Swing Strategy Backtest & Automation

@softsolution2000

I have extensive experience in C Programming, Software Architecture, Data Visualization, and Pandas, making me a great match for the "Swing Strategy Backtest & Automation" project. Once we discuss the full scope, we can adjust the budget accordingly. I am confident and eager to start this project, ensuring it is done efficiently within your budget. Please review my 15-year-old profile to see my work history. Your satisfaction is my priority, and I am ready to showcase my commitment by starting work before being hired. Looking forward to hearing from you.

@Feriver

Hello, I understand you’re looking for a disciplined, end-to-end validation of a rules-based swing trading strategy before committing real capital. I can recreate your strategy logic precisely in Python and run a transparent, data-driven backtest using robust historical market data. The focus will be on objective performance evaluation, including equity curve analysis, maximum drawdown, Sharpe ratio, win/loss distribution, expectancy, and additional risk metrics that highlight strengths and weaknesses under different market conditions. The implementation will be clean, modular, and fully commented, making the logic easy to audit and extend. Results will be delivered in a clear backtest report or notebook that documents assumptions, parameters, and data sources so the findings are defensible. Once the strategy proves itself statistically, the same validated codebase will be adapted into a live automation module integrated with Interactive Brokers using a stable API approach such as ib_insync. The system will publish real-time signals and PnL outputs suitable for monitoring alongside your existing charting setup, with clear instructions for local or VPS deployment. Thanks, Asif

@Muhammadzeesha59

Hello Sir/MAM I am a skilled full stack developer. Having rich experience in Java , C++ , C , C# , Python , Eclipse , Sql , Mysql , .Net ,Oracle , Object Oriented Programming , Data Structure , Algorithms . I have a perfect grip on “Artificial Intelligence” “Automation” , and work in “Machine Learning” Deep Learning ”. My track record as demonstrated in my 100% job completion and 5-star review rating showcases My ability to deliver exceptional results on time and with utmost quality I believe that my skill set makes me the ideal candidate for this project Please come on chat we will discuss more about this I will be waiting for your reply . Thanks and Best Regards

@ducthodg

As an experienced trader and expert in designing and implementing trading algorithms, I am confident that I can be invaluable for your swing strategy backtest and automation needs. With over a decade of experience writing Expert Advisors and Indicators in MQL for MT4 and MT5, my skill set aligns perfectly with your project requirements. To start, I'll reconstruct your swing strategy's logic flawlessly in Python. Using reliable historical data, I’ll conduct meticulous backtests and provide a comprehensive report showcasing the equity curve, maximum drawdown, Sharpe ratio, win-rate, and any other metrics you deem significant. For phase two, I'll turn the meticulously crafted code into an efficient automated system that will integrate seamlessly with Interactive Brokers via the IB API (ib_insync). Real-time signals and PnL data for your usual charting environment are also non-negotiables that I will implement without fail. Remember that on top of my exceptional programming abilities, my background as an Industrial Engineer ensures a thorough approach to detail.

@mobimubasir

Hello. I read your requirement i will do that. Please come on chat we will discuss more about this. I will waiting your reply

@aktarujjamana7

I will recreate your swing strategy in Python on QuantConnect, run robust historical back‑tests, and deliver a clean script plus a comprehensive performance report with equity curve, drawdown, Sharpe, and win‑rate. I’ll also provide an Interactive Brokers automation module with deployment instructions and confirm functionality in a walkthrough, ensuring the strategy proves itself before live trading.

@abhisaini0188

As an abundant backend and AI/ML developer, I offer not only the coding expertise required for this project but also a comprehensive understanding of trading strategies. Having deep practical experience with pandas, backtrader, zipline Quant Connect platform , and live code deployment through IBKR, I am well-prepared to not only recreate and automate your swing strategy but provide you with robust and objective performance metrics. My decade-long successful journey as a Senior Developer has armed me with skills in software architecture and data visualization- crucial components to deliver a fully-documented, clean, and efficient Python script replicating your strategy. Additionally, my proficiency with Quant Connect platform will ensure you receive the high standard results you expect from this project. I maintain clear lines of communication with my clients from inception to delivery, and I am intent on giving you an automation module finely tuned to Interactive Brokers’ specifications. My approach is not just about developing great software— it is about creating strategic solutions tailored to fit my clients' needs. You can be confident that by choosing me for this project, your strategy will undergo rigorous and systematic evaluation resulting in a reliable tool for your trading endeavors. With Regards! Abhi

@maximg10

⭐Hi, I’m ready to assist you right away!⭐ I believe I’d be a great fit for your project since I have strong experience in Python backtesting and live trading automation with Interactive Brokers. I understand the importance of proving your strategy’s robustness before risking capital. I’m confident I can deliver clean, well-commented code that backtests your swing strategy with clear metrics like equity curve, max drawdown, Sharpe ratio, and win rate. I have hands-on experience with pandas and backtrader, and I've automated trading bots using the IB API, ensuring seamless live execution and real-time signal outputs you can monitor alongside your charts. This project will solve your need for transparent strategy validation and smooth transitioning to live trading, giving you confidence in your bot’s performance. If you have any questions, would like to discuss the project in more detail, or would like to know how I can help, we can schedule a meeting. Thank you. Maxim

@mohjib092

I can deliver this cleanly, efficiently, and on time, with clear communication and practical execution. Ready to start immediately. Let’s move forward.

