Do stock returns hedge inflation at long horizons?

We investigate the long-horizon relationship between market returns and inflation in the United States. Conventional tests for long horizon predictability may reject the null too frequently when the predictor variable is highly persistent and endogenous and there are overlapping observations. We use a recently developed econometric technique designed to overcome these problems. We find little to no evidence that securities are able to hedge inflation.     

Do stock market returns predict changes to output? Evidence from a nonlinear panel data model

Recent empirical work suggests a predictive relationship between stock returns and output growth. We employ quarterly data from a panel of 27 countries to test whether stock returns as useful in predicting growth. Unlike previous research, our approach allows for the possible non-linear effect of recessions on the growth-return relationship. There is strong evidence to suggest that a linear model would be misspecified and provide potentially misleading inference. Using a switching regression approach, we find evidence that returns are most useful in predicting growth when the economy is in recession.First version received: November 2002/Final version received: April 2003This paper benefited greatly from discussions with Kalvinder Shields, Mark Harris, Pete Summers, and Vance Martin. Two anonymous referees provided useful comments on an earlier version of the paper for which we are grateful. The usual disclaimer applies to any errors and omissions. Funding from The University of Melbourne greatly assisted in the completion of this paper.     

Forecasting Housing Approvals in Australia: Do Forecasters Herd?

Price trends in housing markets may reflect herding of market participants. A natural question is whether such herding, to the extent that it occurred, reflects herding in forecasts of professional forecasters. Using more than 6,000 forecasts of housing approvals for Australia, we did not find evidence of forecaster herding. On the contrary, forecasters anti‐herd and, thereby, tend to intentionally scatter their forecasts around the consensus forecast. The extent of anti‐herding seems to vary over time. We also found that more pronounced anti‐herding leads to less accurate forecasts.     

Can oil prices help predict US stock market returns? Evidence using a dynamic model averaging (DMA) approach

Crude oil price behaviour has fluctuated wildly since 1973 which has a major impact on key macroeconomic variables. Although the relationship between stock market returns and oil price changes has been scrutinized excessively in the literature, the possibility of predicting future stock market returns using oil prices has attracted less attention. This paper investigates the ability of oil prices to predict S&P 500 price index returns with the use of other macroeconomic and financial variables. Including all the potential variables in a forecasting model may result in an over-fitted model. So instead, dynamic model averaging (DMA) and dynamic model selection (DMS) are applied to utilize their ability of allowing the best forecasting model to change over time while parameters are also allowed to change. The empirical evidence shows that applying the DMA/DMS approach leads to significant improvements in forecasting performance in comparison to other forecasting methodologies and the performance of these models are better when oil prices are included within predictors.     

An analysis of commercial bank common stock returns: 1802–97

This study creates analyses for the first time a continous index of returns on commercial bank common stocks listed in a specific market. The index is constructed from a unique set of historical data and is calculated on both a weighted and unweighted basis, first including and then excluding dividends. A measure of volatility is calculated annually.

The results indicate that the dividend component of holding period returns is very important. Including dividends, average returns were 6.0% for the century; excluding dividends, average returns were 0.1%. Excess returns were calculated using two different measures of a riskless rate of return. Cumulative excess returns for the first half of the nineteenth century were negative. Real returns were calculated, and found to be generally positive over the century. The volatility of returns was quite high during certain periods.

Examining the effects of significant economic and political events on bank common stock returns, we find that the War of 1812, the Civil War, and the National Banking System had a significant impact on bank stock returns. Several economic panics, several depressions, the First and Second Banks of the United States, the Embargo of 1807, and the Suffolk Bank had no measureable impact.     

Does extracting inflation from stock returns solve the purchasing power parity puzzle?

In a recent study by Chowdhry et al. (American Economic Review 95: 255–276, 2005), they suggest that the empirical failure of relative purchasing power parity (PPP) may be because the official inflation data are too sticky. Thus, after extracting the unobservable pure price inflation from equity markets, they find strong evidence supporting relative PPP in the short run. As a replication study, this paper first replicates their original findings successfully. We further investigate whether long-run relative PPP holds using the pure price inflation data constructed by Chowdhry et al. (2005). After constructing pure real exchange rate series using their pure price inflation data, we implement both unit root and cointegration tests on the pure real exchange rates. According to the test results, the evidence suggests that relative PPP does not hold in the long run. Thus, it may be too early to suggest a resolution of the PPP puzzle.     

Do complex inventions need less international patent protection?

I show that very complex inventions stay outside the patent system more often than medium-complexity products. I test this hypothesis using a subset of international patents data. The regressions confirm that patents and technological complexity have an inverted-U shape relation.     

Forecasting inflation and tracking monetary policy in the euro area: does national information help?

The ECB target is set in terms of the year on year growth rate of the euro area Harmonized Index of Consumer Prices. Nonetheless, a good deal of attention is given to national data by market analysts when they try to anticipate monetary policy moves. In this paper we use the Generalized Dynamic Factor Model to develop a set of core inflation indicators that, combining national data with area wide information, allow us to answer two related questions. The first is whether country specific data actually bear any relevance for the future path of area wide price growth, over and above that already contained in area wide data. The second is whether to track ECB monetary policy decisions it is useful to take into account national information and not only area wide statistics. Within our empirical framework we find that once area wide information is properly taken into account the contribution of national idiosyncratic developments is negligible.     

Do speculative bubbles migrate in the Chinese stock market?

