Search Results - subject:"volatility forecasting."

Idiosyncratic volatility forecasting in the stock market of Saudi Arabia

Bley, Jorg; Saad, Mohsen M. - In: Emerging markets finance & trade : a journal of the … 51 (2015) 6, pp. 1342-1357

Persistent link: https://www.econbiz.de/10011561300

Long-memories and mean breaks in realized volatilities

Song, Hyejin; Shin, Dong-wan - In: Applied economics letters 22 (2015) 16/18, pp. 1273-1280

Persistent link: https://www.econbiz.de/10011380139

Does anything beat 5-minute RV? : a comparison of realized measures across multiple asset classes

Liu, Lily Y.; Patton, Andrew J.; Sheppard, Kevin - In: Journal of econometrics 187 (2015) 1, pp. 293-311

Persistent link: https://www.econbiz.de/10011499439

The role of implied volatility in forecasting future realized volatility and jumps in foreign exchange, stock, and bond markets

Busch, Thomas; Christensen, Bent Jesper; Nielsen, … - 2008

We study the forecasting of future realized volatility in the foreign exchange, stock, and bond markets from variables in the information set, including implied volatility backed out from option prices. Realized volatility is separated into its continuous and jump components, and the...

Persistent link: https://www.econbiz.de/10010290353

The Role of Implied Volatility in Forecasting Future Realized Volatility and Jumps in Foreign Exchange, Stock, and Bond Markets

Busch, Thomas; Christensen, Bent Jesper; Nielsen, … - Economics Department, Queen's University - 2008

Persistent link: https://www.econbiz.de/10004979472

Support Vector Regression Based GARCH Model with Application to Forecasting Volatility of Financial Returns

Chen, Shiyi; Jeong, Kiho; Härdle, Wolfgang - Sonderforschungsbereich 649: Ökonomisches Risiko, … - 2008

financial forecasting. This paper deals with the application of SVR in volatility forecasting. Based on a recurrent SVR, a GARCH … in volatility forecasting. Based on a recurrent SVR, a GARCH method is proposed and is compared with a moving average …: recurrent support vector regression; GARCH model; volatility forecasting JEL classification: C45, C53, G32 # This work was …

Persistent link: https://www.econbiz.de/10005677938

Forecasting S&P 500 Daily Volatility using a Proxy for Downward Price Pressure

Visser, Marcel P. - Volkswirtschaftliche Fakultät, … - 2008

This paper decomposes volatility proxies according to upward and downward price movements in high-frequency financial data, and uses this decomposition for forecasting volatility. The paper introduces a simple Garch-type discrete time model that incorporates such high-frequency based statistics...

Persistent link: https://www.econbiz.de/10005619651

Option based forecasts of volatility: An empirical study in the DAX index options market

Muzzioli, Silvia - Dipartimento di Economia "Marco Biagi", Università … - 2008

Option based volatility forecasts can be divided into “model dependent” forecast, such as implied volatility, that is obtained by inverting the Black and Scholes formula, and “model free” forecasts, such as model free volatility, proposed by Britten-Jones and Neuberger (2000), that do...

Persistent link: https://www.econbiz.de/10005636179

Forecasting Stock Market Volatilities Using MIDAS Regressions: An Application to the Emerging Markets

Alper, C. Emre; Fendoglu, Salih; Saltoglu, Burak - Volkswirtschaftliche Fakultät, … - 2008

We explore the relative weekly stock market volatility forecasting performance of the linear univariate MIDAS …

Persistent link: https://www.econbiz.de/10005789569

Modeling the daily electricity price volatility with realized measures

Frömmel, Michael; Han, Xing; Kratochvil, Stepan - In: Energy Economics 44 (2014) C, pp. 492-502

We propose using Realized GARCH-type models to estimate the daily price volatility in the EPEX power markets. The model specifications extract the volatility-related information from realized measures, which improves the in-sample fit of the data. More importantly, evidence on the out-of-sample...

Persistent link: https://www.econbiz.de/10011100137