Industry-level determinants of the linkage between credit and stock markets

This paper examines the relationship between US credit default swaps (CDS) and stock returns on an industry-wide basis across a number of investment horizons, with particular focus on the major determinants of such a relationship. Wavelet analysis is first applied to extract the CDS–stock wavelet correlation for each US industry. Then, Bayesian Model Averaging is employed to identify the key driving factors of the industry CDS–stock wavelet correlations at short- and long-term horizons. The empirical results indicate that the wavelet correlations between the industry CDS and stock returns are primarily negative over time and across time scales. Moreover, the CDS–stock correlation at longer horizons exhibits a much more stable pattern than its counterpart at shorter time frames. The results also demonstrate that the volatility of US Treasury and stock markets, as measured by the MOVE and VIX indices, respectively, the volatility of volatility, as captured by the VVIX index, and US economic policy uncertainty, as measured by the EPU index, are the most robust determinants of the correlation between CDS and stock returns at shorter and longer horizons for most US industries. In contrast, the Fama–French systematic equity factors exhibit a practically negligible explanatory power on the CDS–stock link.     

Oil shocks,US economic uncertainty,and emerging stock markets

This paper investigates the impacts of oil price shocks and US economic uncertainty on emerging equity markets within a structural VAR model. I find that both precautionary oil demand and US economic uncertainty shocks have significant negative effects on emerging stock returns, whereas aggregate demand shocks cause a sustained rise of the returns. In particular, the direct effects of oil shocks on emerging stock returns are amplified by the endogenous response of US economic uncertainty. Variance decomposition analysis shows that oil market fundamentals and US economic uncertainty are an important determinant of emerging equity returns, accounting for 35% and 24% of their long-term variations, respectively. The heterogeneous impacts of structural shocks on individual emerging markets, however, suggest that a well-diversified portfolio can be obtainable.     

The January effect in the foreign exchange market: Evidence for seasonal equity carry trades

In this study, we investigate monthly seasonality in the foreign exchange market. Given the well-known recurrent higher returns in some month than in others in stock markets around the world, we consider it likely that a seasonal outperformance of a country’s stock market over another is associated with similar seasonal patterns in capital flows and exchange rates. A seasonal profit (carry trade) opportunity can be created by the simultaneous appreciation of a country’s currency and the outperformance of its stock market. By focusing on the world’s key currency pairs, the US dollar-Deutsche mark and the US dollar-euro, and by using a Markov-switching framework, we document persistent January and December effects in the foreign exchange market from 1971 to 2017. Analysis of the German-US stock returns differential and their bilateral capital flows reveal similar month effects in 65% of the whole sample.     

Oil shocks,policy uncertainty and stock returns in China

This paper examines the interdependence of China's policy uncertainty, the global oil market and stock market returns in China. A structural VAR model is estimated that shows that a positive shock to economic policy uncertainty in China has a delayed negative effect on global oil production, real oil prices and real stock market returns. Shocks to oil market‐specific demand significantly raise China's economic policy uncertainty and reduce the real stock market returns. As measured by a spillover index, the interdependence between these variables has been rising since 2003 as China's influence in the oil market has increased. An equivalent spillover index calculated for the US is smaller and has been largely flat over time.     

Evaluation by the Aumann and Serrano performance index and Sharpe ratio: Bitcoin performance

We compare Bitcoin performance based on the Aumann and Serrano performance index and Sharpe ratio assuming that asset returns follow the class of discrete normal mixture distributions. The Aumann and Serrano performance index can take into account higher moments of the underlying distribution of assets and is relevant for risk-averse investors. We evaluate Bitcoin performance based on the Aumann and Serrano index relative to the performance of other assets. Our evaluation shows that Bitcoin is rated highly by the Sharpe ratio but rated very poorly by the Aumann and Serrano index. We also find some stock assets can beat Bitcoin by the Sharpe ratio when an investment horizon is monthly.     

Safe havens in the face of Presidential election uncertainty: A comparison between Bitcoin,oil and precious metals

Even though the empirical literature on safe haven properties of different assets with respect to financial risks is increasing, their abilities to safeguard against political risks has not been the subject of large empirical investigations. This paper uses an Empirical Mode Decomposition-based approach to look into the time-varying role of different assets (in particular, oil, precious metals and Bitcoin) as a safe haven against U.S. stocks in times of heightened uncertainty surrounding the outcome of the 2016 U.S. presidential election. Our results suggest that oil can act as an effective safe haven against political risk exposure; but such property varies over time. The abilities of gold and silver to provide positive returns during downturns have been also documented in the medium-and the long-term. Bitcoin also serves as a safe haven against U.S. stock losses but in the short-term. These findings provide useful and relevant information to investors to help ensure better asset allocation in an uncertain environment.     

