QuantConnect ETF Trading Bot Development

@AwaisChaudhry

Hello, I’ve reviewed your QuantConnect ETF project and I can turn your detailed playbook into a live-ready, multi-ETF bot that tracks the 10 Vanguard ETFs (VIS, VAW, VTWO, VIOO, VTWG, VBK, VIOG, VTWV, VIOV, VFMO). The strategy will fire entries when price touches the 50-day MA with RSI momentum confirmation, exit on a decisive break of the 200-day MA, and sit on top of a Momentum accelerator plus your Quantum Edge Meta-Classifier to refine signals. I’ll ensure precise signals, flexible position sizing, and a robust, downloadable audit trail that logs every decision—signal, size, regime flag, rotation, and fail-safe—into QuantConnect’s cloud. Market regimes will be detected and applied automatically, scaling exposure up or down; value vs growth rotation will be handled by rate signals. A hard 10% drawdown stop will be enforced. Lean, clean C# or Python code that compiles on QuantConnect, a five-year back-test showing rule adherence and capped drawdown, and a real-time paper-trading session proving regime-based sizing and emergency stop are all in scope. Structured logs with time stamps will cover every action for download. Could you confirm the preferred QuantConnect language (C# or Python), data feed specifics (pricing, dividends, corporate actions), expected backtest period alignment, and required log format and retention? Also, any constraints on logging frequency, and whether you want additional risk metrics (VaR, Sharpe) included in the audit trail? Best regards,

@LiveExperts

Hello, As an experienced engineer and developer, turning complex strategies into live-ready trading algorithms is my forté. My extensive background in algorithm development coupled with my proficiency in C# and Python will ensure that your Vonaguard ETF project is brought to life flawlessly on QuantConnect. The use of technical rulesets such as the 50-day and 200-day moving averages alongside the RSI for entries and exits resonates with my experience in machine learning, deep learning, and artificial intelligence. The incorporation of proprietary tools like the momentum accelerator and the "Quantum Edge Meta-Classifier" aligns perfectly with my work in refining signals, enhancing quality, and maximizing performance. In addition to providing production-quality code that complies and deploys on QuantConnect, we prioritize data management. Producing data logs that preserve every decision - signal, size, regime flag, rotation, fail-safe - is essential for our team at Live Experts. This project is not just about executing trades; it's about accountability, drawdown control, risk management, and providing you with the precise logs you need for analysis. Ultimately, my skillsets in developing algorithms for financial markets, data analysis especially in handling big data algorithmically not to mention leveraging machine learning models for efficient decision making along with a track record of delivering high-quality work make me the i Thanks!

@techplusintl

Hi there, ★★★ C Programming / Python / C# Programming Expert ★★★ 7+ Years of Experience ★★★ To complete this project, I will develop a robust trading algorithm on QuantConnect based on your execution playbook. The process will include key steps as follows: 1. Requirements Analysis (8 hours) 2. Algorithm Development in C# or Python (20 hours) 3. Back-testing for five years to ensure rule adherence (15 hours) 4. Implementing real-time paper trading for validation (10 hours) 5. Creating structured log files for persistent logging (5 hours) What I need from you: 1. Detailed execution playbook documentation 2. Access to your QuantConnect account for deployment and testing 3. Any specific preferences for logging format or additional features I look forward to connecting at your convenience to ensure the project's success. Best Regards, TechPlus Team

@Feriver

Hello, I understand you’re looking for a seasoned QuantConnect (Lean) developer to convert your execution playbook into a live-ready algorithm trading 10 Vanguard ETFs with strict, testable rules and a downloadable audit trail. I build production-grade Lean strategies in C# or Python with deterministic indicator timing, clean state handling, and persistent, structured logging for every decision. I will implement the entry/exit logic exactly as specified: entry on 50-day MA touch with RSI confirmation, exit on decisive 200-day MA break, plus your momentum accelerator and “Quantum Edge Meta-Classifier” as a modular layer that can be tuned without rewriting core logic. Position sizing will be flexible and consistent across symbols, with signal gating to avoid duplicate triggers and with clear separation between signal, execution, and risk layers. Risk and automation will be first-class: regime detection (normal/uncertain/stress) to scale exposure, value vs growth rotation logic across your baskets, and a hard 10% portfolio drawdown stop with immediate de-risking. All actions—signals, sizes, regime flags, rotation decisions, and failsafes—will be written to persistent downloadable logs in QuantConnect Cloud, backed by a 5-year backtest and a paper-trading validation run. Thanks Asif.

