Results 261 to 270 of about 507,052 (301)
Some of the next articles are maybe not open access.
Volatility Processes and Volatility Forecast with Long Memory
Quantitative Finance, 2002We introduce a new family of processes that include the long memory (power law) in the volatility correlation. This is achieved by measuring the historical volatility on a set of increasing time horizons and by computing the resulting effective volatility by a sum with power law weights.
openaire +1 more source
Sentiment-aware volatility forecasting
Knowledge-Based Systems, 2019Abstract Recent advances in the integration of deep recurrent neural networks and statistical inferences have paved new avenues for joint modeling of moments of random variables, which is highly useful for signal processing, time series analysis, and financial forecasting.
Frank Z. Xing +2 more
openaire +2 more sources
Neural network volatility forecasts
Intelligent Systems in Accounting, Finance and Management, 2007AbstractWe analyse whether the use of neural networks can improve ‘traditional’ volatility forecasts from time‐series models, as well as implied volatilities obtained from options on futures on the Spanish stock market index, the IBEX‐35.One of our main contributions is to explore the predictive ability of neural networks that incorporate both implied ...
José R. Aragonés +2 more
openaire +2 more sources
Practical Issues in Forecasting Volatility
CFA Digest, 2005A comparison is presented of 93 studies that conducted tests of volatility-forecasting methods on a wide range of financial asset returns. The survey found that option-implied volatility provides more accurate forecasts than time-series models.
Poon, Ser Huang; id_orcid 0000-0002-7297-9401 +1 more
openaire +1 more source
Earnings forecasts and idiosyncratic volatilities
International Review of Financial Analysis, 2008Abstract We test the theoretical relation between idiosyncratic return volatilities and the volatilities of cash-flow news based on the expected returns on equity (ROE) for CRSP stocks over the period 1977–2008. Consistent with economic intuition, we find that using analyst forecasts of earnings is superior to using realized earnings to proxy for ...
Lawrence Kryzanowski, sana mohsni
openaire +1 more source
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
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
Volatility Forecasting and Microstructure Noise
SSRN Electronic Journal, 2006zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ghysels, Eric, Sinko, Arthur
openaire +1 more source
Volatility forecasts evaluation and comparison
WIREs Computational Statistics, 2011AbstractThis 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 +1 more
openaire +5 more sources
Volatility forecasting: combinations of realized volatility measures and forecasting models
Applied Economics, 2017This 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
openaire +1 more source
Forecasting Volatility with Many Predictors
Journal of Forecasting, 2013ABSTRACTThis 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
openaire +2 more sources