Futures Strategy Development and Testing

@arwamoizds

Hey, I can help research, develop, and rigorously test systematic strategies for interest rate futures, with the focus on finding robust approaches that can meet prop-firm objectives without relying on overfitted backtests. I’ll investigate trend-following, mean-reversion, and relative-value/arbitrage ideas and evaluate them across different market regimes. My process would include clean historical data preparation, rule-based strategy development, in-sample/out-of-sample testing, walk-forward analysis, and forward testing before considering any strategy viable. I’ll pay particular attention to drawdown, daily loss limits, volatility, profit factor, expectancy, Sharpe/Sortino, trade frequency, slippage, commissions, and consistency with the specific prop-firm rules. I’ll also stress-test parameters and assumptions to identify strategies that look good historically but fail under realistic conditions. You’ll receive clearly documented strategy rules, backtest results, forward-test performance, risk metrics, equity curves, trade statistics, and recommendations for further refinement. I understand that no strategy can guarantee prop-firm approval or payouts, so the goal will be to identify statistically robust candidates rather than promise unrealistic returns. Your satisfaction is my guarantee! Just message me & consider your project is done. Thanks.

@Hubready

Hello!, I am a US-based senior software engineer and I’d be glad to help you identify, backtest, and forward test futures strategies the right way, not just throw ideas at a chart. The main challenge here is separating “looks good in hindsight” from something that can actually survive live trading. I work in a practical sequence: 1. Define the market, timeframe, and rules clearly 2. Build a repeatable backtest with fees, slippage, and risk controls 3. Review drawdown, win rate, expectancy, and regime behavior 4. Forward test in paper trading before any real capital is used I’ve built trading systems and data tools where precision matters, so I pay close attention to the details that usually get missed. If your goal is to find a real edge and avoid overfitting, I can help you do that with a disciplined process. Could you please clarify the following questions to help me better understand the project? 1. Which futures markets and timeframes should I focus on first? 2. Do you already have strategy rules, or should I research and generate candidates from scratch? 3. What data source or platform do you want used for backtesting and forward testing? Relevant work examples: - TradePulse Analyzer - NorthBridge Futures Dashboard - QuantGrid Research Tool - ApexSignal Backtest Suite If you want, I can start by narrowing the universe to the best strategy candidates and validating them properly. My name is James Zappi.

@mayr81

Interest rate futures are highly structured, so the strategy needs disciplined hypothesis-testing, not guesswork. I will develop trend-following, mean-reversion, and (where appropriate) relative-value/arbitrage candidates, then run rigorous backtests with realistic execution assumptions (roll effects, costs, slippage, liquidity constraints) and strict walk-forward/forward testing to measure stability beyond in-sample noise. Deliverables include comprehensive performance reporting: signal diagnostics, hit-rate and drawdown analysis, regime breakdowns, sensitivity to parameters, robustness checks, and scenario stress tests aligned with prop-firm risk constraints. The end result is a strategy package designed to survive scaling, evaluation, and payout conditions, clear, auditable, and performance-focused.

@Aaleen110

The constraint here is the interest rate futures market, so I will focus entirely on that. I'll build the strategies from scratch using Python, leveraging libraries like Pandas for data manipulation and NumPy for calculations. For backtesting, I'll use a custom-built engine that handles order execution logic accurately, which is better than off-the-shelf software for the specific nuances of futures roll-over and contract expiry that matter for passing prop firms. This custom engine ensures the backtest truly reflects how a strategy would perform in live trading, so it gets you closer to actual payouts. I will also implement forward testing on a live, simulated feed. Performance reports will be generated using Matplotlib for visualizations of equity curves, drawdowns, and trade statistics, also outputting raw data in CSV for further Data Analysis. Preferred Freelancer here, 5.0 over 10 reviews, no missed deadline and nothing over an agreed price yet. What specific data feed will you be using for both backtesting and forward testing? I need the data feed details before I can proceed.

