Predictive ability of Value-at-Risk methods: evidence from the Karachi Stock Exchange-100 Index

Value-at-risk (VaR) is a useful risk measure broadly used by financial institutions all over the world. VaR is popular among researchers, practitioners and regulators of financial institutions. VaR has been extensively used for to measure systematic risk exposure in developed markets like of the US, Europe and Asia. In this paper we analyze the accuracy of VaR measure for Pakistan’s emerging stock market using daily data from the Karachi Stock Exchange-100 index January 1992 to June 2008. We computed VaR by employing data on annual basis as well as for the whole 17 year period. Overall we found that VaR measures are more accurate when KSE index return volatility is estimated by GARCH (1,1) model especially at 95% confidence level. In this case the actual loss of KSE-100 index exceeds VaR in only two years 1998 and 2006. At 99% confidence level no method generally gives accurate VaR estimates. In this case ‘equally weighted moving average’, ‘exponentially weighted moving average’ and ‘GARCH’ based methods yield accurate VaR estimates in nearly half of the number of years. On average for the whole period 95% VaR is estimated to be about 2.5% of the value of KSE-100 index. That is on average in one out of 20 days KSE-100 index loses at least 2.5% of its value. We also investigate the asset pricing implication of downside risk measured by VaR and expected returns for docile portfolios sorted according to VaR of each stock. We found that portfolios with higher VaR have higher average returns. Therefore VaR as a measure of downside risk is associated with higher returns.Downside risk; Emerging Markets; Value-at-Risk

Predictive Ability of Value-at-Risk Methods: Evidence from the Karachi Stock Exchange-100 Index

Value-at-risk (VaR) is a useful risk measure broadly used by financial institutions all over the world. VaR has been extensively used to measure systematic risk exposure in developed markets like of the US, Europe and Asia. This paper analyzes the accuracy of VaR measure for Pakistan’s emerging stock market using daily data from the Karachi Stock Exchange-100 index January 1992 to June 2008. We computed VaR by employing data on annual basis as well as for the whole 17 year period. Overall we found that VaR measures are more accurate when KSE index return volatility is estimated by GARCH (1,1) model especially at 95% confidence level. In this case the actual loss of KSE-100 index exceeds VaR in only two years 1998 and 2006. At 99% confidence level no method generally gives accurate VaR estimates. In this case ‘equally weighted moving average’, ‘exponentially weighted moving average’ and ‘GARCH’ based methods yield accurate VaR estimates in nearly half of the number of years. On average for the whole period 95% VaR is estimated to be about 2.5% of the value of KSE-100 index. That is on average in one out of 20 days KSE-100 index loses at least 2.5% of its value. We also investigate the asset pricing implication of downside risk measured by VaR and expected returns for decile portfolios sorted according to VaR of each stock. We found that portfolios with higher VaR have higher average returns. Therefore VaR as a measure of downside risk is associated with higher returns.Downside risk; Emerging Markets; Value-at-Risk.

The effect of Goods and Services Tax (GST) imposition on stock market overreaction and trading volume in Malaysia and Australia

This paper investigates the GST imposition effect on stock overreaction and trading volume in Bursa Malaysia and Australian Securities Exchange (ASX). To evaluate the stock overreaction, t-test, Wilcoxon Signed-Rank Test and MannWhitney U-Test are employed to analyse the market-adjusted abnormal returns. The homogeneity of stock trading volume is assessed by block resampling bootstrapping, t-test and regression. Consistent with the Overreaction Hypothesis, this research reveals that all arbitrage portfolios over one-month interval in Bursa Malaysia are able to generate significant abnormal profits. This infers the profitability of implementing short-term contrarian strategy in the Malaysian stock market. However, the analysis for ASX shows the opposite. Additionally, GST imposition reduces the trading volume in Bursa Malaysia but not in ASX. This empirical result will be of interest to the policymakers who are considering imposing tax on fee-based financial services, as well as the investors and fund managers who are concern about profits maximisation

Portfolio Optimization and Diversification in China: Policy Implications for Vietnam and other Emerging Markets

This article is conducted to examine risk, return, and portfolio optimization at the industry level in China over the period 2007–2016. On the ground of the classical Markowitz framework for portfolio optimization, the mean-semivariance optimization framework is established for China’s stock market at the industry level. Findings from this study indicate that healthcare sector plays a significant role among 10 industries in China on a stand-alone basis. In addition, a significant change of rankings among the sectors in term of risk is found when the mean-semivariance optimization framework is used. We also find that utilizing this new framework helps improve the optimal portfolios in relation to performance, measured by Sortino ratio, and diversification. A simulation technique, generally known as resampling method, is also utilized to check the robustness of the estimates. While the use of this resampling method appears not to improve the performance of optimal portfolios compared with the mean-semivariance framework for China, there is a remarkable advance in diversification of the optimal portfolios. Implications for investors and the governments in Vietnam and other emerging markets have emerged from the study

