Economic State Variables Research Articles

Uncertainty premia in REIT returns

AbstractWe provide a systematic study of how financial and real estate uncertainty affect the aggregate return performance of the U.S. REIT market from 1994 to 2017. A temporal causality analysis reveals a negative uncertainty impact on REIT returns. The asset pricing analysis confirms the predictive relation and suggests that REITs are statistically significantly exposed to changes in market‐wide uncertainty, for which investors require a return compensation. We also identify economic state variables to explain time‐varying uncertainty exposures as well as periodic hedging characteristics of REITs. Finally, we find evidence that the source of uncertainty matters for compensating expected REIT returns.

China Markets and Global Stock Return Predictability

This paper explores the China equity market's impact on the global equity markets through the lens of asset pricing. We study the predictive properties of the lagged China returns for global stock returns and find that the lagged China returns can significantly predict other markets' stock returns, but not vice versa. We augmented three selected global equity pricing models (Chen, Roll, and Ross's model (CRR), Ang and Bekaert's model (AB), and Rapach, Strauss, and Zhou's model (RSZ)) with the lagged China returns respectively, and find that these popular global stock return predictors cannot explain the predictive power of the lagged China returns. Moreover, we find that only the lagged China returns can lead the international returns at the one-month horizon but not the lagged US returns. Further evidence reveals it is due to that the information diffusion of the China market occurs at the longer-horizons (e.g. one-month) while the information diffusion of the US market occurs at the shorter-horizons (e.g. one-week). Lastly, we documented that the lagged China returns during the low investor-attention period have stronger predictability compared to the predictive performance during the high attention period, which is in line with the information friction theory that when the attention-constrained investors make investment decisions they fail to allocate attention to certain economic state variables, which causes the slow information diffusion across markets and leads to the cross-market return predictability. Overall, our results indicate that the lagged China returns should be regarded as a global state variable that helps us predict future stock returns.

Computing the adaptive cycle

Gunderson’s and Holling’s adaptive cycle metaphor provides a qualitative description of the development of a dynamically evolving complex system. According to the metaphor, a complex system alternately passes through phases of stability and predictability and phases of reorganization and stochasticity. So far, there have been no attempts to quantify the underlying notions in a way which is independent of the concrete realization of the system. We propose a method which can be applied in a generic way to estimate a system’s position within the adaptive cycle as well as to identify drivers of change. We demonstrate applicability and flexibility of our method by three different case studies: Analyzing data obtained from a simulation of a model of interaction of abstract genotypes, we show that our approach is able to capture the nature of these interactions. We then study European economies as systems of economic state variables to illustrate the ability of system comparison. Finally, we identify drivers of change in a plant ecosystem in the prairie-forest. We hereby confirm the conceptual dynamics of the adaptive cycle and thus underline its usability in understanding system dynamics.

Economic policy uncertainty and momentum

AbstractWe show that a news‐based measure of economic policy uncertainty (EPU) negatively forecasts momentum. A 1‐standard‐deviation increase in EPU is associated with a 1.11% decrease in risk‐adjusted momentum returns. The predictive power of EPU is robust after controlling for previously documented economic state variables and macroeconomic uncertainty. We provide an explanation for these results from the perspective of a fund flow‐induced trading mechanism and offer direct empirical support. The literature documents that momentum can be partially attributed to performance‐chasing mutual fund flows. We find that this flow‐induced mechanism functions more effectively in low EPU states, thereby generating stronger stock momentum.

Characteristics of Model-Free Pricing Kernels

This study combines model-free conditional estimators for the risk-neutral and the physical distribution of equity returns to obtain daily measures for the pricing kernel at the monthly time horizon. Despite their time-varying nature, our pricing kernels are non-parametric, forward-looking, agnostic about preferences, economic state variables or their dynamics and rely only on minimal technical constraints. Still, our realized pricing kernel estimates are clearly linked to economic state variables like the term spread, the credit spread or liquidity. We decompose the expected variance of the log pricing kernel and find that jumps contribute a considerable portion to overall pricing kernel risk. Building on statistical tests, we confirm an U-shape in the pricing kernel at all times and find a strong link between variations in its magnitude and the variance risk premium. A central hump in the pricing kernel can be confirmed unconditionally, but appears to fade during crisis times.

Do the Q-Factors Proxy for Surprises in Economic State Variables?

In this paper, we investigate whether q-factors, ME, I/A, and ROE correlates the surprises in economic state variables that describe the changes in investment opportunities within the Intertemporal CAPM framework. The paper shows that ME, I/A, and ROE significantly correlate with the surprises in economic state variables. In particular, we find that ME correlates with the surprises in default spread, term spread, and treasury-bill yield; while I/A is related to the surprises in aggregate dividend yield. The profitability factor ROE correlates with surprises in term spread and default spread. These findings suggest that the q-factors are related to the surprises in economic state variables. We also show that for each portfolio formation, loadings on surprises in economic state variables resemble the loadings or a mirror image of loading on q-factors. These findings suggest that the q-factors may act as a proxy for the surprises in economic state variables that describe the changes in the investment opportunity set. The paper adds more insights to the ongoing debate on the theoretical justification of q-factors ME, I/A, and ROE.

