新兴市场收益波动性分析:以德黑兰证券交易所为例

Mehdi Parchehbaf Shoghi, Abdolreza Talaneh
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引用次数: 4

摘要

本文分析了德黑兰证券交易所收益的波动行为。由于波动性是影响投资组合选择、资产定价和风险管理的重要因素,本研究的主要目的是对德黑兰证券交易所(TSE)的收益波动性进行建模和预测。本研究作为第一次尝试的主要贡献是增强了对TSE波动行为的认识。利用2003-2008年东京证券交易所的主要指数数据,研究了自回归(AR)、移动平均(MA)和自回归移动平均(ARMA)模型的适用性。ARMA(2,1)被选为条件均值建模的最佳过程。我们使用EGARCH和TGARCH模型来捕捉负面冲击和正面冲击以及杠杆效应方面的不对称性。ARMA (2,1)-TGARCH(1,1)模型是拟合数据的最佳过程。我们在新闻中没有发现杠杆存在的证据;坏消息对回报波动性的影响也不会大于好消息。在三个预测绩效指标中,TGARCH(1,1)是预测波动率的最佳模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Analysis of Emerging Markets Returns Volatility: Case of Tehran Stock Exchange
This paper analyses the volatility behaviour of Tehran Stock Exchange returns. Since volatility is an important factor in portfolio selection, asset pricing, and risk management, the main purpose of our study is to model and forecast the returns volatility of the Tehran Stock Exchange (TSE). The main contribution of this study as the very first attempt is to enhance the knowledge on the behaviour of volatility of TSE. Using primary index data of TSE for 2003-2008, we investigate the appropriateness of several potential models of autoregressive (AR), moving averages (MA), and autoregressive moving averages (ARMA). The ARMA (2, 1) has been chosen as the best process for modelling the conditional mean. We used EGARCH and TGARCH models to capture asymmetries in terms of negative and positive shocks and the leverage effect. The ARMA (2, 1)-TGARCH (1, 1) model was the best process to fit the data. We find no evidence of the presence of the leverage in the news; nor does the bad news have a larger effect on the volatility of returns than the good news. Of the three forecast performance measures, the TGARCH (1, 1) was the best model to forecast the volatility.
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