Stock Price and Trading Volume during Market Crashes

Abstract

We present a model for stock price and volume behaviour during market crashes. The model incorporates a market mechanism for the share exchange between buyers and sellers while taking into account their cash balances. Using an analytical approach and the Monte-Carlo technique for the simulation of the trading volume, we analyzed the dynamics of the stock price and trading volume during market crashes. The trading volume was simulated through the trading exchange process using Monte-Carlo technique. We found that trading volume is inversely proportional to the square of the stock price in the case of the sharp price declines. This result is empirically supported in price and volume data for major recent US stock bankruptcies and market crashes, including Lehman Brothers Inc, Enron, Wachovia, Washington Mutual, Citigroup, Merrill Lynch, and MF Global. The results of the analytical approach may be used for marketing analysis of the sales in the case of the shocking market conditions.

The Effect of Stock Return Sequences on Trading Volumes

“…Caginalpa and Desantisa (2011) point out that if the stock price is growing, but the trading volume is declining, then stock price growth is considered by technical analysts as unstable. Remorov (2014) presents a model of stock price and volume behavior during market crashes and finds that trading volume is inversely proportional to the square of the stock price in the case of the sharp price declines, the result being empirically supported by price and volume data for major recent US stock bankruptcies and market crashes.…”

“…Namely, I consider lagged stock returns (e.g., following the findings by Chen et al 2001;Khan and Rizwan 2008;Lee and Rui 2002;Pisedtasalasai and Gunasekarage 2007); historical performance of the stock prices, including both returns and their volatility (e.g., following the findings by Griffin et al 2007;Caginalpa and Desantisa 2011;Remorov 2014); companies' earnings announcements (e.g., following the findings by Holthausen and Verrecchia 1990;Barron et al 2005;Garfinkel and Sokobin 2006;Bamber et al 2011;Israeli 2015); and dividend payments (e.g., following the findings by Lakonishok and Vermaelen 1986;Tran and Mai 2015;Ndjadingwe and Radikoko 2015).…”

Panic Indicator for Measurements of Pessimistic Sentiments from Business News

“…7, No. 5;2014 issued negative and positive news was calculated for the weekly period from different news agencies, however, in the current report we present the results of our analysis obtained from Thomson Reuters. The articles from Thomson Reuters were collected since 2007 year; the total number of articles exceeded 6 mln articles.…”

“…7, No. 5;2014 relationship of negative news with market indices. Our empirical analysis showed that the ratio of pessimistic to optimistic macroeconomic news is the most sensitive to the negative stock price declines during stock market crisis.…”

“…The trading activity of the unsophisticated investors could limit the applications of the various arbitrage strategies applied by rational arbitrageurs. Remorov (2014) showed that the disequilibrium market can be modelled through cash-flow exchange between market-makers at the stock market crashes through behavioural process. Graham (1999) investigated the impact of public and private information on the herd behaviour among investment analysts.…”