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Building an Options Portfolio with Deep Learning.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Building an Options Portfolio with Deep Learning./
作者:	Jorling, Dylan Kinach.
面頁冊數:	1 online resource (43 pages)
附註:	Source: Masters Abstracts International, Volume: 84-11.
Contained By:	Masters Abstracts International84-11.
標題:	Statistics. -
電子資源:	click for full text (PQDT)
ISBN:	9798379577179

Building an Options Portfolio with Deep Learning.
Jorling, Dylan Kinach.

Building an Options Portfolio with Deep Learning. - 1 online resource (43 pages)

Source: Masters Abstracts International, Volume: 84-11.

Thesis (M.A.S.)--University of California, Los Angeles, 2023.

Includes bibliographical references

Recent applications of powerful machine learning models within the field of portfolio optimization have shown promising results. This paper explores the application of similar methods to create an actively managed options portfolio, rather than a traditional portfolio containing stocks and ETFs. Although financial options are popular assets amongst both retail and institutional investors, they are almost exclusively traded for one of two purposes: hedging or intra-asset speculation. Little, if any, literature exists on the topic of inter-asset options strategies. Using percent change in implied volatility data as a proxy for single-day straddle returns, various machine learning models are trained by directly optimizing the Sharpe Ratio-a risk-adjusted return metric. The models output daily volatility positions in 315 underlying assets thereby creating the Options Portfolio. Results show significant potential in such a strategy, with the Attention Transformer model yielding a before-cost average annual Sharpe Ratio of 10.76 compared to the GRU model of 6.41, the LSTM model of 5.07, and the equal-weighted baseline of 0.53.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798379577179Subjects--Topical Terms:

556824
Statistics.
Subjects--Index Terms:

Portfolio optimizationIndex Terms--Genre/Form:

554714
Electronic books.

Building an Options Portfolio with Deep Learning.
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