Search results

This paper compares the performance and volatility of the Toronto Stock Exchange in Canada and the Karachi Stock Exchange in Pakistan, as well as the sensitivities of the two stock exchanges to major global events. The purpose of this paper is to assist the Pakistani immigrants in Canada in their investment decisions.

This paper uses the generalized autoregressive conditional heteroskedasticity model to estimate volatility of the two stock exchanges. Moreover, the mean adjusted returns approach associated with the event study methodology is used to find out the impact of major global events on these stock exchanges.

The study finds that the Toronto Stock Exchange outperforms the Karachi Stock Exchange in the pre-September 11 attack period, while the latter outperforms the former in the post-September 11 attack period. The study also shows that there has been a significant improvement in the risk-adjusted return of the Karachi Stock Exchange in the post-September 11 attack period. Moreover, this paper finds that the impact of major global events is more significant on the Toronto Stock Exchange relative to the Karachi Stock Exchange on the event date.

This paper is one of the very few to analyze and compare stock performances from the perspective of immigrant communities. The paper is valuable for Pakistani immigrants living in Canada or any investors interested in Karachi Stock Exchange and its comparison with Toronto Stock Exchange. Moreover, the paper can be of value to the Pakistani Government in terms of their promotional activities.

This research paper aims to analyze the stock exchanges of developed, emerging and developing countries to investigate the volatility in stock markets and to evaluate the rate of mean reversion.

The stock exchanges included in the research are NASDAQ, Tokyo stock exchange, Shanghai stock exchange, Bombay stock exchange, Karachi stock exchange and Jakarta stock exchange. Secondary daily data from Bloomberg are used to conduct the research for the period from January 2011 to December 2018. Generalized autoregressive conditional heteroskedasticity (GARCH) (1,1) model was applied to examine volatility and the half-life formula was used to calculate mean reversion in days.

The research concluded that all the stock exchanges included in the research satisfy the assumptions of mean reversion. Developing countries have the lowest volatility while emerging countries have the highest volatility which means that the rate of mean reversion is fastest in developing countries and slowest in emerging countries.

Future studies can determine the reasons for fastest rate of mean reversion in developing countries and slowest rate of mean reversion in emerging countries.

Developing countries show the lowest mean reversion in days while the emerging countries show the highest mean reversion in days indicating that developing countries take less time to revert to their mean position.

The majority of previous studies on univariate volatility models are mostly on applications of the models. Only a few researchers have taken the robustness of the models into account when applying them in emerging countries and not in developed, developing and emerging countries in one place. This makes the current study unique and more rigorous.

Reports concerns that the lifting of restrictions on portfolio investment by foreigners would lead to overheating or excessive volatility in the capital markets of developing countries. Describes the abrupt lifting of restrictions on the Karachi Stock Exchange in Pakistan, given six notable developments in 1991. Examines the homogeneity of variance on weekly returns on the market index from 1988 to 1993 (over the period of liberalization). Finds that stock market volatility will reflect economic variables in the long run, while the market is shown to be information‐efficient.

The purpose of this paper is to examine the investment behavior of Pakistani stock market participants, specifically with respect to their tendency to exhibit herd behavior.

The study employed two different methodologies suggested by Christie and Huang (1995) and Chang et al. (2000) to test herd formation. Results are based on daily and monthly stock of KSE-100 index for the period 2002-2007.

Results based on daily and monthly stock data from Karachi Stock Exchange indicate the non-existence of herd behavior for the period 2002-2007 and find no support for the rational asset pricing model and investor behavior found inefficient. This study denied proved evidence of herding due to market return asymmetry, high and low trading volume states and asymmetric market volatility. Macroeconomic fundamentals have insignificant role in decision-making process of investor therefore has no impact on herding behavior. However, during liquidity crisis of March 2005, Pakistani stock market exhibit herding behavior due to asymmetry of information among investors, presence of speculator and questionable badla financing-local leverage financing mechanism.

In future, this study can be improved by employing stock returns portfolios based on market capitalization or sector wise portfolio returns from KSE-100. Furthermore by identifying those factors that cause market to be overall inefficient and define the pattern of the investor trading activities.

For an accurate valuation of assets investors should incorporate the herding factor.

As the assets are mispriced, investor behavior is uncertain and markets are inefficient, foreign investors should invest with caution, as large numbers of securities are needed to achieve the same level of diversification than in an otherwise normal market.

