Volatility Spillover Effect of Pan-Asia’s Property Portfolio Markets

This study assesses the spillover effect of the listed property companies that cover pan-Asian countries, namely Malaysia, Thailand, Indonesia, Singapore, Vietnam, South Korea, Japan, China, the Philippines, and Hong Kong. The impact of market integration will create a spillover effect to the countries’ economic performances, in particular the property market. As macroeconomic factors have high correlation with the performance of property security markets, it is therefore important to study the spillover effect by integrating the macroeconomic factors. This study has employed the exponential generalised autoregressive conditional heteroscedasticity (EGARCH) technique to develop the volatility spillover effect among pan-Asian countries. The results reveal high volatility of listed property companies recorded in Hong Kong and China, while Singapore, The Philippines and Japan have shown low volatility spillovers. In terms of macroeconomic factors, gross domestic product (GDP) and money supply (MS) are the most significant factors in influencing the volatility spillover effect among pan-Asian countries. From the standpoint of regional investors, the volatility spillover characteristics of pan-Asian countries will aid property stakeholders in the region in developing their own methods for making investment decisions in the property security market. Furthermore, in uncertain conditions of the financial market, this study will elevate the transparency of the pan-Asian property portfolio market by providing information on the property market volatility spillovers.

Research on volatility spillover effect between foreign exchange and stock market based on computer simulation multi resolution analysis

In order to analyze the volatility spillover effect between foreign exchange and stock market, this paper adopts the wavelet multi-resolution analysis method of computer simulation. Firstly, aiming at the problem of high and low frequency oscillation and exchange rate de-noising, we adopts the generalized autoregressive conditional heteroskedasticity (GARCH) model to carry out the oscillation correction and exponential modification of the exchange rate denoising signal based on wavelet multi-resolution, and carries out the corresponding decomposition and fitting combined with the wavelet multi-resolution of the state transition GARCH. Then, through the computer simulation of the modified wavelet multi-resolution analysis, this paper studies the volatility spillover effect between the foreign exchange market and the stock market from different scales, so as to explore the simultaneous research from the time domain and frequency domain. The empirical results show that the low-frequency signals of RMB exchange rate volatility (RMB-ERV) and stock price volatility (SPV) have co-integration relationship. It is unique in that the volatility spillover effect in different trading cycles is inconsistent: in the short term, it is mainly manifested in the volatility spillover from the stock market (VS-SM) to the foreign exchange market (VS-FEM); and with the extension of the trading cycle, it shows both sides of effects on the VS.

Tracing Return and Volatility Spillover Effect between Exchange Rate and Pakistan Stock Exchange Index

The volatility spillover is broadly measured as the transmission of variability from one financial market to other markets. This study explores the spillover effect between the newly emerged index of the Pakistan stock exchange (PSX) and exchange rate by using the newly proposed alternative methodology by Ghouse et al. (2019) and GARCH model. Furthermore, the index under study is more concise in its composition than other readily used indices. The study finds shreds of evidence for the bidirectional spillover effect between PSX and exchange rate, which will be helpful for central policy makers and markets players in designing effective policy frameworks. Keywords: ARDL; GARCH; spillover effect