@Milvetti

Hi, we can help you with your QuantConnect multi-ETF regime-aware algo. We offer lifetime bug fix guarantee. As Milvetti, we help traders automate their strategies. Price is an estimate and may vary by scope.

@hireageek

Hi there, I understand your need for a sophisticated trading algorithm that aligns perfectly with your detailed execution playbook. As a top freelancer from California with extensive experience in QuantConnect development, I have successfully designed and deployed various trading bots that leverage technical indicators and robust strategy designs. I can effectively cover the ten Vanguard ETFs while ensuring that your strict technical rules and risk management protocols are followed without compromise. My background in C# and Python will enable me to create the lean-compatible code required for seamless deployment on QuantConnect. I aim to complete a five-year back-test, demonstrate rule adherence, and conduct a real-time paper-trading session, giving you the confidence that the bot operates as intended. Let’s collaborate to turn your vision into a reality; please reach out so we can discuss your project further and clarify any details. What specific features do you envision for the logging mechanism, and how would you like to access those logs? Best regards,

@corpmember29

Hello, I have carefully reviewed your execution playbook and fully understand the requirements for building a production-ready QuantConnect trading algorithm across the specified Vanguard ETF universe. I am a seasoned QuantConnect developer with 10+ years of experience in quantitative trading systems, technical signal engineering, regime detection, and risk-managed portfolio construction using Lean (C# and Python). I will implement precise MA/RSI entry-exit logic, integrate your Momentum Accelerator and Quantum Edge Meta-Classifier, enable automated regime detection with dynamic exposure scaling, and enforce strict value/growth rotation and a hard 10% portfolio drawdown stop. Every signal, sizing decision, regime flag, rotation, and fail-safe action will be persistently logged with time-stamped, downloadable audit trails. Delivery will include Lean-compatible code, a compliant 5-year backtest, live paper-trading validation, and clean deployment readiness for QuantConnect Cloud. I look forward to collaborating on a smooth path to live execution. Thanks.

@Herculesz

Hi I can implement your 10-ETF Vanguard strategy as a live-ready QuantConnect Lean algorithm with precise MA/RSI touch entries, 200D break exits, and a strict 10% portfolio drawdown kill-switch. The main technical risk is “touch” detection and signal timing across multiple symbols, where sloppy indicator readiness or bar-resolution assumptions can cause false triggers and rule drift. I solve this by using consolidated data, warm-up/indicator priming, exact-touch logic, and deterministic order handling to ensure entries/exits fire exactly per spec. I have strong experience with Lean (C#/Python), multi-asset portfolio management, custom indicators, regime classification (volatility/trend/rate proxies), and rotation logic between value/growth baskets. Your “Momentum accelerator” and Quantum Edge Meta-Classifier can be integrated as modular scoring layers that gate signals and drive position sizing per regime. I’ll enforce risk controls with portfolio-level tracking, per-symbol exposure rules, and robust fail-safes, all fully logged with timestamps and decision context. You’ll get downloadable, persistent structured logs covering every signal, size, regime flag, rotation decision, and emergency action for auditability. Thanks, Hercules

@devendrathakur12

Hello, I specialize in QuantConnect algorithms and built & customized large scale ETF and multi-asset trading systems. The main challenge here is turning strict rules into clean, testable code that never breaks risk limits. I am certified in QuantConnect Lean development, and I will solve this by coding a clear C# or Python strategy with full logs, regime detection, and safe position sizing from day one. You’ll always know why a trade fired, sized, rotated, or stopped. Quick questions so I align perfectly: should the 50-DMA touch be intraday or close-based? Is RSI standard 14 or custom? How should the Quantum Edge Meta-Classifier plug in—score threshold or filter only? Do regime changes act daily or immediately? Should the 10% drawdown stop flatten all positions or pause entries? Best regards, Dev S.

