Algorithmic Stock Signal & Risk Tool

@Herculesz

Hi I can build a Windows-ready stock scanning tool that identifies systematic buy opportunities and displays entry, take-profit, and volatility-based stop-loss levels clearly. I have experience with Python, pandas, TA-Lib, backtesting, equity data feeds, trading dashboards, risk rules, parameterized strategies, and clean reporting. A key technical challenge is making live scan signals match back-test logic closely enough that results remain repeatable under real market conditions. I can solve that with one shared strategy engine for both back-testing and live scanning, transparent parameters, slippage assumptions, and reproducible signal logs. The model can be tuned for equities using volume behavior, gaps, volatility bands, trend or mean-reversion rules, and watch-list based scanning. I’ll deliver commented source code, a runnable app, setup documentation, parameter notes, sample watch-list config, and back-test results matching the default settings. My focus will be robust, explainable algorithmic logic rather than black-box discretionary signals. Thanks, Hercules

@ducthodg

Hi, I can build this stock scanner as a clean, systematic trading tool for Windows. My suggested stack is Python for the strategy/back-test engine and either Streamlit/web dashboard or a lightweight desktop UI, with modular data adapters so you can connect your own brokerage feed later. My approach would be: Define the model logic: trend-following, mean-reversion, or hybrid equity-specific rules. Build a back-test engine with entry signal, TP zone, volatility-based SL, slippage assumptions, and CSV/PDF reports. Add real-time/watch-list scanning with configurable parameters. Build the UI showing fresh opportunities, entry, TP, SL, signal reason, and logs. Package the app with setup documentation and sample watch-list config. I have experience with algorithmic trading tools, back-testing, live data integration, risk logic, and clean reusable code. I will keep the strategy fully rule-based, transparent, and parameterized so you can tune it without rewriting core functions. I suggest milestone delivery: model design → prototype/back-test → live data hookup → final UI/package.

@toriquldev123

Hello Dear! Greetings from Toriqul Global Solutions! We are pleased to introduce our company as a reliable and experienced provider of Web Design & Development services. Founded and led by Engineer Toriqul Islam, a B.Sc. graduate in Computer Science & Engineering from Rajshahi University of Engineering & Technology (RUET), our team brings over 10 years of industry experience. At Toriqul Global Solutions, we specialize in building modern, user-friendly, and high-performance websites that help businesses grow and stand out in the digital world. Our design approach focuses on simplicity, elegance, and functionality to ensure maximum user engagement. Technologies We Use: Custom Websites Development Using ======>Full Stack Development. 1. HTML5 2. CSS3 3. Bootstrap4 4. jQuery 5. JavaScript 6. Angular JS 7. React JS 8. Node JS 9. WordPress 10. PHP 11. Ruby on Rails 12. MYSQL 13. Laravel 14. .Net 15. CodeIgniter 16. React Native 17. SQL / MySQL 18. Mobile app development 19. Python 20. MongoDB What you'll get? • Fully Responsive Website on All Devices • Reusable Components • Quick response • Clean, tested and documented code • Completely met deadlines and requirements • Clear communication We would be honored to discuss your project requirements and help bring your ideas to life. Thank you for your time and consideration. Warm Regards, Toriqul Global Solutions

@GameOfWords

Drawing from my 9+ years of experience, I'm more than capable of developing the algorithmic stock signal and risk tool you seek. With a comprehensive understanding of C# and .NET, I can create a robust, reliable software that seamlessly connects to live/eod equity data on any Windows platform. Furthermore, as a proficient Python developer skilled in using pandas/TALib, I am also able to offer you alternative environment support. As you rightly noted, equity markets are distinct phenomena with idiosyncrasies such as session gaps, volume profiles and tick size quirks. Having worked extensively in financial markets developing systematic trading models for stocks I have accrued an exceptional understanding of these intricacies and how they shape investment decision-making. This well-acquaintance would be channelized into producing a project that not just reflects your ideal approach - be it trend-following, mean-reversion or hybrid - but also optimize core functions easily to adapt to changing market behaviours. Transparency will be a bedrock of my work; your stringent request for well-commented code aligns perfectly with my coding philosophy and the standards that I hold myself to.

