Index Futures Strategy Backtesting

@AbhyudayaCodes

Hi, Warm Greetings ! First of all, kudos for the truly different kind of innovative project idea. We are a team of expert algo trading systems developers, having vast experience in algo trading field, mainly using Python. We have built the following types of algos: > NSE/MCX/NYSE/Nasdaq Markets > Algos trading F&O, stocks, cryptos & commodities > Indicator/price movement based algos > Multi client systems > Systems with Spreads, Straddles, Iron Flys, Heikin Ashi, Renko, etc. > Algos having extremely complicated logic and signal generation procedures > Have built custom indicators and timeframes > Brokers like IBKR/Oanda/Alpaca/Tastytrade/TOS, Binance/, Zerodha/Fyers/Upstox/Finvasia/XTS, and many more ... > US Backtesters and Stock Screeners The features we provide: > Multiple Instance dashboard > Orderbook and logs for tracking > User friendly UI to manage everything > Emergency Safety buttons > Detailed statistics of the algo as per logic > Paper trading as well as Live trading > Editable input boxes for modifiable parameters The project has many different parts, and the complexity level is also high, but considering our skill set and experience, we think we will be a perfect fit for your project. We will handle the complete process from development and testing till deployment. We focus on delivering quality to our clients, keeping in mind safety, security, aesthetics, scalability. Looking forward to working with you ... Message me to discuss further

@prashanpatel557

Hello, I can help you rigorously backtest your index futures strategy and deliver a fully reproducible framework with detailed performance analytics and validation reports. I have experience building Python-based backtesting systems for futures, options, and equity strategies using Pandas, NumPy, and custom trading engines. What I will deliver: • Accurate implementation of your entry, exit, and position-sizing rules • Clean, well-documented Python code • Reproducible backtest runnable with a single command • Performance metrics including: * Total Return * CAGR / Annualized Return * Maximum Drawdown * Sharpe Ratio * Win Rate * Profit Factor * Average Trade Statistics * Equity curve and drawdown charts * Trade-by-trade logs for validation * Summary report highlighting strengths, weaknesses, and assumptions Validation Process: • Verify results against your sample trades • Include slippage and brokerage assumptions if required • Test across multiple market conditions and periods Deliverables: • Python source code • Backtest report (PDF/Excel) • Equity curve visualisation • Setup and execution guide Timeline: 7–10 days, depending on strategy complexity and data quality. Please share the strategy rules and historical data source, and I can start immediately.

@mahads31

As an experienced web and software developer with extensive proficiency in Python, numpy, pandas and other tools vital for effective futures backtesting, I am your perfect partner for this project. My speciality lies in transforming complex requirements like yours into clear, robust and efficient digital systems producing real business value. I completely understand the importance of rigorous and accurate backtesting in validating trading strategies. My strong analytical mindset combined with my experience dealing with data-driven problems ensures meticulous adherence to your entry, exit and position-sizing rules to replicate your strategy accurately. As desired, I will provide you with clear performance statistics including total and annualized returns, max drawdown, Sharpe ratio, win-rate. Additionally, I will accompany these results with an easy-to-understand equity curve chart critically analyzed summary to highlight the strategy's viability. My dedication to innovation-first thinking aligns well with your project requirement - building a python code that's clean, well-structured yet powerful to perform tasks at hand. Moreover, having worked across diverse industries and international clients, my approach is client-centered thriving on understanding your business goals to ensure your unique needs are met in a way that exceeds expectations.

@Algokage

Hello, I can efficiently backtest your index-futures trading strategy using Python with Pandas/NumPy, ensuring accurate replication of your rules and clear performance metrics. I’ll deliver well-structured, reproducible code, detailed statistics, and an equity-curve chart with a concise viability summary. With 5+ years of experience in backtesting futures systems, I’ll meet your acceptance criteria, including spot-check verification and transparent assumptions. Send a message to discuss further or see samples of similar projects. Thanks, Adegoke. M

@nsinfosoftwebapp

Hello, Full Stack Web Developer with 8+ years of experience in Python, Laravel, CodeIgniter, Core PHP, Node JS, React JS, MySQL, API Integration, and Web Application Development. I have successfully developed and maintained: - E-commerce Websites - Custom Admin Panels - Inventory Management Systems - Booking Systems - CRM/ERP Solutions - API Integrations - Responsive Websites I can complete your project with: - Clean and scalable code - Mobile responsive design - Fast performance optimization - Secure development standards - Proper testing and support Why choose me? - 8+ years experience - Quick communication - On-time delivery - Long-term support - Professional development approach I am available to start immediately and would be happy to discuss your project requirements in detail. Looking forward to working with you.

