High-Frequency Stock Trading Strategy

@Softeria

✅ Proposal for High-Frequency Stock Trading Strategy With a proven track record in developing high-frequency trading (HFT) systems, I am ideally suited to create a robust trading strategy for your needs. My expertise includes sophisticated algorithm design, integrating and analyzing high-volume data streams, and executing trades with ultra-low latency. I have successfully implemented similar strategies that leverage historical tick data, real-time market feeds, and dynamic news analysis to drive decision-making processes. I am proficient in creating back-test frameworks, executing modules, and news-feed parsers that meet stringent performance benchmarks. I am committed to delivering a comprehensive, automated trading solution that achieves consistent, net-positive returns under realistic market conditions. Let’s collaborate to realize the full potential of your trading infrastructure.

@LiveExperts

Hello, As a team, we offer expertise in a vast range of disciplines that are highly relevant to your project's needs. Notably, our skills in Machine Learning (ML), Data Analysis and Statistics will be instrumental in designing, optimizing, and evaluating the best trading strategy for your equities project. Additionally, our experience in Risk Management is fitting as it aligns with your requirement of a fully automated approach without any human intervention. Our professional background also includes proficiency in Signal Processing, which will prove useful for building a high-frequency trading system that can process critical financial signals within microseconds. We understand the importance of latency and transaction costs in HFT and are accustomed to working under such rigorous constraints Thanks!

@quan9824

Hi, this is a serious HFT systems challenge, not just a strategy build—and that’s exactly where I work best. Approach: 1. Strategy Design (Edge + Microstructure) • Combine order book imbalance, trade flow, and short-term alpha signals • Integrate event-driven signals from news feeds (NLP scoring → latency-aware triggers) • Use hybrid model: statistical + lightweight ML for low-latency inference 2. Backtesting Framework • Tick-level simulator with queue position, slippage, and latency modeling • Deterministic replay of your historical data • Metrics: Sharpe, drawdown, hit rate, capacity, execution efficiency 3. Low-Latency Execution Engine • Event-driven architecture (Python with optimized components where needed) • Direct integration with your market feed and broker API • Pre-trade risk checks, position limits, and kill-switch logic 4. News Signal Engine • Real-time parsing and scoring (keyword + embedding-based models) • Priority-based signal routing for minimal latency impact 5. Risk & Stability • Position sizing, exposure limits, volatility filters • Failover handling and deterministic execution Stack: Python (core), optional C++ modules for critical paths, async pipelines, low-latency data handling I focus on realistic, execution-aware profitability, not theoretical models. If you want, I can outline a specific alpha model and execution architecture before we proceed.

@prabhathk5

Thanks for sharing the details. I’ve reviewed your requirement and would be glad to discuss it further. I’m Prabhath, an experienced MQL4/MQL5, Pine Script, Python, and C++ developer specializing in automated trading systems and institutional-grade algorithmic solutions. I develop Expert Advisors, indicators, dashboards, data tools, and custom trading utilities for MT4/MT5, TradingView, and standalone platforms. Along with MQL5 systems, I also build fully automated trading software in Python and C++ for Indian stock markets and global exchanges (US, EU, and others). These solutions can be tailored for stocks, indices, futures, forex, and crypto based on project needs. As an active trader, I work with ICT, SMT, market structure, liquidity models, order blocks, FVGs, VWAP, and volume-based logic, ensuring each strategy follows the client’s trading methodology. My expertise includes institutional-grade EA and indicator development, ICT/SMT-based trading systems, Pine Script automation, Python and C++ systems for Indian and global markets, backtesting, paper trading and live trade integration, strategy optimization, and low-latency execution. I also fix, optimize, and enhance existing trading systems to make them stable and production-ready. Where permitted, I can share demos or walkthroughs of previously completed projects while respecting client confidentiality. Thank you for your time and consideration.

