The data presented in this article are related to the research article entitled "Testing and comparing the performance of dynamic variance and correlation models in value-at-risk estimation. North American Journal of Economics and Finance, 40, 116-135. doi:10.1016/j.najef.2017.02.006 (Li, 2017) [1]. Data on daily stock index return for the Canadian, UK, and US equity markets, as compiled by Mor...

In this papeT we study the performance of the GARCH model and two of its non-linear modifications to forecast weekly stock market volatility. The models are the Quadratic GARCH (Engle and Ng. 1993) and the Glosten. Jagannathan and Runkle (1992) models which have been proposed to describe, for example, the often observed negative skewness in stock market indices. We find that the QGARCH model is...

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Investors in stock market are usually greedy during bull markets and scared during bear markets. The greed or fear spreads across investors quickly. This is known as the herding effect, and often leads to a fast movement of stock prices. During such market regimes, stock prices change at a super-exponential rate and are normally followed by a trend reversal that corrects the previous overreacti...

The use of intelligent systems for stock market predictions has been widely established. This chapter introduces two Genetic Programming (GP) techniques: Multi-Expression Programming (MEP) and Linear Genetic Programming (LGP) for the prediction of two stock indices. The performance is then compared with an artificial neural network trained using Levenberg-Marquardt algorithm and Takagi-Sugeno n...

In this paper, we examine the stock market efficiency of the members of the Association of South East Asian Nations (ASEAN). We use the conventional individual variance ratio tests like the Lo and MacKinlay (1988) test, Choi (1999) test, Wright (2000) test and Chen and Deo (2006)) test to check for the efficient market hypothesis in these markets. We also perform the spectral shape test of Durl...