Do Beta Pricing Models Explain January Mean Reversion in Stock Returns?

Jegadeesh (1991) finds evidence of January mean reversion in stock returns. In this paper we attempt to distinguish between two competing economic explanations of January mean reversion in returns: (1) mispricing in irrational markets versus (2) predictable time variation in security risk premia. Excess portfolio returns are decomposed into “explained” and “unexplained” components using the Fama-French (1993) pricing model. The explained excess returns exhibit January mean reversion. The unexplained excess returns are not mean reverting. Mean reversion is therefore consistent with rational pricing in the framework of the Fama-French model. Mean reversion can be attributed to the component of return related to a relative distress factor (SMB). A comparison with the Chen, Roll, and Ross (1986) macroeconomic factors reveals that mean reversion is due to the components related to SMB and bond default premium.     

Can Costs of Consumption Adjustment Explain Asset Pricing Puzzles?

We investigate Grossman and Laroque's (1990) conjecture that costs of adjusting consumption can account, in part, for the empirical failure of the consumption-based capital asset pricing model (CCAPM). We incorporate small fixed costs of consumption adjustment into a CCAPM with heterogeneous agents. We find that undetectably small consumption adjustment costs can account for much of the discrepancy between the observed variance of nondurable aggregate consumption growth and the predictions of the CCAPM, and can partially reconcile nondurable consumption data with the observed equity premium. We conclude that the CCAPM's implications are nonrobust to extremely small adjustment costs.     

Can Affine Term Structure Models Help Us Predict Exchange Rates?

This paper proposes an arbitrage-free model to extract the information that the term structure of forward premia contains for forecasting future spot exchange rates. Using monthly data on four U.S. dollar bilateral exchange rates, we find evidence that this model provides statistically better forecasts than those produced by a random walk for the British pound and Canadian dollar exchange rates. Negative results for the German mark/Euro and Swiss franc are explained by a rejection of the restrictions imposed by the term structure model.     

Can China Help Lower World Inflation?: A Panel Study

In this paper, the effect of China's imports on importing countries' inflation is examined. Using data from 1994 to 2003, it is argued that China's export surge is an important contributor to lowering inflation in importing countries. Using fixed and random effect models, we identify a statistically significant negative correlation between the share of a country's imports from China and its rate of inflation.     

What Drives Anomaly Returns?

We decompose the returns of five well-known anomalies into cash flow and discount rate news. Common patterns emerge across the five factor portfolios and their mean-variance efficient (MVE) combination. Whereas discount rate news predominates in market returns, systematic cash flow news drives the returns of anomaly portfolios and their MVE combination with the market portfolio. Anomaly cash flow and discount rate shocks are largely uncorrelated with market cash flow and discount rate shocks and with business cycle fluctuations. These rich empirical patterns restrict the joint dynamics of firm cash flows and the pricing kernel, thereby informing models of stocks' expected returns.     

Are Securitized Real Estate Returns more Predictable than Stock Returns?

This paper examines whether the predictability of securitized real estate returns differs from that of stock returns. It also provides a cross-country comparison of securitized real estate return predictability. In contrast to most of the literature on this issue, the analysis is not based on a multifactor asset pricing framework as such analyses may bias the results. We use a time series approach and thus create a level playing field to compare the predictability of the two asset classes. Forecasts are performed with ARMA and ARMA–EGARCH models and evaluated by comparing the entire empirical distributions of prediction errors, as well as with a trading strategy. The results, based on daily data for the 1990–2007 period, show that securitized real estate returns are generally more predictable than stock returns in countries with mature and well established REIT regimes. ARMA–EGARCH models are found to have portfolio outperformance potential even in the presence of transaction costs, with generally better results for securitized real estate than for stocks.     

Do Industries Explain Momentum?

This paper documents a strong and prevalent momentum effect in industry components of stock returns which accounts for much of the individual stock momentum anomaly. Specifically, momentum investment strategies, which buy past winning stocks and sell past losing stocks, are significantly less profitable once we control for industry momentum. By contrast, industry momentum investment strategies, which buy stocks from past winning industries and sell stocks from past losing industries, appear highly profitable, even after controlling for size, book-to-market equity, individual stock momentum, the cross-sectional dispersion in mean returns, and potential microstructure influences.     

Can Time‐Varying Risk of Rare Disasters Explain Aggregate Stock Market Volatility?

Why is the equity premium so high, and why are stocks so volatile? Why are stock returns in excess of government bill rates predictable? This paper proposes an answer to these questions based on a time‐varying probability of a consumption disaster. In the model, aggregate consumption follows a normal distribution with low volatility most of the time, but with some probability of a consumption realization far out in the left tail. The possibility of this poor outcome substantially increases the equity premium, while time‐variation in the probability of this outcome drives high stock market volatility and excess return predictability.     

How Does Information Quality Affect Stock Returns?

Using a simple dynamic asset pricing model, this paper investigates the relationship between the precision of public information about economic growth and stock market returns. After fully characterizing expected returns and conditional volatility, I show that (i) higher precision of signals tends to increase the risk premium, (ii) when signals are imprecise the equity premium is bounded above independently of investors' risk aversion, (iii) return volatility is U-shaped with respect to investors' risk aversion, and (iv) the relationship between conditional expected returns and conditional variance is ambiguous.     