In Karachi Stock Exchange, it is first attempt to uncover the herding behavior. This paper contribute to the body of knowledge by investigating the herding behavior in the emerging markets since most of the previous study concentrate more on the developed markets. Furthermore, the study also analyzed the herding behavior in different economic condition and includes economic variables and examines asymmetric effect. This study presents an integrated model to test herding behavior in Pakistani equity market. Consideration of said behavioral effect in the decision-making process of investor will make the decisions more rational and optimal.

The purpose of this paper is to investigate the market reaction to the decision made by the management of the Karachi Stock Exchange (KSE) to impose a price floor that resulted in trading curbs in 2008. The paper analyzes if regulatory intervention helped in restoring investor confidence.

The paper examines the effect of enforcement of a price floor and trading curbs by splitting the time period studied into two periods: pre-floor and post-floor period. The parametric t-statistics and non-parametric Mann-Whitney test are used to compare the abnormal returns (ARs), abnormal trading volume, bid-ask spread, Amihud illiquidity ratio, and price volatility between the two periods. Event study was conducted to observe the behavior of market returns surrounding market-wide price floor. Finally, multivariate regression analysis was also applied by controlling for factors that might influence valuation, liquidity, and volatility. The standard errors have been corrected for cross-sectional clustering due to market-wide restrictions.

The study found an adverse impact of price freeze and trading curb in the KSE, following the relaxation of floor (resumption of active trading). First, the price of securities (or ARs) significantly declined following the relaxation of the price freeze. Second, the market liquidity deteriorated following the relaxation of the price floor. Third, the price volatility increased in the post-floor period. It seems that the decision made by the KSE’s board to implement lower cap on prices for an extended period was ineffective.

Market intervention by regulators to bring calm in the financial markets have negative consequences across the globe. The results presented in this paper suggest that implementing price floor brought inefficiency in the market and prevented firms from raising capital to finance their future investments. The author believe this study will add to the knowledge base of regulatory intervention and its impact on the performance of financial markets.

There is no empirical evidence on the impact of price limits on volatility in emerging markets. The author selected Pakistan as a case study, where we particularly focus upon impact of the enforcement of a price floor around the peak of Global Financial Crisis (or market intervention) in Pakistan. This study also documents the effect of trading curb on liquidity and volatility in an emerging market, given that a majority of research on trading halt/price limits is based on developed markets.

This study examines return and volatility spillovers from the US and Japanese stock markets to three South Asian capital markets – (i) the Bombay Stock Exchange, (ii) the Karachi Stock Exchange and (iii) the Colombo Stock Exchange. We construct a univariate EGARCH spillover model that allows the unexpected return of any particular South Asian market to be driven by a local shock, a regional shock from Japan and a global shock from the USA. The study discovers return spillovers in all three markets, and volatility spillovers from the US to the Indian and Sri Lankan markets, and from the Japanese to the Pakistani market. Regional factors seem to exert an influence on these three markets before the Asian financial crisis but the global factor becomes more important in the post-crisis period.

Internationalization of capital markets gives opportunities to investors to invest their money in the country of their choice, not just in their own country. The relationships between international stock markets have become increasingly important in recent times. The purpose of this paper is to study the inter‐linkages between stock markets of India, Pakistan and Sri Lanka.

This paper studies the inter‐linkages between stock markets of India, Pakistan and Sri Lanka. Daily closing levels of the benchmark indices in the three countries are taken for a period of January 2003‐June 2010. While line charts, correlogram and unit‐root test are applied to check the stationary nature of the series; Granger's causality model, vector auto regression (VAR) model and variance decomposition analysis are performed to find out the linkages between the markets under study.

The paper concludes that while the National Stock Exchange (India) Granger causes Karachi Stock Exchange (Pakistan) and Colombo Stock Exchange (Sri Lanka), the vice versa is not true. These results of Granger's causality model are also confirmed by the VAR models.

Studies have been conducted in large numbers to test the linkages and integration between stock exchanges of the developed nations, namely the USA, Canada, Europe and Japan. Even the studies that have focused on the developing and under‐developed nations have studied the linkages of those with the developed nations. Little research has been conducted about the inter‐linkages between the nations from Asia. Even fewer studies have focused on stock exchanges in the South‐Asian region. This research paper focuses on the return from the benchmark stock exchanges from these three countries and also on the linkages between India, Pakistan and Sri Lanka.

The current paper aims to fill a gap in the literature by analyzing the nature of volatility on the Karachi Stock Exchange (KSE) 100 index of the KSE, and develop an understanding as to which model is most suitable for measuring volatility among those used. The study contributes significantly to the literature as, compared with the limited previous studies of Pakistan undertaken in the past, it covers three types of data (i.e. daily, weekly and monthly) for the whole period from the introduction of the KSE 100 index on November 2, 1991 to December 31, 2013. In addition, to analyze the impact of global financial crises upon volatility, the data have been divided into pre-crisis (1991-2007) and post-crisis (2008-2013) periods.

