Factors affecting the development of the Vietnamese derivative securities market

Pakistan’s capital market and economy have significant features for examining the dynamics of the dividend policy. The agency conflicts between the management and the investors of the firms are main barriers to the success of the firm. The shareholder is generally taking away all the rights and similarly has a control on the decision concerning the dividend policy. The dividends are conveying better information than any other source regarding the firm’s prospects. The aim of this research is to identify and analyze the influence of shareholder preference and dividend signaling on the dividend policy of the corporations in Pakistan. The respective study presents the analysis of top financial management beliefs by taking eighty listed corporations on Pakistani stock exchanges during 2017–2018. Pearson correlation and multiple regressions are applied on responses to explore whether there is an influence regarding the shareholder preferences and the signaling mechanism on the dividend policy of the listed firms in Pakistan. Through statistical techniques the findings proved that shareholder preferences and dividend signaling have a positive and significant relationship with the dividend policy of listed corporations. Dividend policy is the response of investor preferences and signaling aspect of dividends.

The stock market represents complex systems where multiple agents interact. The complexity of the environment in the financial markets in general has encouraged the use of modeling by multi-agent platforms and particularly in the case of the stock market.
In this paper, an agent-based simulation model is proposed to study the behavior of the volume of market transactions. The model is based on the case of a single asset and three types of investor agents. Each investor can be a zero intelligent trader, fundamentalist trader or traders using historical information in the decision making process. The goal of the study is to simulate the behavior of a stock market according to the different considered endogenous and exogenous variables.

The government bond (GB) has become the most attractive investment portfolio option, even though many macroeconomic factors affect the bond yield. This paper aims to investigate the determining factor of local currency government bond yield by considering the inflation rate, credit default swap, stock market index, exchange rate, and volatility index. This study used 240 data panel from the Bloomberg stock market in the form of data panel covering Southeast developing countries, namely Indonesia, Thailand, Malaysia, and the Philippines, for five years or sixty months from January 2015 to December 2019. Data analysis used recursive models and multivariate regression techniques using EViews software. The random effect model results revealed that change in the foreign exchange rate and volatility indexes affected, partially and simultaneously, the changes in the stock market index. The result also showed that changes in the stock market index, inflation rate, and credit default swap affected, partially and simultaneously, government bond yield changes. These results suggest that the government bond yield could be managed by controlling volatility index, foreign exchange rate, stock market index, inflation rates, and credit default swaps. This finding could provide an insight into the policymaker and fiscal authority on managing the risk of government bonds under control during high volatility or even making it reasonably lower. This result could contribute to the current research in the field of financial management.

Acknowledgment
It is the author’s pleasure to thank Muhammad Aulia SE MSc CSA® from the Ministry of Finance of Republic Indonesia, for his invaluable contribution to encourage this study and also to share the data required for this paper. He also delivers essential insights into improving the quality of this work. This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.