1 / 25

Revisiting the Reversal of Large Stock-Price Declines

Revisiting the Reversal of Large Stock-Price Declines. Harlan D. Platt. Breakdown. Previous research and methodology Danielle Overall results Jon Risk measure and comparing closing prices to daily lows Jordan How often do companies appear on the list and bid/ask spread Dmitry.

cheryl
Download Presentation

Revisiting the Reversal of Large Stock-Price Declines

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Revisiting the Reversal of Large Stock-Price Declines Harlan D. Platt

  2. Breakdown • Previous research and methodology • Danielle • Overall results • Jon • Risk measure and comparing closing prices to daily lows • Jordan • How often do companies appear on the list and bid/ask spread • Dmitry

  3. Previous Research • Most studies have found that investors overreact to bad news and stock prices recover at least in part from large one-day declines • Other studies offer contradictory evidence or argue that institutional factors such as bid/ask spreads explain the findings

  4. Previous Research • Psychological factors (loss aversion, herd behavior) may influence investors to accept price levels below their true economic value • Price reversal theory • Theory should be reevaluated • In the past few years, minimum bid/ask spread differentials have shrunk from 1/8th of a dollar to 1 cent • Dramatic volatility of bull market run-up in 1990’s and bear market plunge in 2000-2001

  5. Previous Research • De Bondt and Thaler (1985) developed theoretical foundation of market overreactions: investors weigh new information more heavily than old information • Found that over the 50-year span, lower portfolios outperformed the market by an average 19.6% while winner portfolios underperformed the market by an average 5.0%, 36 months after portfolio formation • Atkins and Dyl (1990) found that bid/ask spread differentials misrepresented a price reversal • Bremer and Sweeney (1991) found larger-than-expected positive rates of return, with returns accumulating over a 3-day horizon • Cox and Peterson (1994) found no price reversals

  6. Methodology • CRSP data • January 1997-December 2001, about 1,250 trading days • Reassessment of price reversals during a period of declining bid/ask spreads • Prior research did not address market cycles • All NYSE and NASDAQ stocks that fit definition of a major price decline: core data comprised of 20 worst-performing stocks every day on the NYSE and NASDAQ

  7. Methodology • Examine short- and long-term price reversals over 7 time periods of 1, 3, 7, 30, 90, 180, and 360 trading days after price decline • Assume beta = 1 • Objective: To identify abnormal returns Abnormal return = Individual stock return – Return on market

  8. Overall results • Price reversals provide substantial market corrected short-term trading success on the NYSE and NASDAQ • This strategy does not work similarly well for long-term investments • The results when the 20 worst performing stocks were bought……

  9. Overall results

  10. Overall results • Price reversals consistently produce positive returns on an adjusted basis in the NYSE and NASDAQ for investments held less than 8 days • Bull markets have the same effect for up 7 days • Bear markets • Price reversal method in the NYSE beat the market for every holding period • Only beat the market in the NASDAQ for holding periods between 1 and 30 days

  11. Overall results • 20-worst performing stock list is then broken down into cohorts by percentage price declines • In both the NYSE and the NASDAQ, the higher the percentage decline, the lower the average prices • For one-day holding period return • NYSE: stocks falling by less than 10% have best returns • NASDAQ: stocks falling by less than 10% to 30% have best returns

  12. Overall results • List broken down by the prices of stocks • Low priced stocks made up a higher proportion on the list compared to the overall market • Average price and percentage decline are not correlated • Even premier companies appeared on the list like Berkshire Hathaway • The lowest priced strata achieve the best returns

  13. Risk Measurement • Platt (2002 & 2005) argues that a portfolio of equities that has just experienced a large price decline has less risk than the market portfolio • All company specific risk factors are revealed in news announcements • Two measures of portfolio risk may be used: • Standard deviation • Semi-variance

