Abu Hassan Shaari Mohd Nor

Modelling financial observable-volatility using long memory models

This article proposes a generalized long persistence observable volatility model which comprises of leverage effect autoregressive fractionally integrated moving average model with time-varying volatility and the inclusion of heterogeneous autoregressive components as the contemporaneous variables. Our empirical results found that the proposed model provides substantial improvement in the model fitting as well as specification.

Adjusted Hurst exponent evaluations for equity and energy markets

Abstract This study introduced an alternative method in long memory volatility financial time series evaluation using the autoregressive conditional heteroscedasticity models. Instead of direct measurement for long memory Hurst exponent parameter, this approach suggested a short memory filtering procedures using the conditional heteroscedastic specification. The stationary time series which is free from short memory is later evaluated using two heuristic long memory estimations. It is found that this method is able to eliminate the possible spurious long memory in the selected equity and energy markets. The findings of this study are important in long memory estimation and market efficiency analysis.

The Stylized Facts and Market Risk Evaluations of Malaysian Shariah Index

Abstract This study investigates some interesting empirical stylized facts in the Malaysian Shariah index. These included the clustering volatility, leverage effect, fat-tailed behavior, long memory property and flexible power volatility representation. A conditional heteroscedasticity model is used to capture all the stylized facts. The stylized facts for Shariah index is compared with the major barometer indicators such as FTSE-KLCI, Singapore Strait-time index (STI) and Indonesian Jakarta Stock Exchange (JSE). The results of the analysis are used in quantifying the market risk using the value-at-risk approach.

An empirical study of realized and long-memory GARCH standardized stock-return

In this article, we study the standardized returns by using the realized volatility and long-memory GARCH models. The various normality tests indicate that the realized–standardized returns follow a Gaussian distribution. On the other hand, the standardized returns by GARCH models are able to reduce but not eliminate the excess kurtosis condition compare to the realized–standardized returns.

CAUSALITY-IN-VARIANCE BETWEEN THE STOCK MARKET AND MACROECONOMIC VARIABLES IN SINGAPORE

The present study investigates the causality-in-variance between macroeconomic variables and the stock market in Singapore from November 1990 to March 2013. This study utilizes the [Sanso, A, V Arago and JL Carrion (2004). Testing for change in the unconditional variance of financial time series. Revista de Economia Financiera, 4, 32–53.] test to detect the structural break in variance; a generalized autoregressive conditional heteroskedasticity (GARCH) process to model volatility; and the cross correlation function (CCF) causality method. The results demonstrate that the most important macroeconomic causes of stock market volatility in Singapore is exchange rate volatility. The findings provide preliminary insights on risk elements for policy makers monitoring the stability of financial markets by providing insights about volatility spillovers and risk transmission between the stock market and macroeconomic variables in Singapore.

Exploring heterogeneous market hypothesis using realized volatility

This study investigates the heterogeneous market hypothesis using high frequency data. The cascaded heterogeneous trading activities with different time durations are modelled by the heterogeneous autoregressive framework. The empirical study indicated the presence of long memory behaviour and predictability elements in the financial time series which supported heterogeneous market hypothesis. Besides the common sum-of-square intraday realized volatility, we also advocated two power variation realized volatilities in forecast evaluation and risk measurement in order to overcome the possible abrupt jumps during the credit crisis. Finally, the empirical results are used in determining the market risk using the value-at-risk approach. The findings of this study have implications for informationally market efficiency analysis, portfolio strategies and risk managements.