Oil price shocks and the US stock market: A nonlinear approach

We study the response of US stock market returns to oil price shocks and to what extent it behaves asymmetrically over the different phases of the business cycle. For this purpose, we decompose the oil price changes into supply and demand shocks in the oil market and assess the state-dependent dynamics of structural shocks on US stock returns using a smooth transition vector autoregression model. When nonlinearity is considered, quantitatively very different asymmetric dynamics are observed. Our findings show that the responses of US stock returns to disaggregated shocks are asymmetric over the business cycle and that the impact of demand-driven shocks on US stock returns is stronger and more persistent, especially when economic activity is depressed. Furthermore, the contribution of shocks to expectation-driven precautionary demand in recessions accounts for a larger share of the variability of US stock market returns than that predicted by standard linear vector autoregressions.     

Stock market liberalization and international risk sharing

This paper empirically examines what macroeconomic risks are shared (or not shared) internationally after stock market liberalization in several developing countries. To address this issue, we incorporate an international asset pricing model into a non-linear structural vector autoregression (VAR) system that identifies various sources of macroeconomic risks. We find that most of the risks corresponding to exogenous financial market shocks are surprisingly well shared, although other macroeconomic risks associated with exogenous shocks to output, inflation and monetary policies are not fully shared across countries. Our results suggest that one of the main benefits from stock market liberalization is to allow the countries studied in this paper to better hedge against exogenous and idiosyncratic financial market risks, and stock market liberalization needs to be accompanied by other measures of economic integration in order to achieve the full benefits of international risk sharing.     

Liquidity shocks and real GDP growth: Evidence from a Bayesian time-varying parameter VAR

We examine the dynamic impact of liquidity shocks resonating in stock and housing markets on real GDP growth. We fit a Bayesian time-varying parameter VAR model with stochastic volatility to US data from 1970 to 2014. GDP becomes highly sensitive to house market liquidity shocks as disruptions in the sector start to emerge, yet more resilient to stock market liquidity shocks throughout time. We provide substantial evidence in favour of asymmetric responses of GDP growth both across the business cycle, and among business cycle troughs. Stock and house market liquidity shocks explain, on average, 17% and 35% of the variation in GDP during the Great Recession, respectively.     

Stock prices, news, and business conditions

Previous research finds that fundamental macroeconomic newshas little effect on stock prices. We show that after allowingfor different stages of the business cycle, a stronger relationshipbetween stock prices and news is evident. In addition to stockprices, we examine the effect of real activity news on proxiesfor expected cashflows and equity discount rates. We find thatwhen the economy is strong the stock market responds negativelyto news about bigger real economic activity. This negative relationis caused by the larger increase in discount rates relativeto expected cashflows.     

Changes in the international comovement of stock returns and asymmetric macroeconomic shocks

We study whether asymmetric macroeconomic shocks help to explain changes in the international comovement of monthly stock returns in major industrialized countries over the period 1975–2004. Based on a time-varying parameter model, we trace out how the pattern of international comovement of stock returns changed over time. In order to identify asymmetric macroeconomic shocks, we estimate vector-autoregressive models. The results of estimating time-series regression models and panel-data models indicate that changes in the international comovement of stock returns are not systematically linked to macroeconomic shocks.     

Macroeconomic news, announcements, and stock market jump intensity dynamics

This paper examines the effect of macroeconomic releases on stock market volatility through a Poisson-Gaussian-GARCH process with time-varying jump intensity, which is allowed to respond to such information. The day of the announcement, per se, is found to have little impact on jump intensities. Employment releases are an exception. However, when macroeconomic surprises are considered, inflation shocks show persistent effects while monetary policy and employment shocks reveal only short-lived effects. Also, the jump intensity responds asymmetrically to macroeconomic shocks. Evidence on macroeconomic variables relevance in explaining jump dynamics and improving volatility forecasts on event days is provided.     

THE CAUSES OF VOLATILITY IN A SMALL,INTERNATIONALLY INTEGRATED STOCK MARKET: IRELAND,JULY 1975–JUNE 1994

I examine the causes of conditional volatility in a small, internationally integrated stock market using the Irish stock market as an example. I relate Irish stock market conditional volatility to British stock market conditional volatility and business cycle variables from July 1975 to May 1994. Exchange rate volatility is a more significant determinant of volatility in a small, internationally integrated stock market than is interest rate volatility. It follows that a potential benefit of membership in the European Monetary System may be reduced stock market volatility in the smaller member countries.     

What Is the Importance of Monetary and Fiscal Shocks in Explaining U.S. Macroeconomic Fluctuations?

