A common factor analysis for the US and the German stock markets during overlapping trading hours

We employ a bivariate common factor model to establish a permanent-transitory decomposition of two major stock indices (the Deutsche Aktienindex (DAX) for Germany and the Dow Jones Industrial Average (DJIA) for the United States). Using high-frequency data, we (1) identify a common trend shared by both indices, (2) find that the DJIA contributes up to 95% to the total innovation of the common factor, (3) show that both markets adjust within minutes to a system-wide shock, and (4) verify by hypothesis testing that the DJIA is the driving force in the transatlantic system of stock indices.     

Share Issuance and Factor Timing

We show that characteristics of stock issuers can be used to forecast important common factors in stocks' returns such as those associated with book‐to‐market, size, and industry. Specifically, we use differences between the attributes of stock issuers and repurchasers to forecast characteristic‐related factor returns. For example, we show that large firms underperform after years when issuing firms are large relative to repurchasing firms. While our strongest results are for portfolios based on book‐to‐market (i.e., HML), size (i.e., SMB), and industry, our approach is also useful for forecasting factor returns associated with distress, payout policy, and profitability.     

Does Greater Firm‐Specific Return Variation Mean More or Less Informed Stock Pricing?

Roll [1988] observes low R² statistics for common asset pricing models due to vigorous firm‐specific return variation not associated with public information. He concludes that this implies “either private information or else occasional frenzy unrelated to concrete information”[p. 56]. We show that firms and industries with lower market model R² statistics exhibit higher association between current returns and future earnings, indicating more information about future earnings in current stock returns. This supports Roll's first interpretation: higher firm‐specific return variation as a fraction of total variation signals more information‐laden stock prices and, therefore, more efficient stock markets.     

ON THE RATIONALITY OF COMMON STOCK RETURN VOLATILITY

This paper derives the relationship between the population unconditional variance of common stock returns and the variance of expected returns conditional on a well-specified information set. As a consequence, a lower bound is obtained for the variance of common stock returns. The sample counterpart of this bound is then empirically tested against the sample variance of returns. The paper's main conclusion can be stated as follows: the observed volatility of real (inflation-adjusted) common stock returns is not “irrationally” large. The paper admits of this conclusion because the point estimate of the lower-bound variance derived in this model is actually larger than the point estimate of common stock return volatility. However, since these point estimates are found to have a statistically insignificant difference, equality of the two variances cannot be ruled out. Hence, “rationality” of common stock returns—as implied by a utility-based valuation conditional on a specified information set—cannot be rejected.     

A nested factor model for non-linear dependencies in stock returns

The aim of our work is to propose a natural framework to account for all the empirically known properties of the multivariate distribution of stock returns. We define and study a ‘nested factor model’, where the linear factors part is standard, but where the log-volatility of the linear factors and of the residuals are themselves endowed with a factor structure and residuals. We propose a calibration procedure to estimate these log-vol factors and the residuals. We find that whereas the number of relevant linear factors is relatively large (10 or more), only two or three log-vol factors emerge in our analysis of the data. In fact, a minimal model where only one log-vol factor is considered is already very satisfactory, as it accurately reproduces the properties of bivariate copulas, in particular, the dependence of the medial point on the linear correlation coefficient, as reported in Chicheportiche and Bouchaud [Int. J. Theor. Appl. Finance, 2012, 15]. We have tested the ability of the model to predict out-of-sample the risk of non-linear portfolios, and found that it performs significantly better than other schemes.     

Hedging jump risk,expected returns and risk premia in jump-diffusion economies

This article presents a pure exchange economy that extends Rubinstein [Bell J. Econ. Manage. Sci., 1976, 7, 407–425] to show how the jump-diffusion option pricing model of Black and Scholes [J. Political Econ., 1973, 81, 637–654] and Merton [J. Financ. Econ., 1976, 4, 125–144] evolves in gamma jumping economies. From empirical analysis and theoretical study, both the aggregate consumption and the stock price are unknown in determining jumping times. By using the pricing kernel, we determine both the aggregate consumption jump time and the stock price jump time from the equilibrium interest rate and CCAPM (Consumption Capital Asset Pricing Model). Our general jump-diffusion option pricing model gives an explicit formula for how the jump process and the jump times alter the pricing. This innovation with predictable jump times enhances our analysis of the expected stock return in equilibrium and of hedging jump risks for jump-diffusion economies.     

