Shorting at High: Algo Trading Strategy in R

Shorting at High - Algo Trading Strategy in R

By Milind Paradkar

Milind ParadkarMilind began his career in Gridstone Research, building earnings models and writing earnings notes for NYSE listed companies, covering Technology and REITs sectors. Milind has also worked at CRISIL and Deutsche Bank, where he was involved in modeling of Structured Finance deals covering Asset Backed Securities (ABS), and Collateralized Debt Obligations (CDOs) for the US and EMEA region.

Milind holds a MBA in Finance from the University of Mumbai, and a Bachelor’s degree in Physics from St. Xavier’s College, Mumbai.


The Executive Programme in Algorithmic Trading (EPAT) exposed me to all the requisite subjects needed to learn algorithmic trading. As part of the EPAT project work I tried coding many strategies. Since I am a novice to algorithmic trading I wanted to code the simplest, and the most basic strategies. Although simple and basic, one should not underestimate the power of such strategies, as they can generate good returns.

“Shorting at High” was one of the strategies that I formulated for my project work. This post explains the strategy in brief and the coding part. I welcome the readers to give suggestions, improvise or to use the strategy.

Strategy in brief

The strategy is to short the best stocks which cross the set percentage threshold on the upside (say 8%-9%) during intraday trading. The expectation for the shorted stocks is to fall by an amount as predicted in the metrics sheet which is generated upon executing the code.

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