Evaluation and Improvement of the Efficiency of Logistics Companies with Data Envelopment Analysis Model

The performance of global trade depends on the logistics industry to move products, information, finances, technology and human resources along the supply chain. The current situation during the pandemic relies on the logistics industry particularly in the courier, parcel and express service providers to deliver daily essentials. Product customization, customer demand, technological sophistication, threat of new entrants, border closure, compliance to Covid-19 regulations and global economic crisis have taken the logistics industry by storm. For the sustainment and growth of these companies, strategic decision making shall take place. A huge determinant of these decisions is the financial efficiency of the companies. Therefore, this paper aims to determine the efficiency of the logistics companies in Malaysia by analyzing their financial performances using current ratio, debt to assets ratio, debt to equity ratio, earnings per share, return on assets and return on equity with data envelopment analysis model. The results of this study found that five companies, COMPLET, GDEX, MISC, SURIA and WPRTS are efficient. This study fills the research gap by determining the efficiency scores of these companies and suggesting potential improvements for inefficient companies to enhance and optimize their financial positions

The direct and indirect influence of brand image, brand experience, and brand personality on brand loyalty

The objective of this study is to investigate the relationships between brand image (BI), brand experience (BE), brand personality (BP), and brand loyalty (BL) of automobile local brands in Malaysia and also determining the mediating effect of brand satisfaction (BS) and brand trust (BT) on those relationships. This study is embarked on the fact that only a few studies have examined how brand image, brand experience, brand personality, brand satisfaction, and brand trust contribute towards the emergence of brand loyalty. Based on a theoretical consideration, a model was proposed and 17 hypotheses were formulated. Questionnaires were used to collect data. A total of 330 usable responses were received from respondents in the northern part of Malaysia, (Kedah, Penang, and Perlis). Partial Least Squares Structural Equation Modelling (PLS-SEM) was employed in the data analysis. The findings reveal significant relationships between brand image and brand loyalty, and between brand experience and brand loyalty. However, this study does not find any significant relationships between brand personality and brand loyalty. This study observes that brand satisfaction mediates both the relationships between brand image, brand personality, and brand loyalty. In addition, brand trust mediates the relationships between brand personality and brand loyalty. However, brand satisfaction does not mediate the relationships between brand experience and brand loyalty. No significant mediation is observed of brand trust on the relationships between brand image, brand experience, and brand loyalty. The significance of this study can be seen in the incorporation of brand satisfaction and brand trust as the mediating tools to explain the relationships between brand image, brand experience, brand personality, and brand loyalty. The study concludes with a discussion on the contributions, limitations as well as suggestions for future researc

Calendar seasonality in the Irish equity market : 1988-1998

Detection of 'anomalies', empirical regularities that are inexplicable within a preeminent or accepted paradigm, is a key aspect of the operation of scientific endeavour. The dominant theories of financial economics, those deriving from the CAPM/APT literature, hold that there should not exist persistent differences in the returns to assets across calendar frequencies. An extensive review of the literature reveals that in a wide variety of assets and markets there is evidence that returns differ according to the calendar frequency, in particular across days of the week and months of the year and around recurrent holidays. However, this review also reveals considerable room for increased methodological and statistical sophistication. In particular, the nature and extent of the data indicate that techniques based on robust regression, non-parametric statistics and Bayesian inference are more appropriate than the predominantly OLS based approaches displayed in the literature. Papers that adopt these more sophisticated approaches generally find much weaker evidence for such calendar anomalies. In essence, the Irish Stock Exchange operated free from exchange controls and in a broadly homogenous monetary and economic environment from 1988 to 1998. Daily returns from 1988 to 1998, on official equity indices, and from 1993 to 1998 on equal and value weighted equity indices, are examined. The evidence is that even when more sophisticated and appropriate techniques are used there is still some evidence for a daily pattern in the returns to these indices. However this pattern is dissimilar to that found elsewhere, consisting of a midweek positive peak as opposed to the more commonly found low returns at the start of the week and higher returns on Friday. This pattern is not a function of the settlement system, does not appear to be related to the pattern of either microeconomic (firm-specific) or macroeconomic information releases, nor does it appear to be a function of endogenous news generation. Previous international research indicates a January peak in returns, while previous research on the Irish market had also found an April peak. While the investigation here of the monthly pattern of returns confirms, in a statistically and methodologically robust manner, the January peak no evidence is found of an April peak. Examination of the return pattern around exchange holidays indicates that, in common with other markets referenced in the literature, there is a rise in returns before a holiday. However, on decomposition into local and international components we find that although the local effect is strong this effect is negative, which is a major point of departure from previous research findings

