In eras of intense debates on the appointment of women on corporate boards, this research sheds light on the structure of board in Asian emerging economies by examining how women on board of family businesses separately and collectively affect the dividend announcement of business organizations. On the basis of the panel data of four Asian emerging economies—China, Malaysia, Pakistan, and India—for the period 2010–2018, the results from our Tobit regression showed the adverse (negative) and significant impact of women on boards and in family businesses upon dividend announcement. It is important that policymakers should not view firms with one eye. There should be a spillover on board gender diversity from international to domestic levels, and international firms should be set as an example for domestic firms for the inclusion of women on boards. It might be the best time for Asian emerging economies to take productive action for balancing the gender in boardroom settings, and to set a minimum mass of women on boards for better and more effective decision making.

We use a bivariate GJR-GARCH model to investigate relationship between trading volume and stock returns. We apply our approach on Pakistan stock exchange on data from January 2012 to March 2016. Our major findings include that negative shock has a greater impact on volatility and investors are more prone to the negative news whereas according to GJR-GARCH good news has greater impact on stock return and there is a strong relationship exist between the trading volume,stock return and stock volatility.

The purpose of this thesis is to distinguish between efficient and inefficient markets and check the validity and efficiency of Arbitrage Pricing Theory in these markets (United States and Hong Kong). In order to distinguish between efficient and inefficient markets, Durbin Watson Autocorrelation tests were applied on 12 stock exchanges name EUROPE, HONG KONG, INDIA, TAIWAN, AMSTERDAM, MALAYSIA, UNITED STATES, CANADA, TOKYO, AUSTRALIA, AUSTRIA, and SWITZERLAND. Furthermore, the efficiency was further checked through comparison of the market and locally listed mutual funds. After the selection of Hong Kong and United States Stock Exchanges, 10 macroeconomic variables (Inflation, Short Term Interest Rate, Long Term Interest Rate, Exchange Rate, Money Supply, Gold Prices, Oil Prices, Industrial Production Index, Market Return and Unemployment Rate were tested upon so that the APT model could be constructed. Tests like Normality and Multi-co-linearity were performed. Principle Component Analysis was used to reduce the number of variables. After all the above mentioned tests 4 variables were chosen to represent the APT in both the Hong Kong and United States Stock Exchanges. Lastly OLS Regression was applied to study the effect of these macroeconomic variables on the stock prices. The results showed that Hong Kong Stock Exchange was the most efficient while United States Stock Exchange fell in the inefficient category. The efficiency of APT was proven through the analysis of the value of R2. This value proved that when similar model of APT is applied in two different stock exchanges, the results would be more efficient in an efficient market like Hong Kong. This is the first attempt at constructing an APT Model based on the economic conditions in one country and applying the same model in a highly efficient market; in order to relate the performance of APT with market efficiency.

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