Results 181 to 190 of about 16,252 (305)

Cross-city hedging with weather derivatives using bivariate DCC GARCH models [PDF]

open access: yes
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

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT We consider the estimation of the conditional expectation š”¼(Xh|X0>UX(1/p)), provided š”¼|X0|<āˆž, at extreme levels, where (Xt)tāˆˆā„¤$$ {\left({X}_t\right)}_{t\in \mathbb{Z}} $$ is a strictly stationary time series, UX$$ {U}_X $$ its tail quantile function, h$$ h $$ is a positive integer and p∈(0,1)$$ p\in \left(0,1\right) $$ is such that p→0$$ p\to ...
Yuri Goegebeur   +2 more
wiley   +1 more source

Robust Estimation and Inference for Time‐Varying Unconditional Volatility

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT We derive a general and robust estimator of a large class of parametric specifications of time‐varying 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

Empirical‐Process Limit Theory and Filter Approximation Bounds for Score‐Driven Time Series Models

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT This article examines the filtering and approximation‐theoretic properties of score‐driven time series models. Under specific Lipschitz‐type 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

On Testing for Independence Between Generalized Error Models of Several Time Series

open access: yesJournal of Time Series Analysis, EarlyView.
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 regime‐switching models with possibly zero‐inflated regimes.
Kilani Ghoudi   +2 more
wiley   +1 more source

Forecasting Agricultural Commodity Prices with Asymmetric-Error GARCH Models

open access: yes
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
core  

Penalized Convex Estimation in Dynamic Location Models

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT This paper studies L1$$ {L}^1 $$‐penalized estimation for location models yt=mt+ϵt$$ {y}_t={m}_t+{\epsilon}_t $$, where mt$$ {m}_t $$ is defined by a possibly non‐Markovian recursion and ϵt$$ {\epsilon}_t $$ is a martingale difference sequence with possibly time‐varying conditional variance.
Reda Alami Chentoufi
wiley   +1 more source

Garch Parameter Estimation Using High-Frequency Data

open access: yes
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  

Home - About - Disclaimer - Privacy