The Best Investment Strategy
What if I told you that with the best investment strategy, you could:
- Buy and hold SPY when it is above the 200 days moving average.
- Sell your SPY holding and buy TLT when SPY is below the 200 moving average.
I present you with an analysis from backtesting historical data showing that this strategy continuously has been beating the market (SPY).
What does all that mean?
If this doesn’t make any sense, don’t worry! We will cover all of this information in the e-book.
For a simple overview:
- The first chart represents the investment strategy (backtest) returning better than the market (SPY).
- The CAGR chart represents the yearly return, which is higher for the investment strategy at 10.2%.
- The Drawdown chart represents the most significant loss. Therefore, the backtest is also better there.
- The Volatility chart illustrates how unpredictable the price is. Once again, the backtest beats the market (SPY).
Can we trust that?
Actually, yes! We can use the same backtesting to validate the calculations.
. . . but there is a catch!
Did you know that Python can help you test your investment strategies?
You will learn how to analyze whether an investment strategy is solid and why some strategies look good under ideal circumstances, but cannot be applied generally.
This explains why you need to build the backtesting yourself.
What will this e-book teach you?
The main focus of this guide is to teach you the Python libraries Pandas, NumPy, and Matplotlib for backtesting investment strategies.
By the time you finish this eBook, you will have covered the following with practical code examples (available on GitHub):
- How to work with financial time series data.
- Read data from CSV files and directly from API.
- Visualize financial time series data with Matplotlib.
- Calculate return (CAGR), maximum drawdown, and volatility (backtesting performance).
- How to work with investment strategies.
- Backtesting investment strategies.
Simply, master all you need to know for backtesting investment strategies with Python.
Not only is this a free resource, but it’s a quality one. Great work Rune!Peter
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