Portfolio Risk Management with Simplectica Covariance Matrix
In investment portfolio management, every investor generally wishes to obtain the highest possible expected returns for a given level of risk, as represented by the volatility of the returns of the investor’s portfolio. Therefore, in order to make rational capital allocation decisions, the investor must predict the volatility of any given portfolio. In turn, this requires knowledge of the covariance matrix of the returns of all available securities. Simplectica Covariance Matrix (SCM) is the first commercially available dataset providing an accurate measurement of realized single-ticker variance and realized pairwise covariance for all pairs of tickers in the stock market. Unlike multi-factor models, which explain volatility and correlations through a small number of theoretically determined factors (e.g. market-wide returns, momentum, size, etc.), that result in a low-rank approximation, SCM directly measures the full-rank covariance structure of the market. On account of the relative stability of this covariance structure over time, SCM, though retrospective in nature, can be used with great efficacy to model portfolio volatility and compress said volatility through hedging
Year of publication: |
[2023]
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Authors: | Thaeler, Jordan |
Publisher: |
[S.l.] : SSRN |
Subject: | Risikomanagement | Risk management | Theorie | Theory | Portfolio-Management | Portfolio selection | Korrelation | Correlation | Risikomaß | Risk measure |
Saved in:
freely available
Extent: | 1 Online-Ressource (9 p) |
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Type of publication: | Book / Working Paper |
Language: | English |
Notes: | Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments May 5, 2023 erstellt |
Other identifiers: | 10.2139/ssrn.4453479 [DOI] |
Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10014350215
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