Bear Market Research Articles

Bear Market Behavior of Institutional Investors in Sweden

Using a unique dataset of ownership structure for all stocks listed on the Stockholm Stock Exchange in Sweden, we examine different degrees of institutional holdings in Swedish firms during the bear market of 2000 to 2002. We find that examination by institutional investor domicile reveals that both Swedish and foreign institutions increase their equity holdings, although the increase by foreign institutions is proportionately higher, (individuals reduce their equity holdings). We find evidence that foreign and domestic institutional investors exhibit different preferences for excess returns and standard deviations in excess returns when we control for firm size; excess return is associated with changes in foreign institutional holdings while higher standard deviation in excess return is associated with the change in domestic institutional holdings. Both types of institutions are sensitive to liquidity and trading factors, causing portfolio realignment.

Budget for 2009 – Tax Increases in a Bear Market

In this note, the author provides details of the Budget for 2009. The most important changes are to net wealth tax, gift and inheritance tax, the exemption method in respect of the dividends and gains of corporate taxpayers and exit taxation. There are also changes to tonnage tax and the customs regime. Unless otherwise indicated, the changes apply from 1 January 2009.

Is There a Size Effect in the Pricing of Stocks in the Chinese Stock Markets?: The Case of Bull Versus Bear Markets

Size effect studies generally suggest that a return premium exists for small firms. While the size effect has mostly disappeared in recent years in mature markets (e.g., US and UK), it remains mostly strong in developing markets. The purpose of this paper is to examine the relationship between firm size and excess stock returns in the Chinese stock markets, and to examine this effect in both a bull and bear market. No studies have previously examined these relationships in the Chinese markets. The results of the study indicate that a size effect exists in the Chinese stock markets over the 6-year period from 1998 to 2003. We find small firms have significantly greater excess returns than large firms. Moreover, small firms are found to have a stronger reaction to the direction of the market than large firms. Small firms have significantly greater positive excess returns than large firms during the bull market. However, small firms have significantly greater negative returns (using total market value), or no significant difference in returns (using float market value) during the bear market period.

How to Make Money in a Bear Market: Learning from Options and Futures Traders

How to Make Money in a Bear Market: Learning from Options and Futures Traders

Prospective Earnings per Share

This report considers the relation between pro-forma and forecast consensus earnings per share (EPS) figures in terms of six measures identified, qualitatively, as good indicators for quality of earnings. These are, return on capital employed (RoCE), productive asset reinvestment ratio (PARR), cash realisation (CR), tax rate (TR), Standard and Poors (S&P) equity rating and S&P debt rating as identified by Merrill Lynch. The choices are thought to capture aspects of and differentiate between long term strategies and short term, non-sustainable earnings through financial engineering. Analyses are run on ten years of data from 1992 to 2001 for 131 S&P500 companies also provided by Merrill Lynch, using consensus EPS forecasts one year ahead. This sample is smaller than 500 because the index is subject to change, with companies being added and removed based on their market share or other factors. S&P debt ratings were not available over the entire sample length for all companies thus cutting the two ratings from analyses. However, correlations between the two S&P ratings and other indicator measures are found to be high so their removal is not a significant problem. The ten years are split into three phases based on market sentiment: 1992-1995 Bull market, emphasis on sustainable growth 1996-1999 Bull market, emphasis on high earnings per share (bubble) 2000-2001 Bear market, refocussing on sustainability. Given the radical change in conditions after 2000, the sample is enlarged for 2000 to 2001 and investigated separately. This increases sample size to 366, but does not change results significantly or give any further insights. The ability of the four indicator measures to connect EPS predictions to released figures appears weak in analyses. Adding lagged information and market proxies improves the situation, but unfortunately not sufficiently for linear regression to be used confidently for out-of-sample prediction. Given a sample of ten observations in time, non-linear regressions were not carried out. The indicator measures are not thought to be effective indicators of companies' future performance.