@quan9824

As a well-seasoned Full-Stack Developer, I fully understand the unique challenges and intricacies involved in crafting high-performance financial applications. My proficiency with Python (specifically Pandas), .NET/C#, and experience connecting to live equity data make me an ideal fit for your Algorithmic Stock Signal & Risk Tool project. In line with your requirements, I'm confident that my strength in algorithmic trading strategies - be it trend-following, mean reversion or hybrid logic - will positively impact your project as I can meticulously build a tailor-made, systematic tool that caters to the idiosyncrasies of equities as you've described. Over the years, my skillset (including but not restricted to AI, time-series forecasting and prediction) combined with my commitment to writing clean, maintainable code - which I've showcased in numerous projects prior - will ensure we establish a solid foundation through robust design and coherent back-test reports for efficient parameter tweaking. Let’s discuss further how I can translate these capabilities into impressive deliverables and a successful partnership.

@nrajuu07

As a seasoned Machine Learning Engineer specialized in time series forecasting and algorithm development, I am well-equipped to create your desired stock signal and risk tool. Over the years, I have consistently delivered production-ready AI systems built on the bedrock of real-world data, a cardinal attribute necessary to construct a tool that thrives in financial markets. My strong analytical foundations in Python, backed by libraries like pandas and TALib, as well as deep learning frameworks such as PyTorch and TensorFlow, make me particularly suited for this endeavor. I comprehend your need for transparency, repeatability and understand the significance of backtest reports intertwined with the ability to flexibly modify parameters. While my past projects revolve around medical image analysis and computer vision, some of my most successful forays include finance-related domains like demand forecasting, predictive maintenance as well as anomaly detection - a stringent parallel with the stock signaling conjecture. In conclusion, choosing me ensures not only an immaculately coded tool but also one grounded deeply in performance based on my thorough understanding of equity market behaviors.

@prashanpatel557

Hello, I can build your algorithmic stock signal & risk tool with real-time scanning, clear entry/TP/SL outputs, and backtested logic. Approach: • Python (Pandas + TA-Lib) with Flask backend • Data: live feed (broker/API) or EOD (configurable) • Event-driven scanner: watchlist → signals → display Signal Engine: • Hybrid model: trend + volatility breakout / mean-reversion filter • Entry: rule-based (no discretion) • SL: volatility-based (ATR / recent swing) • TP: RR-based zones (dynamic) Core Features: • Real-time stock scanning (custom watchlist) • Output per trade: Entry, TP zone, SL • Parameter config (no code edits) • Backtesting module (same logic as live) UI Options: • Desktop (lightweight) or Web dashboard • Shows signals, charts, risk levels Reliability: • Clean modular code • Logging + reproducible signals • Handles gaps, volume filters (equity-specific tuning) Deliverables: • Full Web application (code + runnable build) • Backtest report (CSV/PDF) • Setup + configuration guide Timeline: 5–7 days Budget: $250 – $500 I focus on practical, non-overfitted trading systems with clear risk outputs. Question: Do you want intraday real-time scanning or is EOD-based signals sufficient for the first version?

@loxtic

Hi, how are you doing? I’ve built robust, repeatable algo-trading tools for equity data on Windows using Python (pandas/TALib) and .NET, with clear entry/exit signals, risk controls, back-test reports, and easy parameter tweaks. I can deliver well-commented source, a runnable installer or Docker image, setup docs, and sample watch-lists, plus back-test CSV/PDF that align with live or end-of-day data. I’ll tailor the model to equity behavior, ensure transparent code, and set milestones from research to UI polish. Let me know further if interested

@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

@cindyviorinar

Hello, I am eager to help you develop a robust tool for algorithmic stock trading. With extensive experience in building algorithmic trading systems using Python and C#, I understand the specific needs of equity trading, including managing session gaps and daily volume profiles. Your project aims to create a systematic tool that identifies buy opportunities and provides clear entry signals, take-profit zones, and stop-loss levels. I suggest using Python with pandas and TA-Lib for its flexibility and extensive libraries for financial analysis, but I'm plenty comfortable with C# if that aligns better with your preferences. The implementation will follow a phased approach: first, we'll focus on research and model design, followed by prototype development with comprehensive back-testing. This structure allows us to prioritize robustness over speed, aligning perfectly with your timelines. I can provide a simple demo within 12 hours of starting. What specific features or data points do you envision as crucial for the tool's success? Best regards, Cindy Viorina

