THIN TRADING AND THE ESTIMATION OF BETAS: THE EFFICACY OF ALTERNATIVE TECHNIQUES

Infrequent trading induces biased estimates of the beta risk coefficient. This paper reports on the efficacy of approaches that seek to correct for this bias and documents the extent of thin trading among New Zealand securities. Parameter estimates free of the thin-trading bias are obtained. These are compared with estimates obtained using ordinary least squares (OLS) applied in the conventional manner to nonsynchronous data, with and without bias-correcting procedures. OLS beta estimates are found to be less biased, more efficient, and as consistent when compared with Dimson or Scholes-Williams estimators. Lower beta estimates are associated with lower trading frequencies.     

Sources of gains to shareholders from bankruptcy resolution

Using a logistic regression model, we identify the characteristics of firms whose shareholders are likely to benefit from bankruptcy resolution. That is, winners (losers) are firms whose shareholders experience positive (negative) excess returns after bankruptcy filing. We find that winners are relatively smaller firms with higher proportions of convertible debt, tend to file for bankruptcy for strategic reasons, have low share-ownership concentration, and suffer comparatively larger pre-filing stock price declines. Among winners, shareholder returns are greater for firms that have higher levels of private debt and research and development (R&D) expenditures, and operate in more concentrated industries. In addition, our analysis indicates that an ex ante trading strategy of purchasing bankrupt stocks with a greater than 50% probability of being a winner on the day after bankruptcy filing and holding the stocks for a year, on an average, can generate average compounded and excess compounded holding-period returns of +71% and +42%, respectively.     

Trading activity around chapter 11 filing

This paper uses institutional ownership data and order flow information to document and explain equity trading patterns prior to chapter 11 bankruptcy filing.We provide a model that predicts trading activity prior to filing which results from a difference of opinion amongst different types of investors about whether the firm should be liquidated. We then test trading data to show that trading activity is elevated around chapter 11 filing as the model predicts. We show how institutional holdings change around filing and that chapter 7 firms appear relatively more attractive to institutional investors than emerging firms around filing.     

A hybrid bankruptcy prediction model with dynamic loadings on accounting-ratio-based and market-based information: A binary quantile regression approach

While using the binary quantile regression (BQR) model, we establish a hybrid bankruptcy prediction model with dynamic loadings for both the accounting-ratio-based and market-based information. Using the proposed model, we conduct an empirical study on a dataset comprising of default events during the period from 1996 to 2006. In this study, those firms experienced bankruptcy/liquidation events as defined by the Compustat database are classified as “defaulted” firms, whereas all other firms listed in the Fortune 500 with over a B-rating during the same time period are identified as “survived” firms. The empirical findings of this study are consistent with the following notions. The distance-to-default (DD) variable derived from the market-based model is statistically significant in explaining the observed default events, particularly of those firms with relatively poor credit quality (i.e., high credit risk). Conversely, the z-score obtained with the accounting-ratio-based approach is statistically significant in predicting bankruptcies of firms of relatively good credit quality (i.e., low credit risk). In-sample and out-of-sample bankruptcy prediction tests demonstrated the superior performance of utilizing dynamic loadings rather than constant loadings derived by the conventional logit model.     

Credit default swaps and debt specialization

We examine the effect of credit default swaps (CDSs) on debt specialization. We argue that reference firms in CDS contracts, seeking to minimize creditor conflicts and bankruptcy costs, exhibit higher debt concentration than firms on which no CDSs are traded. Our results show that firms engage in greater debt specialization and are more likely to specialize following the inception of CDS trading. Additionally, we find that, while lender concentration in firms increases, the number of bank lenders drops, lead arranger share rises, and the probability that lead arrangers and lenders are repeated increases following the onset of CDS trading. Our results are robust to instrumental variable estimation, propensity-score matching, different model specifications, and different subsamples.     

Nonsynchronous Security Trading and Market Index Autocorrelation

The theoretical portfolio autocorrelation due solely to nonsynchronous trading is estimated from a derived model. This estimated level is found to be substantially less than that observed empirically. The theoretical and empirical relationship between portfolio size and autocorrelation also is investigated. The results of this study suggest that other price-adjustment delay factors in addition to nonsynchronous trading cause the high autocorrelations present in daily returns on stock index portfolios.     

RANDOM WALK TESTS FOR LATIN AMERICAN EQUITY INDEXES AND INDIVIDUAL FIRMS

In this study we re-examine the presence of random walk in stock prices in Brazil and Mexico. We employ variance ratio tests on weekly stock returns for indexes as well as individual firms. The results reveal mean aversion in Mexico at both the index level and the firm level. In contrast, the Brazil indexes show a greater tendency toward random walk; however, the results for the individual firms suggest mean reversion. The results cannot be attributed to a firm size effect. Evidence is presented in favor of a greater degree of nonsynchronous trading for Brazilian securities than for Mexican securities.     