This paper analyzes the importance of monetary and fiscal policy shocks in explaining U.S. macroeconomic fluctuations, and establishes new stylized facts. The novelty of our empirical analysis is that we jointly consider both monetary and fiscal policy, whereas the existing literature only focuses on either one or the other. Our main findings are twofold: fiscal shocks are relatively more important in explaining medium cycle fluctuations whereas monetary policy shocks are relatively more important in explaining business cycle fluctuations, and failing to recognize that both monetary and fiscal policy simultaneously affect macroeconomic variables might incorrectly attribute the fluctuations to the wrong source.     

宏观经济因素、企业家信心与公司融资选择

本文研究经济周期、信贷风险、信贷配给、股市表现和企业家信心对公司融资选择的影响,发现宏观经济上行时,公司的融资偏好为股权—债务,而宏观经济衰退时,公司的融资偏好则调整为债务一股权;信贷配给增加后,股权融资的概率上升;银行不良贷款不影响公司融资选择;企业家对经济前景越有信心,债务融资的可能性就越大。研究结果表明,我国上市公司不存在单一的股权融资偏好,而且公司融资决策基本符合最优融资顺序理论。     

How do policy and information shocks impact co-movements of China’s T-bond and stock markets?

We investigate the impacts of policy and information shocks on the correlation of China’s T-bond and stock returns, using originally the asymmetric dynamic conditional correlation (DCC) model that allows for the coexistence of opposite-signed asymmetries. The co-movements of China’s capital markets react to large macroeconomic policy shocks as evidenced by structural breaks in the correlation following the drastic 2004 macroeconomic austerity. We show that the T-bond market and the bond–stock correlations bear more of the brunt of the macroeconomic contractions. We also find that the bond–stock correlations respond more strongly to joint negative than joint positive shocks, implying that investors tend to move both the T-bond and stock prices in the same direction when the two asset classes have been hit concurrently by bad news, but tend to shift funds from one asset class to the other when hit concurrently by good news. However, the stock–stock correlation is found to increase for joint positive shocks, indicating that investors tend to herd more for joint bullish than joint bearish stock markets in Shanghai and Shenzhen.     

中国股市行业风险与宏观经济之间的风险传导机制

本文采用行业收益率溢出指数度量股市行业风险,并进一步研究中国股市行业风险与宏观经济的相互影响,同时引入股息率和利率两个中介渠道深入挖掘其传导机制。我们运用GARCH-in-Mean模型对股市行业风险和宏观经济变量之间的一阶矩和二阶矩相互关系同时进行分析,结果发现,股市行业风险和宏观经济变量之间水平值和波动率都存在双向影响,对外溢出效应较大的行业起主导作用。此外,股市行业风险对宏观经济变量的影响方面,股息率和利率均起到中介渠道作用;宏观经济变量对股市行业风险的影响方面,只是利率起到中介渠道作用。股市行业风险与宏观经济的传导效应在不同时期差异显著。本文研究结论有助于深刻理解金融与实体经济之间的风险传导机制,对防范系统性风险、防止金融和实体经济“风险共振”以及提升金融服务实体经济能力等具有参考意义。     

Financial and monetary policy responses to oil price shocks: evidence from oil-importing and oil-exporting countries

In this study, we investigate the financial and monetary policy responses to oil price shocks using a Structural VAR framework. We distinguish between net oil-importing and net oil-exporting countries. Since the 80s, a significant number of empirical studies have been published investigating the effect of oil prices on macroeconomic and financial variables. Most of these studies though, do not make a distinction between oil-importing and oil-exporting economies. Overall, our results indicate that the level of inflation in both net oil-exporting and net oil-importing countries is significantly affected by oil price innovations. Furthermore, we find that the response of interest rates to an oil price shock depends heavily on the monetary policy regime of each country. Finally, stock markets operating in net oil-importing countries exhibit a negative response to increased oil prices. The reverse is true for the stock market of the net oil-exporting countries. We find evidence that the magnitude of stock market responses to oil price shocks is higher for the newly established and/or less liquid stock markets.     

中国股市行业风险与宏观经济之间的风险传导机制

本文采用行业收益率溢出指数度量股市行业风险,并进一步研究中国股市行业风险与宏观经济的相互影响,同时引入股息率和利率两个中介渠道深入挖掘其传导机制。我们运用GARCH-in-Mean模型对股市行业风险和宏观经济变量之间的一阶矩和二阶矩相互关系同时进行分析,结果发现,股市行业风险和宏观经济变量之间水平值和波动率都存在双向影响,对外溢出效应较大的行业起主导作用。此外,股市行业风险对宏观经济变量的影响方面,股息率和利率均起到中介渠道作用;宏观经济变量对股市行业风险的影响方面,只是利率起到中介渠道作用。股市行业风险与宏观经济的传导效应在不同时期差异显著。本文研究结论有助于深刻理解金融与实体经济之间的风险传导机制,对防范系统性风险、防止金融和实体经济“风险共振”以及提升金融服务实体经济能力等具有参考意义。     

Risk,uncertainty and monetary policy

The VIX, the stock market option-based implied volatility, strongly co-moves with measures of the monetary policy stance. When decomposing the VIX into two components, a proxy for risk aversion and expected stock market volatility (“uncertainty”), we find that a lax monetary policy decreases both risk aversion and uncertainty, with the former effect being stronger. The result holds in a structural vector autoregressive framework, controlling for business cycle movements and using a variety of identification schemes for the vector autoregression in general and monetary policy shocks in particular. The effect of monetary policy on risk aversion is also apparent in regressions using high frequency data.     