中国股票市场和债券市场收益率动态相关性分析

基于A股综合市场收益率和中信全债指数收益率数据来研究中国股票市场和债券市场收益率的动态相关性,并分析时变的股债相关性影响因素,以及在横截面上对股票收益率的定价影响进行考察后得知:股债相关性是时变的,股票市场的不确定性和预期通货膨胀率是影响股债相关性的主要因素;通过虚拟变量回归发现,股债相关性在横截面上对股票收益率的影响很小。这些结论对于投资者来说具有直接的现实意义。     

US economic policy uncertainty and co-movements between Chinese and US stock markets

This paper investigates the impact of innovations in US economic policy uncertainty on the co-movements of China's A/B stock markets with the US stock market. We show that it is the absolute changes in the US economic policy uncertainty index that have a negative impact on the co-movements. The finding is robust to the asymmetric effects of non-policy-uncertainty shocks, to a break in the correlation structure, and to the four Chinese A/B stock markets investigated. Our results provide the first evidence regarding how stock market correlations are driven by policy-related uncertainty shocks in the international context.     

International stock return predictability: on the role of the United States in bad and good times

In this article, we document the asymmetric role that the US stock market plays in the international predictability of excess stock returns during recession and expansion periods. Most of the positive evidence accrues during the periods of recessions in the United States. During the expansions, there is only a limited evidence supporting the importance of lagged US returns in predictability of stock returns in 10 industrialized countries.     

Safe haven,hedge and diversification for G7 stock markets: Gold versus bitcoin

We compare gold and Bitcoin for the G7 stock markets, finding that gold and Bitcoin have distinct safe haven and hedging characteristics. Gold is an undisputable safe haven and hedge for several G7 stock indices, whereas Bitcoin takes these two functions in Canada. The out-of-sample hedging effectiveness of gold is much superior to that of Bitcoin. Furthermore, we find that the conditional diversification benefits offered by gold to equity investments in the G7 markets are comparatively much higher and more stable than those of Bitcoin, especially in the lower return quantiles, i.e., when both the stock and gold markets are in a bearish state. Implications are further discussed.     

Can volume predict Bitcoin returns and volatility? A quantiles-based approach

Prior studies on the price formation in the Bitcoin market consider the role of Bitcoin transactions at the conditional mean of the returns distribution. This study employs in contrast a non-parametric causality-in-quantiles test to analyse the causal relation between trading volume and Bitcoin returns and volatility, over the whole of their respective conditional distributions. The nonparametric characteristics of our test control for misspecification due to nonlinearity and structural breaks, two features of our data that cover 19th December 2011 to 25th April 2016. The causality-in-quantiles test reveals that volume can predict returns – except in Bitcoin bear and bull market regimes. This result highlights the importance of modelling nonlinearity and accounting for the tail behaviour when analysing causal relationships between Bitcoin returns and trading volume. We show, however, that volume cannot help predict the volatility of Bitcoin returns at any point of the conditional distribution.     

The influence of Taiwan’s stock market on Bitcoin’s price under Taiwan’s monetary policy threshold

ABSTRACT

This study uses a smooth transition autoregressive model with exogenous variables (STARX) to investigate whether there is a nonlinear relationship between Bitcoin and Taiwan’s stock market taking into account Taiwan’s monetary policy threshold during 2 February 2012 to 31 August 2019. The statistical results show there is a threshold effect and confirm a nonlinear relationship between Taiwan’s stock market and Bitcoin, with variations over time and across Bitcoin and Taiwan’s stock market. Specifically, we find that Bitcoin responds asymmetrically to Taiwan’s stock market according to the threshold value. Furthermore, the return on the closing price of TAIEX with a lag of two periods under Taiwan’s monetary policy threshold has a nonlinear impact on the return on the closing price of Bitcoin.     

Does investor sentiment dynamically impact stock returns from different investor horizons? Evidence from the US stock market using a multi-scale method

This article uses the investor sentiment index to investigate the Granger causality between investor sentiment and stock returns for the US economy using a multi-scale method. To focus on the local analysis of different investor horizons, bivariate empirical mode decomposition is used to decompose time series of investor sentiment and stock returns at different timescales. We employ the linear and nonlinear integrated Granger causality method to examine the causal relationship of decomposed series on similar timescales. The results indicate both strong bilateral linear and nonlinear causality between longer-term investor sentiment and stock returns. However, there is no strong evidence for correlation of stock returns and investor sentiment on shorter timescales.     

Exchange rate uncertainty and US bilateral fresh fruit and fresh vegetable trade: an application of the gravity model

In order to analyse the effect of exchange rate uncertainty, we apply an empirical gravity equation to two sets of US bilateral trade data: fresh fruit over the period 1976–1999 for a panel of 26 countries; and fresh vegetables over the period 1976–2006 for a panel of nine countries. Based on panel estimation methods, and using both a moving SD measure and the Perée and Steinherr (1989) measure of exchange rate uncertainty, the results show that US bilateral fresh fruit trade has been negatively affected by exchange rate uncertainty. We also find some evidence that the exchange rate between the US dollar and the currencies of Latin American trading partners accounts for most of the negative impact of exchange rate uncertainty on bilateral trade flows in fresh fruit. In contrast, when using panel estimation methods and both measures of exchange rate uncertainty, we find no statistically significant evidence for any negative effect of exchange rate uncertainty on US bilateral fresh vegetable trade. However, we do find a statistically significant negative effect for exchange rate uncertainty when we estimate a US export gravity equation for fresh vegetables using the same panel of countries.     

