[See Description] Programming for Finance Part 3 - Back Testing Strategy | Summary and Q&A
TL;DR
Learn to create a finance algorithm using SMA crossover method with Python.
Key Insights
- ⌛ The initialize method is used for one-time initialization of the finance algorithm.
- 🍵 Handle data method calculates moving averages for trading decisions.
- 💂♂️ SMA crossover logic determines the buy/sell signals in the algorithm.
- ⚾ Buying shares is based on available cash divided by the current price.
- 😫 Selling shares is implemented using order_targets function for setting targets.
- 👣 The algorithm tracks various variables using the record function.
- 🛀 Performance comparison with benchmark is shown through backtesting results.
Transcript
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Questions & Answers
Q: What is the purpose of the initialize method in building the finance algorithm?
The initialize method is for one-time initialization, defining the security of interest for trading in the algorithm. Code under this method runs as part of initialization.
Q: How does the handle data method function in the finance algorithm?
The handle data method runs once per iteration of the time period, calculating moving averages based on daily data. It defines series based on the data frame for trading decisions.
Q: What logic is used in the algorithm to determine when to invest or trade?
The algorithm uses SMA crossover logic, checking if the 50-day moving average crosses above or below the 200-day moving average to signal price movements. It includes conditions to avoid unnecessary trades.
Q: How is the buying and selling of shares implemented in the finance algorithm?
Shares are bought based on available cash divided by the current price to determine the number of shares to purchase. Order and order_targets functions are used for buying and selling shares respectively.
Summary & Key Takeaways
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Tutorial on building a finance algorithm in Python.
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Explains initializing, handling data, and implementing logic.
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Demonstrates using SMA crossover for trading decisions.