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Table Of Contents
Algorithmic Short Selling with Python - Second Edition
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This chapter focuses on refining the investment universe for short-selling by filtering out ideas that are theoretically attractive but practically dangerous. Short-selling is asymmetric by nature: liquidity evaporates; crowding creates explosive short squeeze risks, and corporate actions can distort prices for long periods. As a result, success on the short side depends less on finding "good stories" and more on weeding out bad setups. This chapter introduces the fundamental and risk-based filters required to build a robust, tradable short universe.
By the end of this chapter, you will be able to systematically narrow a broad equity universe into a short-ready subset, avoid structural short-selling hazards, interpret valuation and beta signals in context, and understand how these filters support more resilient long/short portfolio construction.
In this chapter, we will cover the following topics:
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