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Selected techniques of detecting structural breaks in financial volatility

Stawiarski, Bartosz - In: E-Finanse : finansowy kwartalnik internetowy 11 (2015) 1, pp. 32-43

breaks) in the volatility of financial time series. Comparative study of three techniques: ICSS, NPCPM and Cheng's algorithm … breaks in volatility, while Cheng's technique works well only when a single break occurs. …

Persistent link: https://www.econbiz.de/10011393264

Model uncertainty and forecast combination in high-dimensional multivariate volatility prediction

Amendola, Alessandra; Storti, Giuseppe - In: Journal of forecasting 34 (2015) 2, pp. 83-91

Persistent link: https://www.econbiz.de/10011305317

Commodity value-at-risk modeling : comparing riskmetrics, historic simulation and quantile regression

Steen, Marie; Westgaard, Sjur; Gjølberg, Ole - In: The journal of risk model validation 9 (2015) 2, pp. 49-78

Persistent link: https://www.econbiz.de/10011326305

How candlestick features affect the performance of volatility forecasts : evidence from the stock market

Su, Jung-bin - In: The European journal of finance 21 (2015) 4/6, pp. 486-506

Persistent link: https://www.econbiz.de/10010528953

How can long memory in volatility be eliminated in portfolio optimization : an empirical evidence using copulas

Mzoughi, Hela; Mansouri, Fayçal - In: Journal of quantitative economics : official journal of … 11 (2013) 1/2, pp. 1-14

Persistent link: https://www.econbiz.de/10010338365

Asymmetric connectedness on the US stock market : bad and good volatility spillovers

Baruník, Jozef; Kočenda, Evžen; Vácha, Lukáš - 2015

This paper suggests how to quantify asymmetries in volatility spillovers that emerge due to bad and good volatility … stocks at the disaggregate level. Moreover, the spillovers of bad and good volatility are transmitted at different magnitudes …

Persistent link: https://www.econbiz.de/10010509638