Volatility modeling
نویسنده
چکیده
• So far we have maintained the assumption of iid data in the estimation of distributions and risk measures. However, this assumption does not hold for financial data, which are known to be intertemporally dependent, especially in the volatility. Estimation of risk measures under the assumption of iid can be viewed as unconditional estimates. In contrast, we can model the intertemporal dependence explicitly and calculate conditional risk measures based on prior information.
منابع مشابه
Modeling Stock Market Volatility Using Univariate GARCH Models: Evidence from Bangladesh
This paper investigates the nature of volatility characteristics of stock returns in the Bangladesh stock markets employing daily all share price index return data of Dhaka Stock Exchange (DSE) and Chittagong Stock Exchange (CSE) from 02 January 1993 to 27 January 2013 and 01 January 2004 to 20 August 2015 respectively. Furthermore, the study explores the adequate volatility model for the stoc...
متن کاملModeling Gold Volatility: Realized GARCH Approach
F orecasting the volatility of a financial asset has wide implications in finance. Conditional variance extracted from the GARCH framework could be a suitable proxy of financial asset volatility. Option pricing, portfolio optimization, and risk management are examples of implications of conditional variance forecasting. One of the most recent methods of volatility forecasting is Real...
متن کاملA Neural-Network Approach to the Modeling of the Impact of Market Volatility on Investment
In recent years, authors have focused on modeling and forecasting volatility in financial series it is crucial for the characterization of markets, portfolio optimization and asset valuation. One of the most used methods to forecast market volatility is the linear regression. Nonetheless, the errors in prediction using this approach are often quite high. Hence, continued research is conducted t...
متن کاملModeling the Impact of News on volatility The Case of Iran
In this paper various ARCH models and relevant news impact curves including a partially nonparametric (PNP) one are compared and estimated with daily Iran stock return data. Diagnostic tests imply the asymmetry of the volatility response to news. The EGARCH model, which passes all the tests and appears relatively matching with the asymmetry in the data, seems to be the most adequate characteriz...
متن کاملModeling Stock Return Volatility Using Symmetric and Asymmetric Nonlinear State Space Models: Case of Tehran Stock Market
Volatility is a measure of uncertainty that plays a central role in financial theory, risk management, and pricing authority. Turbulence is the conditional variance of changes in asset prices that is not directly observable and is considered a hidden variable that is indirectly calculated using some approximations. To do this, two general approaches are presented in the literature of financial ...
متن کاملModeling Volatility Spillovers in Iran Capital Market
This paper investigates the conditional correlations and volatility spillovers between the dollar exchange rate return, gold coin return and crude oil return to stock index return. Monthly returns in the 144 observations (2005 - 2017) are analyzed by constant conditional correlation, dynamic conditional correlation, VARMA-GARCH and VARMA-AGARCH models. So this paper presents interdependences in...
متن کامل