@alluankit01

Hi, I can build a Windows friendly stock signal and risk tool with transparent algorithmic logic, backtesting, and adjustable parameters. I understand the goal is not a black box “profit promise,” but a repeatable system that scans stocks, identifies buy setups, and shows entry, take profit zone, and stop loss based on recent volatility. I can build it in Python or C# with clean modules for data loading, strategy rules, risk calculation, backtesting, and UI. My approach would be to first define the default strategy logic, such as trend, mean reversion, or hybrid, then test it against historical stock data and generate reports showing signals, exits, drawdowns, and performance. After that, I’ll connect the tool to your preferred live or end of day data feed and make parameters easy to adjust without editing core code. I’ll deliver commented source code, runnable app, setup guide, sample watchlist, and backtest output that matches the default settings. Best regards Ankit

@adily1

Hey , I just finished reading the job description and I see you are looking for someone experienced in C++ Programming, Data Science, Machine Learning (ML), Algorithm, C# Programming, Data Analysis, Python and Software Architecture. This is something I can do. Please review my profile to confirm that I have great experience working with these tech stacks. While I have few questions: 1. These are all the requirements? If not, Please share more detailed requirements. 2. Do you currently have anything done for the job or it has to be done from scratch? 3. What is the timeline to get this done? Why Choose Me? 1. I have done more than 250 major projects. 2. I have not received a single bad feedback since the last 5-6 years. 3. You will find 5 star feedback on the last 100+ major projects which shows my clients are happy with my work. Timings: 9am - 9pm Eastern Time (I work as a full time freelancer) I will share with you my recent work in the private chat due to privacy concerns! Please start the chat to discuss it further. Regards, Adil.

@johnhygh

Hello Sir, With 9+ years of experience as a Senior Full Stack & DevOps Engineer, my expertise centers on demystifying complex ideas by turning them into robust, scalable, and efficient software applications. Combining this with my strong background in Machine Learning (ML) and deep proficiency in the use of Python, the language renowned for its agility in data handling, I offer you an exceptional candidate to develop your Algorithmic Stock Signal & Risk Tool. I recognize your need for a completely systematic and repeatable workflow for reliable stock market scanning, buy opportunity identification, precise entry signals, and effective risk management tools. This meticulousness perfectly aligns with my penchant for maintainable code that doesn't compromise performance for such tasks. My proven experience in Full Stack Development (React.js to Python and everything in between), Backend Architecture (Node.js, Python among others) pairs well with your need for a functional UI that meets your equity behavior-specific preferences. Moreover, I see eye-to-eye with your desire to set "sensible milestones" ensuring correct research is done, prototypes are accurate and documentation is thorough before each phase can be considered complete. My extensive skillset in cloud infrastructure enables me to seamlessly connect live or end-of-day equity data sources within reliable systems. From the unique buy opportunities to precise entry signals to take-pr Thanks! John

@pedrowilberthr2

Hello there, I’m excited to help you build an automated, fully- systematic stock signal tool tailored for equity markets. The plan centers on a robust, repeatable workflow that scans real-time or end-of-day data on Windows, with a clean stack choice: Python + pandas/TALib or C# .NET, your pick. The model will generate every entry, take-profit, and stop-loss using tested algorithmic rules (trend-following, mean-reversion, or hybrids), tuned for session gaps, daily volume profiles, and tick-size quirks. Deliverables cover the entire lifecycle: well-commented source code plus a runnable installer or Docker image; comprehensive documentation (setup, parameter explanations, and a sample watch-list); and back-test results in CSV/PDF that align with the shipped defaults. You’ll receive a transparent codebase designed for parameter tweaking without rewriting core logic, with safeguards for back-test reproducibility and easy live data hookup. Proposed milestones: 1) research & model design, 2) prototype with back-test, 3) live data integration, 4) UI polish and documentation. I’ll provide clear, testable modules and a reusable framework that you can extend for future instruments. Best regards,

@indreshpnk

Hello, I understand you need an algorithmic stock signal tool that scans markets, identifies buy opportunities, and provides precise entry, take-profit, and stop-loss levels based on systematic logic. The goal is to deliver a reliable, transparent, and fully configurable trading system with back-tested validation. Here’s what I can provide: • Python-based tool (pandas + TA-Lib) for signal generation with clean, modular architecture • Strategy implementation (trend/mean-reversion) with volatility-based stop-loss and profit targets • Backtesting engine with CSV/PDF reports matching live signal logic • Live/EOD data integration and Windows-compatible runnable app (or lightweight UI) • Parameterized system for easy tuning without modifying core code I bring 4+ years of experience in algorithms, data analysis, and building logic-driven systems with a focus on performance, clarity, and reproducibility. Just to clarify: Do you have a preferred data source (broker API, Yahoo, Alpha Vantage, etc.)? Should the UI be desktop-based or a simple web dashboard? Please come to the chat box to discuss more about your project. Best regards Indresh Kushwaha