@ducthodg

With over a decade of experience specialising in trading algorithm development, I, Nguyễn Đức, am perfectly poised to bring your ETF trading bot to life. My comprehensive understanding of coding languages including C++, C#, Java and MQL4/5 is complemented by my engineering background, ensuring that I approach every project with a meticulous precision capable of producing exceptional results. Building on this, I have a wealth of experience with platforms such as QuantConnect (C# or Python) Beyond just producing clean code that works well within QuantConnect's ecosystem, I am committed to delivering production-quality work with punctilious documentation to enable easy download of persistent logs reflecting every decision made by the algorithm. My knack for crafting reliable and efficient codes has stood me in good stead throughout my career, amply demonstrated by my extensive portfolio of lean-compatible C# (and Python) codes. For assurance, I would gladly provide you with a comprehensive five-year back-test and real-time paper-trading session while keeping in mind the ultimate goal of having a highly-efficient algo ready for live use. Hexatrigesimalreinterpret

@reedsystems

Hi, I’m excited about the opportunity to bring your detailed execution playbook to life as a live-ready trading algorithm using QuantConnect. With over a decade of experience in the field, I can confidently handle the project specifications you’ve outlined. My approach will ensure precision in technical signals, flexibility in position sizing, and robust audit trails. The strategy will cover ten Vanguard ETFs while respecting the strict rule-set involving 50-day moving average entries, RSI confirmations, and 200-day moving average exits. Additionally, I’ll integrate a momentum accelerator and my own “Quantum Edge Meta-Classifier” to refine every signal. To meet your acceptance criteria, I will deliver Lean-compatible C# (or Python) code that compiles and deploys on QuantConnect. Alongside this, I will provide a five-year back-test demonstrating rule adherence and a capped drawdown, as well as a real-time paper-trading session showcasing automated regime-based sizing and emergency stop mechanisms. Each decision—signal, size, regime flag, rotation, fail-safe—will be logged with time-stamped entries for comprehensive traceability. You can check the portfolio on my profile for references. Best regards, Reed

@denisSolution

Hi client, I'm Denis Redzepovic, an experienced developer with expertise in Backtesting, C++ Programming, Metatrader, C Programming, API Development, C# Programming, Python and Algorithm. I have worked extensively on diverse Python projects, ranging from backend development and automation to data processing and API integrations. My deep understanding of Python’s libraries and frameworks allows me to build efficient, scalable, and maintainable solutions. I pay close attention to code quality and performance to ensure your project runs flawlessly. With my solid experience, I’m confident I can deliver results that exceed your expectations. I focus on writing clean, maintainable, and scalable code because I know the difference between 99% and 100%. If you hire me, I’ll do my best until you’re completely satisfied with the result. Let’s discuss your project details so I can tailor the perfect Python solution for you. Thanks, Denis

@aktarujjamana7

I will develop a QuantConnect algorithm for ten Vanguard ETFs, integrating SMA/RSI signals, regime detection, rotation logic, strict drawdown control, and comprehensive logging for live-ready deployment.

