Downtick (Financial Markets) Explained

Cite this article as:"Downtick (Financial Markets) Explained," in The Business Professor, updated November 24, 2018, last accessed October 21, 2020,


Downtick (Financial Markets) Explained

When a financial instrument sells at a lower price than the previous transaction, it is called the downtick. It happens when a stock’s price decreases from the preceding price. It is the opposite of uptick. It is generally used for stock’s price, but it may also be applied to commodities or other forms of securities.

For example, a stock of X is traded at $20, and in the following trade, it sells at $18, so the stock is on a downtick. Tick is a measurement of small price movements of the stocks. In the U.S the minimum tick size is 1 cent for the stocks trading for more than $1. A downtick not always indicates a downturn and a natural part of stock market fluctuation. Many reasons may contribute towards downtick including an increase in supply over demand.

Downtick-Uptick Test

Downtick-uptick test is implemented by the New York Stock Exchange to restrict market volatility. According to it, whenever the Dow Jones Industrial Average moves more than 2% in any direction from the previous trading day the volume of trades must be restricted. The objective is to restrict the high volume of trading during an unstable market situation as that contributes to even more fluctuation and affects the exchange negatively.

References for Downticks

Academic Research on Downtick in Financial Market

  • ●      Automating the price discovery process: Some international comparisons and regulatory implications, Domowitz, I. (1993). Journal of Financial Services Research6(4), 305-326. This paper examines automated trade execution system with respect to the degree to which they automate the price discovery process. Seven levels of automation of price discovery are identified, and 47 systems are classified according to these criteria. Systems operating at various levels of automation are compared with respect to age, geographical location, and type of securities traded.The main objective is to show the effect of price discovery automation on trading abuse.
  • ●      Bid-ask bounce and speads in the foreign exchange futures market, Chu, Q. C., Ding, D. K., & Pyun, C. S. (1996). Review of Quantitative Finance and Accounting6(1), 19-37. This paper examines the intraday bid-ask bounce in Deutschemark and Japanese yen futures prices. The main objective is to show the movement of speads during different hours of the day. To achieve this, we take into account overnight inventory carrying cost and information flow.
  • ●      Inferring trade direction from intraday data, Lee, C. M., & Ready, M. J. (1991). The Journal of Finance46(2), 733-746. This paper evaluates alternative methods for classifying individual trades as market buy or market sell orders using intraday trade and quote data.This paper highlights two problems related to quote-based methods of trade classification. The objective of this paper is to generate different procedures for improving trade classification by proper analysis of the problems stated above.
  • ●      The total cost of transactions on the NYSE, Berkowitz, S. A., Logue, D. E., & Noser Jr, E. A. (1988). The Journal of Finance43(1), 97-112. This paper develops a measure of execution costs (market impact) of transactions on the NYSE using data from 14,000 actual trades. It also explores the possible tradeoff between commission expenditures and market impact costs.
  • ●      The overthecounter market and New York Stock Exchange trading halts, Fabozzi, F. J., & Ma, C. K. (1988). Financial Review23(4), 427-437. This paper examines the over‐the‐counter (OTC) market activities for stocks temporarily suspended by the New York Stock Exchange (NYSE). The main objective is to show the price adjustment process between market equilibra by using various transaction-to-transaction data on the NASDAQ during the NYSE trading halts.
  • ●      Marketbuzz: Sonification of real-time financial dataa, Janata, P., & Childs, E. (2004). Georgia Institute of Technology.  This paper describes a system for the sonification of real-time financial data, in use by financial traders in five pilot projects. The aim of this paper is to use these data to draw different conclusions and get results about the most important system for monitoring teh movement of volatile market indexes.
  • ●      The price impact of trading on the stock exchange of Hong Kong, Chan, Y. C. (2000). Journal of Financial Markets3(1), 1-16. This article studies the price formation process on the Stock Exchange of Hong Kong (SEHK). The objective is to show the importance of the information effect over the inventory effect in explaining transaction price movement.
  • ●      Patterns of stock option exercise in the United States, Huddart, S. (1999). Executive compensation and shareholder value (pp. 115-142). Springer, Boston, MA.  This study analyses the many benefits of stock options granted by an employer corporation to its employees. The aim of this paper is to show the impact of employee exercise behavior on the cost and benefits of such options.
  • ●      The behavior of option price around large block transactions in the underlying security, Kumar, R., Sarin, A., & Shastri, K. (1992). The Journal of Finance47(3), 879-889. This paper investigates the behavior of stock and option prices around block trades in stocks. The results indicate that for both up tick and downtick block trades the stock prices adjust within a fifteen minute period after the block trade. It also shows that option price behavior differs considerably from stock price behavior.
  • ●      Momentum and reversals in Taiwan index futures returns during periods of extreme trading imbalance, Kao, E. H. (2011). International Review of Economics & Finance20(3), 459-467. The study analyzes the relation between a trading imbalance metric that captures data observable by investors, and future momentum and reversals in Taiwan index futures returns.
  • ●      A direct test of methods for inferring trade direction from intra-day data, Finucane, T. J. (2000).  Journal of Financial and Quantitative Analysis35(4), 553-576. This study directly tests the ability of several competing methods to identify market buy and sell orders using intra-day quote and trade prices, and identifies factors that affect the accuracy of the methods. The objective is to show the similarity and differences between the Lee and Ready’s algorithm and the tick test in identifying trade directions.

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