Python Intraday Strategy Automation
Summary
Freelancer Client is hiring: Python Intraday Strategy Automation.
Location: Remote
I have a clearly-defined intraday and positional trading system written up in a text file. Your task is to turn those rules into clean, production-ready Python that connects to my Broker API, pulls live market data, and produces real-time trade signals in OpenAlgo.
Parse the requirement document and translate each rule into code
Stream price and volume data directly from the broker’s REST/WebSocket endpoints (no Yahoo, AlphaVantage, etc.)
Calculate the indicators and conditions that trigger long, short, or exit signals
Structure the logic so I can call a single function and receive today’s actionable signals in JSON/DataFrame form
Skills: Python, Algorithm, Software Architecture, Financial Analysis, API, NumPy, Data Analysis, Pandas
Budget: $4000–$6000 USD
Source: Freelancer Client via Remote / Online. Apply on the source website.
Original
I have a clearly-defined intraday and positional trading system written up in a text file. Your task is to turn those rules into clean, production-ready Python that connects to my Broker API, pulls live market data, and produces real-time trade signals in OpenAlgo.
Key points you’ll tackle
• Parse the requirement document and translate each rule into code
• Stream price and volume data directly from the broker’s REST/WebSocket endpoints (no Yahoo, AlphaVantage, etc.)
• Calculate the indicators and conditions that trigger long, short, or exit signals
• Structure the logic so I can call a single function and receive today’s actionable signals in JSON/DataFrame form
• Keep latency low and handle basic error/connection retries
Deliverables
1. Well-commented Python module(s) or Jupyter notebook implementing the strategy
2. A short README explaining setup, required libraries, and how to run or import the signal generator
3. Sample output from at least one trading day showing that each rule fires correctly
Acceptance criteria
• All rules from the text file are covered and match expected signal counts in a dry-run test
• Code passes a quick back-fill check on at least three months of intraday data without crashing
• Functions are PEP-8 compliant and use docstrings for clarity
If you’re fluent in Python, comfortable with broker APIs, and can deliver concise, reliable code, let’s make this strategy trade-ready.
Location & Details
Apply on source →About this listing
This remote opportunity was imported from Freelancer and is shown here for discovery. To apply, follow the link to the original posting.