@ttobio69

Hi there, I read your requirements carefully, and I can build a stock-only algorithmic signal and risk tool that shows entry signals, take-profit zones, and stop-loss levels based on recent volatility. My approach would be to build it in Python using pandas, technical indicators, backtesting logic, and a simple desktop/web interface. The strategy rules will be fully systematic, transparent, and adjustable, so you can tune parameters like lookback period, ATR volatility, trend/mean-reversion filters, volume conditions, and risk settings without rewriting the core code. I’ll include back-test output, sample watchlist setup, clear documentation, and well-commented source code. The tool can be prepared for end-of-day data first, then connected to your preferred live/brokerage feed after testing. At this budget, I’ll focus on a clean MVP: strategy logic, back-test report, watchlist scanning, entry/TP/SL output, and a runnable Windows-friendly version. Cost: $30 || Timeline: 1 day Payment and timeline details can be discussed further to align with your expectations. I’d be happy to build a practical, transparent trading tool with no black-box logic or unrealistic claims. Best regards,

@mubashir021

Hello, your project for an algorithmic stock signal and risk tool sounds intriguing, especially with the focus on systematic trading without discretionary filters. I am Mubashir, a Full-Stack Developer with 6+ years building algorithmic trading tools. I understand that you need a reliable system that identifies buy opportunities and calculates entry signals, take-profit zones, and stop-loss levels based on volatility, tailored specifically for equity market behavior. 1. First, I will design the algorithmic trading model, focusing on trend-following and mean-reversion strategies that suit stock trading. 2. Then, I will implement the chosen technology stack, likely Python with pandas and TALib, ensuring it connects to live equity data and operates smoothly on Windows. 3. After that, I will create a prototype and conduct back-tests to validate the entry/exit levels, ensuring the results are reproducible. 4. Next, I will develop well-commented source code, documentation, and a user-friendly interface, allowing you to tweak parameters easily. 5. Finally, I will provide back-test results in your preferred format to match the default settings. Even if you’re not ready to proceed, I will provide a FREE detailed quotation and project proposal with a suggested roadmap at no cost. You can use this as a solid reference document with any other freelancer. >>> My Work: https://www.freelancer.com/u/mubashir021 <<< Drop me a message and let’s get this sorted. Mubashir

@tarasp53

Hi, I am Taras based in Ukraine. With commendable experience in both Full Stack development and AI systems, my skillset merges perfectly with your project needs. Thorough knowledge of data analysis with Python using libraries like pandas and TALib strengthens my capability to handle the required stock signal generation. As far as connectivity goes, I am familiar with .NET which would ensure seamless integration between the software and live or end-of-day equity data, ensuring you get the right information at the right time. Your emphasis on robustness resonates with my core approach to programming. Apart from code intricacies, I truly understand the nuances and market peculiarities of equity trading - be it session gaps, daily volume profiles or tick size quirks. With both trend-following and mean-reversion strategies up my sleeve, I can customize this tool to offer optimal results for your specific requirements. Lastly, delivering a fine-tuned product without compromising quality is more important for me than just meeting strict deadlines. This will allow us the freedom to work together in a flexible manner through different milestones such as research & model design till final UI polish- ensuring you get exactly what you need in a way that fits your schedule. Let's connect soon to discuss how we can turn your idea into an efficient system! Thanks!

@dmytrom99pro

Hello, As a seasoned professional in building scalable, AI-enhanced applications and robust trading systems, I am confident that I am the ideal candidate for your Algorithmic Stock Signal & Risk Tool. With over a decade's worth of experience, I have successfully developed and delivered more than 10 production SaaS products. This includes platforms necessitating intense real-time data processing like live dashboards and high-throughput notification engines - aligning perfectly with the project's objectives. Working with C# and Python, your preferred tech stacks, I will design an architecture prioritizing low-latency, high-concurrency, and smooth user experience. My proficiency in C# programming marvelously harmonized with '.NET' allows me to craft intricate platforms like yours requiring systematic trading decisions through algorithmic models. Furthermore, another reason why I am excited for this project is my familiarity with the trading world. I understand that there are nuances unique to the equity markets such as volume profiles, tick size quirks, and session gaps. My extensive knowledge in this domain will ensure that not only do we meet your requirements but that we'll do it in a way that tunes the logic specifically for equity market behavior. And since you aim for transparency, my deliverables will include well-commented source code alongside detailed documentation to ensure that you can comprehensively understand the syste Thanks!