Central Banks Communication and the State of the Economy

In this paper, I use FOMC minutes transcripts from 1995 to 2019 to estimate a topic model that summarizes Central Banks communication as easily interpretable topical themes and quantifies the proportion of news attention allocated to each theme at each point in time. I then use news attention estimates and show that they accurately predict time series of the key economic state variables. Furthermore, I evidence the link between the news sentiment in FOMC announcements in the dynamic of the key economic state variables.

Economic Policy Uncertainty and Momentum

We find that news-based measures of economic policy uncertainty (EPU) negatively forecast momentum. A one standard deviation increase in EPU is associated with a 1.11% decrease in risk-adjusted momentum returns. The predictive power of EPU is robust after controlling for previously documented economic state variables and macroeconomic uncertainty. We provide an explanation for these results from the perspective of a fund flow induced trading mechanism and offer direct empirical support. The literature documents that momentum can be partially attributed to performance chasing mutual fund flows. This flow induced mechanism functions more effectively in low EPU states generating stronger stock momentum.

Multiple policy interest rates and economic performance in a multiple monetary-policy-tool environment

This paper assesses the individual effects on economic performance of different monetary policy interest rates for a central bank. To measure these effects, we employ an extension of existing Factor-Augmented Vector Autoregressive (FAVAR) models, such that the number of monetary policy variables can be captured with a few unobservable factors, as well as economic state variables with other unobservable factors. The empirical evidence from Turkey suggests that the four interest rates we consider as policy tools for the central bank affect economic state variables in different magnitudes. Thus, selecting different policy tools provides an environment that allows determining the effects of each tool for differentiated economic outcomes.

Currency Value Strategies

This paper examines the profitability of value strategies based on four different measures of currency valuation. Real exchange rate level strategies generate the largest excess returns on intervals up to 1 month, while real exchange rate changes produce the largest excess returns for intervals of 1-12 months. Purchasing power parity and Big-Mac index based strategies underperform. The returns are not explained by economic state variables or currency risk factors and are larger than estimated transaction costs. A composite strategy based on all four valuation approaches produces superior mean returns but volatility is also higher due to portfolio concentration.

Predictable Return Distributions

Using quantile regression this paper explores the predictability of the stock and bond return distributions as a function of economic state variables. The use of quantile regression allows us to examine specific parts of the return distribution such as the tails and the center, and for a sufficiently fine grid of quantiles we can trace out the entire distribution. A univariate quantile regression model is used to examine the marginal stock and bond return distributions, while a multivariate model is used to capture their joint distribution. An empirical analysis on US data shows that economic state variables predict the stock and bond return distributions in quite different ways in terms of, for example, location shifts, volatility and skewness. Comparing the different economic state variables in terms of their out‐of‐sample forecasting performance, the empirical analysis also shows that the relative accuracy of the state variables varies across the return distribution. Density forecasts based on an assumed normal distribution with forecasted mean and variance is compared to forecasts based on quantile estimates and, in general, the latter yields the best performance. Copyright © 2015 John Wiley & Sons, Ltd.

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INTRODUCTION: DYNAMIC STOCHASTIC GENERAL EQUILIBRIUM MODELLING AND THE STUDY OF ASIA‐PACIFIC ECONOMIES

INTRODUCTION: DYNAMIC STOCHASTIC GENERAL EQUILIBRIUM MODELLING AND THE STUDY OF ASIA‐PACIFIC ECONOMIES

Predictable Return Distributions

Using quantile regression this paper explores predictability of the stock and bond return distributions as a function of economic state variables. The use of quantile regression allows us to examine specific parts of the return distribution such as the tails and the center, and for a sufficiently fine grid of quantiles we can trace out the entire distribution. A univariate quantile regression model is used to examine the marginal stock and bond return distributions, while a multivariate model is used to capture their joint distribution. An empirical analysis on US data shows that economic state variables predict the stock and bond return distributions in quite different ways in terms of, for example, location-shifts, volatility, and skewness. Comparing the different economic state variables in terms of their out-of-sample forecasting performance, the empirical analysis also shows that the relative accuracy of the state variables varies across the return distribution. Density forecasts based on an assumed normal distribution with forecasted mean and variance is compared to forecasts based on quantiles estimates, and in general the latter yields the best performance.

