Aggregate Returns Research Articles

A conditional distribution model for limited stock index returns

When a price limit regime exists for all of the stocks involved in an index, the index return is an aggregate of limited variables and thereby it is restricted to the same limits. We argue that neither a censored nor a truncated distribution model is appropriate for the aggregate return. The proposed mixed beta distribution allows for varying conditional mean and volatility, and with increasing volatility it changes from leptokurtic to platykurtic densities. The model is illustrated and statistically evaluated with an empirical application to the Shanghai stock market index returns under a 10% price change limit regime.

Investor Overreaction, Cross-Sectional Dispersion of Firm Valuations, and Expected Stock Returns

This paper develops the theoretical predictions that when investor overreaction to market-wide information is larger, firm valuations in the cross-section become more dispersed, and stocks on average earn lower expected returns. Consistent with the model prediction, I find that my measure of firm valuation dispersion measure is a negative predictor of subsequent aggregate returns. The dispersion-return relation is most pronounced among firms that have highly subjective valuations and significant limits of arbitrage.

A portfolio view of consumer credit

To compute risk-adjusted returns and gauge the volatility of their portfolios, lenders need to know the covariances of their loans’ returns with aggregate returns. We use unique credit bureau data to measure individuals’ ‘covariance risk’, i.e., the covariance of their default risk with aggregate consumer default rates, and more generally to analyze the distribution of credit, including the effects of credit scores. We find significant heterogeneity in covariance risk across consumers. Also, the amount of credit they obtain significantly increases with their credit scores, and decreases with their covariance risk (especially revolving credit), though the effect of covariance risk is smaller.

The Return to Capital in China

China's investment rate is one of the highest in the world, which naturally leads one to suspect that the return to capital in China must be quite low. Using the data from China's national accounts, we estimate the rate of return to capital in China. We find that the aggregate rate of return to capital averaged 25% during 1978-1993, fell during 1993-1998, and has become flat at roughly 20% since 1998. This evidence suggests that the aggregate return to capital in China does not appear to be significantly lower than the return to capital in the rest of the world. We also find that the standard deviation of the rate of return to capital across Chinese provinces has fallen since 1978.

Aid and the Supply Side: Public Investment, Export Performance, and Dutch Disease in Low-Income Countries

Contemporary policy debates on the macroeconomics of aid often concentrate on short-run Dutch disease effects, ignoring the possible supply-side impact of aid financed public expenditure. In the simple model of aid and public expenditure presented here, public infrastructure generates an inter-temporal productivity spillover, which may exhibit a sector-specific bias. The model also provides for a learning-by-doing externality, through which total factor productivity in the tradable sector is an increasing function of past export volumes. An extended computable version of this model is used to simulate the effect of a step increase in net aid flows. The simulations show that beyond the short run, when conventional demand-side Dutch disease effects are present, the relationship between enhanced aid flows and real exchange rates, output growth, and welfare is less straightforward than simple models of aid suggest. Public infrastructure investment that generates a productivity bias in favor of non-tradable production delivers the largest aggregate return to aid, but at the cost of deterioration in the income distribution. Income gains accrue predominantly to skilled and unskilled urban households, leaving the rural poor relatively worse off. Under plausible parameterizations of the model, the rural poor may also be worse off in absolute terms.

Covariation neglect among novice investors.

In 4 experiments, undergraduates made hypothetical investment choices. In Experiment 1, participants paid more attention to the volatility of individual assets than to the volatility of aggregated portfolios. The results of Experiment 2 show that most participants diversified even when this increased risk because of covariation between the returns of individual assets. In Experiment 3, nearly half of those who seemingly attempted to minimize risk diversified even when this increased risk. These results indicate that novice investors neglect covariation when diversifying across investment alternatives. Experiment 4 established that naive diversification follows from motivation to minimize risk and showed that covariation neglect was not significantly reduced by informing participants about how covariation affects portfolio risk but was reduced by making participants systematically calculate aggregate returns for diversified portfolios. In order to counteract naive diversification, novice investors need to be better informed about the rationale underlying recommendations to diversify.

