Bear Market Research Articles

CORRELATION OF THE PORTUGUESE STOCK MARKET WITH MAJOR GLOBAL CAPITAL MARKETS

In this paper, we will analyse the increase of correlations in the market during periods of crisis, given its importance to the management and optimization of the portfolio, and especially for risk diversification in portfolio management. An evaluation of the level of correlation between the stock markets is important for several reasons. First, it enables to evaluate changes in the patterns of correlation, and thus to make the proper adjustments in portfolios’ investment. Second, policy makers are also interested in these correlations because of its implications for the stability of the financial system.
 The correlation coefficients are biased measures of dependence when markets become more volatile. This paper explores the correlation of the Portuguese capital markets with the Asian, American, European and Latin American Spanish stock markets. To this end, we used the PSI-20 index, Nikkei 225, NASDAQ, S&P 500, Euronext 100 and Ibex-35. Our analysis results show that the correlation does exist as a phenomenon during financial crises (Bear Market), reducing the benefits of portfolio diversification when most needed. Moreover, we believe that correlations have increased between the markets in recent years.

Performance of Dividend Exchange-Traded Funds during Bull and Bear Markets

This study investigates the performance of dividend exchange-traded funds (ETFs) during both bull and bear markets. The authors compare their performance to a proxy for the U.S. market as measured by the SP the portfolio marginally outperformed IVV during two bull markets (January 2004 to September 2007 and April 2009 to December 2014), but it also marginally underperformed IVV during the most recent bear market (October 2007 to March 2009), which means that dividend ETFs are more volatile than IVV. The sample period is limited because the first dividend ETF was created in late 2003. Investors in dividend ETFs, who were expecting to receive superior returns during volatile markets, would not have achieved the results that they anticipated.

Simple New Method to Predict Bear Markets (The Entropic Linkage between Equity and Bond Market Dynamics)

An alternative derivation of the yield curve based on entropy or the loss of information as it is communicated through time is introduced. Given this focus on entropy growth in communication the Shannon entropy will be utilized. Additionally, Shannon entropy’s close relationship to the Kullback–Leibler divergence is used to provide a more precise understanding of this new yield curve. The derivation of the entropic yield curve is completed with the use of the Burnashev reliability function which serves as a weighting between the true and error distributions. The deep connections between the entropic yield curve and the popular Nelson–Siegel specification are also examined. Finally, this entropically derived yield curve is used to provide an estimate of the economy’s implied information processing ratio. This information theoretic ratio offers a new causal link between bond and equity markets, and is a valuable new tool for the modeling and prediction of stock market behavior.

The Director's Desk It’s a Bear Market for Research

The Director's Desk It’s a Bear Market for Research

Going Public in Bear Markets

Going Public in Bear Markets

Does the Bull Market Have “Buffett”?—An Empirical Study on Chinese Mutual Fund Value Investing in Bull and Bear Markets

“Worshipping value investing in the bear market and everyone is ‘Buffett’ in the bull market” is a general impression of China’s stock market. This article uses the open-end fund holdings data from 2006 to 2015 to test whether the investment behavior of fund consistent with value investing both in the bear market and the bull market. This paper finds that the stock with higher fund holdings in the bear market is positively related to the next quarter and the next year’s unexpected earnings, but not in the bull market. At the same time, similar conclusions have been drawn from further analysis of the new-in and new-out investment behaviors. Overall, this paper demonstrates that “the bear market follows the value investment, while the bull market ignores the value investment” has some truths.

Beta Stability Over Bull and Bear Market on the Warsaw Stock Exchange

Abstract Beta parameter is one of the commonly used measures of the investment risk of individual stock or portfolio. It plays a crucial role in modern portfolio theory particularly in management of financial investment portfolios. In the field of beta parameter, numerous studies have been conducted, especially beta properties stability in the context of the stock market cycle phases, measuring frequency of rate of return, and the length of a sample period. There are much fewer studies concerned beta parameter in the countries of Central and Eastern Europe which have undergone systemic transformation at the end of the previous century. From a scientific point of view, it is interesting to know how the beta parameter behaves in these countries. The main goal of this article is to examine the beta parameter stability over bull and bear market conditions on the Warsaw Stock Exchange. The paper presents an analysis of beta stability for 134 stocks of the largest companies listed at the WSE during years 2005–2013. To verify statistically the hypothesis of beta parameter stability, we used monthly returns in the Sharpe’s single-index model. In the first part of the article, we present a brief review of the literature and methodology of the study, while in the second part, the obtained results and conclusions are shown.

What Drives Mutual Funds Long-term Herding: Bear or Bull Markets?

This paper explores the herding dynamics in US mutual funds’ trading and documents the evidence of increased herding over time. I observe (slightly) higher levels of overall herding compared to main stream herding literature with asymmetry on the buy and sell side; the overall herding level is weakly affected by the scale economies and significantly influenced by a fund’s style. Increased participation of mutual funds to the financial markets, proxied by number of quarterly traded securities, appears to be positively correlated with mutual funds’ herding. Both stocks’ beta and market volatility are found to be crucial determinants of herding. A higher demand for the smaller-sized stocks confirms the presence of small-firm-effect anomaly. In addition, I find US mutual funds’ herding more in bad market scenarios compared with good market environment.