The Determinants of Stock and Bond Return Comovements

We study the economic sources of stock‐bond return comovements and their time variation using a dynamic factor model. We identify the economic factors employing a semistructural regime-switching model for state variables such as interest rates, inflation, the output gap, and cash flow growth. We also view risk aversion, uncertainty about inflation and output, and liquidity proxies as additional potential factors. We find that macroeconomic fundamentals contribute little to explaining stock and bond return correlations but that other factors, especially liquidity proxies, play a more important role. The macro factors are still important in fitting bond return volatility, whereas the “variance premium” is critical in explaining stock return volatility. However, the factor model primarily fails in fitting covariances. (JEL G11, G12, G14, E43, E44) Stock and bond returns in the United States display an average correlation of about 19% during the post-1968 period. Shiller and Beltratti (1992) underestimate the empirical correlation using a present value with constant discount rates, whereas Bekaert, Engstrom, and Grenadier (2005) overestimate it in a consumption-based asset pricing model with stochastic risk aversion. Yet, these models generate realistically positive correlations using economic state variables.

Is the Distribution of Stock Returns Predictable?

A large literature has considered predictability of the mean or volatility of stock returns but little is known about whether the distribution of stock returns more generally is predictable. We explore this issue in a quantile regression framework and consider whether a range of economic state variables are helpful in predicting different quantiles of stock returns representing left tails, right tails or shoulders of the return distribution. Many variables are found to have an asymmetric effect on the return distribution, affecting lower, central and upper quantiles very differently. Out-of-sample forecasts suggest that upper quantiles of the return distribution can be predicted by means of economic state variables although the center of the return distribution is more difficult to predict. Economic gains from utilizing information in time-varying quantile forecasts are demonstrated through portfolio selection and option trading experiments.

Market Evidence of Economic State Variable Effects on Resource Sector Returns and Risk Premia

This study provides market evidence of the effects of economic state variables on sector stock returns and risk premia. Corporate values in the oil and gas sector are underpinned by state reserve participation terms that directly affect corporate cash flow entitlement. Progressive sovereign state participation in Non-OECD contracts result in relative stock return under-performance for companies invested in Non-OECD oilfields. Stock returns for oil and gas companies are used to compare the differential effects of OECD and Non-OECD oilfield asset holdings and provide sector evidence of variation in corporate wealth not captured by an overall market factor. Findings demonstrate that state variables limit the value of emerging market investment.

Commodity Price Shocks and Economic State Variables: Empirical Insights Into Asset Valuation and Risk in the Oil and Gas Sector

This study allows insights into the effects of economic state variables on asset values. We use a global sample of oil and gas sector assets to demonstrate that global differences in state participation terms cause oilfield asset values to respond differently to oil price shocks. Our sample recognizes that global reserve replacement is increasingly from Non-OECD countries and contrasts with previous oil and gas valuation and risk studies that have treated reserves as a homogenous asset class. We subject 211 oilfields to price shocks, introduce stochastic oil price volatility, and measure asset value response at each price level. Results provide evidence that state participation in reserve ownership contracts causes heterogenous asset value response to commodity price changes. Specifically, we show that for corporate asset values, it matters in which country reserves are held and the entitlement structures under which corporate agents operate assets.

The decomposition of US and Euro area stock and bond returns and their sensitivity to economic state variables

This paper decomposes US and Euro area excess stock and bond return innovations into news factors using the Campbell–Schiller methodology. The results indicate that stock return volatility is mostly due to volatility of future excess return news. Inflation news plays a minor role although it is significantly correlated with excess return innovations. For the bond market too, it is future return news—not inflation news—that moves bond returns most. For finite investment horizons, however, asset market movements give a differential importance to the various news components. Results are comparable for the US and the Euro area, but differ in terms of magnitudes. In addition, sensitivities (‘betas’) to a set of state variables are estimated, yielding high interest rate betas and low money growth betas. Generally, inflation, unemployment and leading indicator betas are significant. Asset market exposures to oil and exchange rate changes are more significant for the Euro area than in the US.

The determinants of Federal Reserve policy actions: A re-examination

In an earlier article (Journal of Macroeconomics 19, 1997) we presented estimates of Federal Reserve reaction functions including variables representing economic and political influences. Our goal was to examine the relative importance of political versus economic influences in determining Federal Reserve actions, as well as to see which economic state variables influenced Federal Reserve actions during various time periods. This paper extends our earlier work in three ways. First, we re-estimate the monetary policy reaction functions in our earlier study in a way which obviates possible reverse causation problems and better approximates the information set that was available to the Open Market Committee at the time its decisions were made. Second, we now have five more years of data which allows us to examine the Greenspan years more fully. Third, we divide our sample period, 1965–94, into two sub-periods, pre-1979 and post-1979, to examine the view that the Federal Reserve evidenced greater concern for inflation in the latter sub-period. The essential change from our earlier study is to use the interval between FOMC meetings as our observation rather than a calendar month. This change is shown to have significant effects on the estimated importance of political factors and economic state variables as determinants of Federal Reserve actions.