1. Home
  2. Knowledge Base
  3. Bear Market – Definition

Bear Market – Definition

Bear Market Definition

A bear market refers to a market situation wherein there is a steep fall in the prices of securities, resulting in an overall sentiment of negativity in the stock market. Such an internally-motivated decline of the market instigates a sense of apprehensiveness in investors, leading them to panic sell their holdings. Although the technical definition of a bear market is far from unambiguous, a market can safely be assumed to have entered a bearish phase when it exhibits a decline of at least 20 percent from its peak in several market indices over a span of two months.

A Little More on Bear Markets

In sharp contrast to a bear market is a bull market, which represents a market condition wherein there is a sharp rise (or an anticipation thereof) in prices of securities. While the term ‘bull market’ analogizes such a condition with the upward thrusts of a bull’s horns during an attack, the term ‘bear market’ is analogous to the downward wallop of a bear’s paws during an ambush.

Technical definitions of a bear market are rather ambiguous; however, any drop of at least 20 percent over a span of two months can be termed a ‘bear market’.

Several factors contribute to a bear market; the most obvious being an overall stagnant economy that brings with it repercussions such as widespread unemployment, and a reduction in income and profits. Another significant factor is government interference in the economy by way of changes in tax rates. Also, investors play a crucial role in determining a bear market. Often, investors will anticipate a downtrend in the market and will, consequently, indulge in mass selling of shares in order to avoid future losses.

Typically, a bear market exhibits four distinct phases:

  • A phase of surging share prices. Although this heightens investor sentiment, they typically begin to indulge in profit-booking, thus liquidating their holdings.
  • The second  phase witnesses a sharp fall in share prices, thus significantly affecting profits and investor sentiment and possibly causing apprehension among investors.
  • The third phase of the bear market marks the entry of speculators into the market. This may result in a partial increase in prices as well as volume of trade.
  • The fourth phase witnesses a much slower drop in share prices, ultimately leading to a situation where the low share prices seem lucrative to new investors. This newfound interest heralds the transition into a bull market.

However, as similar as they may seem, bear markets are not the same as market corrections, the two principal differences being;

  • Unlike bear markets, a market correction is a much shorter-term price movement, typically lasting less than two months.
  • Unlike bear markets that do not offer scope for a bottom indicator, market corrections do provide traders with an discernible entry point.

Short selling is an important feature of bear markets that allows investors to make profits by liquidating ‘borrowed’ security that is anticipated to fall in value and subsequently purchasing them when prices actually fall. Such a procedure mandates the borrowing of shares by the short seller from a broker before a short sell is initiated. The short seller’s earnings can be measured as;

Total earnings = (Selling price of securities) – (Buy-back price of securities)

In case the short seller is forced to buy back securities at a price higher than his selling price, his total earnings will be negative, i.e. a loss will be incurred.

A put option is a stock market instrument that allows the buyer of the option to voluntarily sell his stocks at a price he favors on a predetermined date. Utilized mostly as speculative tools, put options allow traders to purchase stock with falling prices and long-term investors to hedge their investments.

References for Bear Market

Academic Research on Bear Market

  • Stability tests for alphas and betas over bull and bear market conditions, Fabozzi, F. J., & Francis, J. C. (1977). The Journal of Finance, 32(4), 1093-1099. This study makes use of conventional econometric significance tests on a sample of 700 NYSE stocks to ascertain if the regression statistics display pronounced variations between bull market and bear market samples. The authors cite the findings of Levy and Black that prescribed separate alpha and beta statistics for bull and bear markets.
  • On ignorance, intuition, and investing: A bear market test of the recognition heuristic, Boyd, M. (2001). The Journal of Psychology and Financial Markets, 2(3), 150-156. This paper puts to the test the use of the recognition heuristic (pioneered by the ABC Research Group of Gigerenzer and Goldstein) as an instrument for creating stock portfolios. While Gigerenzer and Goldstein prescribed this heuristic for use in a bull market, Boyd’s study obtained dissimilar results in a bear market, leading to notions that poor results were often the norm in bear markets in the case of companies with high brand recognition.
  • An analysis of risk in bull and bear markets, Kim, M. K., & Zumwalt, J. K. (1979). Journal of Financial and Quantitative analysis, 14(5), 1015-1025. Fabozzi and Francis conducted extensive experiments on the single-index market model, by employing three discrete definitions of both bull and bear markets. The results of those experiments were that there was no noteworthy variance in the regression coefficients of the single-index market model in the context of both bull and bear markets.
  • Trading performance, disposition effect, overconfidence, representativeness bias, and experience of emerging market investors, Chen, G., Kim, K. A., Nofsinger, J. R., & Rui, O. M. (2007). Journal of Behavioral Decision Making, 20(4), 425-451. Chen and Kim analyze statistical data from the Chinese stock markets and conclude that poor decision making is the norm among Chinese investors, who usually display the following three typical behavioral traits: They fail to acknowledge losses and end up holding on to depreciating stocks. They suffer from overconfidence. They make the erroneous assumption that a stock’s good past performance is an accurate indicator of a similar performance in the future.
  • Evaluating fund performance in a dynamic market, Ferson, W. E., & Warther, V. A. (1996). Financial Analysts Journal, 52(6), 20-28. Ferson and Warther’s article illustrates how they employ modified forms of common market indicators such as interest rates and dividend yields as measures for fund performance, while avoiding the prejudices associated with conventional measures. They have termed their approach the ‘conditional performance evaluation approach’. Mutual funds measured using such an approach have displayed seemingly better performance characteristics.
  • Do stock market investors understand the risk sentiment of corporate annual reports?, Li, F. (2006).  Li scrutinizes annual reports, specifically sections pertaining to risk sentiment for future dividends and stock returns, to determine stock market efficiency. Li concludes that with an increase in the risk sentiment of a firm, its negative earnings (aka losses) also increase. Hedging initiated by investing in firms with low risk sentiments and shorting those with higher risk sentiments can result in an excess of a 10 percent increase in the active return on the investments.
  • The behavior of Japanese individual investors during bull and bear markets, Kim, K. A., & Nofsinger, J. R. (2007). The behavior of Japanese individual investors during bull and bear markets. The Journal of Behavioral Finance, 8(3), 138-153. Kim and Nofsinger perform an analysis of individual behavior of Japanese investors in the course of long-term bull and bear markets. The duo have identified significant variations between market conditions when it comes to individual investor behavior, especially when parameters such as risk, stock valuation and historical performance are taken into consideration.
  • Stock market volatility, excess returns, and the role of investor sentiment, Lee, W. Y., Jiang, C. X., & Indro, D. C. (2002). Journal of banking & Finance, 26(12), 2277-2299. This study measures the effect of noise trader risk on the inception of conditional volatility as well as predicted return. A positive shift in sentiment results in excess returns, with the generalization that a bullish sentiment translates to a downward volatility revision and better future excess returns. Conversely, a bearish sentiment translates to an upward volatility revision and lesser future excess returns.
  • Predicting the bear stock market: Macroeconomic variables as leading indicators, Chen, S. S. (2009). Journal of Banking & Finance, 33(2), 211-223. Chen’s paper scrutinizes the possibility of forecasting bearish market conditions through macroeconomic variables such as unemployment rates, rate of inflation and nominal exchange rates. Chen employs both parametric as well as nonparametric methods to predict market recessions and concludes that yield curve spreads and inflation rates are the best indicators of an imminent bear market.

Was this article helpful?