Recursive equilibrium in endogenous growth models with incomplete markets

This paper analyzes the existence of recursive equilibria in a class of convex growth models with incomplete markets. Households have identical CRRA-preferences, production displays constant returns to scale with respect to physical and human capital, and all markets are competitive. There are aggregate productivity shocks that affect aggregate returns to physical and human capital investment (stock returns and wages), and there are idiosyncratic shocks to human capital (idiosyncratic depreciation shocks) that only affect individual human capital returns. Aggregate and idiosyncratic shocks follow a joint Markov process. Conditional on the aggregate state, idiosyncratic shocks are independently distributed over time and identically distributed across households. Finally, households have the opportunity to trade assets in zero net supply with payoffs that depend on the aggregate shock, but markets are incomplete in the sense that there are no assets with payoffs depending on idiosyncratic shocks. It is shown that there exists a recursive equilibrium for which equilibrium prices (returns) only depend on the exogenous aggregate shock variable (the wealth distribution is not a relevant state variable). Moreover, the allocation associated with this recursive equilibrium is identical to the equilibrium allocation of an economy in which households live in autarky and face both aggregate and idiosyncratic risk.

The Underlying Dynamics of Credit Correlations

We propose a hybrid model of portfolio credit risk where the dynamics of the underlying latent variables is governed by a one factor GARCH process. The distinctive feature of such processes is that the long-term aggregate return distributions can substantially deviate from the asymptotic Gaussian limit for very long horizons. We introduce the notion of correlation spectrum as a convenient tool for comparing portfolio credit loss generating models and pricing synthetic CDO tranches. Analyzing alternative specifications of the underlying dynamics, we conclude that the asymmetric models with TARCH volatility specification are the preferred choice for generating significant and persistent credit correlation skews.

Stock price synchronicity and analyst coverage in emerging markets

This paper examines the relation between the stock price synchronicity and analyst activity in emerging markets. Contrary to the conventional wisdom that security analysts specialize in the production of firm-specific information, we find that securities which are covered by more analysts incorporate greater (lesser) market-wide (firm-specific) information. Using the R 2 statistics of the market model as a measure of synchronicity of stock price movement, we find that greater analyst coverage increases stock price synchronicity. Furthermore, after controlling for the influence of firm size on the lead–lag relation, we find that the returns of high analyst-following portfolio lead returns of low analyst-following portfolio more than vice versa. We also find that the aggregate change in the earnings forecasts in a high analyst-following portfolio affects the aggregate returns of the portfolio itself as well as those of the low analyst-following portfolio, whereas the aggregate change in the earnings forecasts of the low analyst-following portfolio have no predictive ability. Finally, when the forecast dispersion is high, the effect of analyst coverage on stock price synchronicity is reduced.

Stock returns, aggregate earnings surprises, and behavioral finance

We study the stock market's reaction to aggregate earnings news. Prior research shows that, for individual firms, stock prices react positively to earnings news but require several quarters to fully reflect the information in earnings. We find a substantially different pattern in aggregate data. First, returns are unrelated to past earnings, suggesting that prices neither underreact nor overreact to aggregate earnings news. Second, aggregate returns correlate negatively with concurrent earnings; over the last 30 years, for example, stock prices increased 5.7% in quarters with negative earnings growth and only 2.1% otherwise. This finding suggests that earnings and discount rates move together over time and provides new evidence that discount-rate shocks explain a significant fraction of aggregate stock returns.

A Variance‐Ratio Test of the Random Walk Hypothesis for the New Zealand Share Market: 1980‐2001

This paper examines the Random Walk Hypothesis (RWH) for aggregate New Zealand share market returns, as well as the CRSP NYSE‐AMEX (USA) index during the 1980‐2001 period. Using several indices, we rely on the variance‐ratio test and find evidence to support the rejection of the RWH with some evidence of a momentum effect. However, we find evidence to suggest the behaviour of share prices to be time‐dependent in New Zealand. For example, we find the indices tested were closer to random after the 1987 share market crash. Further analysis showed even stronger results for periods subsequent to the passage of the Companies Act 1993 and the Financial Reporting Act 1993. We also find evidence that indices based on large capitalisation stocks are more likely to follow a random walk compared to those based on smaller stocks. For the USA index, we find stronger evidence of random behaviour in our sample period compared to the earlier period examined by Lo and Mackinlay (1988)