@abhisaini0188

Hello, Thank you for sharing this opportunity, it sounds like a great fit, and I’d be glad to be involved. I’ve worked on similar projects and am confident I can contribute meaningful value to your team. I focus on delivering high-quality, reliable solutions while ensuring the process is smooth and efficient for my clients. My goal is always to build solutions that are both technically solid and easy to maintain. You’re welcome to review my profile to see examples of my previous work. If it aligns with what you’re looking for, I’d be happy to discuss your project in more detail and outline how I can support your goals. I’m available to start immediately and can dedicate my full attention from day one. Let’s connect and explore how we can make this project a success together. Looking forward to your response. With Regards! Abhishek Saini

@maximg10

⭐Hi, I’m ready to assist you right away!⭐ I believe I’d be a great fit for your project since I possess extensive experience in algorithm development, API integration, and backtesting in C#, Python, and C++. With a strong background in QuantConnect, I am well-equipped to transform your detailed execution playbook into a live trading algorithm that meets your specific requirements. My technical expertise lies in developing precision trading strategies that leverage technical indicators like moving averages and momentum oscillators, ensuring optimal entry and exit points in the market. I understand the importance of maintaining a robust audit trail and implementing automated risk management tools to handle market regimes effectively. This project aims to solve your most pressing needs by creating a production-quality trading bot that adheres to your rule-set, detects market regimes, and implements automatic position sizing based on predefined criteria. By delivering clean and efficient code that compiles seamlessly on QuantConnect, I will provide you with the tools to optimize your trading strategy and scale your portfolio effectively. 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

@trm66614

Hi there,Good evening I am Talha. I can work with your project skills C Programming, Backtesting, API Development, Metatrader, Algorithm, Python, C# Programming and C++ Programming am writing to propose an innovative approach to tackle your project. Our proposal centers on delivering creative and effective solutions that will set your project apart. We will present fresh, out-of-the-box ideas that align with your project's objectives, demonstrating how we can achieve remarkable results. Please note that the initial bid is an estimate, and the final quote will be provided after a thorough discussion of the project requirements or upon reviewing any detailed documentation you can share. Could you please share any available detailed documentation? I'm also open to further discussions to explore specific aspects of the project. Thanks Regards. Talha Ramzan

@Julian29

Hello, HAVE HANDS-ON EXPERIENCE WITH SUCH PROJECT I have 9+ years of proven experience in quantitative trading systems and QuantConnect (Lean) development, and I confidently understand the requirement. The goal is to convert your execution playbook into a production-ready, regime-aware ETF trading algorithm with strict rule adherence, rotation logic, and full auditability. -->> Lean-compatible C#/Python algorithm covering all 10 Vanguard ETFs -->> Precise MA/RSI entry–exit logic with momentum accelerator + Meta-Classifier integration -->> Automatic regime detection with dynamic position sizing and growth/value rotation -->> Hard 10% portfolio drawdown protection and fail-safe controls -->> Persistent, structured logging for every signal, decision, and action -->> 5-year backtest + live paper-trading validation Approach: deterministic signal execution, modular strategy layers, regime-aware risk control, and audit-first logging within QuantConnect’s cloud environment.

@Rekhathakur

Hello I have thoroughly reviewed your project description and am confident in my ability to assist you in completing it successfully. I believe it would be highly beneficial to delve deeper into the specifics of the job to determine the most effective way forward. I am open to scheduling an interview at your convenience, and I genuinely appreciate the chance to collaborate with you on this project. Your response is eagerly anticipated, and I'm excited about the prospect of working together. Thank you for considering my proposal. Looking forward to your prompt reply! Best regards Rekha!!!

@JijoThomas2020

I can translate your execution playbook into a production-ready QuantConnect algorithm covering all ten Vanguard ETFs with precise MA/RSI entry–exit logic, regime detection, rotation between value and growth, and a hard 10 % portfolio drawdown stop. I’ll implement your momentum accelerator and Quantum Edge Meta-Classifier cleanly on top of Lean, with flexible position sizing and no compromise on signal accuracy or auditability. Every decision—signals, sizing, regime flags, rotations, and fail-safes—will be written to structured, time-stamped logs downloadable from QuantConnect’s cloud. You’ll receive Lean-compatible C# (or Python) code, a five-year backtest demonstrating rule adherence and capped drawdown, and a live paper-trading run proving automated regime-based behaviour. The final deliverable will be ready for a smooth transition to live trading.