Research on The Volatility Spillover Effect among Foreign Exchange Market Stock Market and Bond Market in China

This study examines the effects of oil shocks by their respective causes and of volatility spillover including leverage effects. Previous studies did not analyze oil factor by categorizing it into three components (supply shock, demand shock, and market shock) as determinants of rate of return in stock markets, a key issue in finance. Results show that oil shocks determine returns in the global stock market, bond market, foreign exchange market, and energy market, and that their effects vary by types of markets, levels of oil prices, and types of oil shocks. Second, the leverage effect of oil shocks and the spillover effect of volatility in demand shock and market shock are mostly statistically significant during periods characterized by high oil prices.

Contagion effect between China's bond market and China's stock market are analyzed by Granger-causality test among four markets, which are exchange bond market, interbank bond market, Shanghai stock market and Shenzhen stock market. The empirical results show that there is a two-way strong contagion effect between exchange bond market and inter-bank bond market, and there is a one-way contagion effect from Shanghai stock market and Shenzhen stock market to inter-bank bond market, and there is no contagion effect between exchange bond market and stock market. The results indicate that the unified degree of China's bond market increases, and the bond market can hedge risk of stock market, and the exchange bond market is independent of the stock market and has little influence on the stock market.

With the openness and marketization of China’s financial market accelerating, the linkage between various financial markets is increasingly significant. By utilizing VAR model and asymmetric GARCH (1,1)-BEKK model, this paper analyzes the price spillover effect and the volatility spillover effect among stocks returns, exchange rate of returns and money rate. The results show that 1) between currency market and stock market there is only unidirectional mean spillover effect from currency market to stock market; 2) however, there exists asymmetrical bidirectional mean spillover effect both between stock market and money market and currency market and money market, which exhibits time-varying variance and volatility persistence; 3) there exists bidirectional volatility spillover effect between currency market and money market, however there is only unidirectional volatility spillover effect from stock market to money market, which is demonstrated from money market to currency market.

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.

Background The purpose of this study is to examine volatility spillover effects between stock market and foreign exchange market in selected Asian countries; Pakistan, India, Sri Lanka, China, Hong Kong and Japan. This study considered daily data from 4th January, 1999 to 1st January, 2014. Methods This study opted EGARCH (Exponential Generalized Auto Regressive Conditional Heteroskedasticity) model for the purpose of analyzing asymmetric volatility spillover effects between stock and foreign exchange market. Results The EGARCH analyses reveal bidirectional asymmetric volatility spillover between stock market and foreign exchange market of Pakistan, China, Hong Kong and Sri Lanka. The results reveal unidirectional transmission of volatility from stock market to foreign exchange market of India. The analysis reveals no evidence of volatility transmission between the two markets in reference to Japan. Conclusions The result of this study provide valuable insights to economic policy makers for financial stability perspective and to investors regarding decision making in international portfolio and currency risk strategies.

(ProQuest: ... denotes formulae omitted.)I. INTRODUCTIONA number of studies have examined the effect of macroeconomic variables on financial asset returns. Since the work of Ross (1976), various macroeconomic variables such as GDP, inflation, and the trade balance as well as financial market variables such as interest rates and exchange rates have been tested to identify the influential factors for the expected return of a financial asset. However, few studies have been conducted about the relationships between macroeconomic volatility and asset market volatility. Schwert (1989) states that volatility in macroeconomic fundamentals and financial market factors are helpful in predicting stock return volatility, and vice versa.The key objective of this study is to investigate the return and volatility spillover effects between domestic and international financial and asset markets focused on the Korean economy. In particular, the presence of return and volatility spillover effects from country risk and advanced economy asset markets to Korean asset markets is the primary interest in this study.Before approaching the main subject, it is necessary to specify the concept of country risk. The Credit Default Swap (CDS) spread underlying government bonds is used as a measure of country risk in this paper.1 The CDS premium generally rises when credit risk of the underlying asset increases. Hence, the CDS premium is interpreted as a measure of credit rating of the authorities or the institutions which issue the underlying asset. For this reason, the CDS premium which is on the basis of bond in foreign money issued by the each country's government is used well as an indicator which reflects the country's credit rating.There have been considerable studies which show when external or internal economic and financial shocks affect the country's economy, the CDS market reacts sensitively and shows the current state through its index, called the CDS spread (see Remolona et al., 2008; Baum and Wan, 2010; Longstaff et al., 2011). However, compared with the substantial amount of empirical and theoretical studies on the foreign CDS market since 2000, most studies related to credit risk in Korea have focused on the credit premium in the bond market because of immature market conditions and deficiency of data for the Korean CDS market. Recently, several pioneering works for the Korean CDS spread are in progress. Nam and Byun (2006) conduct empirical analysis to find deterministic elements of the Korean CDS spread. They find that variations of the Korean CDS spread is affected by the variations of past value of CDS spread itself, domestic macroeconomic fundamentals, and financial variables such as yields on government bonds, stock prices, and the won/dollar exchange rate. They also find that the CDS market is more efficient in reflecting the change of credit status in the underlying asset to the change of credit risk spread than is the bond market. Considering the determinants of the CDS premium underlying Korean government bonds, Kim (2009) finds that typically well-known determinants of the CDS premium such as the short-term foreign debt ratio, exchange rate, and stock prices are ascertained to be statistically significant in the Korean CDS market. That is, he finds that the CDS premium decreases when stock prices increase and the exchange rate decreases.Early studies on the relationship between CDS spread and other macroeconomic or financial market variables usually focus on the link between the levels of the series without considering the link between the returns or volatilities of the series. However, examining the relationship between returns or volatilities of the series reflects the current trend of studies on the analysis for the relationship between financial markets. In a study on the relationship between CDS spread change and stock return, Norden and Weber (2009) analyse the relationship among CDS, bond and stock markets empirically. …

