• The Korean Journal of Financial Studies
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• v.2 no.2
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• pp.213-220
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• 1995

• International Area Studies Review
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• v.12 no.2
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• pp.3-26
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• 2008

This article investigates the usefulness of the skewed Student-t distribution in modeling the long memory volatility property that might be present in the daily returns of two Australian financial series; the ASX200 stock index and AUD/USD exchange rate. For this purpose we assess the performance of FIGARCH and FIAPARCH Value-at-Risk (VaR) models based on the normal, Student-t, and skewed Student-t distribution innovations. Our results support the argument that the skewed Student-t distribution models produce more accurate VaR estimates of Australian financial markets than the normal and Student-t distribution models. Thus, consideration of skewness and excess kurtosis in asset return distributions provides appropriate criteria for model selection in the context of long memory volatility models in Australian stock and foreign exchange markets.

• International Area Studies Review
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• v.14 no.2
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• pp.25-40
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• 2010

Accurate forecasting of volatility is of considerable interest in financial volatility research, particularly in regard to portfolio allocation, option pricing and risk management because volatility is equal to market risk. So, we attempted to delineate a model with good ability to forecast and identified stylized features of volatility, with a focus on volatility persistence or long memory in the Australian futures market. In this context, we assessed the long-memory property in the volatility of index futures contracts using three conditional volatility models, namely the GARCH, IGARCH and FIGARCH models. We found that the FIGARCH model better captures the long-memory property than do the GARCH and IGARCH models. Additionally, we found that the FIGARCH model provides superior performance in one-day-ahead volatility forecasts. As discussed in this paper, the FIGARCH model should prove a useful technique in forecasting the long-memory volatility in the Australian index futures market.

• International Area Studies Review
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• v.14 no.3
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• pp.62-84
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• 2010

Accurate forecasting of volatility is of considerable interest in financial volatility research, particularly in regard to portfolio allocation, option pricing and risk management because volatility is equal to market risk. So, we attempted to delineate a model with good ability to forecast and identified stylized features of volatility, with a focus on volatility persistence or long memory in the Australian futures market. In this context, we assessed the long-memory property in the volatility of index futures contracts using three conditional volatility models, namely the GARCH, IGARCH and FIGARCH models. We found that the FIGARCH model better captures the long-memory property than do the GARCH and IGARCH models. Additionally, we found that the FIGARCH model provides superior performance in one-day-ahead volatility forecasts. As discussed in this paper, the FIGARCH model should prove a useful technique in forecasting the long-memory volatility in the Australian index futures market.

• The Korean Journal of Financial Management
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• v.27 no.1
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• pp.1-30
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• 2010

This paper tested the lead-lag relationship as well as the symmetric and asymmetric volatility spillover effects between international currency futures markets and cash markets. We use five kinds of currency spot and futures markets such as British pound, Australian and Canadian dollar, Brasilian Real and won/dollar spot and futures markets. daily closing prices covering from September 15, 2003 to July 30, 2009. For this purpose we employed dynamic time series models such as the Granger causality based on VAR and time-varying MA(1)-GJR-GARCH(1, 1)-M. The main empirical results are as follows; First, according to Granger causality test, we find that the bilateral lead-lag relationship between the five countries' currency spot and futures market. The price discover effect from currency futures markets to spot market is relatively stronger than that from currency spot to futures markets. Second, based on the time varying GARCH model, we find that there is a bilateral conditional mean spillover effects between the five currency spot and futures markets. Third, we also find that there is a bilateral asymmetric volatility spillover effects between British pound, Canadian dollar, Brasilian Real and won/dollar spot and futures market. However there is a unilateral asymmetric volatility spillover effect from Australian dollar futures to cash market, not vice versa. From these empirical results we infer that most of currency futures markets have a much better price discovery function than currency cash market and are inefficient to the information.