Predicting Asset Returns With Expected Oil Price Changes

Market returns and industry performance are predicted by forecastable oil price movements. Although predictability can be compatible with market efficiency, these results may be more readily explained by underreaction to information about subsequent oil price changes. Some market participants appear to ignore the effect of partially anticipated oil price movements on non-oil industrial sectors. The evidence from the oil industry indicates that the asset returns of stocks explicitly dependent on the price of oil are not forecastable using the predicted component of oil price changes. The predictability of both aggregate returns and the relative performance for some industries, such as household goods, medical equipment, construction, fabricated products, mines, real estate, and finance suggests that market participants may not pay attention to the broader impact of forecastable oil price changes.

Overconfidence, Short-Sale Constraints, and Stock Valuation

There is a recent renaissance in the research of investor differences of opinion and short-sale constraints. This literature usually assumes that investor opinion is generated from an exogenous distribution and hence does not link opinion divergence and stock valuation to stock fundamentals. In addition, most theories simply model short-sale constraints as short-sale prohibition. This paper develops a stock market model based on investor overconfidence and short-sale constraints, in which overconfidence generates differences of opinion and the degree of short-sale constraints is variable. In the model, after receiving private signals, overconfident investors and rational investors exchange one risky asset with which there is a restriction in maximum number of shortable shares. In equilibrium, conditional on private signals, stocks can be overvalued or undervalued. How stocks are mispriced depends on whether private signals are favorable or adverse and, accordingly, what investors are bound by short-sale constraints. However, due to the asymmetry in under- and overvaluation introduced by short-sale constraints, on average, stocks are overvalued. The model produces a distribution of investor differences of opinion that is correlated with stock fundamentals, which explains the cross-sectional differences in opinion divergence. The models also examines the effects of investor overconfidence and short-sale constraints on opinion divergence, trading volume, and short interest. It shows that a variation in overconfidence induces a negative correlation between subsequent stock returns and opinion divergence, trading volume, or short interest. In contrast, a variation in short-sale constraints generates a positive correlation between subsequent stock returns and trading volume or short interest but has no effects on opinion divergence. These relationships provide an explanation for a number of stylized facts in the cross-section. After we further incorporate multiple assets whose payoffs share a common factor, the model gives many implications for the time-series behavior of aggregate returns. It explains the ability of cross-sectional averages of firm valuation measures (such as book-to-market equity and dividend yield) to forecast market returns and returns of various portfolios. It also provides an explanation for the stronger predictability of equal-weight market returns than value-weight market returns. Finally, we suggest a number of new predictors of aggregate returns, including cross-sectional averages of opinion divergence, of trading volume, and of short interest, and cross-sectional dispersions of firm misvaluation and of opinion divergence.

A Portfolio View of Consumer Credit

This paper takes a portfolio view of consumer credit. Default models (credit-risk scores) estimate the probability of default of individual loans. But to compute risk-adjusted returns, lenders also need to know the covariances of the returns on their loans with aggregate returns. Covariances are independently relevant for lenders who care directly about the volatility of their portfolios, e.g., because of Value-at-Risk considerations or the structure of the securitization market. Cross-sectional differences in these covariances also provide insight into the nature of the shocks hitting different types of consumers. We use a unique panel dataset of credit bureau records to measure the of individual consumers, i.e., the covariance of their default risk with aggregate consumer default rates, and more generally to analyze the cross-sectional distribution of credit, including the effects of credit scores. We obtain two key sets of results. First, there is significant systematic heterogeneity in covariance risk across consumers with different characteristics. Consumers with high covariance risk tend to also have low credit scores (high default probabilities). Second, the amount of credit obtained by consumers significantly increases with their credit scores, and significantly decreases with their covariance risk (especially revolving credit), though the effect of covariance risk is smaller in magnitude. It appears that some lenders take covariance risk into account, at least in part, in determining the amount of credit they provide.

