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Volatility forecasting: combinations of realized volatility measures and forecasting models

Applied Economics, 2017
This article examines financial time series volatility forecasting performance. Different from other studies which either focus on combining individual realized measures or combining forecasting mo...
Linlan Xiao   +3 more
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Forecasting Volatility with Many Predictors

Journal of Forecasting, 2013
ABSTRACTThis study investigates the forecasting performance of the GARCH(1,1) model by adding an effective covariate. Based on the assumption that many volatility predictors are available to help forecast the volatility of a target variable, this study shows how to construct a covariate from these predictors and plug it into the GARCH(1,1) model.
Ke, Tsung-Han, Hu, Yu-Pin
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Volatility homogenisation decomposition for forecasting

2014 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr), 2014
We explore the idea that by modeling a financial time series at regular points in space (i.e. price) rather than regular points in time, more predictive power can be extracted from the time series. We will term this concept of modeling time series at regular points in space as “volatility homogenisation”. Our hypothesis is that if we select the correct
Adam W. Kowalewski   +2 more
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Forecasting Volatility with Time-Varying Leverage and Volatility of Volatility Effects

SSRN Electronic Journal, 2018
Abstract Predicting volatility is of primary importance for business applications in risk management, asset allocation, and the pricing of derivative instruments. This paper proposes a measurement model that considers the possibly time-varying interaction of realized volatility and asset returns according to a bivariate model to capture its major ...
Catania, L, Proietti, T
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Forecasting realized volatility: A review

Journal of the Korean Statistical Society, 2018
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Forecasting exchange rate volatility

Economics Letters, 2002
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Implied Volatility Forecasting Realized Volatility

2021
This chapter conducts an empirical analysis of IV to forecast the RV through testing hypothesis 1–9. The analysis includes three steps. First, estimate the IV for ATM price of currency options with 1-, 2-, and 3-month maturity during opening, midday, and closing period.
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Forecasting the Volatility of Stock Price Index

Expert Systems with Applications, 2006
Accurate volatility forecasting is the core task in the risk management in which various portfolios’ pricing, hedging, and option strategies are exercised. Prior studies on stock market have primarily focused on estimation of stock price index by using financial time series models and data mining techniques.
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A Stochastic Volatility Model, Volatility Smile and Forecasting Volatility

SSRN Electronic Journal, 2004
In this paper we propose a stochastic valuation model based on the Fourier transform for option price. This model can be used for the valuation of European options, characterized by two state variables: the price of the underlying asset and its volatility.
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Neural Network–Based Financial Volatility Forecasting: A Systematic Review

ACM Computing Surveys, 2023
Wenbo Ge   +2 more
exaly  

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