Ｂｏｘ‐Ｃｏｘ変換とオプション評価

The Box-Cox transformation, which is a basic method in time series analysis, is not so popular among researchers and practitioners in financial engineering. The well-known Black-Scholes model assumes that stock price exhibits geometric Brownian motion. In other words, log transformed return follows a generalized Wiener process. The log transformation is a special case of the Box-Cox transformation. The goal of this article is to present a valuation method for the option under the assumption that the Box-Cox transformed return process follows a generalized Wiener process. We also empirically examine the effect of the generalization from the log transformation to the Box-Cox transformation in both the stock process itself and the option price based on AIC. Our result indicates first that, in general, the Box-Cox transformation with optimal parameter is close to the log transformation in a continuing Bull market, while it is not in a Bear market. Second, the result for an equity process based on AIC is mostly reflected in the option price and AIC nearly captures precisely the difference in option prices with respect to the difference in equity process models. As a practical implication, our option pricing model assuming that the Box-Cox transformed return process follows a generalized Wiener process is able to capture the volatility skew phenomenon often observed in the option market.

Co-Movements of U.S. and Latin American Equity Markets in Bull and Bear Markets

ABSTRACT In this paper, we study the co-movements of the U.S., Argentine, Brazilian, Chilean, and Mexican equity markets during the October 12, 1998-March 24, 2000 bull market and the March 24, 2000-September 10, 2001 bear market. We find that these five markets are more closely correlated and, therefore, there is less diversification benefit to global investors during the bear market than during the bull market. Our findings, using rolling correlation analysis, indicate that the most volatile U.S. correlation coefficient is with Chile, both in the bull market and in the bear market. The U.S. correlation coefficient with Mexico is more stable (i.e., more predictable) during the bull market than during the bear market. However, the U.S. correlation coefficients with Argentina and Chile are less stable (i.e., less predictable) during the bull market than during the bear market. The degree of stability (i.e., predictability) of the U.S.-Brazilian correlation coefficient is about the same, both in the bull ma...

Are the Gains from International Portfolio Diversification Exaggerated? The Influence of Downside Risk in Bear Markets

Are the Gains from International Portfolio Diversification Exaggerated? The Influence of Downside Risk in Bear Markets

Stability of Alphas and Betas over Bull and Bear Markets: An Empirical Examination

This paper examines the influence of bull and bear markets on the stability of alpha and beta for the single index market model. The data for the study is collected for the period March 01, 1996 to March 31, 2001. The data pertains to the adjusted daily closing prices of 74 scrips that form a part of BSE-100 index. Two definitions of bull and bear markets are used. The analysis is carried out by estimating dummy variable regression, conducting a joint test (F-test) on alphas and betas, test for correlation coefficient and the paired t-test. The results indicate that alpha varies over both definitions of bull and bear market conditions whereas beta varies for one definition and is stable for the other. The variability of beta also dependents upon specific industry groups. However, one should take large samples from each industry group to draw any generalizations. The implications of the results for a portfolio manager are explained. It is also observed that the stability of alpha and beta depends upon the choice of bull and bear market conditions.

The Asymmetric Relation between Initial Margin Requirements and Stock Market Volatility across Bull and Bear Markets

The Asymmetric Relation between Initial Margin Requirements and Stock Market Volatility across Bull and Bear Markets

Investment blunders (of the rich and famous) ... and what you can learn from them

