An Algorithmic Trading Strategy to Balance Profitability and Risk

Guillermo Peña

A chapter in Big Data in Finance, 2022, pp 35-53 from Springer

Abstract: Abstract This chapter proposes an algorithmic trading (AT) strategy based on a newly developed investment indicator called the “Balanced Investment Indicator” (BII), which has been shown to be able to balance risk and profitability accurately. This indicator is crucial for developing an AT strategy that allows algorithmic traders to use big data to analyze portfolios and seek the BII algorithm's highest value. The chapter reviews and analyzes current AT strategies and compares them with the proposed strategy of the chapter. The results of this comparison show that the indicator performs strongly, as its investment recommendations coincide in some cases with relevant institutions, such as the Bank of America. For investors, this chapter provides decision-making tools for selecting different portfolios that balance profitability with default risk.

Keywords: Algorithmic trading; Investment; High-frequency trading; Big data; Bid-ask spread; Financial services; G11; G12; G21 (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-12240-8_3

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DOI: 10.1007/978-3-031-12240-8_3

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