  14. Risk Measurement • Standard deviation – square root of variance • Semivariance- proportion of a portfolio’s distribution of returns that lie in the negative range • SV = 1.00 → strategy always makes money • SV = 0.50 → equally likely to make or lose money • Hedge funds / short term traders use semivariance risk measurements because it takes into account the sign of the mean return

  15. Risk Measurement • Ex. A dense population distribution with a negative mean return (A) is less risky using S.D. than a less dense distribution with a positive mean return (B)

  16. Risk Measurement • Platt theorizes that companies whose prices plunge in a single day are more volatile than an average stock • Platt uses 50,000 stocks in the 5-year price reversal portfolio comprising the 20 worst-performing stocks each day on the NYSE and Nasdaq • It is assumed the portfolio of 20 stocks on each market is sold on the following trading day and replaced • The market portfolio is represented by daily returns on the S&P 500 for the NYSE, and the Nasdaq index

  17. Risk Measurement • The annual standard deviations are fairly consistent on the S&P index • The Nasdaq index showed large variations in 2000, 2001 • On average Nasdaq stocks are about 75% more volatile than NYSE stocks using standard deviations • Annual S.D.’s with price reversals are relatively constant over time on both markets • Highest annual S.D. is just 30% greater than the lowest S.D. year • Compared to the market index is 40% greater for the S&P and 160% greater for the Nasdaq

  18. Risk Measurement • Kurtosis is the next moment of the distribution, measuring the stability of the variance • A higher value indicates a tighter distribution of variances around its mean • The Nasdaq and NYSE price reversal kurtosis is greater than their respected index • Price reversals have more return volatility than the market portfolio, but more consistency in the volatility • Price reversals gain some volatility due to large daily gains after suffering a large daily loss • The worst performing stocks on the NYSE fell on average 9.5%, whereas an average stock had a price change of .04% • The worst performing stocks on the Nasdaq declined 16.4%, whereas an average stock had a price change of .07% • After the event, the average price change for the price reversal portfolio was .18% on the NYSE and 1.60% on the Nasdaq

  19. Comparing Closing Prices to Daily Low Prices • It is assumed that a stock is bought at the end of the day • This may distort the returns than an investor may earn by investing at the daily low • Traders using the price reversal strategy contend that on average fallen stocks increase at the end of the day • A more realistic assumption is that the position is acquired somewhere between the daily low and the daily closing price

  20. Comparing Closing Prices to Daily Low Prices • Platt tests this theory using the worst daily 5 stocks on NYSE and Nasdaq in 2001 • 1250 companies are studied in all • 15.7% of NYSE and 11.9% of Nasdaq stocks closed at their daily low • 12.2% of Nasdaq and 4.8% of NYSE stocks closed at least 10% or more above their daily low • The difference between the closing price and daily low resulted in a significant statistic of 2.8% on the NYSE and 4.0% on the Nasdaq • Platt’s results find that on average higher priced stocks are more likely to increase intraday • This may be psychological as investors seek value and try to minimize risk

  21. Stock appearance on the list • Not a significant difference between the average number of times NYSE and NASDAQ stocks appear on the list

  22. Bid/Ask spreads • Bid/Ask spread may account for some return superiority for lower priced stocks at ~0.83% (NYSE) and ~0.80%(NASDAQ) given 1/16 spread prior to ’94. • Defense against the bid/ask hypothesis • 40% of the NYSE stocks that rose increased by 4.5% • 39% of the NASDAQ stocks that rose increased by 8.0% • Bid/ask spread does not explain the entire effect. • The spread now is $0.01 or less. Spread impact is reduced at higher stock price levels.

  23. Conclusions • Buying 20 worst performing stocks and then selling them one day later produces adjusted annual returns of 32.50% on NYSE and 387.50% on NASDAQ • Ideal holding period varies during bull and bear markets • Reduction of bid/ask spread did not reduce the approach returns

  24. Taking a step back • Stop loss orders to protect against a large drop in daily price do not appear to minimize the loss • A better alternative could be to close the position the next day after the large price drop

More Related