High-risk Stocks Research Articles

Is Default Risk Negatively Related to Stock Returns?

We find a positive cross-sectional relationship between expected stock returns and default risk, contrary to the negative relationship estimated by prior studies. Whereas prior studies use noisy ex post realized returns to estimate expected returns, we use ex ante estimates based on the implied cost of capital. The results suggest that investors expected higher returns for bearing default risk, but they were negatively surprised by lower-than-expected returns on high default risk stocks in the 1980s. We also extend the sample compared to prior studies, and find that the evidence based on realized returns is considerably weaker in the 1952-1980 period.

Systematic Risk and the Performance of Mutual Funds Pursuing Momentum and Contrarian Trades

We examine mutual fund trading activity to determine whether they rebalance their portfolios towards stocks that were recent superior performers (a momentum strategy) or towards stocks that recently underperformed (a contrarian strategy). Using 2,829 funds with 49,661 fund-periods between 1991 and 2005, we find that around 15% of the funds exhibit contrarian trading behavior with a similar percentage following a momentum strategy. We highlight the importance of a stock’s risk to traders adopting momentum and contrarian strategies. Mutual funds that follow a momentum strategy and acquire high-risk stocks improve their performance, while those following a contrarian strategy in these stocks diminish their performance. Both contrarian and momentum trading behavior by funds persists.

Bankruptcy Risk and the Value Premium in Australia

We develop a model to predict bankruptcy for the largest listed companies in Australia using both accounting ratios and market data. The model has high prediction accuracy, with 70-90% of bankruptcy predictions being correct. We show that high risk (of bankruptcy) stocks do not typically deliver a higher return than low risk stocks. In fact, the penalty for holding risk is highest both in portfolios of small stocks and deep value stocks. We also show that value does not consistently increase as bankruptcy risk increases, whether value is measured in terms of book-to-price or earnings-to-price. Also, bankruptcy risk is shown to be higher in low value portfolios than high value portfolios. Adding a factor that directly measures aggregate distress to a 4-factor model, the loading on the value factor remains statistically significant, implying that the value factor contains substantially more than just distress-related information. Our results provide out-of-sample support for studies showing the value factor is not a proxy for distress risk in the US market.

Daily short interest, idiosyncratic risk, and stock returns

This paper examines the relation between short selling and returns and the impact of arbitrage costs on short sellers’ behavior. Using daily UK short selling data, we find that stocks with low short interest levels experience significant positive returns on both an equal- and value-weighted basis. Economic theory predicts that short sellers avoid establishing positions in stocks with high idiosyncratic risk. Our results indicate a negative relation between short interest and returns among high idiosyncratic risk stocks and that short selling activity is mostly concentrated in low idiosyncratic risk stocks where it is less costly to arbitrage fundamental risk.

Which past returns affect trading volume?

Anecdotal evidence suggests and recent theoretical models argue that past stock returns affect subsequent stock trading volume. We study 3,000 individual investors over a 51 month period to test this apparent link between past returns and volume using several different panel regression models (linear panel regressions, negative binomial panel regressions, Tobit panel regressions). We find that both past market returns as well as past portfolio returns affect trading activity of individual investors (as measured by stock portfolio turnover, the number of stock transactions, and the propensity to trade stocks in a given month). After high portfolio returns, investors buy high risk stocks and reduce the number of stocks in their portfolio. High past market returns do not lead to higher risk taking or underdiversification. We argue that the only explanations for our findings are overconfidence theories based on biased self-attribution and differences of opinion explanations for high levels of trading activity.

Daily Short Interest, Idiosyncratic Risk, and Stock Returns

This paper examines the relation between short selling and returns and the impact of arbitrage costs on short sellers' behavior. Using daily UK short selling data, we find that stocks with low short interest levels experience significant positive returns on both an equal- and value-weighted basis. Economic theory predicts that short sellers avoid establishing positions in stocks with high idiosyncratic risk. Our results indicate a negative relation between short interest and returns among high idiosyncratic risk stocks and that short selling activity is mostly concentrated in low idiosyncratic risk stocks where it is less costly to arbitrage fundamental risk.

