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Your Workflow on Developing and Testing New Trading Algorithms

Quantitative Model

I recently struggle on creating good trading strategy...    
Just wanna to know what is your workflow for developing and testing new trading algorithms? From idea generation to live deployment, what steps do you follow to ensure your algorithms are robust and effective? Any good factors or tools that you find usuful? .
1 0
Posted on : 2024-08-02 03:54:34.118643
 
Bumblebee
Well. Here’s how I approach it:

  • Idea Generation: I read a lot of financial literature and sometimes get ideas from academic journals or whitepapers.
  • Hypothesis Testing: I write down my hypothesis and the expected outcomes before I even look at the data.
  • Data Collection: I download historical data from Yahoo Finance or ALGOGENE to my local PC.
  • Data Analysis: I then use Python for data analysis and model training. Libraries like pandas, NumPy, statsmodels are very useful.
  • Backtesting: After getting some preliminary results, I will implement on ALGOGENE for detailed backtesting and optimization. They are flexible and have a lot of built-in features.
  • Validation: I validate my strategy on out-of-sample data to ensure it’s not overfitted.
  • Paper Trading: I use paper trading accounts to test the strategy in real market conditions without risking real money.
  • Live Trading: Once I’m confident, I go live but monitor the strategy closely to make adjustments as needed.
  • Tools: I use Jupter Notebook for interactive data analysis. ALGOGENE also supports version control and collaboration. 
1 0
Posted on : 2024-08-03 06:20:21.763853



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