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.     

What determines the stock market's reaction to monetary policy statements?

We find that information communicated through monetary policy statements has important business cycle dependent implications for stock prices. For example, during periods of economic expansion, stocks tend to respond negatively to announcements of higher rates ahead. In recessions, however, we find a strong positive reaction of stocks to seemingly similar signals of future monetary tightening. We provide evidence that the state dependence in the stock market's response is explained by information about the expected equity premium and future corporate cash flows contained in monetary policy statements. We also show state dependence in the average stock returns on days of scheduled FOMC meetings and in the impact of monetary policy statements on stock and bond return volatility.     

Business cycle variation in the risk-return trade-off

In the United States and other Organisation for Economic Co-operation and Development (OECD) countries, the expected returns on stocks, adjusted for volatility, are much higher in recessions than in expansions. We consider feasible trading strategies that buy or sell shortly after business cycle turning points that are identifiable in real time and involve holding periods of up to 1 year. The observed business cycle changes in expected returns are not spuriously driven by changes in expected near-term dividend growth. Our findings imply that value-maximizing managers face much higher risk-adjusted costs of capital in their investment decisions during recessions than expansions.     

A Consumption-Based Explanation of Expected Stock Returns

When utility is nonseparable in nondurable and durable consumption and the elasticity of substitution between the two consumption goods is sufficiently high, marginal utility rises when durable consumption falls. The model explains both the cross‐sectional variation in expected stock returns and the time variation in the equity premium. Small stocks and value stocks deliver relatively low returns during recessions, when durable consumption falls, which explains their high average returns relative to big stocks and growth stocks. Stock returns are unexpectedly low at business cycle troughs, when durable consumption falls sharply, which explains the countercyclical variation in the equity premium.     

Four centuries of return predictability

We combine annual stock market data for the most important equity markets of the last four centuries: the Netherlands and UK (1629–1812), UK (1813–1870), and US (1871–2015). We show that dividend yields are stationary and consistently forecast returns. The documented predictability holds for annual and multi-annual horizons and works both in- and out-of-sample, providing strong evidence that expected returns in stock markets are time-varying. In part, this variation is related to the business cycle, with expected returns increasing in recessions. We also find that, except for the period after 1945, dividend yields predict dividend growth rates.     

Business cycle,storage, and energy prices

This study examines the effect of the state of the economy and inventory on interest-adjusted bases and expected returns for five energy commodities. We find that interest-adjusted bases and returns have a business cycle pattern. Consistent with the theory of storage, demand shocks near business cycle peaks generate negative interest-adjusted bases and positive returns. In recessions, the bases become positive, and the average returns are negative. Our regression results also show that the interest-adjusted bases of energy commodities are counter-cyclical and the expected returns are pro-cyclical. For petroleum commodities, inventory has a significant effect on interest-adjusted bases at low levels of inventory, whereas at high inventory levels the effect of inventory on the bases is weak. Finally, we find that the bases and economic conditions predict spot returns in energy commodity markets.     

Nonlinear relationship between monetary policy and stock returns: Evidence from the U.S.

This paper studies the relationship between monetary policy and stock market return in the U.S. using nonlinear econometric models. It first employs a univariate Markov-switching model on each of the three stock indices and three monetary policy variables, displaying significant regime-switching patterns and common movements. This paper then uses a Markov-switching dynamic bi-factor model to simultaneously extract two latent common factors from stock indices and monetary policy variables to represent monetary policy changes and stock market movements separately. The smoothed probabilities of regimes demonstrate that expansionary monetary policy regimes follow economic recessions, but bear stock markets usually occur before economic recessions. The maximum likelihood estimation results show that expansionary monetary policy such as a decrease in the federal funds rate raises stock returns, but stock returns don't directly influence monetary policy decision.     

Investor Attention and Stock Returns: International Evidence

This article examines the asymmetric/discriminative effects of investor attention on expected stock returns among 15 markets through economic expansions and recessions. The predictive power of attention tends to be short-lived and weakens the autocorrelation within returns. Accounting for business cycles not only confirms that the predictability of attention endures with volatility but also explicates the asymmetric effects that underlying pessimism functions better. International evidence contributes to the literature on investor attention and reveals the discrepant effects of attention with three levels of market efficiency: semi-strong, stronger than semi-strong, and weak.     