Financial Distress and Idiosyncratic Volatility: An Empirical Investigation

We address the twin puzzles of anomalously low returns for high idiosyncratic volatility and high distress risk stocks, documented by Ang, Hodrick, Xing and Zhang (2006) and Campbell, Hilscher and Szilagyi (2005), respectively. We accomplish two objectives in this study. First, we investigate the link between idiosyncratic volatility and distress risk and find that the idiosyncratic volatility effect exists only conditionally on high distress risk. Second, using a corrected single-beta CAPM model, we provide a rational explanation for the twin puzzles. Joint statistical tests cannot reject the null hypothesis of zero abnormal returns across the idiosyncratic volatility and distress risk portfolios, for the corrected model.

The Relation between Liquidity Risk and Default Risk in Equity Returns

This paper demonstrates the relative importance of default and liquidity risks in equity returns. While previous studies have shown that both default and liquidity risks affect equity returns, none, to our knowledge, has examined their interrelation and relative importance for equity returns. We consider three alternative liquidity measures: the Pastor-Stambaugh measure, the turnover measure, and the illiquidity ratio measure. The default measure of choice is the one based on Merton's (1974) contingent claims approach. The alternative liquidity measures are very different from each other, but they are all related to our default measure. While we know from past research that low liquidity stocks earn higher returns than high liquidity stocks, we demonstrate here that this is the case only when these stocks also have high default risk, and in no other case. In contrast, high default risk stocks always earn higher returns than low default risk stocks, independently of their liquidity level. Vector autoregressive tests reveal the existence of a two-way causal relation between default risk and stock market returns, which is not present in the case of liquidity. Liquidity risk does not affect the future path of stock market returns. The robustness of these relations remains unaltered when we take into account the correlation of the default and liquidity measures with aggregate stock market volatility. Consistent with previous evidence, the inclusion of default and liquidity variables in popular asset pricing specifications improves a model's performance. However, the improvement is much larger when the included variable is default, rather than liquidity. In the presence of the default variable, the inclusion of a liquidity proxy in an asset pricing specification results in only a marginal improvement of the model's performance. The opposite is not true.

What works on Wall Street: a guide to the best-performing investment strategies of all time

This title offers long-term strategies that have always beaten the markets, and how to make them work for you. Works on Wall Third Edition, cuts straight to the chase, examining actual historic performance figures to tell you which strategies have provided investors with the best returns, which should be avoided at all costs, and why. Comprehensively updated from its bestselling second edition, this investor classic goes beyond hype and rumor to focus on actual results, and tell you what smart investors are doing now. 'O'Shaughnessy's conclusion that some strategies do produce consistently strong results while others underperform could shake up the investment business' - Barron's. Works on Wall is indisputably a major contribution to empirical research on the behavior of common stocks in the United States! Conceivably, the influence of Works on Wall will prove immense' - Financial Analysts' Journal.'O'Shaughnessy's latest, Works on Wall Street, is a serious inquiry into the investment strategies that stand up under long-term scrutiny and is refreshing research for every investor' - Stocks and Commodities. 'O'Shaughnessy's study is already making waves in the investment community! Could well become a classic' - Smart Money. 'James O'Shaughnessy has enshrined P/S in the investing hall of fame in his superb new book, Works on Wall Street' - James K. Glassman, Washington Post. 'What investment strategies have worked over the last 40 years? Ask this man' - Barron's.For many investors, the stock market is little more than a guessing game. The stock market bubble of the late 1990s had many investors convinced that the rules of the game had changed and that this time, it really was different. Works on Wall Third Edition - with all new data through 2003 - shows that it's never different this time. Armed with earlier editions of this book, investors would have avoided the devastation visited on the high risk stocks that were the favorites of investors during the bubble. Works on Wall Third Edition, takes the guesswork out of your investment decision-making. This in-depth, updated and data-driven book looks at key strategies and benchmarks that millions of investors rely on to make their investment decisions, and tells you which of these tools have provided investors with the best long-term results.Acclaimed author and portfolio manager James P. O'Shaughnessy presents factual, unbiased and unexpected findings that prove you can do vastly better than the market simply by consistently using stock selection strategies that have withstood the test of time. Moreover, these five decades of results warn investors to steer clear of some popular investment strategies that are toxic to your wealth. Expanded to include how various investment strategies perform when used on All Stocks, Large Stocks, Market Leaders and Small Stocks, this new edition of the book also covers all the new research O'Shaughnessy has conducted since the last edition.Which investment strategies are winners - and which are losers? What factors most reliably indicate that a stock will rise or fall? Are value strategies better than growth? Do small capitalization stocks do better than large? What's the worst-case scenario for the various investment strategies and how long did it take for them to recover? Do these strategies work outside the United States?What Works on Wall answers these questions and outlines a methodical, scientific, and results-based method for making intelligent stock market decisions. 'To make the best investment plans for the future, investors need access to unbiased, long-term performance results,' O'Shaughnessy writes. And that is exactly what he gives you in this history-making book. James P. O'Shaughnessy is the Director of Systematic Equity for Bear Stearns Asset Management and a Senior Managing Director of the firm. O'Shaughnessy's investment strategies have been featured in Wall Street Journal, Barron's, New York Times, Washington Post, Investor's Business Daily, Financial Times, London's Daily Mail, Japan's Nikkei Shimbun Daily, and many other publications worldwide, as well as on NBC's Today Show, Oprah Winfrey Show, CNBC and CNN.

