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Stock index volatility forecasting with high frequency data

Hol Uspensky, Eugenie; Koopman, Siem Jan - 2002

improved ex-post volatility measurements but has also inspired research into their potential value as an informa-tion source … for longer horizon volatility forecasts. In this paper we explore the forecasting value of these high fre-quency series in … conjunction with a variety of volatility models for returns on the Standard & Poor's 100 stock index. We consider two so …

Persistent link: https://www.econbiz.de/10011326944

Performance of the multifractal model of asset returns (MMAR) : evidence from emerging stock markets

Günay, Samet - In: International Journal of Financial Studies : open … 4 (2016) 2, pp. 1-17

In this study, the performance of the Multifractal Model of Asset Returns (MMAR) was examined for stock index returns of four emerging markets. The MMAR, which takes into account stylized facts of financial time series, such as long memory, fat tails and trading time, was developed as an...

Persistent link: https://www.econbiz.de/10011474619

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

Chen, Shiyi - 2017

financial forecasting. This paper deals with the application of SVR in volatility forecasting. Based on a recurrent SVR, a GARCH … to forecast financial markets volatility. The real data in this study uses British Pound-US Dollar (GBP) daily exchange …

Persistent link: https://www.econbiz.de/10012966267

Hurst Dynamics of S&P500 Returns : Implications and Impact on Market Efficiency, Long Memory, Multifractality and Financial Crises Predictability

Vogl, Markus; Roetzel, Peter Gordon - 2021

In this study, we apply a rolling window approach to wavelet-filtered (denoised) S&P500 returns (2000–2020) to obtain time varying Hurst exponents. We analyse the dynamics of the Hurst exponents by applying statistical tests (e.g., for stationarity, Gaussianity and self-similarity), a...

Persistent link: https://www.econbiz.de/10013229642

Allowing for Jump Measurements in Volatility : A High-Frequency Financial Data Analysis of Individual Stocks

Papavassiliou, Vassilios G. - 2016

Following recent advances in the non-parametric realized volatility approach, we separately measure the discontinuous … volatility models. We analyze the distributional properties of the jump measures vis-à-vis the corresponding realized volatility … accuracy of high-frequency volatility models …

Persistent link: https://www.econbiz.de/10013004411

Forecasting leveraged loan market volatility using GARCH models

Keßler, Andreas - 2021

volatility. The study investigates whether the asymmetric effects of good and bad news on volatility is present and how … distributional assumptions affect the selection of GARCH models. Compared to two widely used historical volatility models, the simple … the forecasts of loan market volatility. The model comparison involves a regression-based approach, loss functions and …

Persistent link: https://www.econbiz.de/10013220294

Evaluation of forecasting methods from selected stock market returns

Mallikarjuna, M.; Rao, R. Prabhakara - In: Financial innovation : FIN 5 (2019) 40, pp. 1-16

Forecasting stock market returns is one of the most effective tools for risk management and portfolio diversification. There are several forecasting techniques in the literature for obtaining accurate forecasts for investment decision making. Numerous empirical studies have employed such methods...

Persistent link: https://www.econbiz.de/10012268500

Volatility and spillover analysis between cryptocurrencies and financial indices : a diagonal BEKK and DCC GARCH model approach in support of SDGs

Iuga, Iulia Cristina; Nerișanu, Raluca-Andreea; … - In: Cogent economics & finance 12 (2024) 1, pp. 1-36

This study explores the volatility spillover effects between clean and dirty cryptocurrencies and key financial indices … results reveal significant volatility spillovers from both clean and dirty cryptocurrencies, with clean cryptocurrencies such … volatility impacts on green finance indices. Furthermore, the persistent correlations identified through the DCC GARCH model …

Persistent link: https://www.econbiz.de/10015192299

Stylized facts and simulating long range financial

Davies, Laurie; Krämer, Walter - 2016

We propose a new method (implemented in an R-program) to simulate long-range daily stock-price data. The program reproduces various stylized facts much better than various parametric models from the extended GARCH-family. In particular, the empirically observed changes in unconditional variance...

Persistent link: https://www.econbiz.de/10011444067

Uusing the symmetric models garch (1.1) and garch-m (1.1) to investigate volatility and persistence for the european and us financial markets

Duță, Violeta - In: Financial studies 22 (2018) 1, pp. 64-86

In this paper, we used the GARCH (1,1) and GARCH-M (1,1) models to investigate volatility and persistence at daily … persistence of volatility, meaning that the conditional volatility tends to revert faster to the long-term mean than the other … statistically significant and positive (thus confirming the hypothesis that an increase in volatility leads an increase in future …

Persistent link: https://www.econbiz.de/10011964941