This study has used an advanced set of volatility models such as autoregressive conditional heteroskedasticity [ARCH (1)], generalized autoregressive conditional heteroskedasticity [GARCH (1, 1)], GARCH in mean [GARCH-M (1, 1)], exponential GARCH [E-GARCH (1, 1)], threshold GARCH [T-GARCH (1, 1)], power GARCH [P-GARCH (1, 1)] and also a simple exponentially weighted moving average (EWMA) model.

The results reveal that daily, weekly and monthly return series show non-normal distribution, stationarity and volatility clustering. However, the heteroskedasticity is absent only in the monthly returns making only the EWMA model usable to measure the volatility level in the monthly series. The P-GARCH (1, 1) model proved to be a better model for modeling volatility in the case of daily returns, while the GARCH (1, 1) model proved to be the most appropriate for weekly data based on the Schwarz information criterion (SIC) and log likelihood (LL) functionality. The study shows high persistence of volatility, a mean reverting process and an absence of a risk premium in the KSE market with an insignificant leverage effect only in the case of weekly returns. However, a significant leverage effect is reported regarding the daily series of the KSE 100 index. In addition, to analyze the impact of global financial crises upon volatility, the findings show that the subperiods demonstrated a slightly low volatility and the global economic crisis did not cause a rise in volatility levels.

Previously, the literature about volatility modeling in Pakistan’s markets has been limited to a few models of relatively small sample size. The current thesis has attempted to overcome these limitations and used diverse models for three types of data series (daily, weekly and monthly). In addition, the Pakistani economy has been beset by turmoil throughout its history, experiencing a range of shocks from the mild to the extreme. This paper has measured the impact of those shocks upon the volatility levels of the KSE.

The purpose of the study is to find out the impact of gold and oil prices on the stock market.

This study uses the data on gold prices, stock exchange and oil prices for the period 1991–2016. This study applied descriptive statistics, augmented Dickey–Fuller test, correlation and autoregressive distributed lag test.

The data analysis results showed that gold and oil prices have a significant impact on the stock market.

Following empirical evidence of this study, the authors recommend that investors should invest in gold because the main reason is that hike in inflation reduces the real value of money, and people seek to invest in alternative investment avenues like gold to preserve the value of their assets and earn additional returns. This suggests that investment in gold can be used as a tool to decline inflation pressure to a sustainable level. This study was restricted to use small sample data owing to the availability of data from 1991 to 2017 and could not use structural break unit root tests with two structural break and structural break cointegration approach, as these tests require high-frequency data set.

This study provides information to the investors who want to get the benefit of diversification by investing in gold, oil and stock market. In the current era, gold prices and oil prices are fluctuating day by day, and investors think that stock returns may or may not be affected by these fluctuations. This study is unique because it focusses on current issues and takes the current data in this research to help investment institutions or portfolio managers.

This paper aims to examine the performance of Islamic and conventional stocks listed at the Pakistan Stock Exchange by using both parametric and non-parametric approaches. The motivation is to do risk-return analysis of Islamic stock prices and conventional stock prices.

It uses various measures of performance, e.g. Sharpe ratio, Treynor ratio, Jensen's alpha, beta, generalized auto-regressive conditional heteroskedasticity and stochastic dominance. Using the Karachi Meezan Index-30 (KMI-30) and the Karachi Stock Exchange Index-30 (KSE-30) as proxies for Islamic and conventional stock prices, respectively, it examines the performance of Islamic and conventional stocks. The daily data of KMI-30 and KSE-30, covering period from June 9, 2009 to June 20, 2020 are used.

The results show that the overall KMI-30 outperforms the KSE-30. The returns of the KMI-30 are greater than the KSE-30. However, the risk and volatility of the KMI-30 and KSE-30 are similar. Further, the KMI-30 has higher excess returns per unit of total risk than the KSE-30. But both indexes have similar excess returns per unit of systematic risk. Moreover, the KMI-30 returns have stochastically dominance over the KSE-30 returns. These results reveal that the Islamic index performs better than the conventional index.

The findings provide several practical implications in financial and investment decisions making by investors, managers and policymakers such as strategies for asset allocation and investment. Further, in risk management, it provides guidance for allocating portfolios and managing risk. The investment in Islamic stocks may mitigate potential risk within asset portfolios.

This research is unique in its approach to the analysis of the performance comparison of conventional and Islamic stock by using comprehensive parametric and non-parametric estimation techniques. Such research has not been undertaken in the Pakistan's equity market since.