Preface. Acknowledgments. 1. Other People's Problems. Do-It-Yourself Investing. Investor Performance. Effect of a Blunder. Endnotes. I. SELF-INFLICTED COMMON PROBLEMS. 2. Behavioral Finance. Your Psychological Biases. Emotions. Simplification. The Investment Environment. Summary. Endnotes. 3. Patterns and Predictions. Gambler's Fallacy. Streaks. Investors and Trends. From Dogs to Fools. Mining Fool's Gold. High-Tech Data Mining. Foresight and Hindsight. Summary. Endnotes. 4. Mood, Optimism, and Investing. Moods and Expectations. Sunshine. The Bias of Optimism. Optimism, Exuberance, And Blunders. Rampant Optimism and Pessimism. Summary. Endnotes. 5. Profits from the Prophets? Analysts. The Biases of Analysts. Dartboard. Barron's Annual Roundtable. Value Line. Newsletters. Insiders. Economists. Summary. Endnotes. 6. Foolish Risks. The Right Risks. Fall of a Titan. Your 401(k) Plan. Active Risk Management. How Much Diversification? Picking Portfolios. Endnotes. II. TRYING TO BEAT THE MARKET. 7. Timing the Market. All Types of Market Timing. Tools of the Trade. Professional Timing. The Timing Newsletter. Timing in Bull and Bear Markets. Individual Investors and Market. Timing. Market Timing and Risk. Summary. Endnotes. 8. Mutual Funds: Performance. Mutual Fund Managers are Superior. Investors. Mutual Fund Investors Underperform the Market. Paradox Resolved. Do Winners Repeat? Mutual Fund Ads. Chasing Winners. Tournaments and Temptations. Star Power. Summary. Endnotes. 9. Mutual Funds: Carrying the Load. Mutual Fund Fees. LOADING UP. QUID PRO QUO. A FEE BY ANY OTHER NAME. What Mutual Funds Give, the Tax Man Takes Away. Out of Sight and Out of Mind. Endnotes. 10. The Social Investor. The Friends You Keep. Being Social. Talking Stocks. Investment Analysis. Media. Summary. Endnotes. 11. Get Rich Quick. The Pyramid. A Pyramid in Albania. The Caritas Pyramid in Romania. A Pyramid in Russia. Pyramids in the United States. Gifting As A Pyramid. The Internet, an Effective Pyramid Medium. Summary. Endnotes. III. COLOSSAL BLUNDERS. 12. The Eggheads Crack. In the Beginning. The Hedged Bet. The Hedge Fund. Long-Term Capital Management. LTCM'S TRADING. Leverage. Overconfidence. Imitation May Be Flattering, Butu. The Beginning of the End. The Fear Of A Crisis. Summary. Endnotes. 13. An Orange Squeezed. The Rise of Robert Citron. Citron In Demand. The Repo Man. The Economy Changes. The Squeeze. A Rescue? The Aftermath. Summary. Endnotes. 14. Betting the Bank. Barings Bank. Nicholas Leeson. Arbitrage and Futures Contracts. An Error in Singapore. DoubleuOr Double Again. Margin Calls. The Shake Down. Toshihide Iguchi and Daiwa Bank. Kent Ahrens and First Capital. Joseph Jett and Kidder Peabody. Summary. Endnotes. 15. Investing to Win and Avoid the Blunders. Getting on the Right Track. Financial Goals. (Your Destination). Investment Return. Asset Allocation. Implementation. Index Mutual Funds. Indexing With Exchange. Traded Funds. Implementation in the Real World. Continuing Process. Summary. Endnotes. Appendix. Index.

Comparing Bear Markets - 1973 and 2000

In nominal terms, the fall in global share prices since 1999/2000 bears a close resemblance to that experienced worldwide in the years following 1972/3. This article seeks to compare the two periods of market weakness in the G-7 countries in terms not only of share prices but also focusing on macroeconomic trends, financial market developments, sectoral patterns of shareholding and potential wider economic consequences of falling share prices. It is shown that the earlier period was much more severe in terms of adverse economic developments, in particular high inflation. But the current situation also presents some risks, in particular a disruptive correction of US sectoral imbalances.

Major Stock Market Linkages in the 2000–2001 Bear Market

This study of the co-movements of the U.S., Japanese, U.K., German, and French stock markets during the March 27, 2000-April 4, 2001, bear market indicates that the five stock markets were highly correlated, and diversification benefits to U.S. investors with these markets were quite limited during the bear market period. Low correlations among the world9s equity markets are often presented as evidence in support of portfolio gains to investors from international diversification. These findings indicate that investments in other major stock markets provide little or no diversification benefit to U.S. investors in a severe bear market, when diversification protection is needed the most. Comparisons of the March 2, 1999-March 26, 2000, bull market period and temporary up- and downswings in bull or bear markets confirm the point.

The Asymmetric Relation Between Initial Margin Requirements and Stock Market Volatility Across Bull and Bear Markets

Higher initial margin requirements are associated with lower subsequent stock market volatility during normal and bull periods, but show no relationship during bear periods. Higher margins are also negatively related to the conditional mean of stock returns, apparently because they reduce systemic risk. We conclude that a prudential rule for setting margins (or other regulatory restrictions) is to lower them in sharply declining markets in order to enhance liquidity and avoid a depyramiding effect in stock prices, but subsequently raise them and keep them at the higher level in order to prevent a future pyramiding effect.