On the Economic Link Between Asset Prices and Real Activity

Abstract:  This paper presents a model linking two financial markets (stocks and bonds) with real business cycle, in the framework of the Consumption Capital Asset Pricing Model with Generalized Isoelastic Preferences. Besides interest rate term spread, the model includes a new variable to forecast economic activity: stock market term spread. This is the slope of expected stock market returns. The empirical evidence documented in this paper suggests systematic relationships between business cycle's state and the shapes of two yield curves (interest rates and expected stock returns). Results are robust to changes in measures of economic growth, stock prices, interest rates and expectations generating mechanisms.     

The cross-section and time series of stock and bond returns

Bond factors which predict future U.S. economic activity at business cycle horizons are priced in the cross-section of U.S. stock returns. High book-to-market stocks have larger exposures to these bond factors than low book-to-market stocks, because their cash flows are more sensitive to the business cycle. Because of this new nexus between stock and bond markets, a parsimonious three-factor dynamic no-arbitrage model can be used to jointly price book-to-market-sorted portfolios of stocks and maturity-sorted bond portfolios, while reproducing the time-series variation in expected bond returns. The business cycle itself is a priced state variable in stock and bond markets.     

Real‐Time Risk Pricing Over the Business Cycle: Some Evidence for the UK

Abstract:   The fully‐revised data typically utilized in empirical research do not reflect the true information available to financial market participants at the time of their decision‐making. This paper uses a new real‐time macroeconomic dataset to appraise the relative importance of different vintages of data on economic variables as determinants of UK stock returns using the framework of Arbitrage Pricing Theory. We find that two factors influence expected stock returns, namely unanticipated inflation and economic uncertainty, but only when measured in real‐time. Moreover, their pricing influence is only present during phases of the business cycle when their associated risks are at their most prevalent.     

The impact of (global) business cycle risk on the German and British stock markets: Evidence from the first age of globalization

In the period from 1880 to 1913, time-varying German and British stock market returns are related to business cycle variables such as the deviation of industrial production from trend. Common British and German business cycle dynamics Granger cause stock returns and explain more than 20% of time variation in one-year ahead stock market returns. The link between business cycle variables and stock returns is less pronounced in the modern era of financial globalization. A potential explanation for this finding is the fact that during the first globalization period stock indices were dominated by industrial companies and stock prices varied in line with dividends. In the modern era of globalization stock price dynamics predominantly reflect time-varying risk premia.     

Predicting stock returns: A regime-switching combination approach and economic links

This paper introduces a regime-switching combination approach to predict excess stock returns. The approach explicitly incorporates model uncertainty, regime uncertainty, and parameter uncertainty. The empirical findings reveal that the regime-switching combination forecasts of excess returns deliver consistent out-of-sample forecasting gains relative to the historical average and the Rapach et al. (2010) combination forecasts. The findings also reveal that two regimes are related to the business cycle. Based on the business cycle explanation of regimes, excess returns are found to be more predictable during economic contractions than during expansions. Finally, return forecasts are related to the real economy, thus providing insights on the economic sources of return predictability.     

Is presidential cycle in security returns merely a reflection of business conditions?

We confirm previous findings that both large-cap and small-cap stock returns in the US exhibit a presidential cycle pattern, i.e. returns are significantly higher in the last 2 years than in the first 2 years of the presidential term. We attempt to examine if this presidential cycle pattern can be explained away by the traditional business cycle proxies, namely the term spread (TERM), dividend yield (D/P), and default spread (DEF). Our motivation arises from the political business cycle theory that monetary and fiscal measures undertaken by presidents are usually translated into the business cycle. We find that the presidential cycle has explanatory power beyond business conditions proxies shown to be important in explaining stock returns. Tests of slope parameters show that stock returns are less sensitive to only the D/P during the last 2 years of the presidential term. The presidential cycle effect prevails even after controlling for the party in power and the incumbent versus nonincumbent presidents.     