Predictive ability of Value-at-Risk methods: evidence from the Karachi Stock Exchange-100 Index

Value-at-risk (VaR) is a useful risk measure broadly used by financial institutions all over the world. VaR is popular among researchers, practitioners and regulators of financial institutions. VaR has been extensively used for to measure systematic risk exposure in developed markets like of the US, Europe and Asia. In this paper we analyze the accuracy of VaR measure for Pakistan’s emerging stock market using daily data from the Karachi Stock Exchange-100 index January 1992 to June 2008. We computed VaR by employing data on annual basis as well as for the whole 17 year period. Overall we found that VaR measures are more accurate when KSE index return volatility is estimated by GARCH (1,1) model especially at 95% confidence level. In this case the actual loss of KSE-100 index exceeds VaR in only two years 1998 and 2006. At 99% confidence level no method generally gives accurate VaR estimates. In this case ‘equally weighted moving average’, ‘exponentially weighted moving average’ and ‘GARCH’ based methods yield accurate VaR estimates in nearly half of the number of years. On average for the whole period 95% VaR is estimated to be about 2.5% of the value of KSE-100 index. That is on average in one out of 20 days KSE-100 index loses at least 2.5% of its value. We also investigate the asset pricing implication of downside risk measured by VaR and expected returns for docile portfolios sorted according to VaR of each stock. We found that portfolios with higher VaR have higher average returns. Therefore VaR as a measure of downside risk is associated with higher returns

Predictive ability of Value-at-Risk methods: evidence from the Karachi Stock Exchange-100 Index

Value-at-risk (VaR) is a useful risk measure broadly used by financial institutions all over the world. VaR is popular among researchers, practitioners and regulators of financial institutions. VaR has been extensively used for to measure systematic risk exposure in developed markets like of the US, Europe and Asia. In this paper we analyze the accuracy of VaR measure for Pakistan’s emerging stock market using daily data from the Karachi Stock Exchange-100 index January 1992 to June 2008. We computed VaR by employing data on annual basis as well as for the whole 17 year period. Overall we found that VaR measures are more accurate when KSE index return volatility is estimated by GARCH (1,1) model especially at 95% confidence level. In this case the actual loss of KSE-100 index exceeds VaR in only two years 1998 and 2006. At 99% confidence level no method generally gives accurate VaR estimates. In this case ‘equally weighted moving average’, ‘exponentially weighted moving average’ and ‘GARCH’ based methods yield accurate VaR estimates in nearly half of the number of years. On average for the whole period 95% VaR is estimated to be about 2.5% of the value of KSE-100 index. That is on average in one out of 20 days KSE-100 index loses at least 2.5% of its value. We also investigate the asset pricing implication of downside risk measured by VaR and expected returns for docile portfolios sorted according to VaR of each stock. We found that portfolios with higher VaR have higher average returns. Therefore VaR as a measure of downside risk is associated with higher returns

Are MENA and Pacific Basin Stock Equity Markets Predictable?

This research uses variance ratio analysis to test whether Middle Eastern, North African (MENA) and Pacific Basin emerging equity markets follow a martingale behavior during the period1980-2004. The conventional Lo and MacKinlay variance ratio test, the multiple variance ratio test of Chow and Denning, rank- and sign-based test of Wright, and wild bootstrap of Kim are used for the monthly return series. The problem of thin trading was addressed using Miller, Muthuswamy, and Whaley’s adjusting procedure. Results have shown traces of a martingale behavior at high holding horizons. However, overall conclusions indicate that the null martingale hypothesis is strongly rejected for the whole sample and considered sub-periods at a 5% significance level. The pattern of the variance ratio estimates signify that the selected stock markets exhibit persistent mean-reverting and predictable behavior in their monthly adjusted returns series. The results expose the ineffectiveness of economic liberalization and privatization measures implemented in the early 1990s to improve their market efficiency. The Asian crisis did not affect the outcomes of the variance ratio analysis. Moreover, it sounds as if the perceptible development in terms of size and liquidity was not sufficient to exhibit a martingale behavior in these markets