Unconventional monetary policy and financialization of commodities

Our paper has two stages of analysis. First of all, we examine whether volatility spillover between US equity and commodity markets has significantly changed with the heavy influx of index traders in commodity derivatives markets, which is a phenomenon referred to as financialization. Given that previous findings show institutional traders enter into commodity markets at high liquidity episodes, in the second stage of our analysis, we investigate the particular impact of US quantitative easing policy on spillover between commodity and US stocks. Our results indicate that during financialization period, spillover from stocks to commodities have significantly increased for almost all commodities. More importantly, we show that quantitative easing is one of the underlying reasons for increasing volatility spillover between markets. Including interest rate, currency factors or default spread does not diminish the explicit role of quantitative easing on spillovers.     

Measuring Spot Variance Spillovers when (Co)variances are Time‐varying – The Case of Multivariate GARCH Models

We propose global and disaggregated spillover indices that allow us to assess variance and covariance spillovers, locally in time and conditionally on time‐t information. Key to our approach is the vector moving average representation of the half‐vectorized ‘squared’ multivariate GARCH process of the popular BEKK model. In an empirical application to a four‐dimensional system of broad asset classes (equity, fixed income, foreign exchange and commodities), we illustrate the new spillover indices at various levels of (dis)aggregation. Moreover, we demonstrate that they are informative of the value‐at‐risk violations of portfolios composed of the considered asset classes.     

Is bitcoin a safe haven or a hedging asset? Evidence from China

Based on daily data about Bitcoin and six other major financial assets (stocks, commodity futures (commodities), gold, foreign exchange (FX), monetary assets, and bonds) in China from 2013 to 2017, we use a VAR-GARCH-BEKK model to investigate mean and volatility spillover effects between Bitcoin and other major assets and explore whether Bitcoin can be used either as a hedging asset or a safe haven. Our empirical results show that (i) only the monetary market, i.e., the Shanghai Interbank Offered Rate (SHIIBOR) has a mean spillover effect on Bitcoin and (ii) gold, monetary, and bond markets have volatility spillover effects on Bitcoin, while Bitcoin has a volatility spillover effect only on the gold market. We further find that Bitcoin can be hedged against stocks, bonds and SHIBOR and is a safe haven when extreme price changes occur in the monetary market. Our findings provide useful information for investors and portfolio risk managers who have invested or hedged with Bitcoin.     

Risk spillover between Bitcoin and conventional financial markets: An expectile-based approach

In order to challenge the existing literature that points to the detachment of Bitcoin from the global financial system, we use daily data from August 17, 2011–February 14, 2020 and apply a risk spillover approach based on expectiles. Results show reasonable evidence to imply the existence of downside risk spillover between Bitcoin and four assets (equities, bonds, currencies, and commodities), which seems to be time dependent. Our main findings have implications for participants in both the Bitcoin and traditional financial markets for the sake of asset allocation, and risk management. For policy makers, the findings suggest that Bitcoin should be monitored carefully for the sake of financial stability.     

Time-frequency co-movement and network connectedness between green bond and financial asset markets: Evidence from multiscale TVP-VAR analysis

This study examines the time-frequency co-movement and network connectedness between green bonds and other financial assets in China. We propose wavelet coherence and multiscale TVP-VAR to explore the time-frequency co-movement and spillover connectedness. The empirical results are as follows. First, green bonds positively co-move with conventional bonds across time scales and negatively co-move with stocks and commodities. Second, there is a significant network connectedness of green bonds with conventional bonds in the short term, and the connectedness with stocks and commodities gradually strengthens with the increase in time scales. Third, the dynamic spillover between green bonds and other assets is much greater in the long and medium terms than in the short term. Finally, under crisis shocks, the spillovers spike temporarily in the short term, while they are persistent and at a high level in the long term. Overall, some practical implications are proposed for investors and policymakers.     

