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Finding Alphas: A Quantitative Approach to Building Trading Strategies by Igor Tulchinsky

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10 Backtest – Signal or Overfitting

By Peng Yan

Traditionally, an alpha is defined as the active return from an investment after risk adjustment is applied. In this chapter, alpha means a quantitative model to predict future investment returns.

BACKTEST

The start of an alpha design can be a hypothesis, a paper, a story, an inspiration, or just a random idea.

Ideas Need to be Tested

Similar to academic research, many assumptions are wrong, many trials futile. Only a few of them will be successful. We are human, and market participants are human as well. Humans are different as they have different ideas; only a small portion of those ideas may generate profits consistently in the real environment. At times you will have a strong belief that the model will work, yet after testing, it is proven not true or vice versa.

Asset class prices can be affected by many factors, either directly or indirectly. One idea may affect just one and neglect others.

Simulation and Backtest

We call the process of testing idea simulation. There are different simulation methods, such as:

  1. Monte Carlo simulation, which simulates the various sources of uncertainty that are affecting instrument values to get the range of resultant outcomes.
  2. Pricing model, which calculates asset price (Black-Scholes model is an example of a pricing model for options).
  3. Explanation model, which builds models to explain what happened in history.

In our working environment, simulation means backtest. That is, when there ...

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