The Interaction of Solvency with Liquidity and its Association with Bankruptcy Emergence

Prior research has shown that accounting information available prior to a bankruptcy is associated with the likelihood of bankruptcy. We show that additionally, the accounting information available prior to bankruptcy is associated with whether or not a firm will emerge from bankruptcy. We predict that firms that exhibit low solvency risk and high liquidity risk are most likely to emerge from bankruptcy. Firms that exhibit high solvency risk and high liquidity risk are predicted to be least likely to emerge from bankruptcy. Cross–sectionally, our results support these predictions, but our findings differ across large and small firms.     

THE INFLUENCE OF ORGANIZED OPTIONS TRADING ON STOCK PRICE BEHAVIOR FOLLOWING LARGE ONE-DAY STOCK PRICE DECLINES

In this study I examine the effect of organized options trading on stock price behavior immediately following stock price declines of 10 percent or more. A matched-pair sample of National Market System option and nonoption firms are analyzed from June 1985 through December 1992. After controlling for the bid-ask bounce, firm size, share price, return standard deviation, and beta, I find that three-day cumulative abnormal returns for option firms are approximately 1.57 percent less than those for nonoption firms. Thus, options trading enhances stock market efficiency and/or liquidity. However, no profitable trading strategies are indicated.     

Can Language Predict Bankruptcy? The Explanatory Power of Tone in 10‐K Filings

We examine whether the language used in 10‐K filings reflects a firm's risk of bankruptcy. Our sample contains 424 bankrupt U.S. companies in the period 1994–2015 and we use propensity score matching to find healthy matches. Based on a logit model of failing and vital firms, our findings indicate that firms at risk of bankruptcy use significantly more negative words in their 10‐K filings than comparable vital companies. This relationship holds up until three years prior to the actual bankruptcy filing. With our investigation, we confirm the results from previous accounting and finance research. 10‐K filings contain valuable information beyond the reported financials. Additionally, we show that 10‐Ks filed in the year of a firm's collapse contain an increased number of litigious words relative to healthy businesses. This indicates that the management of failing firms is already dealing with legal issues when reporting financials prior to bankruptcy. Our results suggest that analysts ought to include the presentation of financials in their assessment of bankruptcy risk as it contains explanatory and predictive power beyond the financial ratios.     

An Adjustment Procedure for Predicting Betas When Thin Trading is Present: Canadian Evidence

We have incorporated effects of the process that generates true betas for TSE stocks, as well as thin trading effects, into the beta adjustment model. We note the Blume and Dimson and Marsh beta adjustment techniques aim at eliminating beta forecast error through regression tendency bias. Effects of other sources of forecast error have been ignored. We show the process generating security betas affects both cross-sectional correlation coefficient and order bias, while thin trading affects only cross-sectional correlation coefficient. We demonstrate that when OLS beta estimates are used to forecast their future risk levels, order bias accounts for 86% of forecast error, while thin trading effects account for 14% of forecast error. A beta regression tendency model which properly accounts for effects of cross-sectional correlation (which is a function of thin trading) and order bias completely abates forecast error. Our results have implications for the use of correlation coefficient to measure stability of betas across time, for beta adjustment models proposed in the literature, and for event study methodologies that rely on prediction errors.     

Covered interest arbitrage profits: The role of liquidity and credit risk

We study the profitability of Covered Interest Parity (CIP) arbitrage violations and their relationship with market liquidity and credit risk using a novel and unique dataset of tick-by-tick firm quotes for all financial instruments involved in the arbitrage strategy. The empirical analysis shows that positive CIP arbitrage deviations include a compensation for liquidity and credit risk. Once these risk premia are taken into account, small arbitrage profits only accrue to traders who are able to negotiate low trading costs. The results are robust to stale pricing and the nonsynchronous trading occurring in the markets involved in the arbitrage strategy.     

Empirical Analyses of Three Explanations for the Positive Autocorrelation of Short-Horizon Stock Index Returns

This paper provides empirical analyses of three explanations for the observed positive autocorrelation of short-horizon stock index returns, using NYSE/AMEX and NASDAQ data. Results indicate that index autocorrelation cannot be substantially explained by either autocorrelated, time-varying expected returns, or nonsynchronous trading. The third explanation for index autocorrelation, the nonsynchronous information transfer hypothesis, states that stocks incorporate market-wide information on a nonsynchronous basis due to information and transaction costs. Evidence from analyses of mean returns on various portfolios following large returns on the S 500 futures contract, as well as regressions of portfolio returns on current and lagged futures returns, support this explanation. Small (large) firms collectively require approximately 7 (1-2) weeks to fully incorporate new market information on average, and this delayed impoundment accounts for the bulk of the observed autocorrelation.     

