Backtesting Jobs

I have a set of annotated screenshots that capture every element of an existing TradingView strategy, but no source code. Your job is to translate those images into a clean, fully functioning Pine Script Strategy that behaves exactly like the original: same plots, same signals, same back-test results. You will receive the screenshots and a brief explanation of the intended logic as soon as we start. I expect: • A single .pinescript file written in Pine v5 • Settings, inputs and plots matching what appears on my charts • Comments in the code so I can follow the logic and tweak parameters later • A short note comparing your back-test metrics to the ones visible in my images to confirm the match Please send me a private message that includes at least one TradingVi...

I need an end-to-end AI trading system that can operate across stocks, cryptocurrencies, and forex while holding a casual, friendly conversation with the user. The bot should ingest real-time market data, analyse it with machine-learning models, place trades automatically, and then explain its logic in plain language. Users must be able to ask questions like “Why did you take that position?” or “What’s the risk right now?” and receive understandable, jargon-light answers. Connectivity The engine has to plug into mainstream exchange APIs—Binance, Coinbase, Kraken—and be architected so additional brokers can be added with minimal code changes. Self-improvement Beyond static strategies, the system should evaluate its own performance, retrain whe...

I’m looking for a rules-based day-trading strategy that can be traded right away on the Indian market—NSE / BSE preferred—yet flexible enough to port to any other liquid instrument. The single non-negotiable requirement is proof: I need to see clear, verifiable results that demonstrate the edge of your system. What I expect from you • The full set of entry, exit, position-sizing and risk-management rules, written so a technically minded trader can follow them without guesswork. • A documented performance record—either a well-structured back-test (minimum one year) plus recent forward-test, or a live brokerage statement—showing consistency under day-trading conditions. • A concise implementation guide. Whether you use TradingView Pine Scri...

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I'm seeking an experienced developer to create a sophisticated stock trading bot for the NYSE and NASDAQ. The bot should effectively implement scalping, day trading, and swing trading strategies. Key Requirements: - The bot must be capable of executing trades on both NYSE and NASDAQ. - It should support multiple trading strategies: scalping, day trading, and swing trading. - The bot needs to be robust, secure, and able to handle high-frequency transactions without lag. -The bot must be capable of trading on any time frame, such as 1 Day, 1 Hour, or 1 Minute. -The bot must be capable of also applying to forex and futures. Ideal Skills and Experience: - Proven experience in developing trading bots, especially for stock markets. - In-depth knowledge of stock trading strategies and mark...

I have a fully tested TradingView strategy written in PineScript that hinges on a Range Filter reading a STOCHASTIC oscillator for the signal using a 1 Second Renko Chart with a specific box size. The logic is straightforward: when the STOCHASTIC indicator delivers a bullish crossover I go long, and when a bearish crossover appears I exit—or reverse, while the Range Filter provides the Buy / Sell signal accordingly. I now need this exact behaviour replicated as an automated NinjaTrader strategy so I can execute it live without manual intervention. What matters most is that the Crossover-Based + Range Filter entry and exit signals fire in NinjaTrader with the same timing and values I see on TradingView. Please port every calculation behind the Range Filter reading from what the STOCH...

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There is a suite of pre-configured Python bots that currently run on cTrader. I now want them fully aligned with my own trading system and expanded in two key areas: • Introduce a robust trend-following strategy that fits the logic and data feeds I already use. • Bolt on solid risk-management controls—hard stop-loss orders, dynamic position sizing, and trailing stops—so every position automatically respects my predefined exposure limits. All code must remain within the cTrader Automate (cAlgo) environment while leveraging Python connectors where necessary. Clean, well-commented modules and a brief “how-to” document for deployment are required once the work is complete. I’m based in Kazan and would strongly prefer a local, English-speaking de...

Project Title: NinjaTrader Footprint Chart – Absorption Detection Indicator Project Description: I’m looking for an experienced NinjaTrader developer to create a custom indicator that automatically detects and marks absorption on a footprint (order flow) chart. The goal is to visually identify areas where aggressive buying/selling is being absorbed by passive liquidity. Key Requirements: Platform: NinjaTrader (NT8 preferred) Work with footprint / order flow data (bid/ask, delta, volume) Detect absorption based on conditions such as: High volume with little price movement Delta divergence (e.g., strong buying but price not moving up) Repeated absorption at key levels (optional but preferred) Automatically plot signals on chart: Mark candles/zones where absorption occurs Optional...

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I trade Nifty-50 index options intraday, lean heavily on price action, EMA levels, IV and the Greeks, and have logged more than four years refining a rules-based approach that already gives me clear entries and exits. Where I want fresh eyes is on the risk side. At the moment every position is protected only with fixed stop-loss orders; I want to know whether the same edge can be kept—or improved—while lowering drawdowns and sharpening my capital deployment. Here is what I need from you: • Review the core of my strategy (I will share the exact rules, data sources and recent trade logs). • Propose and test alternative risk management frameworks—dynamic stops, volatility-adjusted position sizing, tiered exits or anything else you feel would add stability. &...

I have a quantitative strategy that performs well in back-tests and now I’m ready to let it trade live through Interactive Brokers. The goal is to turn every buy-and-sell rule I already have into a fully automated system that opens, manages, and exits positions 24/7 without my manual input. Here is what I need from you: • Connect to the Interactive Brokers API (TWS or Gateway) and translate my entry, exit, and risk-control rules into robust, well-commented code. • Build in position sizing, stop-loss/target logic, and a simple dashboard or log so we can see exactly what the bot is doing in real time. • Provide a short walk-through and a week of post-deployment support to make sure orders are routing and filling correctly. I’m looking for someone who is...

I need a Python-based trading algorithm that trades both the Nifty and Bank Nifty indices. The code should run locally on Python (feel free to lean on pandas, NumPy, TA-Lib, backtrader or similar libraries) and must be able to import and work with historical market data only—no live feed is required for this milestone. Here is what I expect: • A clean, well-commented Python script (or notebook) that ingests historical data, generates trade signals, executes the logic, and outputs detailed performance metrics and an equity curve. • Clear instructions on how to map the code to CSVs or API endpoints I already use for historical NSE data. • A short README explaining any configurable parameters so I can tweak settings for further experiments. Back-testing accuracy, ...

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. Strategie-Setup: NQ/MNQ Orderflow Rejection & Session-Trading (Final) 1. Chart-Einstellungen (Range US Charts) Cash Session (US): Range 0/6/18 London Session: Range 0/4/12 Instrument: Ausschließlich NQ / MNQ. 2. Relevante Level (Points of Interest) Profil-Level: VAH, VAL, PDH, PDL, DH, DL. TPO M30: Tails & Single Prints (Zonen-Logik: Eintauchen und Austreten erforderlich). V-WAPs: Weekly VWAP, Daily VWAP. Open Line: Sonderregel: Nur der First Touch pro Session wird gehandelt. 3. Einstiegsszenarien Szenario A (Fake): Preis taucht ein/bricht aus -> Absorption & Delta Switch -> Entry beim Close der Rückkehr-Kerze. Szenario B (Durchbruch): Mindestens eine Kerze schließt komplett außerhalb -> Retest mit Absorption & Delta Switch -> Entry be...