@Sahyadri96

Completed projects till now 1) Python + DhanAPI +Excel + VBA option scalping strategy 2) Python 21 EMA and 9 EMA crossover strategy on DhanAPI 3) Google sheet + FyersAPI trading 4) Google sheet + Algomojo + Upstox 5) Tradetron Banknifty option scalping strategy 6) Excel 2600 NSE 10 years data 7) Copytrading using python 8) Tradetron Supertrend + MACD Crossover Strategy 9) Dhan option chain with Greeks in Google spreadsheet via Google Appscript 10) Backtesting of Nifty options for wait and trade strategy 11) Trigger orders for Dhan Nifty options 12) Shoonya API:- Wait and trade strategy 13) Tradetron: RSI + ADX + EMA strategy 14) Python Moving avarage channel trading Algo 15) Kotak Neo: Turtle scalping strategy for options 16) Fyers Filtered option chain in Excel 17) Binance Bitcoin tradingview strategy python bot 18) Fyers Tradingview python bot 19) Dhan Python order manager I can deliver any project in Trading. Readymade setups for Python available

@ziedb4

Hi, ​Your request for a highly accurate index futures backtest matches my exact background in engineering algorithmic trading logic and statistical modeling. I utilize MetaTrader 5 (MT5) integrated natively with Python (Pandas, NumPy) to extract top-tier historical data and run precise quantitative simulations. ​How I meet your Acceptance Criteria: ​Single-Script Reproducibility: I will deliver a clean, well-commented Python pipeline. You will be able to run a single script to completely reproduce the results, plots, and metrics locally. ​Exact Calculation Matching: Your entry/exit constraints and position sizing will be hard-coded and rigorously double-checked against your spot examples to eliminate any data look-ahead bias. ​Key Performance Metrics: The final automated report will calculate your exact total/annualised returns, maximum drawdown, win-rate, and Sharpe ratio across multiple market cycles. ​Ready to review your link to the historical files or plug in my live MT5 data feeds to benchmark your system today. Let's chat!

@Marwan328

Hi, I can build a clean, fully reproducible Python backtesting script using Pandas and NumPy that replicates your entry, exit, and position-sizing rules exactly. I'll deliver all required performance metrics — annualised return, max drawdown, Sharpe ratio, and win rate — along with an equity curve chart and a concise viability summary. Everything will run from a single script on your side. Please share the strategy rules and historical data link so I can begin immediately. Ready to deliver within 2 days Max.

@RKhakhula

Hi There, I can develop a rigorous, fully reproducible back-testing framework for your index-futures trading strategy to verify its viability across multiple market cycles. With a master degree in economic cybernetics and extensive commercial experience as a senior data analyst, I have a deep background in statistical analysis, mathematical modeling, and processing large financial datasets. My technical expertise includes writing clean, optimized Python scripts using Pandas and NumPy to handle complex numerical calculations, alongside experience building predictive machine learning models in frameworks like TensorFlow and Keras. For your project, I will build a lightweight, vectorised back-testing engine that perfectly replicates your entry, exit, and position-sizing rules without look-ahead bias. The single-script deliverable will generate your required equity-curve chart and compute critical performance metrics, including annualized return, maximum drawdown, Sharpe ratio, and win-rate. I will also deliver a concise summary report highlighting all methodological assumptions and validation checks against your sample trades. Let's contact to discuss details. Solution Vector Roman Khakhula

@Vasylm21

✅✅Hello.✅✅ I have read your project description more detail. As a Senior full-stack developer with over 5 years of experience, I have built rigorous Python backtesting systems for futures and equity strategies using Pandas and NumPy — delivering full performance reports with equity curves, Sharpe ratios, max drawdown, and win-rate analysis across multiple market cycles. I prioritize quality over price. I also wish to negotiate the price during our conversation. Guaranteed on-time delivery & 100% satisfaction! I'll deliver a single reproducible Python script that replicates your exact entry, exit, and sizing rules, with a clean performance report and honest viability assessment so you can make a confident decision before committing real capital. I would like to discuss the assignment in our conversation. Thank you for your time. If you don't mind, please reach out me. Best regards.

@warrick1718

This aligns perfectly with my skill set. I understand the need for clean, professional, and well-documented code for backtesting your index-futures trading strategy. Ensuring a seamless and accurate replication of trade rules is crucial for determining its viability accurately. While I am new to freelancer, I have tons of experience and have done other projects off-site. My expertise lies in developing Python scripts using Pandas/NumPy for backtesting financial strategies, providing clear performance statistics and insightful equity-curve analysis. I would love to chat more about your project! Regards, Warrick Van Eeden

@florezcamilo411

I believe I'm the perfect fit for your project as an Applied Mathematician and Full-Stack Developer with deep expertise in data analysis, machine learning, and web development using Python. With my skills in Pandas/NumPy, I can code a well-structured, maintainable and clean system that accurately replicates your trading strategy from the ground up. Not only do I have ample experience in back-testing futures systems, but my focus on reproducibility aligns perfectly with your acceptance criteria. Combining my strong mathematical background with the power of Python and its libraries, I am confident in my ability to spot-check each trade example and tally it against the calculated output. Even more so, I understand the utmost importance of clean work that can be rigorously evaluated to match theoretical assumptions to real-world trades. Lastly, as an all-around Full-Stack Developer, I am skilled in building efficient, user-friendly dashboards for performance reporting—Sharpe ratio calculations as well as equity-curve charts—with tools such as Plotly or Datapane at my disposal. To ensure comprehensive understanding, your report will also include a high-level summary elucidating the basic viability of your strategy, clearly identifying any data or methodological assumptions made. Let's get started!