@hayat38402

Hi, how are you doing? I went through your project description and I can help you in your project. your project requirements perfectly match my expertise. We are a team of expert engineers, we have successfully completed 1000+ Projects for multiple regular clients from OMAN, UK, USA, Australia, Canada, France, Germany, Lebanon and many other countries. We are providing our services in following areas:  Neural Network/ Natural Language Processing  Machine learning/Data Mining  Deep Learning and Computer Vision  Image Recognition & Artificial Intelligence  AI text analysis model and Reinforcement Learning.  Omnet++ and Sumo simulation,  Python/ MATLAB  Asterisks PBX  NS3 simulation  Linux We'll make sure that your project is done in a perfect way and do our best until you were satisfied. I am confident I can provide you with top-notch materials that will fit your needs.

@prashanpatel557

Hello, I can help design a low-latency trading system in Python. I can build a real-time, event-driven system that is robust and production-ready. Approach: • Event-driven engine (data - signal - execution) • Integrate tick data + real-time feed + news parser • Latency-optimised (async processing, lightweight pipelines) Strategy Layer: • Order-flow + microstructure signals • News sentiment scoring (event-driven triggers) • Hybrid logic for stable performance Execution Module: • Fast order routing + position lifecycle management • Slippage-aware execution + risk checks • Logging + deterministic replay Backtesting: • Tick-level simulation with latency & cost modeling • Metrics: Sharpe, DD, slippage, capacity Deliverables: • Full codebase (modular) • Backtest + live engine • News parser + scoring • Performance report Timeline: 12–18 days Budget: $500–$700 I have experience in trading systems, real-time data handling, and automation, ensuring practical execution. Question: What broker/API are you currently using?

@huonghy89

Hi, How are you? I’m very happy to submit my bid for your project, as my skills and experience align well with your requirements. I am very familiar with leading trading platforms, including MetaTrader 4 (MT4), MetaTrader 5 (MT5), TradingView, Thinkorswim, Robinhood, and eToro. Additionally, I am proficient in advanced analytical and algorithmic trading tools such as TrendSpider, TC2000, NinjaTrader, QuantConnect, AlgoTrader, and Amibroker. Over the years, I have developed expertise in: • Algorithmic trading and strategy development • Technical analysis and indicator creation • Backtesting and optimization of trading strategies • Automation using Expert Advisors (EAs) and trading bots • Integration of APIs for trading systems I have successfully worked on projects involving custom indicator development, automated trading systems, and data-driven trading strategies across forex, stocks, and crypto markets. I am confident in delivering high-quality results tailored to your project needs. If you send the message, we can discuss the project more. Thank you.

@techplusintl

Hi, To create a complete high-frequency trading strategy, I'll develop a solution that integrates your historical data, real-time market feed, and news feeds. I'll use Python for the strategy logic and MySql for data management. Ready to start once you provide access to your data pillars and any specific requirements you have. Thanks!

@Zawiya3

Hello! My name is Jawad and I am an established technology professional, well-versed in key areas that converge with your project requirements. As a software developer and full-stack engineer, I have significant experience handling large-scale real-time data feeds—an essential aspect of your high-frequency trading strategy. And when it comes to implementing complex systems capable of processing and reacting to these feeds within microseconds, my knowledge in cloud architecture and use of Python for data analysis and machine learning is highly beneficial. Rest assured, I will provide you with a comprehensively documented strategy logic and mathematical model as specified in the deliverables. Furthermore, my insights in risk management will ensure your model accounts for slippage, drawdowns, Sharpe ratios, and capacity limits to maximize performance consistency. Given that live market conditions can vary significantly from backtests, I will ensure our risk checks inform realistic latency and transaction cost assumptions while compiling the codebase on a clean machine to promote consistent determinism.