Dependent relationships between Chinese commodity markets and the international financial market: Evidence from quantile time-frequency analysis

In this article, the quantile time–frequency method is utilized to study the dependence of Chinese commodities on the international financial market. The impacts of risk management and diversification benefits of different portfolios are examined by calculating the reduction in downside risk. Moreover, we estimate and compare Sharpe Ratios (SRs) and Generalized Sharpe Ratios (GSRs) based on the frequencies of the investigated portfolios. Our empirical results reveal a strong asymmetric response from Chinese commodity markets. Specifically, we find that gold is a safe-haven asset, and due to negative correlations found at lower quantiles in medium and long term, an increase in the USD index damages bull commodity markets but boosts bear conditions under long-term investments, and negative (positive) tail correlations with interest rates (IRs) in bull (bear) markets are observed. It is proven that WTI can decrease short-run risks while USD and GOLD are more efficient in the diversification of downside risk. Adding international commodities may not improve the returns of Chinese commodities at given risk levels in the short and medium term through SRs and GSRs. In brief, investors should consider these dependence structures and modes of risk management in terms of time and frequency.     

International spillovers in global asset markets

The paper empirically estimates the financial transmission within and across bond and equity markets in the four largest global financial markets – the United States, the Euro area, Japan, and the United Kingdom. We argue that international bond and equity markets are highly interconnected both within and across asset classes in a globalized world, where the complex transmission process across various financial assets is not restricted to just the domestic market. This paper employs identification through generalized forecast error variance decompositions to estimate spillovers across four systemic markets in a Vector Autoregression (VAR) framework. We find that asset prices react most strongly to international shocks within the same asset class, but that there are also substantial international spillovers across asset classes. Rolling estimations analysis provides evidence that global asset markets have become more integrated and that the bilateral relationships change over time. Our results are robust to specifications that take into account the monetary policy stance and include foreign exchange markets.     

Risk spillover analysis across worldwide ESG stock markets: New evidence from the frequency-domain

With the increasing global awareness of green environmental protection, the international environmental, social, and governance (ESG) stock markets are developing rapidly together with rising risk linkages across worldwide markets. Therefore, this study explores the risk spillover characteristics of international ESG stock markets in the time and frequency domains and constructs a risk linkage network to further explore the risk contagion mechanism. The results show that in most cases, the developed North American market is the core of outward risk spillover in international ESG stock markets. The entire system presents a small-world structure, and the internal regions display different risk spillover characteristics. Moreover, international ESG markets generally have strong time–frequency spillover and medium-frequency (a month to a year) spillover. In contrast, the high- (a day to a month) and low-frequency (more than one year) spillovers are located at relatively low levels, but they will rise significantly under sudden financial events. The empirical results expand the ESG stock market's theoretical framework and provide a reference for investors and market regulators to reduce the investment risk of ESG.     

Multiscale features of extreme risk spillover networks among global stock markets

This paper studies the multiscale features of extreme risk spillover among global stock markets over various time–frequency horizons. We propose multiscale risk spillover indexes based on GARCH-EVT-VaR, maximal overlap discrete wavelet transform method, and forecast-error-variance decompositions. We further construct multiscale risk spillover networks to visualize risk spillovers at different scales. Our findings show that the US and the UK are detected as the centers of risk spillovers, while Asian stock markets are mainly at the edge of the risk spillover network. The topological properties are unevenly spread over each time scale. The network tends to be closer not only at the short-term scale but also during the financial crisis. For individual features, the US and the UK are super-spreaders of risk spillover at each time scale, while most developing markets mainly act as absorbers. The role of European stock markets is complex at different scales.     

Risk spillovers and portfolio management between developed and BRICS stock markets

This paper investigates spillover effects and portfolio diversification between the four major developed stock markets (USA, Europe, Japan and Asia) and five of the most important emerging stock markets known as the BRICS (Brazil, Russia, India, China and South Africa). To this end, we apply the multivariate DECO-FIEGARCH model to daily spot indices during the period 1998–2016. The results reveal a significant and asymmetric long memory process for both the developed and the BRICS markets. Moreover, we find a significant variability in the time-varying conditional correlations between the considered markets during both bull and bear markets, particularly from early 2007 to summer 2008. Additionally, we analyze the optimal portfolio weights, time-varying hedge ratios and hedging effectiveness based on the estimates of the model. The results underline the importance of overweighting the optimal portfolios with stocks from the developed countries over those from the BRICS. Finally, we assess the practical implications for mixed developed-BRICS stock portfolios, based on finding strong evidence of diversification benefits and downside risk reductions that confirm the usefulness of using developed market stocks in the BRICS stock portfolio risk management.     