@juanjosec63

Hello, I’m excited about the opportunity to help you back-test your rules-based swing strategy and provide clear metrics before you deploy it live. With experience in Python, **QuantConnect**, and trading automation, I can recreate the strategy logic and back-test it using robust historical data to ensure it’s ready for real-world deployment. I’ll provide a clean and well-commented **Python script** for the strategy, back-test it over historical data, and deliver a comprehensive report that includes metrics like the equity curve, max drawdown, Sharpe ratio, win rate, and additional insights. I will also build an automation module connected to **Interactive Brokers**, providing detailed instructions for running it locally or on a VPS. Once the back-test is complete, I’ll schedule a short call or video walkthrough to ensure everything compiles, connects, and works as expected. Looking forward to getting started on this! Best regards, Juan

@durgesh8527

With over 12 years of experience as a full-stack software engineer, my passion for building and scaling technology products runs deep. Your Swing Strategy Backtest & Automation project speaks directly to my areas of expertise. While my listed skills Prewritten aren't an exact match for this specific project, I've got solid experience with Python and vast exposure working within complex software frameworks which parallel Quant Connect and Interactive Brokers. For instance, my hands-on experience in Django (Python) is reminiscent of the scope and complexity that your project warrants. Moreover, I pride myself on translating clients' needs into concrete deliverables, exactly what you need from the Clean, well-commented Python script of the strategy and Comprehensive back-test report to an Automation module wired to Interactive Brokers. My proficiency in data handling using Pandas is indisputable. Since past performance analyses are pivotal to this project, my strong background in financial trading and live code deployments using IBKR perfectly sets me up for success here.

@phpxpert89

Hello Cynan D., I checked your project, and it looks interesting. This is something we already work on, so the requirements are clear from the start. We mainly work on C Programming, Software Architecture, Data Visualization, Pandas We focus on making things simple, reliable, and actually useful in real life not overcomplicated stuff. Let’s connect in chat and see if we’re a good fit for this. Best Regards, Ali nawaz

@MohmedAbdelwahab

Hi there, With extensive experience in Python trading frameworks including QuantConnect, Backtrader, and direct integration with Interactive Brokers (IBKR), I am confident in delivering a robust, well-documented swing strategy backtest. I will recreate your rules-based logic, conduct a thorough historical backtest, and present detailed performance metrics such as equity curve, max drawdown, Sharpe ratio, and win-rate. I will also develop a seamless automation module wired to IBKR, with clear instructions for local or VPS deployment, followed by a comprehensive walkthrough to ensure smooth operation. Examples of live deployments can be shared upon request. Best Regards MohmedAbdelwahab

@dorians2

Hi there, I have 7+ years of experience in Data Visualization, Pandas, Software Architecture and can deliver a clean, reliable solution for your project. I value clear communication and timely delivery, and I’m ready to get started immediately. Let’s connect and discuss your goals. Best regards, Dorian

@ivank69

Hi there Will the full strategy rules be provided in exact terms, entry, exit, position sizing, and filters, and which markets and timeframe should be tested first? For automation, do you want this executed inside QuantConnect live trading with IBKR, or a standalone Python bot using IBKR API, and what order type and risk limits are required? This can be done in two steps: first recreate the logic and run a clean, objective backtest on reliable historical data with equity curve, drawdown, Sharpe, win rate, and sensitivity checks. After it proves out, connect the same logic to IBKR with a small execution layer, logging, and a safe paper trading mode before any real orders. A similar swing system was audited where the risk was overfitting and unrealistic fills. The weak spots were data quality, slippage assumptions, and hidden lookahead bias. That was solved by using clean data, adding realistic commissions and slippage, running out of sample and walk forward tests, then adding strict risk controls and a kill switch in the IBKR layer. Strong fit for this work with QuantConnect, Python backtesting, and IBKR automation done carefully. Ready to start immediately and produce a backtest report first, then wire the automation once metrics look solid.

@emmanuelv0826

Hi I’ve recreated swing strategies in Python, backtested them with pandas and backtrader, then connected the same logic to Interactive Brokers using ib_insync for live trading. Which market and timeframe is the strategy built for? Do you already have historical data sources in mind, or should I supply them? Thank you, Emmanuel

@Coredev794

Hi Cynan, We went through your project description and it seems like our team is a great fit for this job. We are an expert team which have many years of experience on C Programming, Software Architecture, Data Visualization, Pandas Please come over chat and discuss your requirement in a detailed way. Thank You

@omarz33

Hello, I'm excited to tackle your Swing Strategy Backtest & Automation project. I understand the importance of proving the strategy's historical performance before automating it. Here's how I can help: - Recreate your swing strategy logic in Python for accurate backtesting - Provide detailed metrics such as equity curve, max drawdown, Sharpe ratio, and more - Develop an automated system integrated with Interactive Brokers API for live trading - Ensure real-time signal outputs and PnL tracking on your preferred charting platform With experience in pandas and backtrader, I've successfully deployed strategies through IBKR. Let's discuss how I can bring your strategy to life effectively. Looking forward to further discussions.

@milosm25

Hi — this is exactly the right way to approach automation: prove the edge first, then scale it. I’ll start by recreating your rules-based swing strategy in Python, keeping the logic transparent and well-commented. Using robust historical data, I’ll run a proper back-test (pandas + backtrader or similar) and produce an objective report including equity curve, max drawdown, Sharpe, win rate, expectancy, exposure, and trade distribution. Assumptions, parameters, and data sources will be clearly documented so you can trust the results. Once the performance is validated, I’ll extend the same codebase into a live trading module using ib_insync for Interactive Brokers. Orders, position sizing, risk controls, and error handling will be production-safe. The bot will also emit real-time signals, PnL, and state so you can view them alongside your existing charting setup (via logs, files, or lightweight dashboard). Deliverables Clean, modular Python strategy + back-test code Jupyter/PDF back-test report with metrics and insights IBKR automation module with local/VPS launch instructions Short walkthrough call or Loom to verify connection and execution I’ve worked extensively with pandas, backtrader-style frameworks, and live IBKR deployments. Let’s validate the edge on paper first—then let the bot trade with confidence.