Size Effect and Default Risk in the UK

The basic results of Vassalou and Xing (J.Finance 2004) held in the UK over the period 1970-1989: high default risk companies earned a substantial premium, this is concentrated among small stocks, conversely the size effect appears primarily among high default risk stocks and the impact of changes in default risk on returns is short lived. Nevertheless, after 1990 this default risk premium has disappeared, along with the size effect. In addition, even over the 1970-1989 period, tests that go beyond those of Vassalou and Xing suggest important differences between high default risk and small stocks: most importantly, high default risk stocks underperform in risky environments whereas small stocks outperform. Finally, changes in measured default risk seem to be driven mainly by known effects like short-term reversal.

An Asset Allocation Sub-Puzzle

This paper documents a sub-puzzle in asset allocation. Canner, Mankiw and Weil (1997) point out that empirically the ratio of bond to stock holdings of a typical investor varies with her risk-averse attitude. This observation directly challenges the well-known mutual fund separation theorem of Tobin (1958) and Markowitz (1952). This paper reports additional evidence on investor's portfolio choice, finding that not only does the bonds to stocks ratio change, but within the stock portfolio, the ratio of high-risk stocks to low-risk stocks also changes with an investor's risk tolerance. This finding is important because most current literature attempts to solve the asset allocation puzzle by applying different interest rate models. Our finding shows that the puzzle involves more than just about interest rates, and needs a more fundamental examination from the perspective of an investors' risk attitude. Drawing on the loss aversion literature, we propose a general model that can solve both the Canner-Mankiw-Weil puzzle and the sub-puzzle. The key is that investors are loss averse and care about their expected worst-case returns. When an expected worst-return constraint is added to investors' utility maximization, the optimal ratio of low-risk to high-risk assets, be it bonds to stocks or low-risk stocks to high-risk stocks, changes with investors' risk attitudes.

Session Topic: Individual Investors and Mutual Funds

Summary. The modern theory of finance suggests that most investors should put part or all of their money into a “market portfolio” mixed with borrowing or lending. Empirical evidence generally supports the theory, but there are some unanswered questions about the composition of the best market portfolio, about the apparent attractiveness of low risk stocks relative to high risk stocks, and about ways of minimizing transaction costs. Attempts to create a fund based on these principles and to make it available to a large number of investors have uncovered some important problems. Legal costs due to government regulation, the costs of managing a fund, and especially the costs of selling it are all much higher than one might expect. Despite these problems, efforts to create such funds seem destined for eventual success.

A NOTE ON THE RETURN BEHAVIOR OF HIGH RISK COMMON STOCKS

The Journal of FinanceVolume 29, Issue 1 p. 199-202 Article A NOTE ON THE RETURN BEHAVIOR OF HIGH RISK COMMON STOCKS Richard W. McEnally, Richard W. McEnallyUniversity of Texas at Austin.Search for more papers by this author Richard W. McEnally, Richard W. McEnallyUniversity of Texas at Austin.Search for more papers by this author First published: March 1974 https://doi.org/10.1111/j.1540-6261.1974.tb00035.xCitations: 18 Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Citing Literature Volume29, Issue1March 1974Pages 199-202 RelatedInformation