Adaptive Learning in an Expectational Difference Equation with Several Lags: Selecting among Learnable REE

It is demonstrated that adaptive learning in the least squares sense may be incapable of satisfactorily reducing the number of attainable equilibria in a rational expectations model when focusing on the forward‐solutions to the model. The model examined, as an illustration, is a basic asset pricing model for exchange rate determination that is augmented with technical trading in the currency market in the form of moving averages since it is the most commonly used technique according to questionnaire surveys. The forward‐solutions to such a model are preferable to the backward‐solutions that are normally utilized since announcement effects is an important feature in currency trade. Because of technical trading in foreign exchange, the current exchange rate depends on j _max lags of the exchange rate, meaning that the model has j _max+1 rational expectations equilibria, where several of them are adaptively learnable in the least squares sense. However, since past exchange rates should not affect the current exchange rate when technical trading is absent, it is possible to single out a unique equilibrium among the adaptively learnable equilibria that is economically meaningful. It is worth noting that the model examined can also be viewed as a model for stock price determination in which the forward‐solutions to the model are preferable to the backward‐solutions since the importance of announcement effects is a common characteristic for currency and stock markets.     

Contrarian Profits and the Overreaction Hypothesis: the Case of the Athens Stock Exchange

This paper investigates the existence of contrarian profits and their sources for the Athens Stock Exchange (ASE). The empirical analysis decomposes contrarian profits to sources due to common factor reactions, overreaction to firm‐specific information, and profits not related to the previous two terms, as suggested by Jegadeesh and Titman (1995). Furthermore, in view of recent evidence that common stock returns are related to firm characteristics such as size and book‐to‐market equity, the paper decomposes contrarian profits to sources due to factors derived from the Fama and French (1993, 1996) three‐factor model. For the empirical testing, size‐sorted sub‐samples that are rebalanced annually are employed, and in addition, adjustments for thin and infrequent trading are made to the data. The results indicate that serial correlation is present in equity returns and that it leads to significant short‐run contrarian profits that persist even after we adjust for market frictions. Consistent with findings for the US market, contrarian profits decline as one moves from small stocks to large stocks, but only when market frictions are considered. Furthermore, the contribution to contrarian profits due to the overreaction to the firm‐specific component appears larger than the underreaction to the common factors.     

Book Assets,Real Estate,and Returns on Common Stock

Since real estate is common to most firms, this study examines whether there is a real estate factor in common stock returns that is not completely captured by existing asset pricing models. The three-factor model of Fama and French (1993), hereafter FF, is extended to incorporate a unique real estate factor. Using his extended-FF model, we examine the returns on 53 industry portfolios of common stocks over the 1972 through 1995 time period. The results indicate that a significant 19 percent of the industries are systematically related to the real estate factor. Most interestingly, we show that the loading of the real estate factor in common stock return is related to the loading of the book-to-market equity factor in these returns. We also construct decile portfolios of common stocks based on historical sensitivities of common stock returns to the real estate factor. The coefficients on the real estate factor vary systematically across the decile portfolios. The results of our analysis suggest that portfolio managers should manage their exposure to real estate.     

In search of distress risk in China's stock market

We examine the significance of size, book-to-market, and momentum factors in capturing financial distress risk in China's stock market. Consistent with the market underreaction hypothesis, we find that the momentum factor proxies for distress risk in China's stock market and that the explanatory power of momentum is subsumed when a distress factor is included in the asset pricing model. Our analysis demonstrates no evidence that size and book-to-market effects are driven by financial distress risk.¹     

Market Expectations in the Cross‐Section of Present Values

Returns and cash flow growth for the aggregate U.S. stock market are highly and robustly predictable. Using a single factor extracted from the cross‐section of book‐to‐market ratios, we find an out‐of‐sample return forecasting R² of 13% at the annual frequency (0.9% monthly). We document similar out‐of‐sample predictability for returns on value, size, momentum, and industry portfolios. We present a model linking aggregate market expectations to disaggregated valuation ratios in a latent factor system. Spreads in value portfolios’ exposures to economic shocks are key to identifying predictability and are consistent with duration‐based theories of the value premium.     

Stock returns and expected inflation: evidence from an asymmetric test specification

Previous studies that examined the relationship between stock returns and inflation have used a symmetric test specification, and have reported evidence of an inverse relation. We use an asymmetric model to re-examine this fundamental relationship between stock returns and inflation. We partition the study period into sub-samples of high and low inflation regimes. An inverse relation between stock returns and inflation forecasts is found during only low inflation periods, while a positive relation is detected through high inflation periods. In combination, results from both high and low inflation regimes suggest that stocks have delivered favorable inflation protection.      

A MODEL OF HETEROGENEOUS EXPECTATIONS AS A DETERMINANT OF SHORT SALES

This study examines the role of heterogeneous expectations as a determinant of short selling of common stock. A theoretical model demonstrates that the degree of heterogeneity of opinion and the number of investors in a market both positively influence short selling. This theory is substantiated empirically using ex-ante data. Short selling is related directly to merger activity and the presence of options.     

