Results 181 to 190 of about 16,252 (305)
Cross-city hedging with weather derivatives using bivariate DCC GARCH models [PDF]
As monopolies gave their way to competitive wholesale electricity markets, volumetric risk came into play. Electricity supplier can buy weather derivatives to protect from volumetric risk due to unexpected weather conditions.
Kosater, Peter
core
A Conditional Tail Expectation Type Risk Measure for Time Series
ABSTRACT We consider the estimation of the conditional expectation š¼(Xh|X0>UX(1/p)), provided š¼|X0|<ā, at extreme levels, where (Xt)tāā¤$$ {\left({X}_t\right)}_{t\in \mathbb{Z}} $$ is a strictly stationary time series, UX$$ {U}_X $$ its tail quantile function, h$$ h $$ is a positive integer and pā(0,1)$$ p\in \left(0,1\right) $$ is such that pā0$$ p\to ...
Yuri Goegebeur +2 more
wiley +1 more source
Robust Estimation and Inference for TimeāVarying Unconditional Volatility
ABSTRACT We derive a general and robust estimator of a large class of parametric specifications of timeāvarying unconditional volatility of financial returns, both univariate and multivariate, and establish the Consistency and Asymptotic Normality (CAN) of the estimator.
Adam Lee +2 more
wiley +1 more source
ABSTRACT This article examines the filtering and approximationātheoretic properties of scoreādriven time series models. Under specific Lipschitzātype and tail conditions, new results are derived, leading to maximal and deviation inequalities for the filtering approximation error using empirical process theory.
Enzo D'Innocenzo
wiley +1 more source
Modeling Saudi stock index returns and volatility: a dual approach using GARCH and neural networks. [PDF]
Al-Besher S, Al-Najjar D.
europepmc +1 more source
On Testing for Independence Between Generalized Error Models of Several Time Series
ABSTRACT We define generalized innovations associated with generalized error models having arbitrary distributions, that is, distributions that can be mixtures of continuous and discrete distributions. These models include stochastic volatility models and regimeāswitching models with possibly zeroāinflated regimes.
Kilani Ghoudi +2 more
wiley +1 more source
Forecasting Agricultural Commodity Prices with Asymmetric-Error GARCH Models
The performance of a proposed asymmetric-error GARCH model is evaluated in comparison to the normal-error- and Student-t-GARCH models through three applications involving forecasts of U.S. soybean, sorghum, and wheat prices.
Ramirez, Octavio A. +1 more
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Penalized Convex Estimation in Dynamic Location Models
ABSTRACT This paper studies L1$$ {L}^1 $$āpenalized estimation for location models yt=mt+ϵt$$ {y}_t={m}_t+{\epsilon}_t $$, where mt$$ {m}_t $$ is defined by a possibly nonāMarkovian recursion and ϵt$$ {\epsilon}_t $$ is a martingale difference sequence with possibly timeāvarying conditional variance.
Reda Alami Chentoufi
wiley +1 more source
Strategic Risk Based Forecasting of Brent Crude Oil Prices: A Comparative Analysis of Econometric and Machine Learning Models. [PDF]
Yılmaz TE, Zehir C.
europepmc +1 more source
Garch Parameter Estimation Using High-Frequency Data
Estimation of the parameters of Garch models for financial data is typically based on daily close-to-close returns. This paper shows that the efficiency of the parameter estimators may be greatly improved by using volatility proxies based on intraday ...
Visser, Marcel P.
core

