Portfolio management with big data

Francisco Peñaranda () and Enrique Sentana
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Francisco Peñaranda: Queens College CUNY, https://www.qc.cuny.edu/

Working Papers from CEMFI

Abstract: The purpose of this survey is to summarize the academic literature that studies some of the ways in which portfolio management has been affected in recent years by the availability of big datasets: many assets, many characteristics for each of them, many macro predictors, and various sources of unstructured data. Thus, we deliberately focus on applications rather than methods. We also include brief reviews of the financial theories underlying asset management, which provide the relevant background to assess the plethora of recent contributions to such an active research field.

Keywords: Conditioning information; intertemporal portfolio decisions; machine learning; mean-variance analysis; stochastic discount factors. (search for similar items in EconPapers)
JEL-codes: C55 G11 G12 G17 (search for similar items in EconPapers)
Date: 2024-06
New Economics Papers: this item is included in nep-big, nep-cmp and nep-fmk
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Working Paper: Portfolio management with big data (2024)
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Persistent link: https://EconPapers.repec.org/RePEc:cmf:wpaper:wp2024_2411

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