The monetary origins of asymmetric information in international equity markets

Existing studies using low-frequency data have found that macroeconomic shocks contribute little to international stock market covariation. However, these papers have not accounted for the presence of asymmetric information where sophisticated investors generate private information about the fundamentals that drive returns in many countries. In this paper, we use a new microstructure data set to better identify the effects of private and public information shocks about U.S. interest rates and equity returns. High-frequency private and public information shocks help forecast domestic money and equity returns over daily and weekly intervals. In addition, these shocks are components of factors that are priced in a model of the cross-section of international returns. Linking private information to U.S. macroeconomic factors is useful for many domestic and international asset-pricing tests.     

International house prices and macroeconomic fluctuations

The paper investigates linkages between general macroeconomic conditions and the housing market for the G-7 area. Among the key results of the paper, we find that the US are an important source of global fluctuations not only for real activity, nominal variables and stock prices, but also for real housing prices. Secondly, albeit distinct driving forces for real activity and financial factors can be pointed out, sizeable global interactions are also evident. In particular, global supply-side shocks are an important determinant of G-7 house prices fluctuations. The linkage between real housing prices and macroeconomic developments is however bidirectional, with investment showing in general a stronger reaction than consumption and output to housing price shocks. Implications for the real effects of the sub-prime crisis are also explored.     

Changes in Factor Betas and Risk Premiums Over Varying Market Conditions

We show risk exposures and premiums associated with the Chen, Roll, and Ross (1986) risk factors change over time and depend on stock market and business cycle condition. Findings also indicate that factor risk premiums change sign between January and non-January, especially during bull markets. These findings serve as a caveat for portfolio managers who allocate assets to match desired exposures to key macroeconomic risk factors.     

Macroeconomic News, Business Cycles and Australian Financial Markets

This paper examines the effects of news surprises of macroeconomic announcements on Australian financial markets across different business cycles. We find that overall, the news arrivals are influential in both stock and debt markets but in an interesting array of responses across asset classes. Debt markets are more responsive to macroeconomic news surprises compared to the stock market, hence supporting the notion that information revealed from the macroeconomic news is related to interest rates. Specifically, news about CPI is important over the full sample period and especially during expansions for both stock and bond returns while the unemployment rate news is influential to the money market rates. Furthermore, these effects are seemingly asymmetric in nature, with their directions and magnitudes conditional on the state of economy.     

The stock–bond correlation and macroeconomic conditions: One and a half centuries of evidence

Using monthly stock and bond return data in the past 150 years (1855–2001) for both the US and the UK, this study documents time-varying stock–bond correlation over macroeconomic conditions (the business cycle, the inflation environment and monetary policy stance). There are different patterns of time variation in stock–bond correlations over the business cycle between US and UK, which implies that bonds may be a better hedge against stock market risk and offer more diversification benefits to stock investors in the US than in the UK. Further, there is a general pattern across both the US and the UK during the post-1923 subperiod and during the whole sample period: higher stock–bond correlations tend to follow higher short rates and (to a lesser extent) higher inflation rates.     

Forecasting stock volatility with economic policy uncertainty: A smooth transition GARCH-MIDAS model

Given that policy uncertainty shocks in the economic environment can exacerbate financial market volatility and pose financial risks, this paper utilizes a smooth transition version of the GARCH-MIDAS model to investigate the impact of different structural state changes in economic policy uncertainty (EPU) on stock market volatility. The extended model explains the nonlinear effects of the macro variables and the structural break changes in regime transitions. The empirical results confirm that the EPU indicators provide effective prediction information for stock volatility from the in-sample and out-of-sample analyses, which reveals that the smooth transition model provides an effective method for detecting the possible regime changes between stock volatility and macroeconomic uncertainty. Additionally, we further confirm that some category-specific EPU indicators also have strong smooth transition behaviour with respect to stock volatility. More important, our new model provides significant economic value to investors from a utility gain perspective. Overall, the institutional changes present in EPU play a nonnegligible and important role in stock market volatility. Accurate identification of the structural features of financial data helps investors deepen their understanding of the sources of stock market volatility.