Global imbalances and asymmetric returns to US foreign assets: fitting the missing pieces of the US balance of payments puzzle

The issue of whether the US earns a persistently higher return on its foreign direct investment (relative to returns to foreign-owned direct investment in the US) has received considerable attention but little closure in the ‘global imbalances’ debate. Measuring the rate of returns to US direct investment abroad and foreign direct investment in the US we find higher returns to US foreign direct investment relative to its foreign counterparts in the US. Given the evidence indicating higher returns to US direct investment overseas, we link the irresolution in the contemporary literature regarding the existence of these returns to the unsettled debate over the origin of global imbalances. Reviewing the macro-financial literature on global imbalances, we find a failure to acknowledge that the US current account deficit is, in part, the outcome of transnational production networks in a global economy under-pinned by dollar hegemony. Given the growth in US multinational supply chains, we argue that the US trade deficit is consistent with asymmetric returns to US direct investment and that the sustainability of these return differentials rests on the stability of the status quo.     

Modelling the dynamics of Bitcoin and Litecoin: GARCH versus stochastic volatility models

We examine and compare a large number of generalized autoregressive conditional heteroskedastic (GARCH) and stochastic volatility (SV) models using series of Bitcoin and Litecoin price returns to assess the model fit for dynamics of these cryptocurrency price returns series. The various models examined include the standard GARCH(1,1) and SV with an AR(1) log-volatility process, as well as more flexible models with jumps, volatility in mean, leverage effects, t-distributed and moving average innovations. We report that the best model for Bitcoin is SV-t while it is GARCH-t for Litecoin. Overall, the t-class of models performs better than other classes for both cryptocurrencies. For Bitcoin, the SV models consistently outperform the GARCH models and the same holds true for Litecoin in most cases. Finally, the comparison of GARCH models with GARCH-GJR models reveals that the leverage effect is not significant for cryptocurrencies, suggesting that these do not behave like stock prices.     

Bitcoin—A hype or digital gold? Global evidence

This study explores whether Bitcoin constitutes as a hedging instrument whilst seeking portfolio diversification opportunities among sustainable, conventional and Islamic asset classes since Bitcoin emerges as a distinct alternative investment and asset class across the world. We apply multivariate generalised autoregressive conditional heteroscedastic-dynamic conditional correlation and continuous wavelet transforms based on the recent data set ranging from August 18, 2011, to September 10, 2018. First, our findings show that Bitcoin returns are mean-reverting which implies that its value tends to come down to mean value in the long run and not completely crushed to zero irrespective of price changes suggesting Bitcoin as a sustainable asset class. Second, the time-invariant model shows that Bitcoin offers portfolio diversification opportunities with almost all equity indices, in particular, Dow Jones Islamic followed by FTSE 4 Good index. Finally, the time-variant analysis reconfirms that Bitcoin offers portfolio diversification benefits both in the short and long run. These findings carry meaningful policy considerations for fund managers and cross-country investors.     

Economic policy uncertainty,financial markets and probability of US recessions

We use probit recession forecasting models to assess the ability of economic policy uncertainty indexes developed by Baker et al. (2013) to predict future US recessions. The model specifications include policy indexes on their own, and in combination with financial variables, such as interest rate spreads, stock returns and stock market volatility. Both in-sample and out-of-sample analysis suggests that the policy uncertainty indexes are statistically and economically significant in forecasting recessions at the horizons beyond five quarters. The index based on newspaper reports emerges as the best predictor, outperforming the term spread at the longer forecast horizons.     

Causal relationship between stock returns and real economic growth in the pre- and post-crisis period: evidence from China

This article empirically examines the causality in mean and variance between stock returns and real economic growth in China before and after the outbreak of US subprime crisis. Using a nonuniform weighting cross-correlation approach and the multivariate generalized autoregressive conditional heteroscedasticity model, we found no causality in mean or variance between China’s stock returns and real economic growth for the period before the subprime crisis. Interestingly, however, in the period after the crisis, we detected unidirectional causality in mean from real economic growth to stock returns and unidirectional causality in variance from stock returns to real economic growth. These new findings imply that the linkage between China’s stock market and its real economy has become stronger in the post-crisis period. The implication of our results is that Chinese policymakers should continue the deregulation and improve the efficiency of the stock market to sustain high economic growth rate in the future.     

Spillover effects of the 2008 financial crisis on NIE stock markets

This article estimates dynamic conditional correlations of stock returns across countries by using DCC–GARCH model and analyse spillover effects of the 2008 financial crisis on the NIE’s stock markets. The results show that there is no regime shift in mean equation of the correlation coefficient during the financial crisis. It may imply there are no mean spillover effects of the US financial crisis on the NIE’s stock markets. However, there are volatility spillover effects of the financial crisis sparked in 2008 from the US to the NIE’s markets.