Information transmission between small and large stocks in the National Stock Exchange in India: An empirical study

The study investigates return and volatility spillover effects between large and small stocks in the national stock exchange in India using daily index data on S&P CNX Nifty, CNX Nifty Junior and CNX Midcap. The VAR model together with the variance decomposition (VDC) and the impulse response function (IRF) analysis have been employed to uncover both casual and dynamic relationship between the large stocks and small stocks. The results show that there are very significant return spillovers from the market portfolio of large stocks to the portfolio of small stocks. To investigate the volatility spillover the study has used standard BEKK model and asymmetric BEKK model. Although, based on the standard BEKK model we have observed unidirectional volatility spillovers from the portfolio of large stocks to the portfolio of small stocks, the finding was less reliable. The more reliable finding, which is based on asymmetric BEKK model, is that there is bidirectional volatility spillover between the portfolio of large stocks and the portfolio of small stocks.     

Jumps,cojumps and macro announcements

We use recently proposed tests to extract jumps and cojumps from three types of assets: stock index futures, bond futures, and exchange rates. We then characterize the dynamics of these discontinuities and informally relate them to US macroeconomic releases before using limited dependent variable models to formally model how news surprises explain (co)jumps. Nonfarm payroll and federal funds target announcements are the most important news across asset classes. Trade balance shocks are important for foreign exchange jumps. We relate the size, frequency and timing of jumps across asset classes to the likely sources of shocks and the relation of asset prices to fundamentals in the respective classes. Copyright © 2010 John Wiley & Sons, Ltd.     

Intraday Volatility Spillover between the Shanghai and Hong Kong Stock Markets—Evidence from A+H Shares after the Launch of the Shanghai-Hong Kong Stock Connect

Using minute data of eligible A+H stocks under the Shanghai-Hong Kong Stock Connect (SHHKSC), we investigate the volatility spillover between the Shanghai and Hong Kong stock markets based on a generalized autoregressive conditional heteroskedasticity-X (GARCH-X) model with four exogenous variables, namely, volatilities of the corresponding stocks on the other market, volatilities of the indexes of both stock markets, and volatilities of the correlated stocks, which are selected using the dynamic conditional correlation model and bootstrap approach. Results show that after the launch of the SHHKSC, volatility spillovers are significant in both directions almost all the time, and the volatility spillover between the two stock markets tends to be larger when bidirectional capital flows under the SHHKSC increase or when important financial events occur. We also analyze the influences of the volatilities of correlated stocks and industries on the volatility spillover and volatilities of A+H stocks. The bidirectional volatility spillovers between Shanghai and Hong Kong stock markets do not change qualitatively after incorporating the volatilities of correlated stocks and industries in the GARCH-X model. Moreover, the average volatilities of the correlated stocks are shown to have significant influences on the volatilities of individual A+H stocks, and the influences increase when the local stock market shows a sharp rise or fall. Compared with the market indexes, the correlated stocks could be regarded as a more important and indispensable factor for individual A+H stocks’ volatilities modeling, which may carry more information than the industry.     

Asset market response to monetary policy news from SNB press releases

This paper analyses the effects of Swiss National Bank (SNB) communication on asset prices. It distinguishes between different monetary policy news contained in press releases following a monetary policy decision. Employing a latent variable approach and event-study methods, I find that medium- and long-term bond yields respond to changes in the communicated inflation and GDP forecasts as well as to the degree of pessimism expressed in press releases. Exchange rates mainly react to changes in the GDP forecast while stocks do not react to SNB communication on monetary policy announcement days. Additionally, short-term expectations about the future path of the policy rate are driven by the communicated inflation forecast. The results underline the role of qualitative news beyond quantitative forecasts in influencing market expectations and asset prices.     

STRATEGIC ASSET ALLOCATION FOR LONG‐TERM INVESTORS: PARAMETER UNCERTAINTY AND PRIOR INFORMATION

We study the effect of parameter uncertainty on the long‐run risk for three asset classes: stocks, bills and bonds. Using a Bayesian vector autoregression with an uninformative prior we find that parameter uncertainty raises the annualized long‐run volatilities of all three asset classes proportionally with the same factor relative to volatilities that are conditional on maximum likelihood parameter estimates. As a result, the horizon effect in optimal asset allocations is much weaker compared to models in which only equity returns are subject to parameter uncertainty. Results are sensitive to alternative informative priors, but generally the term structure of risk for stocks and bonds is relatively flat for investment horizons up to 15 years. Copyright © 2013 John Wiley & Sons, Ltd.     