How to Identify and Forecast Bull and Bear Markets?

SummaryBecause the state of the equity market is latent, several methods have been proposed to identify past and current states of the market and forecast future ones. These methods encompass semi‐parametric rule‐based methods and parametric Markov switching models. We compare the mean‐variance utilities that result when a risk‐averse agent uses the predictions of the different methods in an investment decision. Our application of this framework to the S&P 500 shows that rule‐based methods are preferable for (in‐sample) identification of the state of the market, but Markov switching models for (out‐of‐sample) forecasting. In‐sample, only the mean return of the market index matters, which rule‐based methods exactly capture. Because Markov switching models use both the mean and the variance to infer the state, they produce superior forecasts and lead to significantly better out‐of‐sample performance than rule‐based methods. We conclude that the variance is a crucial ingredient for forecasting the market state. Copyright © 2016 John Wiley & Sons, Ltd.

Momentum Crash, Credit Risk Burst and Optionality-Effect in Bear Markets: Evidence from the US Stock Market

This study explores whether the credit risk anomaly exhibits option-like behavior similar to the momentum anomaly. Employing a market-timing regression model as in Daniel and Moskowitz (2013), it finds that the inverted credit risk spread indeed displays option-like behavior in bear market states. Unlike a momentum portfolio, which is effectively a short call option on the market, an inverted credit risk portfolio appears to be a long call option on the market. A strategy that invests 50% in credit risk and 50% in momentum does not exhibit any significant optionality effects in times of market stress.

Does Herding Behaviour Vary in Bull and Bear Markets? Perspectives from Egypt

Purpose: the paper aims at examining the existence of herding behaviour in two opposite market condition: bullish and bearish. Design/method/approach: Christie and Huang (1995) and Chang et al. (2000) Methods are used in the study. The sample includes daily and monthly data of listed companies in the Egyptian stock market from January 2007-December 2012. Findings: The authors have reached general results based on hypotheses developed from related literature. The results show that: (a) the Egyptian market exhibits herding behaviour in general especially when the market is down, (b) the Egyptian market was found to be inefficient during bull and bear markets, and (c) there is asymmetric effects of trading volume and volatility on herding behaviour. Originality/value: The study contributes to the literature as (a) it extends studies of herding behaviour to an emerging market, not yet being thoroughly investigated, (b) it investigates the presence of herding during market stress, bearish and bullish market phases, and (c) it also examines the existence of asymmetric herding associated to trading volume and market volatility.

Risk and Volatility During Bear Markets

Wall Street would have investors believe that if they “miss the 10 best days” of the stock market that their investment returns will be lower. Though an investor who buys and holds may reap the benefits of “the best 10 days,” they may also suffer through “the worst 10 days.” Alternative analysis yielded actionable observations. That is, during bear markets, the best and worst days tended to cluster together. If investors had successfully reduced their exposure to periods of increased market volatility, then they would have avoided large portions of bear markets during The Period. This research paper will attempt to show that the buy and hold theory is flawed, and present a counter argument that could be the basis for an alternative strategy.

Bear market periods during the 2007–2009 financial crisis: Direct evidence from the Visegrad countries

The main goal of this paper is a quantitative identification of bear market periods during the 2007–2009 global financial crisis in the case of the Visegrad Group stock markets. We analyse four countries, namely Poland, the Czech Republic, Hungary, and Slovakia and, for comparison, the US stock market. The sample period begins on May1, 2004, and ends on April 30, 2013, i.e. it includes the 2007 US subprime crisis. We use the statistical method of dividing market states into bullish and bearish markets. Our results reveal October 2007–February 2009 as the common downmarket period of the recent global financial crisis, except for Slovakia. It is instructive to formally identify crises, as it enables sensitivity analyses of various relationships and linkages among international stock markets using econometric and statistical tools, with respect to the pre-, post- and crisis periods. Moreover, we investigate the effect of increasing cross-market correlations in the crisis compared to the pre-crisis period, applying both standard contemporaneous correlations and volatility-adjusted correlation coefficients. The results confirm that accommodating heteroskedasticity is critical for detecting contagion across economies. A number of studies document that crossmarket correlations vary over time, thereby making the benefits of international portfolio choice and diversification questionable.

INVITED EDITORIAL

1. Ryan Leggio 2. Steven Romick TOPICS: [Mutual funds/passive investing/indexing][1], [portfolio management/multi-asset allocation][2] According to Vanguard’s 2001 Bear Market Survival Guide , “a bear market is Wall Street jargon for a sharp decline in prices. There’s no official

Why Investors are Loss Averters During Bull Markets and Gain Seekers During Bear Markets?