@PINESCRIPTERR

Hi, I can research and evaluate systematic strategies for interest-rate futures across trend-following, mean-reversion, relative-value, and spread structures. The process will use clean continuous-contract data, realistic rolls, commissions, slippage, bid/ask spreads, margin, session rules, and contract specifications. Results will include walk-forward testing, out-of-sample validation, Monte Carlo analysis, parameter-stability checks, drawdown behaviour, and performance by market regime. Reports will cover returns, Sharpe/Sortino ratios, profit factor, maximum drawdown, exposure, trade distribution, execution sensitivity, and compliance with the selected prop firm’s daily-loss and trailing-drawdown rules. No strategy can guarantee profitability or prop-firm payouts, so robustness and risk containment will be prioritised over optimised headline returns. Three technical questions: 1. Which contracts should be tested—SOFR, U.S. Treasuries, Euribor, SONIA, or others? 2. Which prop firms, account rules, holding restrictions, and data feeds apply? 3. What execution platform and maximum acceptable drawdown should the strategies target? Best regards, Houssame

@mdabdullahallm5

Hi, I can research and develop systematic strategies for interest rate futures across trend following, mean reversion, and arbitrage, with a strong focus on robustness rather than curve-fitting. I’ll backtest across quality historical data, perform walk-forward and out-of-sample validation, then forward-test the strongest candidates under prop-firm-style risk constraints. You’ll receive detailed performance reports covering returns, drawdown, win rate, profit factor, stability, and risk metrics to identify strategies with realistic payout potential.

@prashanpatel557

Hello, I can help develop and rigorously evaluate futures trading strategies for interest rate futures, with a strong focus on realistic risk management and prop-firm evaluation requirements. My approach would include: - Researching and developing rule-based trend-following and mean-reversion strategies - Evaluating whether suitable arbitrage opportunities can realistically be tested with the available data and execution infrastructure - Building robust backtests using realistic commissions, slippage, and trading constraints - Performing out-of-sample and forward testing to reduce overfitting - Analysing key metrics including profit factor, expectancy, win rate, maximum drawdown, Sharpe ratio, and consistency - Applying prop-firm risk constraints such as daily loss limits and drawdown rules - Providing detailed performance reports and clear documentation I have experience developing Python-based trading systems, backtesting frameworks, technical strategies, market-data analysis, and automated trading workflows. I will focus on finding statistically robust strategies rather than promising guaranteed profits or payouts. The final result should provide an honest assessment of which approaches deserve further live or simulated testing.

@prabhathk5

Hello, I’m very interested in your project. I actually already have a **promising trading strategy** that I have developed and tested, and I believe it could be relevant to your objective of passing prop-firm evaluations and achieving consistent payouts. Rather than starting completely from scratch, I would like to **discuss the strategy with you**, explain the core concept, testing results, risk-management approach, and how it could potentially be adapted specifically for interest-rate futures and prop-firm requirements. If you’re interested, I’d be happy to discuss the strategy with you and explore whether it fits your objectives. Looking forward to hearing from you.

@Algokage

Hello, I hope you're doing well. I am an experienced futures trading and strategy development professional with a strong background in interest rate futures and a proven track record in developing and testing trading strategies. I have successfully delivered projects that have achieved high performance and profitability, including trend following, mean reversion, and arbitrage strategies. I am proficient in trading platforms and backtesting software, and I can analyze and interpret market data effectively. I deliver clean, well-documented code and provide comprehensive performance reports. If you are interested in discussing this project further, please send a message, and I will be happy to share relevant samples or a quick demo. Thanks, Adegoke M.

@richard031596

You need systematic futures strategies that can be objectively backtested and forward tested across trend following, mean reversion, and arbitrage, with performance measured against realistic trading conditions. I can build the research and testing framework in Python, including historical data processing, strategy logic, parameter testing, walk-forward validation, and detailed performance analysis. My background includes Python development, statistical analysis, data processing, algorithmic workflows, and data visualization, which fits the technical side of systematic strategy research. I would focus on avoiding overfitting and reporting results such as drawdown, Sharpe, win rate, expectancy, and out-of-sample performance rather than optimizing only for historical returns. Which interest-rate futures and historical data source do you want to use for the initial testing?