Risk spillover and network connectedness analysis of China’s green bond and financial markets: Evidence from financial events of 2015–2020

This study investigated the dynamic return and volatility spillovers, together with the network connectedness analysis between China’s green bond and main financial markets. Based on a multidimensional DCC-GJRGARCH model and the spillover index method, we found significant two-way risk spillovers between the green bond market and traditional bond markets. Moreover, the green bond market was subject to one-way risk spillover from the stock and commodities markets. Meanwhile, risk spillovers between the green bond market, forex market, and monetary market were not significant. Finally, network connectedness analysis provided specific information about connectivity and strength during different subperiods corresponding to financial events. The analysis indicated that under the influence of emergencies, China’s financial market will enhance the risk-spillover level by transforming the same type of market’s internal spillover into cross-market spillover.     

Prices,debt and market structure in an agent-based model of the financial market

We develop an agent-based model in which heterogeneous and boundedly rational agents interact by trading a risky asset at an endogenously set price. Agents are endowed with balance sheets comprising the risky asset as well as cash on the asset side and equity capital as well as debt on the liabilities side. A number of findings emerge when simulating the model: we find that the empirically observable log-normal distribution of bank balance sheet size naturally emerges and that higher levels of leverage lead to a greater inequality among agents. Furthermore, greater leverage increases the frequency of bankruptcies and systemic events. Credit frictions, which we define as the stickiness of debt adjustments, are able to explain a key difference in the relation between leverage and assets observed for different bank types. Lowering credit frictions leads to an increasingly procyclical behavior of leverage, which is typical for investment banks. Nevertheless, the impact of credit frictions on the fragility of the model financial system is complex. Lower frictions do increase the stability of the system most of the time, while systemic events become more probable. In particular, we observe an increasing frequency of severe liquidity crises that can lead to the collapse of the entire model financial system.     

Multivariate risk aversion utility,application to ESG investments

This paper uses the concept of multivariate or multi-attributive utility to attach different risk aversion levels to different sources of wealth (e.g. sectors, stocks, asset classes). In this context, we address the topic of environmental, social, and corporate governance (ESG) investments from the perspective of an investor with different risk aversion levels to green and brown stocks. We obtain closed-form solutions for the optimal allocations, value function, and wealth equivalent losses (WEL) from suboptimal choices. The numerical analysis demonstrates the significant increase, of up to 33%, in green investments when accounting for a differential in risk aversions levels, with up to 65% in WEL when using same risk-aversion levels.¹     

COVID-19 and asymmetric volatility spillovers across global stock markets

In this study, I improve the assessment of asymmetry in volatility spillovers, and define six asymmetric spillover indexes. Employing Diebold-Yilmaz spillover index, network analysis, and my developed asymmetric spillover index, this study investigates the time-varying volatility spillovers and asymmetry in spillovers across stock markets of the U.S., Japan, Germany, the U.K., France, Italy, Canada, China, India, and Brazil based on high-frequency data from June 1, 2009, to August 28, 2020. I find that the global markets are well connected, and volatility spillovers across global stock markets are time-varying, crisis-sensitive, and asymmetric. Developed markets are the main risk transmitters, and emerging markets are the main risk receivers. Downside risk dominates financial contagion effects, and a great deal of downside risk spilled over from stock markets of risk transmitters into the global markets. Moreover, during the coronavirus recession, the total degree of volatility spillover is staying at an extremely high level, and emerging markets are the main risk receivers in the 2020 stock markets crash.     

MNEs,technological efforts and channels of export spillover: An analysis of Indian manufacturing industries

The present study provides some empirical evidence for the export spillover effect examining the case of an emerging market economy, namely India, using firm level data for the period 1994–2006. We disentangle different spillover channels, namely the demonstration effect, the imitation effect (R&D spillover) and a proxy to measure spillover effects coming from higher MNEs’ skills. We also account for the heterogeneous technological behaviour of local firms considering how in-house R&D efforts and disembodied technological imports may affect the exporting performance. Our findings show how export spillover effects are mainly mediated by an imitation effect, contrary to the case of other emerging market economies like China, where a demonstration effect is evident. We also recognise that both the decision to export and export intensity are influenced most of all by the technological activities of local firms. Moreover, the findings of the analysis suggest that in-house R&D is more relevant than other external sources of technological knowledge such as disembodied technology imports to internalise the positive spillover effect emanating from MNEs.