Information aggregation around macroeconomic announcements: Revisions matter

I show that an empirical relation exists between stock returns on macroeconomic news announcement days and the future revisions of the released data but that this link differs across the business cycle. Using three major macroeconomic series that undergo significant revisions (nonfarm payroll, gross domestic product, and industrial production), I present evidence that daily returns on the Standard & Poor's 500 index and revisions are positively related in expansions and negatively related in recessions. The results suggest that revisions do matter, i.e., that investors care about the final revised value of a macroeconomic series, that they infer accurate information from the release of the preliminary inaccurate report, and that the more precise information is aggregated into prices on the day of the initial announcement. The results are consistent with the predictions of rational expectations trading models around public announcements combined with well-established empirical results on the asymmetric interpretation of information across the business cycle.     

Consumption growth and time-varying expected stock returns

When the consumption growth rate is measured based upon fourth quarter data, it tracks predictable variation in future excess stock returns. Low fourth quarter consumption growth rates predict high future excess stock returns such that expected returns are high at business cycle troughs and low at business cycle peaks. The consumption growth rate loses predictive power when it is measured based upon other quarters. This is consistent with the insight of Jagannathan and Wang [2007. Journal of Finance 62, 1623–1661] that investors tend to review their consumption and investment plans during the end of each calendar year, and at possibly random times in between. The consumption growth rate measured based upon fourth quarter data is a much stronger predictive variable than benchmark predictive variables such as the dividend–price ratio, the term spread, and the default spread.     

Realizing stock market crashes: stochastic cusp catastrophe model of returns under time-varying volatility

This paper develops a two-step estimation methodology that allows us to apply catastrophe theory to stock market returns with time-varying volatility and to model stock market crashes. In the first step, we utilize high-frequency data to estimate daily realized volatility from returns. Then, we use stochastic cusp catastrophe theory on data normalized by the estimated volatility in the second step to study possible discontinuities in the markets. We support our methodology through simulations in which we discuss the importance of stochastic noise and volatility in a deterministic cusp catastrophe model. The methodology is empirically tested on nearly 27 years of US stock market returns covering several important recessions and crisis periods. While we find that the stock markets showed signs of bifurcation in the first half of the period, catastrophe theory was not able to confirm this behaviour in the second half. Translating the results, we find that the US stock market’s downturns were more likely to be driven by the endogenous market forces during the first half of the studied period, while during the second half of the period, exogenous forces seem to be driving the market’s instability. The results suggest that the proposed methodology provides an important shift in the application of catastrophe theory to stock markets.     

Comovement,information production,and the business cycle

Recent theoretical research suggests that information production is a positive externality of aggregate economic activity (Veldkamp, 2005). Both the quantity and quality of information increase during periods of economic expansion and decrease during periods of contraction. Based on this insight, we hypothesize and confirm that time-varying information production drives the comovement patterns observed in stock returns. We examine stock return comovement in 36 countries from 1980 to 2007 and show that, consistent with the theory, comovement patterns are countercyclical; that is, when information production is high (low), comovement is low (high). We also find that the relation between comovement and the business cycle is stronger in countries that experience large intertemporal swings in information production. Finally, we show that the relation between business cycle and comovement is stronger in poor countries, countries with less developed financial markets, and countries with weaker accounting and transparency standards. These results suggest that financial development and transparency are conducive to a steady flow of financial information over the business cycle.     

Long-Term Asset Allocation under Dynamic Interaction of Earnings and Interest Rates

The interaction of interest rates and corporate earnings over the economic cycle generates stock price movements. These movements are captured in the present valuation context. Superior returns are observed when long-term asset allocation techniques are applied to the model.     

Volatility risk and the value premium: Evidence from the French stock market

This paper documents that systematic volatility risk is an important factor that drives the value premium observed in the French stock market. Using returns on at-the-money straddles written on the CAC 40 index as a proxy for systematic volatility risk, I document significant differences between volatility factor loadings of value and growth stocks. Furthermore, when markets are classified into expected booms and recessions, volatility factor loadings are also time-varying. When expected market risk premium is above its average, i.e. during expected recessions, value stocks are seen riskier than their growth counterparts. This implies in bad times, investors shift their preferences away from value firms. Instead they use growth stocks as hedges against deteriorations in their wealth during those times. The findings are in line with the predictions of rational asset pricing theory and support a “flight-to-quality” explanation.