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.     

Institutional investor sentiment and aggregate stock returns

This paper examines the equity market return predictability of institutional investor sentiment, in comparison to individual investor sentiment. Our findings suggest that institutional traders are informed and that their sentiment helps to tilt stock prices towards the intrinsic value. This is because the sentiment of institutions encompasses news regarding expectations on future cash flows of underlying firms that impounds itself into future price expectations. In this study, we add to the large number of studies that investigate the role and implications of investor sentiment, which has long been viewed as a pure behavioural phenomenon, on market efficiency and price discovery.     

When is a MAX not the MAX? How news resolves information uncertainty

A well-known asset pricing anomaly, the “MAX” effect, measured by the maximum daily return in the past month, depicts stocks’ lottery-like features and investor gambling behaviour. Using the comprehensive stock-level Dow Jones (DJNS) news database between 1979 and 2016, we consider in a empirical setting how the presence of news reports affects these lottery-type stocks. We find an augmented negative relationship between MAX stocks without news and expected returns, whereby MAX with news coverage generates return momentum. The differing future return relationships between MAX stocks with and without news appears to be best explained by information uncertainty mitigation upon news arrival. Overall, our findings suggest that news plays a role in resolving information uncertainty in the stock market.     

Impact of bitcoin futures on the informational efficiency of bitcoin spot market

This study examines the informational efficiency of the bitcoin spot market by evaluating the predictive power of mechanical trading rules designed to exploit price continuation. Significant return predictability is found until the introduction of bitcoin futures in December 2017. The forecasting ability of trend‐chasing trading rules declines dramatically afterwards. Although evidence suggests that the introduction of bitcoin futures has increased the informational efficiency of the bitcoin spot market, no signs of improvement in informational efficiency are found in ethereum, the second‐largest cryptocurrency—following the introduction of bitcoin futures.     

Indicator selection and stock return predictability

We propose a momentum-determined indicator-switching (MDIS) strategy, simple and effective, to improve the predictability of stock returns, which can effectively select predictors. Empirical results indicate that the stock return forecasts generated by the MDIS strategy are statistically and economically significant. And we find that super long-term momentum of predictability (SMoP) exists in predictive factors. That is, in a long period of time in the past, the best predictor among a series of factors has best prediction ability in the future. We also design restricted momentum-determined indicator-switching (RMDIS) strategy when considering economic constrain. It is robust for the prediction performance of this strategy using a series of extension and robustness test. Success of the RMDIS strategy is also seen in using technical indicators to forecast stock returns.     

Financial crises and the dynamics of the spillovers between the U.S. and BRICS stock markets

We examine the spillover dynamics between the U.S. and BRICS stock markets using the multivariate DECO-GJR-GARCH model and spillover index method. We identify time variations in volatility equicorrelation and significant dynamic spillovers between these stock markets, as well as an increased impact of uncertainty on spillovers. Spillovers between markets intensify after the inception of the global financial crisis and subsequent European sovereign debt crisis. We also find, following the commencement of the crisis periods, that the U.S., Brazilian, and Chinese markets are net volatility transmitters, whereas the Russian, Indian, and South African markets are net recipients. These results shed new light on the information transmission channels between the U.S. and BRICS stock markets.     

U.S. productivity in agriculture and R&D

This paper examines the impact of R&D on multifactor productivity in the U.S. agricultural sector over the 1910–1990 period. We use the Bennet–Bowley indicator to measure agricultural productivity based on a multiple output-multiple input technology. We demonstrate the relationship between the price dependent Bennet–Bowley indicator and the Luenberger productivity indicator which is constructed from directional distance functions without requiring price information. These performance measures are dual to the profit function which arguably makes them especially useful in the agricultural setting. We employ time-series techniques to investigate the effect of R&D on the pattern of productivity growth. We find that we cannot reject the presence of a cointegrating relationship between the two series and that productivity growth in the U.S. agriculture responds positively to R&D expenditure with a lag of between four and ten periods.

Index Futures and Predictability of the Underlying Stocks’ Returns: The Case of the Nikkei 225

Theories predict that launching index futures could affect the price informativeness for the underlying stocks. We test this hypothesis by taking advantage of the introduction of the Nikkei 225 futures contracts in Singapore on September 3, 1986. Employing two alternative statistical methods applied to both daily and weekly data, we find that, following the listing of the index futures, returns become significantly more random and less predictable for the underlying stocks, even after controlling for concurrent marketwide shifts. These findings suggest improved price informativeness for the underlying stocks, which is further corroborated by their higher trading volume following the event.

Predicting capacity utilization: Federal Reserve vs time-series models

This study evaluates the Federal Reserve forecasts of manufacturing capacity utilization employing, as benchmarks, the forecasts from a univariate model which utilizes past information in capacity utilization, and from a bivariate model which utilizes past information in both capacity utilization and the federal funds rate. In addition to accurately predicting the directional change in capacity utilization, the Federal Reserve forecasts are “weakly” rational and generally superior to the bivariate forecasts. In light of another finding that monetary policy is non-neutral, we argue the Federal Reserve forecasts of capacity utilization have positively contributed to the Fed’s success in maintaining a low inflationary environment.

Residential investment and recession predictability

We assess the importance of residential investment for the prediction of economic recessions for an unbalanced panel of 12 OECD countries over the period 1960Q1–2014Q4. Our approach is to estimate various probit models with different leading indicators and evaluate their relative prediction accuracies using the area under the receiver operating characteristic curve as our forecasting performance metric. We document that residential investment contains information that is useful for predicting recessions both in-sample and out-of-sample. This result is robust to adding typical leading indicators, such as the term spread, stock prices, consumer confidence surveys and oil prices. It is shown that residential investment is particularly useful for the prediction of recessions for countries with high home-ownership rates. Finally, in a separate exercise for the US, we show that the predictive ability of residential investment is — in a broad sense — robust to employing real-time data.