Daily Trading Limit Definition
It is the highest and lowest limit of the price range within which the price of a derivative contract (such as an options or futures contract) is allowed to fluctuate in a trading session. Once the limit is reached that particular derivative cannot be traded on that day for a higher or lower price These limits are imposed for safeguarding the interests of the investors against market manipulation and volatility.
A Little More on What is Daily Trading Limits
The derivative markets contain a high level of leverage; thus, these limits are in place for protecting the investors from any extremities. This is also known as the “fluctuation price limits”.
Once the limit is reached, the market is called the “locked market”. That means the market for that derivative is locked for the day. If the trading limit reaches the highest point on a day, it is the up-limit day for the derivative. Similarly, if it reaches the lowest level, then it is the down-limit day.
For example, if a country has a daily trading limit of 0.5% on its national currency, then on a particular day if the price changes more than 0.5% in any direction, the trading must be halted for the day.
Occasionally, during the expiration month of a derivative, these limits are revoked as the prices can become extremely volatile.
References for Daily Trading Limit
Academic Research on Daily Trading Limit
Price limit performance: evidence from the Tokyo Stock Exchange, Kim, K. A., & Rhee, S. G. (1997). the Journal of Finance, 52(2), 885-901. This paper examines the Tokyo Stock Exchange price limit system to test the hypothesis that price limits decrease stock price volatility.
An empirical analysis of the limit order book and the order flow in the Paris Bourse, Biais, B., Hillion, P., & Spatt, C. (1995).. the Journal of Finance, 50(5), 1655-1689. This paper analyzes the supply and demand of liquidity in Paris Bourse. The paper shows that to gain price and time priority, investors quickly place orders within the quotes when the depth at the quotes or the spread is large.
An examination of herd behavior in equity markets: An international perspective, Chang, E. C., Cheng, J. W., & Khorana, A. (2000). Journal of Banking & Finance, 24(10), 1651-1679. This paper examines the investment behavior of market participants within different international markets (i.e., US, Hong Kong, Japan, South Korea, and Taiwan), specifically with regard to their tendency to exhibit herd behavior. The paper finds no evidence of herding on the part of market participants in the US and Hong Kong and partial evidence of herding in Japan.
A specialist’s quoted depth and the limit order book, Kavajecz, K. A. (1999). The Journal of Finance, 54(2), 747-771. By partitioning quoted depth into the specialist’s contribution and the limit order book’s contribution, the paper investigates whether specialists manage quoted depth to reduce adverse selection risk. The results show that both specialists and limit order traders reduce depth around information events, thereby reducing their exposure to adverse selection costs.
Transitory price changes and price-limit rules: Evidence from the Tokyo Stock Exchange, George, T. J., & Hwang, C. Y. (1995). Journal of Financial and Quantitative Analysis, 30(2), 313-327. This paper compares the volatility of 24-hour returns computed from the opening and closing prices of a diverse sample of Tokyo Stock Exchange (TSE) stocks. The paper find that volatility at the open is greater than volatility at the close only for the most actively traded TSE stocks. These results challenge the view that open-to-open returns are more volatile than close-to-close returns for stocks, in general, and are consistent with the hypothesis that TSE price limit rules have a significant impact on the dynamics of security prices.
Trading costs and returns for US equities: Estimating effective costs from daily data, Hasbrouck, J. (2009). The Journal of Finance, 64(3), 1445-1477. The effective cost of trading is usually estimated from transaction‐level data. This study proposes a Gibbs estimate that is based on daily closing prices. In a validation sample, the daily Gibbs estimate achieves a correlation of 0.965 with the transaction‐level estimate. When the Gibbs estimates are incorporated into asset pricing specifications over a long historical sample (1926 to 2006), the results suggest that effective cost (as a characteristic) is positively related to stock returns.
The relation between price changes and trading volume: A survey, Karpoff, J. M. (1987). Journal of Financial and quantitative Analysis, 22(1), 109-126. This paper reviews previous and current research on the relation between price changes and trading volume in financial markets, and makes four contributions. First, two empirical relations are established: volume is positively related to the magnitude of the price change and, in equity markets, to the price change per se. Second, previous theoretical research on the price-volume relation is summarized and critiqued, and major insights are emphasized. Third, a simple model of the price-volume relation is proposed that is consistent with several seemingly unrelated or contradictory observations. And fourth, several directions for future research are identified.
The information content of the limit order book: evidence from NYSE specialist trading decisions, Harris, L. E., & Panchapagesan, V. (2005). Journal of Financial Markets, 8(1), 25-67. This paper examines whether the limit order book is informative about future price changes and whether specialists use this information when trading. It uses order quantities as well as option values to capture the information content of the limit order book. The paper finds that the limit order book is informative about future price movements. It also finds that specialists use this information in ways that favor them (and sometimes the floor community) over the limit order traders.
Limit order trading, Handa, P., & Schwartz, R. A. (1996). The Journal of Finance, 51(5), 1835-1861. This paper analyzes the rationale for limit order trading. The paper suggests that trading via limit orders dominates trading via market orders for market participants with relatively well balanced portfolios, and that placing a network of buy and sell limit orders as a pure trading strategy is profitable.
Market liquidity and trading activity, Chordia, T., Roll, R., & Subrahmanyam, A. (2001). The journal of finance, 56(2), 501-530. In this paper, spreads, depths and trading activity for US equities are studied over an extended time sample. The paper shows that daily changes in market averages of liquidity and trading activity are highly volatile, negatively serially correlated and influenced by a variety of factors. It suggests that long and short term interest rates influence liquidity and trading activity. Depth and trading activity increase just prior to major macroeconomic announcements.