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High-frequency volatility combine forecast evaluations: An empirical study for DAX
Journal of Finance and Data Science, 2017 This study aims to examine the benefits of combining realized volatility, higher power variation volatility and nearest neighbour truncation volatility in the forecasts of financial stock market of DAX.
Min Cherng Lee, Wencheong Chin
exaly +3 more sources
Volatility Forecast in Crises and Expansions [PDF]
Journal of Risk and Financial Management, 2015 We build a discrete-time non-linear model for volatility forecasting purposes. This model belongs to the class of threshold-autoregressive models, where changes in regimes are governed by past returns. The ability to capture changes in volatility regimes and using more accurate volatility measures allow outperforming other benchmark models, such as ...
exaly +4 more sources
Economic Journal of Emerging Markets, 2011 This paper uncovers the nature of conditional correlations between and volatility spillovers across bond, stock and foreign exchange in Indonesia, Malaysia, the Philippines, and Thailand.
Abdul Hakim
doaj +9 more sources
Journal of Futures Markets, 1999 The forecasting ability of the most popular volatility forecasting models is examined and an alternative model developed. Existing models are compared in terms of four attributes: (1) the relative weighting of recent versus older observations, (2) the estimation criterion, (3) the trade-off in terms of out-of-sample forecasting error between simple and
Ederington, Louis H., Guan, Wei
openaire +1 more source
Volatility Forecasting for Low-Volatility Investing
SSRN Electronic Journal, 2022 Low-volatility investing often involves sorting and selecting stocks based on retrospective risk measures, for example, the historical standard deviation of returns. In this paper, we use the volatility forecasts from a wide spectrum of volatility models to sort and select stocks and estimate portfolio weights.
Christian Conrad +2 more
openaire +2 more sources
Management forecasts of volatility [PDF]
Review of Accounting Studies, 2019 AbstractWe examine the predictive information content of the management forecasts of stock return volatility (i.e., expected volatility) that are disclosed in annual reports. We find that expected volatility predicts near-term and longer-term stock return volatility and earnings volatility incremental to implied volatility, historical volatility, firm ...
Atif Ellahie, Xiaoxia Peng
openaire +1 more source
Real Estate Management and Valuation, 2023 The presence of volatility in residential property market prices helps investors generate substantial profit while also causing fear among investors since high volatility implies a high return with a high risk.
Suleiman Ahmad Abubakar +6 more
doaj +1 more source
Forecasting Renminbi Exchange Rate Volatility Using CARR-MIDAS Model
Complexity, 2022 In this study, we propose to employ the conditional autoregressive range-mixed-data sampling (CARR-MIDAS) model to model and forecast the renminbi exchange rate volatility. The CARR-MIDAS model exploits intraday information from the intraday high and low
Xinyu Wu, Mengqi Wu
doaj +1 more source
Forecasting multifractal volatility [PDF]
Journal of Econometrics, 2001 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Laurent Calvet, Adlai Fisher
openaire +4 more sources
Modeling the volatility of Bitcoin returns using Nonparametric GARCH models
Academic Finance, 2022 Objective: The purpose of this paper is to demonstrate the effectiveness of the nonparametric GARCH model for the prediction of future Bitcoin prices. Methodology: The parametric GARCH models to characterize the volatility of Bitcoin returns are ...
Sami MESTIRI
doaj +1 more source