In this paper, a duration dependence test for speculative bubbles in the Chinese stock market is developed. It is found that bubbles in the aggregate stock price existed before the split share reform. After the reform, we observe the phenomenon of bubble migration across industries. In particular, bubbles migrate from the telecommunications industry to the health care industry. Moreover, we find that monetary policy used to have a significant impact on the bubble size before the reform but the impact diminished after the reform.

     

Do your brains help you out of unemployment?

This study examines the relationship between individuals’ cognitive abilities, unemployment propensity and unemployment entry or exit. Cognitive skills only weakly affect unemployment propensity and contribute little to individual heterogeneity. They, however, help employed males to stay out of unemployment.     

Do political connections decrease the accuracy of stock analysts' recommendations in the Chinese stock market?

This paper studies the association between the accuracy of analysts' recommendations and political connections in the Chinese stock market. As most brokerage firms in China are state-owned, it raises concerns about conflicts of interest among their employed analysts issuing recommendations for Chinese state-owned enterprises. Based on 8469 analysts' recommendations with different ratings for both state-owned and non-state-owned enterprises from 74 brokerage firms, we document that analysts' recommendations are less accurate for Chinese state-owned enterprises, which supports the hypothesis that conflicts of interest create recommendation biases. Political connections encourage analysts to be more optimistic on SOEs and even to generate misleading “Buy” and “Hold” recommendations. Our results demonstrate the existence of an optimism bias among politically connected analysts on state-owned enterprises in China.     

A Note on Forecasting the Euro: Do Forecasters Have an Asymmetric Loss Function?

Based on the approach advanced by Elliott, Komunjer, and Timmermann (2005 Elliott, G., Komunjer, I., & Timmermann, A. (2005). Estimation and testing of forecast rationality under flexible loss. Review of Economics Studies, 72, 1107–1125. doi: 10.1111/0034-6527.00363[Crossref], [Web of Science ®] , [Google Scholar]), we analyzed whether the loss function of a sample of exchange-rate forecasters is asymmetric in the forecast error. Using forecasts of the dollar/euro exchange rate, we found that the shape of the loss function varies across forecasters. Some forecasters appear to make forecasts under an asymmetric loss function, while a symmetric loss function seems to describe well the loss function of other forecasters. Accounting for an asymmetric loss function does not necessarily make forecasts ‘look’ rational.     

Forecasting US real house price returns over 1831–2013: evidence from copula models

Given the existence of nonnormality and nonlinearity in the data generating process of real house price returns over the period of 1831–2013, this article compares the ability of various univariate copula models, relative to standard benchmarks (naive and autoregressive models) in forecasting real US house price over the annual out-of-sample period of 1874–2013, based on an in-sample of 1831–1873. Overall, our results provide overwhelming evidence in favour of the copula models (Normal, Student’s t, Clayton, Frank, Gumbel, Joe and Ali-Mikhail-Huq) relative to linear benchmarks, and especially for the Student’s t-copula, which outperforms all other models both in terms of in-sample and out-of-sample predictability results. Our results highlight the importance of accounting for nonnormality and nonlinearity in the data generating process of real house price returns for the US economy for nearly two centuries of data.     

Expected inflation, expected stock returns, and money illusion: What can we learn from survey expectations?

We show empirically that survey-based measures of expected inflation are significant and strong predictors of future aggregate stock returns in several industrialized countries both in-sample and out-of-sample. Empirically discriminating between competing sources of this return predictability by virtue of a comprehensive set of expectations data, we find that money illusion seems to be the driving force behind our results. Another popular hypothesis – inflation as a proxy for aggregate risk aversion – is not supported by thedata.     

Do national soccer results really impact on the stock market?

This study is a response to Klein et al. (2008), which was highly critical of earlier work by Ashton et al. (2003). This work considering the link between international soccer results and stock market returns was challenged by Klein et al. (2008), who reject the presence and importance of this link. In response, this work provides a reassessment of the link between international soccer results and stock market returns within Ashton et al. (2003). This new analysis extends the original work by using a larger dataset, employing an extended range of tests and allowing for outliers. It is reported that, contrary to the findings of Klein et al. (2008), the link between international soccer results and stock market prices does indeed exist particularly within the sample period 1984–2002 used by Ashton et al. (2003). After extending the dataset to include observations from 2002 until 2009, it is reported that the effect on stock market returns has declined in importance over this period, particularly the impact of wins.     

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.     

Drivers of expected returns in Istanbul stock exchange: Fama–French factors and coskewness

We investigate the impact of coskewness on the variation of portfolio excess returns in Istanbul Stock Exchange (ISE) over the period July 1999 to December 2005. We form portfolios according to size, industry, size and book-to-market ratio, momentum and coskewness and compare alternative asset pricing models. The traditional capital asset pricing model (CAPM) and the three-factor model of Fama and French are tested in the multivariate testing procedure of Gibbons–Ross–Shanken (1989). Coskewness is introduced as a fourth factor and its incremental effect over CAPM and Fama–French factors is examined both in multivariate tests and in cross-sectional regressions. The findings reveal that coskewness is able to explain the size premium in ISE. Hence, the basic two-moment CAPM without the coskewness factor would underestimate the expected return of size portfolios. Multivariate test results indicate that coskewness reduces the pricing bias, albeit insignificantly. Cross-sectional analysis uncovers that coskewness has a significant additional explanatory power over CAPM, especially for size and industry portfolios. However, coskewness does not have a significant incremental explanatory power over Fama–French factors in ISE.