@huonghy89

Hi, I hope you are doing well. Very happy to bid your project because my skills are fitted in your project. I have strong experience developing quantitative futures trading strategies using Python, including trend-following, mean-reversion, and statistical/arbitrage approaches. I am experienced with historical market data, backtesting, walk-forward validation, risk management, performance analysis, and avoiding overfitting when developing systematic strategies. I will research and develop strategies specifically for interest rate futures, with particular attention to prop-firm drawdown and risk constraints. I will perform rigorous backtests and forward/walk-forward tests using realistic commissions, slippage, position sizing, and out-of-sample data. I will provide comprehensive reports covering P&L, win rate, profit factor, Sharpe ratio, maximum drawdown, trade distribution, robustness, and the strategy rules/code required for implementation. If you send the message, we can discuss the project more. Thanks.

@CauaAlves

Developing and validating quantitative strategies to pass and sustain prop firm evaluations in interest rate futures (ZN, ZF, ZB, SOFR) requires strict drawdown control, statistical expectancy, and zero data snooping bias. Quantitative Framework: 1. Strategy Architectures: - Trend Following: Adaptive breakout and regime-filtered momentum structures designed to capture yield curve shifts while limiting whipsaw losses. - Mean Reversion: Statistical micro-structure reversion (VWAP/order-flow band deviations) calibrated with time-based stops to protect daily drawdown limits. - Statistical Arbitrage: Inter-commodity spread and curve slope models targeting relative value divergence. 2. Rigorous Backtesting & Slippage Modeling: - Event-driven backtesting factoring tick sizes, exchange fees, and conservative slippage across economic releases. - Walk-Forward Optimization (WFO) and Monte Carlo permutations (1,000+ runs) to verify parameter stability. 3. Prop Firm Compliance Engineering: - Algorithmic position sizing structured around trailing maximum drawdown, daily loss limits, and consistency rules. 4. Deliverables: - Modular source code (Python / Pine Script / NinjaTrader), clean parameter dictionaries, and a performance report detailing Sharpe, Sortino, Profit Factor, and Maximum Drawdown. Ready to discuss your target contracts and preferred platform in chat.

@HamparProd

The important part here is not finding the prettiest backtest, but finding strategies that remain viable after transaction costs, out-of-sample testing and the actual drawdown rules of the target prop firm. My background includes systematic trading, backtesting, Python/data analysis and automated trading workflows. I would test trend-following, mean-reversion and relative-value ideas separately, then reject strategies that depend on narrow parameter choices or unrealistic fills. I’ll model commissions/slippage, use out-of-sample and walk-forward validation, analyse drawdowns and then test the strongest candidates against the exact prop-firm limits such as daily loss, trailing drawdown and consistency requirements. I cannot guarantee profitability or a payout, but I can deliver a reproducible research process and identify which strategies have evidence worth forward testing. I can start immediately after award.

@venplura

I've built systematic strategies for interest rate futures with a focus on what actually works in live markets - trend following, mean reversion, and the occasional arbitrage setup. The prop firm pass requirement is clear, so backtesting rigor and forward testing discipline matter more than optimizing backwards. I'd start by mapping your edge across different rate environments, then backtest on clean data with realistic slippage and commissions baked in. The forward test phase is where most strategies break, so I'd prioritize robustness over curve-fit returns. Past work includes developing yield curve strategies that survived the 2022 volatility spike and consistently beat benchmark thresholds. If you want to dig into specifics - data sources, walk-forward methodology, or what timeframes tend to hold up best - let's talk it through. Corné

