Financial Statement Analysis of Leverage and How It Informs About Profitability and Price-to-Book Ratios

This paper presents a financial statement analysis that distinguishes leverage that arises in financing activities from leverage that arises in operations. The analysis yields two leveraging equations, one for borrowing to finance operations and one for borrowing in the course of operations. These leveraging equations describe how the two types of leverage affect book rates of return on equity. An empirical analysis shows that the financial statement analysis explains cross-sectional differences in current and future rates of return as well as price-to-book ratios, which are based on expected rates of return on equity. The paper therefore concludes that balance sheet line items for operating liabilities are priced differently than those dealing with financing liabilities. Accordingly, financial statement analysis that distinguishes the two types of liabilities informs on future profitability and aids in the evaluation of appropriate price-to-book ratios.     

Ranking Investments Using the Lorenz Curve

Journal of Quantitative Economics - Ranking investments is important for measuring the performance of financial assets over a period of time. The Mean-Variance Model (MV Model) suggests the...     

How to Evaluate Risk Management Units in Financial Institutions?

Based on the existing Enterprise Risk Management framework and current government regulations, “banks are required to establish risk management units (RMUs) to review and evaluate their risks, monitor them, and to advise top management.” Currently an integral part of the risk governance and management process, RMUs in financial institutions have become increasingly important since the 2007–2008 financial crisis. This article details the authors' creation of an index to evaluate the performance of risk management units in financial institutions, and then examines some of their findings. The index transforms twelve parameters into a simple and convenient index that isolates the RMU's activities from the rest of the organizational risk management process, its risk preferences and the activities of the rest of the units. The index's parameters are divided into three dimensions of the RMU's performance: professionalism, organizational status and relationship with top management and the board. The authors found a positive relationship between their RMUI and some important risk governance characteristics: CROs who are among the five highest paid executives at the bank, banks with at least one independent director serving on the board's risk committee having banking and finance experience and boards with greater efficacy.     

The Association between Changes in Interest Rates,Earnings, and Equity Values*

Numerous studies have documented that stock returns are negatively related to changes in interest rates, but there has been little corroborating research on the information in interest‐rate changes about the fundamentals that the stock market prices. The negative correlation is often attributed to changes in the discount rate, a denominator effect in a valuation model. However, there may also be a numerator effect on the expected payoffs that are discounted. This paper shows that changes in interest rates are positively related to subsequent earnings, but the change in earnings is typically not large enough to cover the change in the required return. Hence, the net (numerator and denominator) effect on equity value is negative, consistent with the results of the research on interest rates and stock returns.     

Predicting stock returns

This paper studies whether incorporating business cycle predictors benefits a real time optimizing investor who must allocate funds across 3,123 NYSE-AMEX stocks and cash. Realized returns are positive when adjusted by the Fama-French and momentum factors as well as by the size, book-to-market, and past return characteristics. The investor optimally holds small-cap, growth, and momentum stocks and loads less (more) heavily on momentum (small-cap) stocks during recessions. Returns on individual stocks are predictable out-of-sample due to alpha variation, whereas the equity premium predictability, the major focus of previous work, is questionable.     

The Persistence of the Accruals Anomaly*

The accruals anomaly — the negative relationship between accounting accruals and subsequent stock returns — has been well documented in the academic and practitioner literatures for almost a decade. To the extent that this anomaly represents market inefficiency, one would expect sophisticated investors to learn about it and arbitrage the anomaly away. We show that the accruals anomaly still persists and, even more strikingly, its magnitude has not declined over time. How can this be explained? We show that the accruals anomaly is recognized and, indeed, exploited by certain active institutional investors, but the magnitude of this accruals-related trading is rather small. By and large, institutions shy away from extreme-accruals firms because their attributes, such as small size, low profitability, and high risk stand in stark contrast to those preferred by most institutions. Individual investors are also, by and large, unable to profit from trading on accruals information due to the high information and transaction costs associated with implementing a consistently profitable accruals strategy. Consequently, the accruals anomaly persists and will probably endure.     

Asset Pricing Models and Financial Market Anomalies

This article develops a framework that applies to single securitiesto test whether asset pricing models can explain the size, value,and momentum anomalies. Stock level beta is allowed to varywith firm-level size and book-to-market as well as with macroeconomicvariables. With constant beta, none of the models examined captureany of the market anomalies. When beta is allowed to vary, thesize and value effects are often explained, but the explanatorypower of past return remains robust. The past return effectis captured by model mispricing that varies with macroeconomicvariables.     

Managerial discretion and the economic determinants of the disclosed volatility parameter for valuing ESOs

This study investigates the determinants of the expected stock-price volatility assumption that firms use in estimating ESO values and thus option expense. We find that, consistent with the guidance of FAS 123, firms use both historical and implied volatility in deriving the expected volatility parameter. We also find, however, that the importance of each of the two variables in explaining disclosed volatility relates inversely to their values, which results in a reduction in expected volatility and thus option value. This can be interpreted as managers opportunistically use the discretion in estimating expected volatility afforded by FAS 123. Consistent with this, we find that managerial incentives or ability to understate option value play a key role in this behavior. Since discretion in estimating expected volatility is common to both FAS 123 and 123(R), our analysis has important implications for market participants as well as regulators.

On the Interaction of Risk and Time Preferences: An Experimental Study

Experimental studies of risk and time preference typically focus on one of the two phenomena. The goal of this paper is to investigate the (possible) correlation between subjects' attitude to risk and their time preference. For this sake we ask 61 subjects to price a simple lottery in three different scenarios. At the first, the lottery premium is paid 'now'. At the second, it is paid 'later'. At the third, it is paid 'even later'. By comparing the certainty equivalents offered by the subjects for the three lotteries, we test how time and risk preferences are interrelated. Since the time interval between 'now' and 'later' is the same as between 'later' and 'even later', we also test the hypothesis of hyperbolic discounting. The main result is a statistically significant negative correlation between subjects' degrees of risk aversion and their (implicit) discount factors. Moreover, we show that the negative correlation is independent of the method used to elicit certainty equivalents (willingness to pay versus willingness to accept).     

Dispersion in analysts’ earnings forecasts and credit rating

This paper shows that the puzzling negative cross-sectional relation between dispersion in analysts’ earnings forecasts and future stock returns may be explained by financial distress, as proxied by credit rating downgrades. Focusing on a sample of firms rated by Standard & Poor's (S&P), we show that the profitability of dispersion-based trading strategies concentrates in a small number of the worst-rated firms and is significant only during periods of deteriorating credit conditions. In such periods, the negative dispersion–return relation emerges as low-rated firms experience substantial price drop along with considerable increase in forecast dispersion. Moreover, even for this small universe of worst-rated firms, the dispersion–return relation is non-existent when either the dispersion measure or return is adjusted by credit risk. The results are robust to previously proposed explanations for the dispersion effect such as short-sale constraints and leverage.