003e\n    \u003c\/tr\u003e\n  \u003c\/table\u003e\n  \u003cp style=\"font-size:14px;\"\u003eAlmost all of the backtest profit came from a single month (May 2026). The strategy was roughly flat to slightly negative from July through September.\u003c\/p\u003e\n\n  \u003cp style=\"font-size:14px;margin-bottom:6px;\"\u003e\u003cstrong\u003ePaper-trading session (2026-09-23)\u003c\/strong\u003e\u003c\/p\u003e\n  \u003cp style=\"font-size:14px;margin-top:0;\"\u003e2 trades: 1 win, 1 loss. Net result: $0.00.\u003c\/p\u003e\n\n  \u003cdiv style=\"background:#fef2f2;border:1px solid #fecaca;padding:12px 16px;border-radius:8px;font-size:14px;margin:16px 0;\"\u003e\n    \u003cstrong\u003eLimitations of these results\u003c\/strong\u003e\n    \u003cul style=\"margin:6px 0 0;padding-left:18px;\"\u003e\n      \u003cli\u003eOnly 7 trades. That is well below the 20+ usually needed for any statistical meaning.\u003c\/li\u003e\n      \u003cli\u003eOnly 1 of the last 3 months was profitable, and September 2026 was a losing month.\u003c\/li\u003e\n      \u003cli\u003eFills were approximated from a signal score, not executed trades.\u003c\/li\u003e\n      \u003cli\u003eResults depend heavily on one month and may not repeat.\u003c\/li\u003e\n    \u003c\/ul\u003e\n  \u003c\/div\u003e\n\n  \u003c!-- REQUIREMENTS --\u003e\n  \u003ch3 style=\"font-size:20px;border-bottom:2px solid #e5e7eb;padding-bottom:6px;\"\u003eTechnical Requirements\u003c\/h3\u003e\n  \u003cul\u003e\n    \u003cli\u003ePython 3.10+\u003c\/li\u003e\n    \u003cli\u003eStandard library only: \u003ccode\u003easyncio\u003c\/code\u003e, \u003ccode\u003elogging\u003c\/code\u003e, \u003ccode\u003eos\u003c\/code\u003e, \u003ccode\u003esys\u003c\/code\u003e, \u003ccode\u003etyping\u003c\/code\u003e\n\u003c\/li\u003e\n    \u003cli\u003eAny OHLCV bar data source (4-hour bars were used in the backtest)\u003c\/li\u003e\n    \u003cli\u003eAny broker API or paper-trading adapter, which you supply\u003c\/li\u003e\n  \u003c\/ul\u003e\n\n  \u003c!-- FAQ --\u003e\n  \u003ch3 style=\"font-size:20px;border-bottom:2px solid #e5e7eb;padding-bottom:6px;\"\u003eFrequently Asked Questions\u003c\/h3\u003e\n  \u003cp\u003e\u003cstrong\u003eDo I need a particular broker or data vendor?\u003c\/strong\u003e\u003cbr\u003eNo. All vendor-specific code has been removed. You supply the market data and order execution.\u003c\/p\u003e\n  \u003cp\u003e\u003cstrong\u003eCan I paper-trade this?\u003c\/strong\u003e\u003cbr\u003eYes. Replace the placeholder order methods with a simulated fill engine. We strongly recommend paper trading for a long period before using real money.\u003c\/p\u003e\n  \u003cp\u003e\u003cstrong\u003eWhich contract does it trade?\u003c\/strong\u003e\u003cbr\u003eThe code is set up for the June 2026 MES contract (MESM6), which has expired. Change the \u003ccode\u003eSYMBOL\u003c\/code\u003e setting to the current front-month contract (for example, MESZ6) and roll it each quarter.\u003c\/p\u003e\n  \u003cp\u003e\u003cstrong\u003eCan I use it on other instruments?\u003c\/strong\u003e\u003cbr\u003eYes. Change \u003ccode\u003eSYMBOL\u003c\/code\u003e and recalibrate the settings block (tick size, point value, ATR multipliers and risk limits) for the new market.\u003c\/p\u003e\n  \u003cp\u003e\u003cstrong\u003eIs this a guaranteed or proven profitable system?\u003c\/strong\u003e\u003cbr\u003eNo. This is educational source code. The backtest is hypothetical and based on a very small number of trades.\u003c\/p\u003e\n\n  \u003c!-- DISCLAIMER --\u003e\n  \u003ch3 style=\"font-size:20px;border-bottom:2px solid #e5e7eb;padding-bottom:6px;\"\u003eRisk Disclaimer\u003c\/h3\u003e\n  \u003cp style=\"font-size:13px;color:#4b5563;\"\u003eThis software is for \u003cstrong\u003eeducational purposes only\u003c\/strong\u003e and is not investment advice or a recommendation to buy or sell any security or futures contract. Futures trading involves substantial risk of loss and is not suitable for every investor. You can lose more than your initial investment. Past performance, whether actual or hypothetical, does not guarantee future results. Consult a qualified financial professional before trading real money.\u003c\/p\u003e\n  \u003cp style=\"font-size:12px;color:#6b7280;text-transform:uppercase;\"\u003eHypothetical or simulated performance results have certain limitations. Unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not been executed, the results may have under- or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown.\u003c\/p\u003e\n\n\u003c\/div\u003e\n","brand":"HFTCODE.COM","offers":[{"title":"Default Title","offer_id":67589789679925,"sku":null,"price":19.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0967\/8549\/8421\/files\/bot_mes_short_momentum_thumbnail_1.jpg?v=1790615272","url":"https:\/\/hftcode.com\/products\/micro-s-p-500-short-momentum-python-futures-strategy-source-code-mes","provider":"HFTCODE.COM","version":"1.0","type":"link"}