Hedge Fund and Commodity Fund Investments in Bull and Bear Markets

Hedge Fund and Commodity Fund Investments in Bull and Bear Markets

Increased Correlation in Bear Markets

A number of studies have provided evidence of increased correlations in global financial market returns during bear markets. Other studies, however, have shown that some of this evidence may be biased. We derive an alternative to previous estimators for implied correlation that is based on measures of portfolio downside risk and that does not suffer from bias. The unbiased quantile correlation estimates are directly applicable to portfolio optimization and to risk management techniques in general. This simple and practical method captures the increasing correlation in extreme market conditions while providing a pragmatic approach to understanding correlation structure in multivariate return distributions. Based on data for international equity markets, we found evidence of significant increased correlation in international equity returns in bear markets. This finding proves the importance of providing a tail-adjusted mean–variance covariance matrix.

Are Older Workers Responding to the Bear Market?

In the past year, as the economy has weakened and unemployment has risen, the labor force participation rate for older workers (aged 55-64) has jumped by 2.0 percentage points - an increase unprecedented in post-war U.S. economic history. Recessions typically see very slow or even negative growth in labor force participation. A likely factor contributing to this dramatic change is the steep decline in the stock market that has occurred since the spring of 2000. Plunging stock portfolios may have caused some older workers to postpone retirement and convinced some early retirees to rejoin the labor force.

On Ignorance, Intuition, and Investing: A Bear Market Test of the Recognition Heuristic

This study replicates recent tests of the recognition heuristic as a device for selecting stock portfolios. The heuristic represents a lower limit to the search for information, since simple name recognition is the least one can know about anything. Gigerenzer and others conducted original experiments in this field at the Max Planck Institute for Psychological Research's Center for Adaptive Behavior and Cognition (the "ABC Research Group"). The ABC Group's tests support the use of the heuristic in a bull market environment. This study, conducted in a down market, reaches a different conclusion: Not only can a high degree of company name recognition lead to disappointing investment results in a bear market, it can also be beat by pure ignorance. Virtually the only finding of the ABC Group's study that we match here is that Americans are not very good at picking American stocks to outperform the market.

Hedge Fund and Commodity Fund Investments in Bull and Bear Markets

A primary motivation for investing in hedge funds and commodity funds is to diversify against falling stock prices. The authors evaluate the performance of 16 different such funds during rising and falling stock markets between 1990 and 1998 both as stand–alone assets and as portfolio assets. They use the Sharpe ratio and alternative safety–first criteria to evaluate performance. The conclusion is that commodity funds generally provide more downside protection than hedge funds. Commodity funds have higher returns in bear markets than hedge funds, and generally have an inverse correlation with stock returns in bear markets. Hedge funds typically exhibit a higher positive correlation with stock returns in bear markets than in bull markets. Three hedge fund styles—market–neutral, event–driven, and global macro—provide fairly good downside protection with more attractive returns over all markets than commodity funds.

Hedge Funds and Commodity Fund Investments in Bull and Bear Markets

This study examines the performance of sixteen different hedge fund and commodity fund investment styles during rising and falling stock prices over the period 1990:01 through 1998:08. Since a primary motivation for investing in hedge funds and commodity funds is to diversify against falling stock prices, it is important to examine the performance of these funds during bear stock markets. The study evaluates hedge funds and commodity funds both as stand-alone assets and as portfolio assets, and in both bull and bear stock markets. In addition, it utilizes the Sharpe ratio as well as alternative safety-first performance criteria to evaluate the funds. We conclude that commodity funds generally provide greater downside protection than do hedge funds. Commodity funds have higher returns in bear markets than do hedge funds, and generally have an inverse correlation with stock returns in bear markets, while hedge funds typically exhibit a higher positive correlation with stock returns in bear markets than in bull markets. However, three hedge fund styles - market-neutral, event-driven, and global macro - provide fairly good downside protection while still providing more attractive returns over all markets than do commodity funds.