The Comovement of US and UK Stock Markets

US and UK stock returns are highly positively correlated over the period 1918–99. Using VAR‐based variance decompositions, we investigate the nature of this comovement. Excess return innovations are decomposed into news about future dividends, real interest rates, and excess returns. We find that the latter news component is the most important in explaining stock return volatility in both the USA and the UK and that stock return news is highly correlated across countries. This is evidence against Beltratti and Shiller's (1993) finding that the comovement of US and UK stock markets can be explained in terms of a simple present value model. We interpret the comovement as indicating that equity premia in the two countries are hit by common real shocks.     

American-style Indexed Executive Stock Options

This paper develops a new pricing model for American-style indexed executive stock options. We rely on a basic model framework and an indexation scheme first proposed by Johnson and Tian (2000a) in their analysis of European-style indexed options. Our derivation of the valuation formula represents an instructive example of the usefulness of the change-of-numeraire technique. In the paper's numerical section we implement the valuation formula and demonstrate that not only may the early exercise premium be significant but also that the delta of the American-style option is typically much larger than the delta of the otherwise identical (value-matched) European-style option. Vega is higher for indexed options than for conventional options but largely independent of whether the options are European- or American-style. This has important implications for the design of executive compensation contracts. We finally extend the analysis to cover the case where the option contracts are subject to delayed vesting. We show that for realistic parameter values, delayed vesting leads only to a moderate reduction in the value of the American-style indexed executive stock option.     

How many factors are important in U.K. stock returns?

I use the sequential approach of Harvey and Liu ([2018]. Lucky factors (Working Paper). Duke University) to build linear factor models in U.K. stock returns among a set of 13 candidate factors using individual stocks and three groups of test portfolios between July 1983 and December 2017. My study finds that the Market factor is the dominant factor in reducing mispricing in individual stocks and test portfolios regardless of the pricing error metric used. The Market factor has a bigger impact when using a value weighting pricing error metric. Whether a second factor is used or not depends upon which metric is used for mispricing and the time period examined. My study finds support for a two-factor model for the whole sample period of the Market factor and the Conservative Minus Aggressive (CMA) factor of Fama and French ([2015]. “A five-factor asset pricing model.” Journal of Financial Economics 116: 1–22) when giving greater weight to the mispricing of larger companies.     

Disclosing to Informed Traders

We develop a model in which a firm's manager can voluntarily disclose to privately informed investors. In equilibrium, the manager only discloses sufficiently favorable news. If the manager is known to be informed but disclosure is costly, the probability of disclosure increases with market liquidity and the stock trades at a discount relative to expected cash flows. However, when investors are uncertain about whether the manager is informed, disclosure can decrease with market liquidity and the stock can trade at a premium relative to expected cash flows. Moreover, contrary to common intuition, public information can crowd in more voluntary disclosure.     

Constructing a Multifactor Model for the Shanghai Stock Exchange

ABSTRACT

We examine the validity of five factor models for explaining the time-series and cross-sectional variations in stock returns in the Shanghai Stock Exchange. The factor models include four models proposed by previous literature. Moreover, we propose a four-factor model (comprising market, size, book-to-market, and sales-to-price factors) to explain variations of stock returns in the Shanghai Stock Exchange. The results show that the Shanghai stock market exhibits size, book-to-market, and sales-to-price effects. Both the adjusted coefficient of determination and regression model intercepts indicate that the proposed four-factor model explains variations of stock returns in the Shanghai Stock Exchange more effectively in comparison with other multifactor models.     

Sources of the stock price fluctuations in Chinese equity market

This paper proposes a latent factor approach based on a state–space framework in order to identify which factor, if any, dominates price fluctuations in the Chinese stock markets. We also illustrate the connection of such stock price decomposition with several general equilibrium asset pricing models and show that the decomposition results can potentially offer useful insights with regard to the empirical relevance of asset pricing models. We use quarterly data of the Chinese A-Share equity market over the period 1995Q3–2011Q1 and find that the estimates of the state–space model suggest that the expected return is the primary driving force behind price fluctuations in the Chinese stock market. We show that the time-varying expected returns appear to be counter-cyclical and this result seems to be consistent with the habit formation model of Campbell and Cochrane [1999. By force of habit: A consumption-based explanation of aggregate stock market behavior. Journal of Political Economy 107, no. 2: 205–51.]. However, we also note that there is a great deal of uncertainty with respect to this variance decomposition due to the resulting small signal-to-noise ratio in the estimated state–space model.