forecasting value-at-risk using conditional volatility models: evidence from tehran stock exchange
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abstract
in this paper, we investigate the performance of parametric arch class models to forecast out-of-sample var for two portfolios of tehran stock exchange (tse) companies (market portfolio and a portfolio of 50 liquid companies), using a number of distributional assumptions and sample sizes at low and high confidence levels. we find, first, that leptokurtic distributions are able to produce better oneday- ahead and 10-day-ahead var forecasts; second, the choice of sample size is important for the accuracy of the forecasts.
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Journal title:
تحقیقات مالیجلد ۹، شماره ۴، صفحات ۰-۰
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