Strategic Bankruptcies and Price Reactions to Bankruptcy Filings

This study investigates whether the stock market differentiates between firms that file bankruptcy petitions for strategic reasons and firms that file bankruptcy petitions for financial reasons. We perform both univariate and regression tests on a sample of 245 firms that filed Chapter 11 bankruptcy petitions between 1981 and 1996. After controlling for bankruptcy outcome, probability of bankruptcy, firm financial condition, and firm size, we find that, in the period around bankruptcy filing, firms that file bankruptcy petitions for financial reasons have significantly larger stock price declines than firms that file bankruptcy petitions for strategic reasons.     

Emerging from Bankruptcy with When‐Issued Trading

We examine the set of firms that emerged from Chapter 11 bankruptcy and traded on a when‐issued basis before their official return to the regular way in NASDAQ, Amex, or NYSE. We find that this when‐issued market is liquid and price efficient. The when‐issued closing price is a good indicator of the first closing price in the regular way market. Emerging firms that have when‐issued trading experience lower regular way volatility and smaller relative spreads than those without when‐issued trading. Our probit regressions show that firm size is an important determinant of the adoption of when‐issued trading.     

Can SRI funds better resist global financial crisis? Evidence from Japan

This paper compared Socially Responsible Investment (SRI) funds and conventional funds in the Japanese market with respect to the impact of the global financial crisis in 2008. Taking the bankruptcy of Lehman Brothers as a particular event, we estimated the average cumulative abnormal returns of both funds by event study methodology using a Fama–French three-factor model and EGARCH model. Our results suggest that SRI funds better resisted the bankruptcy of the Lehman Brothers than conventional funds. We also found that this result can be attributed to the existence of international funds, possibly because investors might evaluate the CSR activities of international firms more than those of domestic firms. Alternatively, it can be interpreted that the universe of domestic SRI funds is too limited to enjoy risk diversification.     

Corporate governance and stock returns in Asia

Despite years of study, the impact of firm-level governance on stock returns is not clear, especially in non-U.S. markets. We investigate the returns of governance-based trading strategies in Asia, using bias-free return data and CLSA governance ratings. We argue that poor governance should be associated with higher market risk. We find that a portfolio of poorly governed firms has a higher market beta, higher expected return and higher realized return, compared with a good governance portfolio. In contrast to some earlier studies, we find no abnormal returns after adjusting for risk and country effects. Only investors who can predict in advance which firms will improve their governance can earn abnormal returns.     

Predicting Bankruptcy Resolution

This study examines classification and prediction of the bankruptcy resolution event. Filing of bankruptcy is resolved through one of three alternative resolutions: acquisition, emergence or liquidation. Predicting the final bankruptcy resolution has not been examined in the prior accounting and finance literature. This post-bankruptcy classification and prediction of the final resolution is harder than discriminating between healthy and bankrupt firms because all filing firms are already in financial distress. Motivation for predicting the final resolution is developed and enhanced. A sample of 237 firms filing for bankruptcy is used. Classification and prediction accuracies are determined using a logit model. A ten-variable, three-group resolution logit model, which includes five accounting and five non-accounting variables is developed. The model correctly classifies 62 percent of the firms, significantly better than a random classification. We conclude that non-accounting data add relevant information to financial accounting data for predicting post bankruptcy resolution. Further, public policy implications for investors, researchers, bankruptcy judges, claimants and other stakeholders are discussed.     

On the Perils of Financial Intermediaries Setting Security Prices: The Mutual Fund Wild Card Option

Economic distortions can arise when financial claims trade at prices set by an intermediary rather than direct negotiation between principals. We demonstrate the problem in a specific context, the exchange of open-end mutual fund shares. Mutual funds typically set fund share price (NAV) using an algorithm that fails to account for nonsynchronous trading in the fund's underlying securities. This results in predictable changes in NAV, which lead to exploitable trading opportunities. A modification to the pricing algorithm that corrects for nonsynchronous trading eliminates much of the predictability. However, there are many other potential sources of distortion when intermediaries set prices.     

Effect of corporate tax avoidance activities on firm bankruptcy risk

Corporate tax avoidance has been shown to raise the cost of bank debt and lower credit and bond ratings. However, it is unclear whether tax avoidance actually increases a firm’s bankruptcy risk or whether it is just viewed negatively by banks and rating agencies. We find that firms engaging in tax avoidance and firms that are thinly capitalized face higher bankruptcy risk. To account for endogeneity and functional form misspecification, we verify our results using instrumental variable and propensity score matching methods. Our findings are consistent with the view that tax avoidance is a risk-enhancing activity.