@bizvivo

I am a seasoned trading software developer, data scientist, and full stack engineer with 20+ years of combined experience delivering enterprise grade solutions. I specialize in automated trading bots, having built systems around RSI, MA, MACD, Bollinger Bands, harmonic and Fibonacci strategies. Recent projects include: • AI driven equity day trading bot with real time L1/L2 data ingestion and risk controls. • Options straddle/strangle manager with dynamic hedging and margin optimized basket orders. • Multi asset scalping bot tuned for ultra low latency execution. • Portfolio rebalancer integrating ML forecasts with smart order routing. • Backtest engine validating strategies against years of minute level data. I have recently deployed a machine learning algorithm for predictive trading, combining advanced research with robust live execution. Looking forward to discussing how we can tailor this expertise to your needs. Best Regards, Radhika

@Lincolnwhiz

Over the years, I have honed skills that are germane to this project: from automating complex processes, performing rigorous data modeling with platforms like Power Query, to developing and backtesting strategies using VBA macros and backtesting software. I've turned lengthy hours of work into single-click solutions - what might take days manually can be done within seconds with my custom-architected systems. Hire me, and together we'll design algorithms ranging from trend following to mean reversion and arbitrage strategies —all with unparalleled precision. One thing I can assure you is that my commitment extends beyond delivering a well-performing strategy; it also incorporates fostering clear communication channels and guaranteeing fast turnaround times. Your success is my top priority, and I look forward to turning your vision into profitable reality. Let's reconnect you with time, efficiency and strong investment returns. Click "Hire Me"

@modesorehari6

Hello! I have experience building data-driven platforms, financial analysis tools, and algorithmic systems using Python, statistical analysis, backtesting frameworks, and market data processing. I understand trading strategy development and can help test and improve futures strategies. I will analyse market data, develop trend following, mean reversion, and arbitrage strategies, then backtest and forward test them with detailed performance reports, risk analysis, and optimisation. I will focus on realistic strategies suitable for prop firm challenges, including drawdown control, consistency, and payout-focused performance evaluation. Timeline: 3 weeks I can start immediately as I am available now. I respect your trading approach and suggestions, and I am interested in building a long-term working relationship to continuously improve the strategies. Thanks

@tahasohail763

Hi, I can help develop a reproducible research and testing workflow for your interest rate futures strategies, with the target prop firm's risk and trading rules built into the evaluation. My proposed approach is to define trend-following, mean-reversion, and spread/arbitrage candidates; backtest them with commissions, slippage, and contract rollover handling; then evaluate shortlisted strategies on out-of-sample data before an initial paper-trading forward test. Deliverables will include strategy rules and code, trade logs, equity and drawdown charts, and a comparative report covering net performance, profit factor, risk-adjusted returns, and breaches of the agreed prop-firm limits. Arbitrage candidates will also be assessed for execution feasibility. My $500 / 30-day bid covers an initial research and validation cycle using your agreed platform and available data, including the forward-test observations collected during that period. Longer forward monitoring can be scoped separately. Profitability, challenge passes, and payouts cannot be guaranteed. Which contracts, trading platform, data source, and prop firm are you targeting? This will help finalize the test scope before work begins. Best regards, Muhammad

@Microlent

Hello, I am Dr. Rajesh Rolen, PhD in Computer Science & Engineering, with experience of over 20+ years in Data Visualization As a preferred freelancer in the top 1%, I have done 400+ projects here on freelancer.com, I have 4.9 ratings out of 5 on average, which showcases my quality of work and timely delivery. Key Highlights: - Free Hosting Support on the Cloud or any desired platform. - Free 3 months of post-delivery support to ensure that our client doesn’t face any challenges after the launch of the project. - Free Dedicated tester on projects to ensure quality delivery, so clients don’t need to act as a tester. - 10+ Years experience UI/UX team to ensure intuitive UI. Portfolio: https://www.freelancer.com/u/Microlent Please open the chat and send me a message, so we can have a more detailed discussion about the project to give you the project timeline and cost. Thank you for considering my services. I look forward to engaging in a productive conversation and understanding how I can be of assistance in bringing your project to life. Regards Rajesh Rolen