@ivicab6

With over half a decade of experience as a full-stack engineer, I bring a wealth of knowledge and skills to the table. I've worked extensively with machine learning, which is crucial for the complex task of high-frequency trading. This experience has given me deep insights into not just the technical side of your project but also the quantitative and financial aspects. I am no stranger to challenging projects that require transforming raw data into valuable insights. Establishing a cohesive strategy around your existing data pillars will be a natural extension of my skill set. Furthermore, my previous work automatizing business processes and system workflows aligns perfectly with your need for an automated stock trading strategy without human intervention. To ensure your satisfaction, I offer to run extensive back-tests with reproducible results, create low-latency execution modules that integrate seamlessly with real-time market feeds and broker APIs, and provide performance reports covering key metrics such as slippage, Sharpe ratio, drawdowns, and capacity limits. My commitment is to deliver not just a functional system, but one that generates consistent and significant positive returns after accounting for latency and transaction costs.

@carlosd178

Hello, As a result of a detailed review of your project requirements, I fully understand the scope and expectations. I have experience handling similar quantitative and low-latency system projects and I'm available to start your project right now. I bring strong expertise in algorithm design, backtesting, statistical modeling, financial APIs, machine learning and risk management with over 10 years of experience. One of the key parts here is building a strategy that remains fast, deterministic, and realistic under real trading conditions. I can help structure the full pipeline around your tick data, live feed, and news inputs, including signal generation, event scoring, execution flow, transaction-cost-aware backtesting, and risk controls, while keeping the system reproducible and measurable through slippage, drawdown, Sharpe, and capacity analysis. I have a couple of quick questions. • What broker API and market feed are you currently using for live execution? • Do you want the first phase focused on research and backtesting, or on a full live-ready execution framework from the start? I would be glad to discuss further details and am ready to start immediately. Looking forward to hearing from you. Best regards, Carlos

@tonyc00

Hi,this is exactly the kind of system I like building. I’ve worked on low-latency trading and real-time prediction pipelines, and I’m comfortable turning tick data, live feeds, and news signals into a fully automated strategy. My approach would combine microstructure signals from your tick data with fast event-driven models from the news feed, all connected to a lightweight execution engine with strict risk controls and realistic cost modeling. The focus is not just prediction, but consistent, deployable performance. I’ll deliver a clean, reproducible backtesting setup, a low-latency trading module, and clear performance reporting. Happy to discuss details and align on targets. Best, Tony

@johnhygh

Hello there , Good evening! I’ve carefully checked your requirements and really interested in this job. I’m full stack node.js developer working at large-scale apps as a lead developer with U.S. and European teams. I’m offering best quality and highest performance at lowest price. I can complete your project on time and your will experience great satisfaction with me. I’m well versed in React/Redux, Angular JS, Node JS, Ruby on Rails, html/css as well as javascript and jquery. I have rich experienced in Financial APIs, Financial Analysis, Algorithm, Statistical Modeling, Machine Learning (ML), Data Analysis, Backtesting, Market Analysis, Risk Management and Signal Processing. For more information about me, please refer to my portfolios. I’m ready to discuss your project and start immediately. Looking forward to hearing you back and discussing all details.. With regards

@susiek9805

Hi, there, I am excited about the opportunity to help you develop a high-frequency trading (HFT) strategy tailored for actively-traded equities. With my extensive experience in algorithm development, machine learning, and financial analysis, I am confident in delivering a robust solution that meets your requirements. ✅ Backend scope I will create a comprehensive strategy logic incorporating statistical modeling and risk management principles. This will involve designing a back-test framework that utilizes your historical tick data, ensuring reproducibility of results. The execution module will be optimized for low latency, interfacing seamlessly with your real-time market feed and broker API. ✅ News-feed parser To enhance your strategy, I will implement a news-feed parser capable of scoring events in real-time, allowing the system to react swiftly to market-moving news. This will ensure that the trading strategy remains adaptive and responsive to external signals. ✅ Deliverables The final deliverables will include fully documented strategy logic, a functioning back-test framework, a low-latency execution module, and a performance report covering key metrics like slippage and Sharpe ratios. I will ensure that the codebase runs deterministically and compiles on a clean machine, delivering consistently positive returns after accounting for latency and transaction costs. I can start immediately and am looking forward to working with you. Best Regards, Susie Kalson

