Results 1 to 10 of about 25,094 (140)
Functional generalized autoregressive conditional heteroskedasticity [PDF]
, 2015 Heteroskedasticity is a common feature of financial time series and is commonly addressed in the model building process through the use of ARCH and GARCH processes. More recently multivariate variants of these processes have been in the focus of research
Aue, Alexander +2 more
core +2 more sources
Structural vector autoregressions with heteroskedasticity: A comparison of different volatility models [PDF]
, 2015 A growing literature uses changes in residual volatility for identifying structural shocks in vector autoregressive (VAR) analysis. A number of different models for heteroskedasticity or conditional heteroskedasticity are proposed and used in ...
Lütkepohl, Helmut, Netšunajev, Aleksei
core +5 more sources
Exponential Conditional Volatility Models [PDF]
, 2010 The asymptotic distribution of maximum likelihood estimators is derived for a class of exponential generalized autoregressive conditional heteroskedasticity (EGARCH) models.
Harvey, AC
core +4 more sources
Computing (R, S) policies with correlated demand [PDF]
, 2018 This paper considers the single-item single-stocking non-stationary stochastic lot-sizing problem under correlated demand. By operating under a nonstationary (R, S) policy, in which R denote the reorder period and S the associated order-up-to-level, we ...
Martin-Barragan, Belen +3 more
core +3 more sources
Forecasting currency in circulation in Malaysia using arch and garch models [PDF]
, 2018 The monthly economic time series commonly contains the volatility periods and it is suitable to apply the Heteroscedastic model to it where the conditional variance is not constant throughout the time trend. The aim of this study is to model and forecast
Abdul Razak, Nur Azreen +3 more
core +1 more source
Agribusiness, EarlyView.Abstract The vegetable market experiences significant price fluctuations due to the complex interplay of trend, cyclical, seasonal, and irregular factors. This study takes Korean green onions as an example and employs the Christiano–Fitzgerald filter and the CensusX‐13 seasonal adjustment methods to decompose its price into four components: trend ...
Yiyang Qiao, Byeong‐il Ahn
wiley +1 more source
Business Strategy and the Environment, EarlyView.ABSTRACT This study examined how Bitcoin, energy prices, and geopolitical risk interact by examining the first four moments (mean, variance, skewness, and kurtosis) of their return distributions by using wavelet analysis. The findings reveal that the co‐movement patterns of energy index, geopolitical risk index, and Bitcoin prices are time and ...
Pooja Kumari +4 more
wiley +1 more source
Examining the Financial Impact of Biodiversity‐Related Reputational Disasters
Corporate Social Responsibility and Environmental Management, EarlyView.ABSTRACT This research investigates the reaction of financial markets to biodiversity‐related corporate events, utilising an EGARCH model to assess the implications on stock returns and volatility. Results reveal that markets significantly respond to these events, demonstrating heightened sensitivity and volatility that underscore the financial ...
Erdinc Akyildirim, Shaen Corbet
wiley +1 more source
Modeling and Forecasting the CBOE VIX With the TVP‐HAR Model
Journal of Forecasting, EarlyView.ABSTRACT This study proposes the use of a heterogeneous autoregressive model with time‐varying parameters (TVP‐HAR) to model and forecast the Chicago Board Options Exchange (CBOE) volatility index (VIX). To demonstrate the superiority of the TVP‐HAR model, we consider six variations of the model with different bandwidths and smoothing variables and ...
Wen Xu +2 more
wiley +1 more source
Measuring the Impact of Transition Risk on Financial Markets: A Joint VaR‐ES Approach
Journal of Forecasting, EarlyView.ABSTRACT Based on a joint quantile and expected shortfall semiparametric methodology, we propose a novel approach to forecasting market risk conditioned to transition risk exposure. This method allows us to forecast two climate‐related financial risk measures called CoClimateVaR$$ CoClimateVaR $$ and CoClimateES$$ CoClimateES $$, being jointly ...
Laura Garcia‐Jorcano +1 more
wiley +1 more source