Next Article in Journal
Some Improvements of the Cauchy-Schwarz Inequality Using the Tapia Semi-Inner-Product
Next Article in Special Issue
Generalized Market Uncertainty Measurement in European Stock Markets in Real Time
Previous Article in Journal
Transportation Optimization Models for Intermodal Networks with Fuzzy Node Capacity, Detour Factor, and Vehicle Utilization Constraints
Previous Article in Special Issue
Longer-Term Forecasting of Excess Stock Returns—The Five-Year Case
Article

Portfolio Risk Assessment under Dynamic (Equi)Correlation and Semi-Nonparametric Estimation: An Application to Cryptocurrencies

1
Department of Economics and Economic History and IME, Faculty of Economics and Business, University of Salamanca, Campus Miguel de Unamuno (Edif. F.E.S.), 37007 Salamanca, Spain
2
School of Management, Universidad de los Andes, Calle 21 No. 1-20, Bogotá 111711, Colombia
3
School of Organizations, Economy and Society, Westminster Business School, University of Westminster, 35 Marylebone Road, London NW1 5LS, UK
*
Author to whom correspondence should be addressed.
Mathematics 2020, 8(12), 2110; https://doi.org/10.3390/math8122110
Received: 21 October 2020 / Revised: 13 November 2020 / Accepted: 18 November 2020 / Published: 26 November 2020
The semi-nonparametric (SNP) modeling of the return distribution has been proved to be a flexible and accurate methodology for portfolio risk management that allows two-step estimation of the dynamic conditional correlation (DCC) matrix. For this SNP-DCC model, we propose a stepwise procedure to compute pairwise conditional correlations under bivariate marginal SNP distributions, overcoming the curse of dimensionality. The procedure is compared to the assumption of dynamic equicorrelation (DECO), which is a parsimonious model when correlations among the assets are not significantly different but requires joint estimation of the multivariate SNP model. The risk assessment of both methodologies is tested for a portfolio of cryptocurrencies by implementing backtesting techniques and for different risk measures: value-at-risk, expected shortfall and median shortfall. The results support our proposal showing that the SNP-DCC model has better performance for lower confidence levels than the SNP-DECO model and is more appropriate for portfolio diversification purposes. View Full-Text
Keywords: Gram–Charlier series; DCC; DECO; backtesting; cryptocurrencies Gram–Charlier series; DCC; DECO; backtesting; cryptocurrencies
Show Figures

Figure 1

MDPI and ACS Style

Jiménez, I.; Mora-Valencia, A.; Ñíguez, T.-M.; Perote, J. Portfolio Risk Assessment under Dynamic (Equi)Correlation and Semi-Nonparametric Estimation: An Application to Cryptocurrencies. Mathematics 2020, 8, 2110. https://doi.org/10.3390/math8122110

AMA Style

Jiménez I, Mora-Valencia A, Ñíguez T-M, Perote J. Portfolio Risk Assessment under Dynamic (Equi)Correlation and Semi-Nonparametric Estimation: An Application to Cryptocurrencies. Mathematics. 2020; 8(12):2110. https://doi.org/10.3390/math8122110

Chicago/Turabian Style

Jiménez, Inés, Andrés Mora-Valencia, Trino-Manuel Ñíguez, and Javier Perote. 2020. "Portfolio Risk Assessment under Dynamic (Equi)Correlation and Semi-Nonparametric Estimation: An Application to Cryptocurrencies" Mathematics 8, no. 12: 2110. https://doi.org/10.3390/math8122110

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop