We analyze the economic benefits of several covariance estimation approaches on a tactical asset-allocation problem in the presence of high-frequency return data. Our analysis confirms that the use of robust-to-noise and asynchronicity estimators not only gives statistically more accurate results, but the statistical efficiency is reflected into a financial benefit in most cases.
ALLAJ, Erindi; MANCINO, Maria Elvira. On asset-allocation and high-frequency data: are there financial gains from using different covariance estimators?. Communications in Statistics-Simulation and Computation, 2021, 50.12: 4413-4441 / Allaj, Erindi; Maria Elvira, Mancino. - In: COMMUNICATIONS IN STATISTICS. SIMULATION AND COMPUTATION. - ISSN 1532-4141. - --:(2021). [10.1080/03610918.2019.1643882]
ALLAJ, Erindi; MANCINO, Maria Elvira. On asset-allocation and high-frequency data: are there financial gains from using different covariance estimators?. Communications in Statistics-Simulation and Computation, 2021, 50.12: 4413-4441.
ALLAJ, ERINDI;
2021-01-01
Abstract
We analyze the economic benefits of several covariance estimation approaches on a tactical asset-allocation problem in the presence of high-frequency return data. Our analysis confirms that the use of robust-to-noise and asynchronicity estimators not only gives statistically more accurate results, but the statistical efficiency is reflected into a financial benefit in most cases.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