Can corporate governance save distressed firms from bankruptcy? An empirical analysis

We examine financially distressed firms and document how governance characteristics affect (1) a firm’s ability to avoid bankruptcy and (2) the power of financial/accounting information to predict bankruptcy. Overall, our findings indicate that a distressed firm’s governance characteristics significantly affect its probability of bankruptcy. We find that smaller and more independent boards with a higher ratio of non-inside directors and with larger ownership stakes of inside directors are more effective at avoiding bankruptcy once distress is indicated. These results are consistent with the belief that these types of governance structures induce more effective monitoring. The results are also consistent with the view that the inclusion of governance characteristics enhances the power of financial accounting models in predicting bankruptcy.

Can We Explain Inflation Persistence in a Way that Is Consistent with the Microevidence on Nominal Rigidity?

This paper adopts the impulse-response methodology to understand inflation persistence. It has often been argued that existing models of pricing fail to explain the persistence that we observe. We adopt a common general framework that allows for an explicit modeling of the distribution of contract lengths and for different types of price setting. We also evaluate how far the theories are consistent with recent evidence on price and wage rigidity. We find that allowing for a distribution of durations can take us a long way to solving the puzzle of inflation persistence, but not all the way yet.     

How Do Institutional Factors Affect International Real Estate Returns?

Prior international real estate studies recognize the importance of country-specific factors for explaining real estate security returns. Using firm level observations from the FTSE NAREIT/EPRA Index for 2004?C2006, we construct a set of multifactor multivariate statistical regression models to identify and pin-point country-specific institutional features that determine differences for excess real estate security returns. Our analyses indicate that the excess real estate returns (i.e., required risk premiums) are, in part, determined by the quality of a country??s legal system and the corporate governance environment, controlling for various country-specific macro-economic variables and firm-level characteristics. We further find that the impact of institutional factors on international real estate returns is more prominent in the Asia-Pacific Region, and recent development of the REIT structure across the world does not alter the importance of corporate governance and legal system quality for determining real estate returns.     

What Moves Retail Property Returns at the Metropolitan Level?

In this article the determinants of metropolitan-level appraisal-based retail property returns are examined by estimating a six-equation model of retail construction starts, retail sales, stock-market returns, commercial mortgage rates, inflation, and the logarithm of stock-market volatility. Residuals from these equations are then used to explain actual movements in retail real estate returns. Our empirical procedure looks at both unadjusted and unsmoothed appraisal-based retail real estate returns. The general finding is that unsmoothed appraisal-based retail real estate returns lag significantly behind market conditions. Furthermore, the results suggest that very little of the variation in metropolitan-level appraisal-based retail real estate returns can be explained by macroeconomic news events.     

Digital Tulips? Returns to investors in initial coin offerings

We analyze a dataset of 2390 completed ICOs, which raised a total of $12 billion in capital, nearly all since January 2017. We find evidence of significant ICO underpricing, with average returns of 179% from the ICO price to the first day's opening market price, over a holding period that averages just 16 days. After trading begins, tokens continue to appreciate in price, generating average buy-and-hold abnormal returns of 48% in the first 30 trading days. We also study the determinants of ICO underpricing and relate cryptocurrency prices to Twitter activity.     

Does Inflation Targeting Help Reduce Financial Dollarization?

We examine whether adopting an inflation‐targeting regime helps reduce financial dollarization as predicted by Ize and Levy Yeyati's ( 2003 ) portfolio model. To address the self‐selection problem of policy adoption, we apply a variety of propensity score matching methods to a large sample of 106 developing countries for the years 1985–2004. We find strong evidence that inflation targeting has large and significant treatment effects on lowering both actual financial dollarization and the model implied minimum variance portfolio dollarization. Our results are robust to alternative samples and model specifications and also to control for additional factors in postmatching regressions.     

Can Space Syntax Help Us in Understanding the Intraurban Office Rent Pattern? Accessibility and Rents in Downtown Stockholm

The effect of accessibility upon rent is investigated for office properties located in Downtown Stockholm. Starting from the firm’s cost minimization problem, a translog hedonic model is derived. The results suggest the model has good predictive power in explaining the variation in the log of the rent. A negative rent gradient is obtained with a base approximately 90 m from the postulated focal point. It appears as if Space Syntax adds important information to the understanding of the intraurban office rent pattern.

Non-linear Dependence in Stock Returns: Does Trading Frequency Matter?

The UK has a quote-driven pure dealer market structure that is very different from order driven markets such as the NYSE and Japanese markets. This paper investigates non-linear dependence in stock returns for an exhaustive sample of UK stocks for a 21 year period. The results are analysed on the basis of trading frequency. It is found that non-linear dependence is highly significant in all cases for both individual stocks and stock portfolios formed on the basis of trading frequency. The non-linear dependence is primarily over a one day interval, although statistically significant non-linear dependence exists consistently even up to five trading days. Most of the non-linear dependence is in the form of ARCH-type conditional heteroskedasticity. However, statistically significant non-linearity in addition to an EGARCH(1,1) dependence also appears to be present. This additional non-linearity is greater for individual stocks than for portfolios and greater for smaller, less-liquid portfolios. Non-linear dependence does not appear to be caused by non-stationarity in underlying economic fundamentals or by non-linearity in the conditional mean. However, low dimensional chaos is not generally supported. The limited evidence on chaotic behaviour is stronger for portfolios with long price adjustment delays across component stocks. The main results are consistent with US studies on stock indices, suggesting that the process generating non-linear dependence is not dependent on market microstructure characteristics.