How does market trend sentiment affect investors’ asymmetric loss-gain tradeoffs? Several empirical tests indicate that investors are far more loss adverse during bull markets than during bear markets (see Hwang and Satchell, 2010; Hofschire et al, 2013). In this paper we provide a sound theoretical foundation for this empirical evidence. First, we discuss how to identify the subjectively perceived market trend sentiment. Then, we propose a reference dependent definition of loss aversion and gain appetite, that generalizes the Kahneman and Tversky (1979, p. 279) and Kahneman and Tversky (1992, p. 303) loss aversion definitions. Under mild technical assumptions on utility functions, asymmetrical loss-gain evaluations are normatively influenced by the investor perceived market trend. Specifically, investors are normatively lead to loss aversion during perceived bullish markets and to risk appetite during perceived bearish markets. This market trend dependence holds for the most popular utility functions used in the expected utility and prospect theory.

Determinants of Bear Market Performance at the Nairobi Securities Exchange in Kenya

This study sought to establish the determinants of bear market performance by taking a survey of investors at the Nairobi Securities Exchange. To achieve this, a quantitative and qualitative research design was adopted and the study involved administering questionnaires to 500 retail investors participating at the Nairobi Securities Exchange through five purposively selected stock brokerage firms based in Mombasa Town. Convenient sampling technique was used to administer questionnaires to respondents. Data was analyzed by the use of descriptive statistics and correlation analysis was carried out to determine the relationship between the variables. A multiple regression model was employed to analyze the independent variables and their effect on bear market performance. The ANOVA result at a p-level of .05 showed that all the four variables; transaction cost, mobilization of resources by retail investors, financial literacy and cultural values had an influence on bear market performance. The Pearson Moment correlation analysis showed that bear market performance was weakly associated with transaction costs and financial literacy while the relationship between bear market performance and mobilization of resources by retail investors as well as cultural values was largely insignificant. The study recommends that further research should be carried out on the economic cycle and its influence on bear market performance.

Shelter from the Storm: Bear Market Performance and Average Returns

Stocks that hedge against sustained market downturns — periods from peak to trough in S&P500 levels at the business cycle frequency — should have low expected returns, but they do not. We use ex-ante firm characteristics and covariances to construct a tradeable Safe Minus Risky (SMR) portfolio that hedges market downturns out-of-sample. Although downturns correspond to significant declines in GDP growth, SMR has significant positive average returns and four factor alphas (both about 0.75% per month). Risk-based models do not explain SMR’s returns, but mispricing does. Risky stocks are overpriced when sentiment is high, resulting in subsequent returns of -1% per month.

Fractional Integration and Asymmetric Volatility in European, American and Asian Bull and Bear Markets: Application to High‐frequency Stock Data

AbstractThis paper is a follow‐up to another paper by the same authors. In that paper, fractional integration and symmetric volatility modelling were considered on monthly frequency data, while the present paper considers high‐frequency data on an asymmetric volatility model. The data were first identified within the respective bull and bear phases following earlier results in the previous paper. Then, fractional integration and the asymmetric volatility model of Glosten, Jaganathan and Runkle were applied on the stock returns. Long‐range dependence was detected in the squared stock returns at each market phase, and they were more persistent than those obtained in the monthly frequency data. The estimates of asymmetry of the Glosten, Jaganathan and Runkle model actually detected the different patterns of the bad news (bear phases) and the good news (bull phases). Copyright © 2015 John Wiley & Sons, Ltd.

How does the Occurrence of Stock Price Reversals Following End-of-the day Price Moves Differ in Bull and Bear Markets?

This paper uses intraday price data for 326 individual firms to examine how the occurrence of interday stock price reversals differs in bull and bear markets. We find that price reversals following the previous day’s larger high-to-close (low-to-close) price differences are more likely to occur in a bull (bear) market. Based on these findings, we find that the portfolios based on larger high-to-close price differences in the bull market, and portfolios based on smaller low-toclose price differences both in bull and bear markets are profitable investment strategies. In particularly, in bull markets, the portfolios based on smaller low-to-close price differences in the Mining and Service industries yield higher returns; in bear markets, portfolios based on smaller low-to-close price differences in Construction, Finance and Retail Trade yield higher returns

The Characteristics of Alternative Mutual Funds

This study investigated the portfolio characteristics and investment performance of alternative mutual funds from April 1993 to March 2013, focusing on Bear Market mutual funds, Market Neutral mutual funds, and a sampling of traditional stock mutual funds. The results indicate that alternative mutual funds are, on average, younger and smaller in size than the average traditional fund. Alternative funds, however, have significantly larger expense ratios, larger portfolio turnover, and fewer portfolio holdings. Bear Market fund returns generally move in the opposite direction of the stock market, whereas Market Neutral funds and the average traditional fund returns rise and fall with the stock market. The two categories of alternative funds underperformed the traditional funds, with substantially greater variability of returns and larger tracking errors. Furthermore, Bear Market funds had a negative beta and were more volatile than the stock market, whereas Market Neutral funds had a near-zero beta, making them less volatile than the stock market. The performance of the average traditional fund was not significantly different from zero, and its beta did not differ significantly from unity.