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

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4 Alpha Design

By Scott Bender/Yongfeng He

An alpha is a method of making predictions about future asset price changes. For example, an alpha might be a computer program that predicts future returns of a particular set of stocks.

Alphas we cover in this chapter are fully systematic and can be expressed by a concrete piece of code. The alpha will typically make predictions at some periodic frequency, for example, once per day. Its predictions will then be represented by a number for each asset it intends to predict.

A simple alpha might be, for each day, assigning a prediction of +1 to all stocks that went down yesterday and –1 to all stocks that went up. This is a valid alpha for us because it systematically generates a specific prediction for a set of assets at a specific frequency.

Alphas are predictive models, but without a way to implement those predictions, there is no way to realize the potential profits that those predictions might generate. Typically, an alpha is utilized as a component of a trading strategy, which converts the alpha’s predictions into actual trading decisions. The strategy is largely driven by the combined predictions of its alphas, but it also considers practical issues such as transaction costs and portfolio risk before actually executing a trade.

CATEGORIZATION OF ALPHAS

Alphas may be categorized into three major groups according to the types of instruments traded, such as stocks, exchange-traded funds, currencies, futures, options and bonds, ...

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