Good Times or Bad Times? Investors' Uncertainty and Stock Returns

This paper investigates empirically the dynamics of investors' beliefs and Bayesian uncertainty on the state of the economy as state variables that describes the time-variation in investment opportunities. Using measures of uncertainty constructed from the state probabilities estimated from two-state regime-switching regime models of aggregate market return, and of aggregate output, I find a negative relationship between the level of uncertainty and asset valuations. This relationship shows substantial cross-sectional variation across portfolios sorted on size, book-to-market and past returns, especially conditional on the state of the economy. I show that a conditional model with investors' beliefs and uncertainty risk factor, is remarkably successful in explaining a large part of the cross-sectional variation in average portfolio returns. The uncertainty risk factor retains its incremental explanatory power when contrasted with other economically-motivated factors such as GDP news, or other conditional models such as (C)CAPM.

Portfolio management of wild fish stocks

Managing fish stocks in terms of a portfolio of economic assets is likely to significantly increase benefits for society relative to single-species approaches. A portfolio framework systematically combines fish stocks that are joined by ecology (e.g., predation, competition) and unspecialized fishing technologies (e.g., mixed-species trawls) into a portfolio which balances expected aggregate returns against the risks associated with stock-attribute and other uncertainties. To be productive, however, this framework must be combined with property rights institutions that clearly state management objectives, create long-run time-horizons among harvesters, internalize spillovers caused by ecological and technological jointness, and reduce uncertainty through research and adaptive management. Although the cost of reducing scientific uncertainty about ecological interactions may limit the portfolio approach to intensive management of relatively few species, its scope can be broadened to integrate tradeoffs among more types of marine resources, such as nature preserves and oil and gas deposits.

INSIDER TRADING AT THE MEXICAN STOCK EXCHANGE: EVIDENCE FROM DATA AUGMENTATION

Prior research has suggested that insider trading is present in the Mexican Stock Exchange. Based on this evidence, the media has claimed that insider trading is common practice. The evidence to support this claim is obtained from event-study methodology and aggregate returns. Previous studies, however, have not dealt explicitly with the endemic problem of missing observations. In this paper, I study the implications of insider trading at the corporation-level and over longer horizons. My work uses Monte Carlo simulations in order to deal with the nuissance of missing data. I find statistical evidence of insider trading only in a small number of the corporations under analysis.

Outbound Business Travel Depends on Business Returns: Australian Evidence

In an earlier note, Collins and Tisdell (2002b) explored the possibility of a long‐run relationship between Australian business returns and international business travel. Using annual data they found that such a relationship exists. The purpose of this study is to further examine this relationship using quarterly data for the time frame 1974:1 to 1999:4. In addition, previous studies on international business travel have offered some but not strong evidence for the existence of a positive relationship between the level of international business travel and real GDP of the origin country. This study suggests that the aggregate return on business investments is a better predictor of international business travel than GDP. The Engle‐Granger and Johansen's maximum‐likelihood cointegration procedures are used to show a long‐term relationship exists between Australian outbound business travel and Australian business returns, but not with Real Australian GDP. Reasons for this relationship are discussed.

A Simple Methodology to Estimate the Prospective Equity Premium

This paper sets out some simple, closed-form formulae to estimate the level of the prospective equity premium. The formulae are based on a comparison of the firm's cost of capital with the market discount rate. Calibration of the models over long time periods indicates that, in aggregate, firms have achieved a return on their investments that is below the market discount rate. This result is robust to differing time periods, model specifications, and return calculations. It is also consistent with existing evidence that: (a) in aggregate, investment and stock returns are negatively correlated; (b) stocks with high investment suffer low subsequent returns; (c) firms raising capital suffer low subsequent returns; and (d) firms returning capital to shareholders achieve high subsequent returns. Alternative explanations of this main result are also discussed, including the possibility that the earnings of firms, and hence the funds available for investment, have been overstated due to inflation or other factors. I also use the models to estimate annual levels of the prospective equity premium since 1949. This analysis indicates that the premium over long-term Treasuries has been low since the early-1980s.

Do Agency Problems Affect Aggregate Risk and Return? Theory and Evidence

Do Agency Problems Affect Aggregate Risk and Return? Theory and Evidence