@sjohn117

Hi Client, I'm Sean, a Senior AI & Full-Stack Developer with 8 years of experience in algorithmic trading, low-latency systems, and statistical modeling. I built and productionized microsecond-aware trading engines and market-making strategies, including a system that consistently simulated a 12% annualized return after realistic costs and sub-100µs execution. My approach will translate your historical tick data, real-time feed, and curated news into a unified signal stack: statistical microstructure models, event-driven scoring, and a latency-optimized execution pipeline; I can do this project perfectly and deliver deterministic, reproducible results. I will provide a documented mathematical model, a backtest framework wired to your datasets, a low-latency execution module compatible with your broker API, a real-time news parser with scoring, and comprehensive performance and risk reports. I typically deliver this scope in 60 days, including tests and deployment scripts. I ensure unit and integration tests, logging/monitoring, OWASP basics, clean code, and docs; for AI components I add evals, guardrails, and data-privacy controls. Which broker/execution API(s) and FIX or proprietary gateways do you already have, and can you share sample tick and news feed schemas plus target round-trip latency requirements? Thanks, Sean

@abdf2010

Hello, I am interested in your project, High-Frequency Stock Trading Strategy. I've successfully completed projects involving Algorithm, Machine Learning (ML), Risk Management before. Happy to discuss the details whenever works for you.

@Ashnasajid

Hi, I can do this. I will develop a high-frequency trading strategy tailored to your specifications, leveraging your historical tick data, low-latency market feed, and curated news feeds. My approach will include: - A robust strategy logic and mathematical model, thoroughly documented for clarity. - A back-test framework integrated with your historical data, ensuring reproducible results. - A low-latency execution module that seamlessly connects to your real-time feed and broker API. - A news-feed parser that evaluates events in real-time, efficiently routing signals to the core engine. - A comprehensive performance report detailing slippage, Sharpe ratio, drawdown, and capacity limits. I will ensure the codebase runs deterministically, compiles on a clean machine, and demonstrates consistent, net-positive returns after accounting for latency and transaction costs. Looking forward to collaborating on this project. Ashnasajid

@AITSoft

Hello, I understand you need a fully functional high-frequency trading strategy that makes quick decisions using your historical tick data, real-time feeds, and news events. I'll build a complete system that reads your data streams, reacts in microseconds, and manages trades from signal creation to execution and risk control, all automatic. I'll deliver clear strategy logic, back-testing on your data, a fast execution module linked directly to your broker, a news parser scoring events in real time, and a detailed performance report covering key metrics. My focus will be on reliability and consistent profits after accounting for delays and costs. To get started, I have a few questions to ensure everything fits your needs well. Can you share the format and update frequency of your real-time market feed and broker API details? What latency target or maximum delay is acceptable from signal generation to trade execution? Do you have specific risk parameters or limits to apply during trade lifecycle management? What types of news or events in your feeds are most critical to your trading signals? Are there existing frameworks or languages preferred for the back-testing and execution modules? Thanks,

@letswork92

Your need for a robust high-frequency trading (HFT) strategy highlights the critical importance of speed and reliability in today’s equities market. With over 12 years of experience, I specialize in creating systems that seamlessly integrate historical data, real-time feeds, and event-driven signals. To build your solution, I will utilize technologies such as Node.js for backend efficiency and AWS for scalable infrastructure. My approach includes designing a comprehensive strategy logic supported by a detailed mathematical model, along with a back-test framework to guarantee reproducible results. The execution module will be optimized for low latency, ensuring swift decision-making aligned with your broker API. Furthermore, I will implement a news-feed parser that dynamically scores events and efficiently routes signals to maximize trade accuracy while maintaining risk checks throughout the lifecycle. Could you clarify which specific broker API you're currently using to ensure seamless integration?