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Articles 1 - 4 of 4
Full-Text Articles in Business
Data Driven Value-At-Risk Forecasting Using A Svr-Garch-Kde Hybrid, Marius Lux, Wolfgang Karl Hardle, Stefan Lessmann
Data Driven Value-At-Risk Forecasting Using A Svr-Garch-Kde Hybrid, Marius Lux, Wolfgang Karl Hardle, Stefan Lessmann
Sim Kee Boon Institute for Financial Economics
Appropriate risk management is crucial to ensure the competitiveness of financial institutions and the stability of the economy. One widely used financial risk measure is value-at-risk (VaR). VaR estimates based on linear and parametric models can lead to biased results or even underestimation of risk due to time varying volatility, skewness and leptokurtosis of financial return series. The paper proposes a nonlinear and nonparametric framework to forecast VaR that is motivated by overcoming the disadvantages of parametric models with a purely data driven approach. Mean and volatility are modeled via support vector regression (SVR) where the volatility model is motivated …
Frm Financial Risk Meter, Andrija Mihoci, Michael Althof, Cathy Yi-Hsuan Chen, Wolfgang Karl Hardle
Frm Financial Risk Meter, Andrija Mihoci, Michael Althof, Cathy Yi-Hsuan Chen, Wolfgang Karl Hardle
Sim Kee Boon Institute for Financial Economics
A systemic risk measure is proposed accounting for links and mutual dependencies between financial institutions utilizing tail event information. Financial Risk Meter (FRM) is based on least absolute shrinkage and selection operator quantile regression designed to capture tail event co-movements. The FRM focus lies on understanding active set data characteristics and the presentation of interdependencies in a network topology. Two FRM indices are presented, namely, FRM@Americas and FRM@Europe. The FRM indices detect systemic risk at selected areas and identify risk factors. In practice, FRM is applied to the return time series of selected financial institutions …
Teres: Tail Event Risk Expectile Shortfall, Andrija Mihoci, Wolfgang Karl Hardle, Cathy Yi-Hsuan Chen
Teres: Tail Event Risk Expectile Shortfall, Andrija Mihoci, Wolfgang Karl Hardle, Cathy Yi-Hsuan Chen
Sim Kee Boon Institute for Financial Economics
We propose a generalized risk measure for expectile-based expected shortfall estimation. The generalization is designed with a mixture of Gaussian and Laplace densities. Our plug-in estimator is derived from an analytic relationship between expectiles and expected shortfall. We investigate the sensitivity and robustness of the expected shortfall to the underlying mixture parameter specification and the risk level. Empirical results from the US, German and UK stock markets and for selected NASDAQ blue chip companies indicate that expected shortfall can be successfully estimated using the proposed method on a monthly, weekly, daily and intra-day basis using a 1-year or 1-day time …
Investing With Cryptocurrencies: A Liquidity Constrained Investment Approach, Simon Trimborn, Mingyang Li, Wolfgang Karl Hardle
Investing With Cryptocurrencies: A Liquidity Constrained Investment Approach, Simon Trimborn, Mingyang Li, Wolfgang Karl Hardle
Sim Kee Boon Institute for Financial Economics
Cryptocurrencies have left the dark side of the finance universe and become an object of study for asset and portfolio management. Since they have low liquidity compared to traditional assets, one needs to take into account liquidity issues when adding them to a portfolio. We propose a Liquidity Bounded Risk-return Optimization (LIBRO) approach, which is a combination of risk-return portfolio optimization under liquidity constraints. Cryptocurrencies are included in portfolios formed with stocks of the S&P 100, US Bonds, and commodities. We illustrate the importance of the liquidity constraints in an in-sample and out-of-sample study. LIBRO improves the weight optimization in …