Abstract
Quantitative analysis as a technique of rendering market conditions using an arithmetic value has been employed by several investors for identifying trading opportunities. Quantitative Trading (QT) Strategies are further aggrandized by the victorious amalgamation of finance with AI technologies. However, existing studies fail to leverage elementary finance notions for devising a portfolio optimization algorithm using rudimentary QT strategies to generate maximum profits. Such a portfolio optimization algorithm can be further optimized to require a minimum upfront investment, by exploiting the process of initially going SHORT on a financial asset, and using the generated profit to subsequently enter a LONG on another financial asset. In this paper, we propose Kairos, a computationally-inexpensive, flexible framework for exploiting LONG and SHORT QT strategies for portfolio optimization which minimizes required investment and maximizes returns.
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