Custom Algo for Stock Market Trading - 30/01/2026 07:06 EST

@Milvetti

Hi, we can help you with your DhanHQ Python options averaging bot with Fibonacci scaling and profit-target exits. We offer lifetime bug fix guarantee. As Milvetti, we help traders automate their strategies. Price is an estimate and may vary by scope.

@NEHABHAT92

As a seasoned professional with 9+ years of experience in web and mobile app development and proficient in Python, I am confident that I can build the custom algorithm tailored specifically to your unique stock trading requirements. My familiarity with data analysis and the capability to create complex financial algorithms makes me an ideal candidate for this task. Having an in-depth knowledge of Python, which I see you use as well, I understand the workflow and can efficiently develop effective solutions using it. Moreover, being knowledgeable about the intricate nature of the stock market, including Fibonacci series, puts me in the ideal position to understand and translate your strategy into an automated trading system. Furthermore, my proposed solution comes with a number of benefits such as cost efficiency, cross-browser compatibility, free after-delivery support for three months, and assistance in finding reasonably priced hosting and domain services. By choosing me, you will not only be choosing proficiency in coding but also a partner committed to ensuring your satisfaction and delivering on predetermined targets. I am keen to bring your ideas to reality with quality workmanship and an understanding of your unique needs. Let's make your vision happen together!

@tsoene

Hi, I have gone thru your job post and I am available to perform the task. I am a trader myself and a developer too; all together having over 15yrs of market experience. I am well placed to deliver it to your satisfaction. You can also be assured of after service support. Let's get working on it asap!

@prashanpatel557

Hello, I can help you convert this custom options trading logic into a clear, rule-based Python algo that works with DhanHQ (v2.2.0rc1) and is easy for a non-technical trader to operate and understand. My approach • First, I will formalize your rules (Fibonacci lot sizing, dual-leg entry, deep-down logic, averaging, partial square-off, full exit, max 8 iterations) into an exact step-by-step flow so nothing is ambiguous. • Build a modular Python script: • Order manager (CALL/PUT legs handled independently) • Fibonacci lot controller • Average price & combined P&L calculator • Exit logic (target-based and recovery-based) • Use DhanHQ API for live prices and order placement. • All values (30-point gap, target ₹5000, max iterations, fib sequence) will be editable from a config file, not hard-coded. • Clear console logs so you always know which iteration you’re in, avg price, and profit. What you’ll get • Clean, commented Python code • Config file for all parameters • Safety checks (max iteration, API failure handling) • Step-by-step setup guide for Dhan I’ve built Indian options algos with averaging and recovery logic before and understand the risks involved, so execution control and clarity will be a priority. Happy to discuss and refine the logic once before coding to ensure it matches your exact intent.

@Algokage

Hello, With 5+ years of experience in algorithmic trading and Python development, I can create a custom algo tailored to your Fibonacci-based strategy. I’ll integrate your DhanHQ 2.2.0rc1 setup, ensuring seamless execution of simultaneous call/put purchases, dynamic averaging, and iterative conditions as outlined. My approach focuses on precision and efficiency, aligning with your trading logic. Let’s refine details to ensure it meets your needs. Message me for samples of similar projects. Thanks, Adegoke. M

@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 I can deliver any project in Trading. Readymade setups for Python available

@mrkk4ever

Dear Client I saw your requirements regarding to develop a auto trading bot for stock market of India based on Fibonacci Retracement using dhan api in python. I can develop this application ASAP based your requirements. I developed many applications is similar to your requirements. Such as indicators, analysis applications, auto trading bot for various exchanges. Let share further details. Thanks and Regards Kannadasan K

@abbas021

Hi, I always focus on understanding the full scope of a project before getting started, ensuring that every detail aligns with your goals and expectations. We are an expert team which have many years of experience on PHP, C Programming, Python, Software Architecture, Metatrader, Financial Analysis, Data Science, Data Analysis Lets connect in chat so that We discuss further. Regards

@targaryen007

Hello, I can develop your custom options trading algorithm using Python with DhanHQ 2.2.0rc1 API, exactly as per your Fibonacci lot scaling and hedge logic requirements. What I will implement: ✔ Simultaneous Buy of 1 CE + 1 PE ✔ Fibonacci-based lot scaling (1,1,2,3,5…) ✔ Auto-detection of weaker leg and additional buying at predefined point difference ✔ Real-time average price calculation of both legs ✔ Global profit monitoring (auto exit when ≥ ₹5000 or your defined value) ✔ Deepdown condition logic (30-point drop trigger, configurable) ✔ Selective square-off of last position when recovery occurs ✔ Full exit if price crosses average level ✔ Loop until full exit or max 8 iterations ✔ Configurable parameters (points gap, profit target, iterations) The system will include: Clean modular Python code Proper risk handling & order confirmation checks Logs for tracking each iteration Paper-trade testing support before live deployment Timeline: 5–7 days Support for setup & deployment included. Let’s discuss your exact trigger values and risk limits to finalize execution logic safely.

@syedabdullahh7

Hi, I’m AI/ML & Full-Stack Developer specializing in Agentic AI systems and intelligent automation. I have previously worked on trading automations. I understand market dynamics and can deliver quality solutions. Portfolio available on profile. PRICE NEGOTIABLE ➡️ Fast delivery | 100% satisfaction

@ahmeds0074

Expert Python Developer | Ready-to-Deploy Fibonacci Algo for DhanHQ (Tested & Debugged) "Hello, I have already analyzed your project requirements and, more importantly, I have already built and tested the core logic on a local environment. Why choose me for this task? Issue Solved: I have already fixed the common missing positional argument: 'price' error that occurs with DhanHQ 2.2.0rc1 market orders. Precise Fibonacci Scaling: Your 8-iteration sequence (1, 1, 2, 3, 5, 8, 13, 21) is fully implemented and verified. Risk Management: The script includes the logic for simultaneous Call/Put buying (Hedged) and monitors the 5000 INR profit target to auto-close positions. Zero Latency: The code is optimized to handle the 30-point drop triggers efficiently. I am ready to hop on a quick call or chat to show you the script running in the terminal. I can deliver the final, clean, and commented code immediately. Best regards, Ahmed"

@chaieb4

During my time at Airbnb, I was part of the Guest Experience team, where I focused on improving the scalability, performance, and reliability of the search and booking flow used by millions of users worldwide. I developed and maintained reusable React components within Airbnb’s internal design system, ensuring consistency and high-quality user interfaces across products. On the backend, I optimized microservices built with Java and Ruby on Rails to support high-concurrency traffic. I implemented Redis caching to significantly reduce API latency and improve overall system responsiveness. I also designed and executed A/B tests to measure and improve checkout conversion rates based on real user behavior. To ensure long-term stability and rapid delivery, I worked extensively with CI/CD pipelines, automated testing, and monitoring systems, maintaining zero-downtime deployment standards. I collaborated closely with product managers, designers, and other engineers to deliver features that enhanced the end-to-end user journey while meeting strict performance and reliability requirements. Skills: Cybersecurity · Software Development · Full-Stack Development · Artificial Intelligence (AI)