The volatility spillover effect between the foreign exchange and stock markets has been a major issue in economic and financial studies. In this paper, GC-MSV model was used to study the spillover effect between the foreign exchange market and the stock market after the reform of the RMB exchange rate mechanism. The empirical results show that there is a negative correlation of dynamic price spillovers between the foreign exchange and stock markets. There are asymmetric volatility spillover effects between these two markets for both RMB stages—continued RMB appreciation or constant RMB shock (a significant reduction in appreciation). However, this has been reduced over time. In conclusion, The RMB exchange rate is a key variable that can affect the internal and external equilibrium of the national economy in an open economic environment, and the stock market is capable of quickly reflecting subtle changes in the real economy. In order to keep the stability of the financial markets and the healthy and rapid development of national economy, some suggestions were proposed.

We study the forecasting of future realized volatility in the stock, bond, and foreign exchange markets, as well as the continuous sample path and jump components of this, from variables in the information set, including implied volatility backed out from option prices. Recent nonparametric statistical techniques of Barndor-Nielsen & Shephard (2004, 2006) are used to separate realized volatility into its continuous and jump components, which enhances forecasting performance, as shown by Andersen, Bollerslev & Diebold (2005). We generalize the heterogeneous autoregressive (HAR) model of Corsi (2004) to include implied volatility as an additional regressor, and to the separate forecasting of the realized components. We also introduce a new vector HAR (VecHAR) model for the resulting simultaneous system, controlling for possible endogeneity issues in the forecasting equations. We show that implied volatility contains incremental information about future volatility relative to both continuous and jump components of past realized volatility. Indeed, in the foreign exchange market, implied volatility completely subsumes the information content of daily, weekly, and monthly realized volatility measures, when forecasting future realized volatility or its continuous component. In addition, implied volatility is an unbiased forecast of future realized volatility in the foreign exchange and stock markets. Perhaps surprisingly, the jump component of realized return volatility is, to some extent, predictable, and options appear to be calibrated to incorporate information about future jumps in all three markets.

<abstract> <p>With the aim of effectively preventing and controlling systemic risk, by stimulating the advancement of the green bond market, it is significant and imperative to help investors and policymakers adopt more effective measures, which will ensure them to maximize profit. We construct VAR, DCC-GARCH and Copula-CoVaR models, and study the spillover effect between the green bond market and traditional bond market from the three perspectives of mean spillover, volatility spillover and extreme risk spillover using the data on daily closing prices of green bond market and traditional bond market indices. The research findings of this paper are as follows: (1) There are three spillover effects of mean value, volatility and extreme risk among the green bond market, corporate bond market, enterprise bond market and conventional bond market. (2) From the perspective of mean spillover between markets, only the mean spillover between the conventional bond market and the green bond market is bidirectional, and there is the profoundest impact of spillover from the green bond market to the conventional bond market. (3) As far as the volatility spillover between markets is concerned, the volatility spillover between the three traditional bond market and the green bond markets are all positive. The volatility spillover between the conventional bond market and the green bond market is the largest, which is particularly obvious in the first half of 2018 and the first half of 2020. (4) In terms of inter-market extreme risk spillover, the risk spillover between the green bond market and the traditional bond market is positive. The green bond market contributes more to the risk spillover of the enterprise bond market, and it has a time-varying risk spillover effect on the traditional bond market.</p> </abstract>

