نتایج جستجو برای: regressive conditional heteroscedasticity garch model

تعداد نتایج: 2147628  

2012
Pierre-Julien Trombe Henrik Madsen

Accurate wind power forecasts highly contribute to the integration of wind power into power systems. The focus of the present study is on large-scale offshore wind farms and the complexity of generating accurate probabilistic forecasts of wind power fluctuations at time-scales of a few minutes. Such complexity is addressed from three perspectives: (i) the modeling of a nonlinear and non-station...

Journal: :Vilakshan 2022

Purpose This study aims to analyse whether investment in green and sustainable stocks provide some cushion during current precarious time. To compare the impact of COVID-19 on volatility market-capitalisation-based stocks, daily returns from Greenex, Carbonex, Large-Cap, Mid-Cap Small-Cap index have been analysed over a period six years 2015 2021. Design/methodology/approach At outset, logarith...

2004
Riaz Shareef Michael McAleer

Volatility in monthly international tourist arrivals is defined as the squared deviation from mean monthly international tourist arrivals. Consequently, volatility is directly related to the standard deviation, which is a common measure of financial risk. Fluctuating variations, or conditional volatility, in international monthly tourist arrivals are typically associated with unanticipated even...

2003
JEFF FLEMING

We show that, for three common SARV models, fitting a minimum mean square linear filter is equivalent to fitting a GARCH model. This suggests that GARCH models may be useful for filtering, forecasting, and parameter estimation in stochastic volatility settings. To investigate, we use simulations to evaluate how the three SARV models and their associated GARCH filters perform under controlled co...

Journal: :Jurnal Matematika, Sains dan Teknologi 2023

The Indonesian rupiah (IDR) exchange rate is used to gauge Indonesia's economic stability. Maintaining the IDR rate's stability critical since it has a direct impact on national monetary situation, particularly during Covid-19 pandemic. Forecasting important do and one way assess government policy. data series be here are from Yahoo Finance. It consists of 271 taken August 2017 October 2022. Th...

2004
Felix Chan Michael McAleer

Atmospheric carbon dioxide concentration (ACDC) is a crucial variable for many environmental simulation models, and is regarded as an important factor for predicting temperature and climate changes. However, the conditional variance of ACDC levels has not previously been examined. This paper analyses the trends and volatility in ACDC levels using monthly data from January 1965 to December 2002....

2006
Esther Ruiz Krishna Sarma

This paper analyses how outliers affect the identification of conditional heteroscedasticity and the estimation of generalized autoregressive conditionally heteroscedastic (GARCH) models. First, we derive the asymptotic biases of the sample autocorrelations of squared observations generated by stationary processes and show that the properties of some conditional homoscedasticity tests can be di...

2005
DAN SHAO D. SHAO

This article develops a numerical method to price American-style Asian option in the context of the generalized autoregressive conditional heteroscedasticity (GARCH) asset return process. The development is based on dynamic programming coupled with the replacement of the normally distributed variable with a binomial one and the whole procedure is under the locally risk-neutral valuation relatio...

Journal: :Computers & OR 2016
Vladimir Rankovic Mikica Drenovak Branko Urosevic Ranko Jelic

In accordance with Basel Capital Accords, the Capital Requirements (CR) for market risk exposure of banks is a nonlinear function of Value-at-Risk (VaR). Importantly, the CR is calculated based on a bank’s actual portfolio, i.e. the portfolio represented by its current holdings. To tackle mean-VaR portfolio optimization within the actual portfolio framework (APF), we propose a novel mean-VaR op...

2008
Anna Pajor

Multivariate models of asset returns are very important in financial applications. Asset allocation, risk assessment and construction of an optimal portfolio require estimates of the covariance matrix between the returns of assets (see e.g. Aguilar and West (2000), Pajor (2005a, 2005b)). Similarly, hedges require a covariance matrix of all the assets in the hedge. There are two main types of vo...

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