Asia-Pacific Financial Markets最新文献

In this paper, we have carried out the predictions for growth or spurt in Systemic Risk across the different categories of financial institutions in India relative to the change in the market prices. We have used Bayes Theorem along with Logistic regressions to work out the actual probabilities regarding the growth in Systemic Risk with the fall in stock prices and Wilcoxon Rank sum Test to validate the robustness of the models. In this paper, we have studied the period from July 2007 to December 2020. An important feature observed was any fall in closing prices beyond 30%, is contributing for 90% growth in systemic risk. A policy implication can follow—that it is imperative to monitor a sharp decline in market prices to the tune of 30% or more by regulators to avoid a crisis. We generally presume that state ownership of Banks particularly in India generates public confidence. Our paper has been able to support the theory of public confidence wherein the Public Sector Banks are contributing less towards the growth of Systemic Risk as compared to Private Banks and NBFCs. The NBFCs are the highest contributor of the growth in systemic risk which we have differentiated from our results. So, in coming days NBFCs are to be closely monitored by the regulators and suitable regulatory measures need to be placed.

This study measures the immediate impact of Russia–Ukraine war on the global stock markets for the first four months since Russia’s first invasion attempt on February 24, 2022. Daily closing stock indices have been used from selected stock markets of six different continents. By applying event study method, it observes mixed impact on different stock markets. Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH 1,1) indicates the presence of significant volatility and leverage effect in all the markets. Regression estimates show significantly positive impact of VIX and negative impact of oil on the abnormal returns of the global stock markets. Diversifying energy supply and source, accelerating deployment of renewables and promoting electronic vehicles and machines might bring positive result for the financial market. It is expected that this research will provide policymakers, regulatory authorities, investors and all concerned stakeholders a precise guideline to handle the immediate impact of war on the stock prices and to formulate appropriate strategies to keep investment free from risk and uncertainties.

In this paper, we are interested in the optimal investment and reinsurance strategies of an insurer who wishes to maximize the expected power utility of its terminal wealth on finite time horizon. We are also interested in the problem of maximizing the growth rate of expected power utility per unit time on the infinite time horizon. The risk process of the insurer is described by an approximation of the classical Cramér–Lundberg process. The insurer invests in a market consisting of a bank account and multiple risky assets. The mean returns of the risky assets depend linearly on economic factors that are formulated as the solutions of linear stochastic differential equations. With this setting, Hamilton–Jacobi–Bellman equations that are derived via a dynamic programming approach have explicit solution obtained by solving a matrix Riccati equation. Hence, the optimal investment and reinsurance strategies can be constructed explicitly. Finally, we present some numerical results related to properties of our optimal strategy and the ruin probability using the optimal strategy.