This paper uses the VAR-GARCH-BEKK model, DY spillover index, and event study method to measure the yield spillover effect and volatility spillover effect of international commodity market on China’s stock market, exchange rate market and bond market, and tests the impact of the conflict between Russia and Ukraine. The findings show some interesting results. First, the international commodity market has a yield spillover effect on China’s financial market; that is, the rise of the international commodity price leads to the rise of China’s stock market price, the appreciation of the RMB exchange rate, and the decline of the bond price. Second, the international commodity market has a volatility spillover effect on China’s financial market, which is the largest for the stock market, followed by the exchange rate market, the smallest for the bond market, and the spillover effect is time-varying. Thirdly, the conflict between Russia and Ukraine will significantly increase the volatility spillover effect of the international commodity market on China’s bond market.

This paper put forward a dynamic ΔCoES model to study the time-varying risk spillover between China’s stock market, exchange market and bond market from January 2007 to January 2017, based on the ΔCoVaR model proposed by Adrian and Brunnermeier (2016). The results show that the risk spillover of financial market in China is time-varying and asymmetric. During the financial crisis, the level of risk spillover between financial markets in China is higher than the average of spillover in the whole sample. During the “stock crash” of 2015, the risk spillover level of the stock market to the bond market and the foreign exchange market is higher than the average risk spillover level of the sample and the risk spillover level from the bond market to the stock market and the foreign exchange market is also higher than the average risk spillover level of the sample. After the exchange rate reform on August 11th of 2015, the risk spillover from exchange market to stock market and the bond market showed an upward trend, and in 2016, it was higher than that of the previous 8 years.

from co-integration test, error correction model analysis and the Granger causality test, we found that there is a co-integration relationship between China's bond market and stock market in volume, but there is no Granger causality between the two markets. Overall, the connection between China's bond market and stock market is low, the reaction of the information is not particularly fast, and the two markets are in segmentation state. Based on positive research, some relevant suggestions will be put forward for the above conclusions.

During the period spanning from 2007 to 2021, China had substantial increase in its Gross Domestic Production (GDP). However, it is noteworthy that this rise was not mirrored by a commensurate expansion in China's A-share market. When examining the performance of China's stock market in relation to other major global economies within the same time frame, it becomes evident that the overall returns of China's stock market are comparatively lower. For example, Standard & Poors 500 increased 236.11%, Nasdaq Composite Index increased 547.75%, the German Stock Index 30 increased 109.99%, and Nikkei Stock Average (Nikkei 225) increased 66.21%, whereas Shanghai Stock Exchange Composite Index increased 33.41%. Based on the monthly Initial Public Offering (IPO) proceeds of China's stock market from 2007 to 2021, this paper comprehensively examines the impact of IPO activities on China's stock market, including the correlation coefficients among IPO fundraised, index amplitude, index return, and GDP. By studying the correlation between the Chinese All-securities Index (CSI) data and IPO fundraising, as well as exploring the impact of policy changes on the market, it can be concluded that IPO fundraising itself has a limited impact on market returns. The low yield in China's country's stock market might be due to corporate information asymmetry, corporate information fraud, and imperfect supervision. The contributions of this paper include the summary and interpretation of China's IPO and related data, the interpretation of China's IPO reform and other policy actions, and the suggestions for the future development direction of China's market.

As the virus invaded and policies such as home isolation and remote work were implemented, the global outbreak of the COVID-19 pandemic in 2020 led to severe economic recession worldwide. The high uncertainty in economic development caused by the virus sparked a "cash rush," with people desiring assets with high liquidity, such as cash. This led to turbulence in global financial markets. Different countries' economic development speeds and social conditions, guided by different national policies, also greatly influenced foreign exchange and bond markets. This paper focuses on analyzing the impact of the Federal Reserve's monetary policy during different periods on the three major markets in the UK: the stock market, foreign exchange market, and bond market. This includes an analysis and interpretation of the performance of the UK's three major markets in response to the Federal Reserve's monetary policy, particularly focusing on the most closely watched policies of interest rate hikes and cuts. These analyses provide valuable reference for subsequent market development and how markets should perform prior to anticipating the Federal Reserve's predicted monetary policies.

"The Study of Relationship between Stock Market and Bond Market in China"