業績一覧

Abstract

This study examines whether endogenous inter-firm volatility spillovers amplify industry risk in China's new energy sector. It constructs a leave-one-out industry index, extracts residual stock returns, estimates firm-level residual conditional volatility, and applies a LASSO-VAR connectedness approach. The results show that firm-level residual volatilities remain widely interconnected even after removing common factors, and that spillover measures are positively associated with industry volatility.

Abstract

This study investigates the risk spillovers of economic policy uncertainty across macroeconomic and financial systems in China and the United States using mixed-frequency data. The results show different transmission patterns across the two countries and intensified spillovers during the COVID-19 pandemic.

Abstract

This study investigates the role of common global factors in exchange rate volatility and volatility co-movement. Using a multivariate factor stochastic volatility model, the analysis identifies three currency clusters associated with the USD, EUR, and commodity-exporting countries, and uses wavelet coherence techniques to evaluate common factors as drivers of co-movement.

Abstract

This study proposes a framework that decomposes volatility and higher-moment kurtosis into good and bad volatility/kurtosis related to positive and negative shocks. It analyzes spillover effects between sustainable and traditional investments and finds that bad volatility spillovers dominate good volatility spillovers during most periods, while good kurtosis spillovers usually dominate bad kurtosis spillovers. During extreme events such as Brexit and COVID-19, bad kurtosis spillovers can become dominant.

Abstract

This study investigates whether conditional higher moments provide additional information beyond lower moments in spillover analysis and portfolio construction. Using the autoregressive conditional density model, it estimates conditional skewness and kurtosis for nine major cryptocurrency markets and shows that spillover effects vary across moments. Minimum connectedness portfolios based on higher moment spillovers exhibit superior hedge effectiveness and Sharpe ratios.

Abstract

This study analyzes the impact of the COVID-19 pandemic and the Russia-Ukraine war on connectedness in lower-order moments and higher-order moments across green finance markets. It uses the Diebold-Yilmaz and Barunik-Krehlik methods and finds that COVID-19 had a significant influence on spillovers in the green finance market, while the Russia-Ukraine war had a milder effect.

Abstract

This study estimates conditional skewness for nine S&P Goldman Sachs Commodity indices and applies a TVP-VAR-based connectedness approach to investigate higher moment spillovers across commodity markets. It finds evidence of extreme risk transfers and shows that spillovers in returns, volatility, and skewness strengthen during major extreme events.

Abstract

This study analyzes dynamic connectedness among the ESG stock index, renewable energy stock index, green bond stock index, sustainability stock index, and carbon emission futures using a DCC-GARCH-based dynamic connectedness approach. It further applies the DCC-GARCH t-copula model to calculate hedging ratios and portfolio weights.

Abstract

This paper examines the time and frequency dynamics of spillover effects among eight major world equity market indexes. It extends the Diebold-Yilmaz approach and the Barunik-Krehlik methodology to estimate skewness spillovers, finding that total skewness spillover is much smaller and smoother than total volatility spillover.

Abstract

Using the Diebold-Yilmaz and Barunik-Krehlik models with monthly U.S. data, this study estimates return and volatility connectedness transmitted from commodity markets and the Kansas City financial stress index to macroeconomic indicators. It finds different shock transmission speeds across return and volatility variables and highlights the long-term component of spillovers during the global financial crisis.

Abstract

This study analyzes return and volatility spillovers from fossil fuel markets to electricity spot and futures markets in Europe. It finds that natural gas has the highest return spillover effect on electricity markets, that return spillovers increase with the delivery period of electricity futures, and that volatility spillovers are mostly generated in the long term.

Abstract

This study investigates time-frequency dynamics of return and volatility spillovers between stock markets and natural gas, crude oil, and gold in the United States and China. It finds that crude oil plays a strong role in return spillovers, while gold has a strong volatility spillover effect, and that spillover patterns differ across countries, frequencies, and extreme events.

Abstract

This study analyzes return and volatility spillovers among natural gas, crude oil, and electricity utility stock indices in North America and Europe. It finds stronger total spillovers in Europe than in North America, greater volatility spillovers from crude oil than natural gas, and dynamic changes around extreme events.

Abstract

This study examines the dynamic relationship between housing prices and bank credit in China using a time-varying parameter VAR model with stochastic volatility. It separately studies housing loans on the demand side and real estate development loans on the supply side, finding time-varying relationships and stronger effects from housing prices to bank credit than in the opposite direction.

Abstract

Based on 5-minute high-frequency trading data, this study examines the time-varying causal relationship between herding behavior and multiscale spillovers in the Chinese stock market. It uses a time-varying Granger causality test and finds a strong relationship between herding and spillover effects, particularly for return and skewness spillovers.

Abstract

This study investigates whether conditional higher moments provide additional information beyond lower moments in spillover analysis and portfolio construction. Using the autoregressive conditional density model, it estimates conditional skewness and kurtosis for nine major cryptocurrency markets and shows that higher moment spillovers provide distinct information for hedging and investment strategies.

Abstract

This study presents a framework that breaks down kurtosis into positive and negative shocks, distinguishing between good and bad kurtosis. It analyzes asymmetric kurtosis spillovers among sustainable and traditional investments and finds that good kurtosis spillover generally surpasses bad kurtosis spillover, except during specific extreme events such as Brexit and COVID-19.