Results 261 to 270 of about 113,493 (310)

Functional volatility forecasting

Journal of Forecasting, 2023
AbstractWidely used volatility forecasting methods are usually based on low‐frequency time series models. Although some of them employ high‐frequency observations, these intraday data are often summarized into low‐frequency point statistics, for example, daily realized measures, before being incorporated into a forecasting model. This paper contributes
Yingwen Tan, Zhensi Tan, Yinfen Tang, Zhiyuan Zhang   +3 more
openaire   +1 more source

Forecasting cryptocurrency volatility

International Journal of Forecasting, 2022
Abstract This paper studies the behavior of cryptocurrencies’ financial time series, of which Bitcoin is the most prominent example. The dynamics of these series are quite complex, displaying extreme observations, asymmetries, and several nonlinear characteristics that are difficult to model and forecast.
Catania L., Grassi S.
openaire   +2 more sources

Forecasting volatility

Statistics & Probability Letters, 2005
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Thavaneswaran, A., Appadoo, S. S., Peiris, S.   +2 more
openaire   +2 more sources

Forecasting Volatility

Financial Markets, Institutions & Instruments, 1997
This monograph puts together results from several lines of research that I have pursued over a period of years, on the general topic of volatility forecasting for option pricing applications. It is not meant to be a complete survey of the extensive literature on the subject, nor is it a definitive set of prescriptions on how to get the best volatility ...
openaire   +1 more source

COMMENTARY: Volatility Forecasting

The Journal of Trading, 2018
This paper provides a perspective on volatility forecasting. The basic idea is that a number of factors are leading to volatility having a lower baseline expected value than in prior years. These factors include lower earnings uncertainty, greater market efficiency, better market-marking, and the fact that volatility trading itself tends to reduce ...
Haim A. Mozes, John Launny Steffens
openaire   +1 more source

Forecasting exchange rate volatility

Economics Letters, 2002
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +1 more source

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.
openaire   +1 more source

GARCH, Outliers, and Forecasting Volatility

2011
The issue of detecting and handling outliers in GARCH processes has received considerable attention recently. In this chapter, we put forwardan iterative outlier detection procedure, which is appropriate given that in practice both the number of outliers as well as their timing is unknown. Our procedure aims to test for the presence of a single outlier
Franses, Philip Hans, van Dijk, Dick
openaire   +3 more sources

Volatility forecasts evaluation and comparison

WIREs Computational Statistics, 2011
AbstractThis article surveys the most important developments in volatility forecast comparison and model selection. We review a number of evaluation methods and testing procedures for predictive accuracy based on statistical loss functions. We also review recent contributions on the admissible form of loss functions ensuring consistency of the ordering
VIOLANTE, FRANCESCO, Laurent, Sébastien   +1 more
openaire   +5 more sources

Volatility Forecasting and Microstructure Noise

SSRN Electronic Journal, 2006
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ghysels, Eric, Sinko, Arthur
openaire   +1 more source