@eldare2

Hi there, I am an experienced Python developer specializing in financial data processing, automation, and backend architectures. I can rigorously back-test your index futures trading strategy using Pandas and NumPy to accurately replicate your entry, exit, and position-sizing rules. I will deliver: - A clean, well-structured, and optimized Python script. - Accurate calculation of key performance metrics: total/annualized return, max drawdown, Sharpe ratio, and win-rate. - Complete evaluation over your historical price files across multiple market cycles. I have solid experience working with complex data logic, API integrations, and deploying systems on AWS. Ready to start immediately and deliver a precise, high-quality solution. Let's discuss the details!

@Sumanravivirat59

Hi, I will backtest your Index Futures strategy using Python, Pandas, and NumPy as per your exact rules. Deliverables: 1. Single reproducible Python script that runs end-to-end 2. Performance Report: Total/Annualized Return, Max Drawdown, Sharpe Ratio, Win-Rate 3. Equity-curve chart using Matplotlib with drawdown highlights 4. PDF summary explaining if strategy passes viability test + key assumptions Process: I will load your historical data, apply entry/exit/position-sizing rules, and verify each trade against your spot-checked examples. Code will be clean, commented, and easy to run on your side. I have strong experience in Pandas for financial data analysis and can deliver in 7 days. Ready to start immediately. Please share the rules and data file. Regards, Suman Lata

@Umidjon08a

​I am a results-driven Data Analyst specializing in Python and SQL. With a strong background in economic and financial analysis, I transform complex datasets into clear, actionable business insights. I focus on process optimization, data visualization, and sustainability metrics. Let's collaborate to unlock the full potential of your data and drive strategic growth!

@shivanim005

I'm Python developer with experience in Pandas, NumPy, data analysis, and strategy automation. I can build a clean and fully reproducible backtesting script that accurately follows your entry/exit and position-sizing rules. What you can expect from me: Clean, well-documented Python code Accurate trade replication using your historical data Performance metrics including CAGR, Sharpe ratio, max drawdown, win rate, etc. Equity curve visualization and concise strategy evaluation report Transparent assumptions and methodology documentation Even though I'm new on Freelancer, I'm serious about delivering high-quality work and maintaining clear communication throughout the project. I focus on writing reliable, easy-to-understand code rather than rushed solutions. I can start immediately and aim to deliver within 7 days after receiving the strategy rules and data files. Looking forward to working with you.

@vyto15

Hello, I will build a reproducible Python backtesting script for your index-futures strategy and produce a clear performance report. Scope: - load and validate your historical price files; - implement your entry, exit, and position-sizing rules exactly as specified; - generate a transparent trade log for every position; - calculate total return, annualised return, max drawdown, Sharpe ratio, win rate, and basic trade statistics; - generate an equity curve chart; - compare the output with your spot-check trade examples; - document assumptions such as fees, slippage, timestamps, contract handling, and data gaps. The result will be runnable on your side with a single script. I will not change or optimize the strategy unless requested. First goal is to test the rules as written and show whether the system passes a basic viability check. Best, Vitalie

@ayuscoder5

Hi, I have strong experience building quantitative backtesting systems in Python using Pandas and NumPy. I can implement your strategy exactly as defined, process your historical futures data, validate every entry/exit rule, position sizing logic, and generate reliable performance reports. You will get clean, well-structured code along with detailed metrics including total return, annualized return, max drawdown, Sharpe ratio, win rate, trade statistics and equity curve analysis. I can also help identify any look-ahead bias or data issues to ensure results are realistic. Ready to review the strategy rules and historical data. Thanks. Contact at (+91) 88264-50850

@FletcherDev

Hi — I can backtest your index-futures strategy and give you a clear, honest read on whether it's worth trading. This is exactly the kind of work I do — I build and backtest systematic trading strategies, so I'm comfortable turning a plain-language rule set into clean, reproducible code and a viability verdict. What I'd deliver: - A single Python script (Pandas/NumPy) that runs your strategy end-to-end on your historical data — fully reproducible. - The metrics that matter: total + annualised return, max drawdown, Sharpe, win-rate, plus an equity-curve chart. - A short, straight viability summary — including if the edge looks marginal, because you want the truth before risking capital. - Trade-by-trade output so you can spot-check it against your example trades and confirm the logic matches. Two questions so the backtest is accurate rather than misleading: - What's the data timeframe — daily or intraday bars — and does the strategy hold overnight or close intraday? - For fills, should I assume execution at the signal bar's close or the next bar's open, and do you want slippage/commissions modelled? (These quietly make or break whether a backtest reflects reality.) Timeline: 1 day from receiving your rules + data files. UK-based and happy to walk you through the results.