Publication Type

Journal Article

Version

acceptedVersion

Publication Date

10-2020

Abstract

This research utilized the intrinsic quality of European floating strike lookback call options, alongside selected return and volatility parameters, in a K-means clustering environment, to recommend an alpha generative trading strategy. The result is an elegant easy-to-use alpha strategy based on the option mechanisms which identifies investment assets with high degree of significance. In an upward trending market, the research had identified European floating strike lookback call option as an evaluative criterion and investable asset, which would both allow investors to predict and profit from alpha opportunities. The findings will be useful for (i) buy-side investors seeking alpha generation and/or hedging underlying assets, (ii) sell-side product manufacturers looking to structure the European floating strike lookback call options, and (iii) market trading platforms looking to introduce new products and enhance liquidity of the product.

Keywords

Options, volatility measures, statistical methods, simulations, machine learning, MITB student

Discipline

Data Science | Finance and Financial Management | Numerical Analysis and Scientific Computing

Research Areas

Data Science and Engineering

Publication

Journal of Financial Data Science

Volume

2

Issue

4

First Page

59

Last Page

70

ISSN

2640-3943

Identifier

10.3905/jfds.2020.1.043

Publisher

Portfolio Management Research

Embargo Period

6-7-2021

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.3905/jfds.2020.1.043

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