Elsevier

Pacific-Basin Finance Journal

Volume 45, October 2017, Pages 142-156
Pacific-Basin Finance Journal

Price limits and volatility

https://doi.org/10.1016/j.pacfin.2016.12.002Get rights and content

Highlights

  • New evidence on effectiveness of price limit rules

  • Proposes use of propensity score matching technique to modify the volatility spill over test

  • Reports asymmetric impact of price limit rules on volatility.

  • Reports spill over of permanent component volatility post price limit hit.

  • Reports reduction of transitory volatility on limit hitting days.

Abstract

This study provides new evidence on efficacy of daily price limit rules. We propose use of propensity score matching techniques to reduce sample selection bias in widely used Kim and Rhee (1997). Using data from the Tokyo Stock Exchange over a period of 5 years from January 2001 to December 2005, this study shows that price limit rules work quite efficiently for lower limit hits as there is no evidence of volatility spill-over. We also find that daily price limits have differential effects on permanent and transitory components of daily volatility. Our study reports evidence of spill-over of permanent volatility. However, we find price limit successfully curbs the transitory volatility on the post limit hit days.

Introduction

Effectiveness of rule based trading halt mechanisms such as circuit breakers, trading collars and price limits has been frequently debated (see for example—Fama, 1989, Lehmann, 1989, Miller, 1989; Subrahmanyam, 1994, Kim and Rhee, 1997, Harris, 1998, Phylaktis et al., 1999, Bildik and Elekdag, 2004, Chan et al., 2005, Deb et al., 2010, Deb et al., 2012, Kim et al., 2013, Farag, 2013, Farag, 2015; and Goldstein, 2015). Over time, circuit breakers and price limits has been used in several financial markets, however fresh discussions on these rule based trading halts resurfaced since the May 2010 Flash Crash in US market. In this paper we investigate impact of price limits on equity market volatility.

Kim and Rhee (1997) analyse the relationship between price limits and volatility in the Tokyo Stock Exchange. The authors observe that price limits causes volatility spill over to the following trading days and hence they conclude that price limits are not effective in reducing volatility. However, studies by Lee and Kim (1995) and Berkman and Lee (2002) on Korean market report that price limits reduce volatility. Therefore the verdict on efficacy of price limits is far from clear.

In this paper, while building on Kim and Rhee's (1997) methodology we consider an improved research design. The prior literature on price limit compares average volatility of limit hitting stocks against average volatility of non-price limit hitters around limit hit events (Kim and Rhee, 1997). On the other hand, Kim and Limpaphayom (2000) observe that fundamental characteristics of frequent limit hitting stocks are different from non-limit hitting group. Hence, when average volatility persistence of limit hitters is significantly greater than volatility persistence in non-limit hitting group, the results of volatility spill over test in Kim and Rhee (1997) may only reflect the difference in volatility persistence of between the test and the control group, and may not provide much insight on volatility spill over due to price limit events. Hence in this paper based on findings of Kim and Limpaphayom (2000), we propose to select the control group for volatility spill over test based on stocks estimated propensity to hit price limits.

We aim to add to the literature by providing new evidence about the volatility–price limits relationship. We contribute by decomposing the volatility into permanent and transitory components in order to understand the differential impact of price limits on both components. Stock return volatility may be decomposed into permanent and temporary components (see, for example, Engle and Lee, 1999). We decompose volatility to study the effect of price limits on the permanent and temporary components of volatility. This decomposition is very important to understand the efficacy of price limit rules. Harris (1998) explains that, depending upon the cause of volatility, price limits may have different impact on volatility in the market. If volatility is caused by fundamental information then price limits would cause volatility spill over on the post price limit hit days. On the other hand, if volatility is caused by noise trading activity of uninformed traders then price limits may control such volatility. Hence price limits may effectively reduce the temporary component of volatility. However, an artificial price barrier such as price limit rules should not have any significant impact on reducing the permanent component of volatility. In this paper we follow Engle and Lee (1999) to decompose daily volatility of security returns into permanent and transitory component and use modified Kim and Rhee (1997) methodology discussed earlier to study the impact of price limit rules on these two components of volatility.

We utilize a sample of 1048 stocks listed in the Tokyo Stock Exchange with 6176 limit hit events, during January 2001 to December 2005. Our findings differ from the prior literature as follows. First, we find that price limits are successful in curbing transitory volatility. Second, volatility spill over holds only for upper limit hits (when stock price moves upwards) but not for lower limit hits (when stock prices move downwards). Hence, in spite of the negative effects shown by scholarly researchers, the popularity of price limits among both practitioners and stock exchange officials may be partially justified through our empirical evidence.

The paper is organized in five sections. The introduction in this section is followed by Section 2 where we develop and present testable hypotheses. Section 3 describes our data and other institutional details of Tokyo Stock Exchange. As a subsection, we also present our detailed methodology for testing our proposed hypotheses. Section 4 reports the empirical results. Conclusions are presented in Section 5.

Section snippets

Development of Hypotheses

This section is divided into two subsections, the first subsection focuses on developing hypothesis related to a possible sample selection issue. On the basis of this hypothesis, we would propose a modification to the existing methodology of volatility spill over test. The second subsection explains hypotheses related to impacts of price limit rules on permanent and transitory component of volatility.

Institutional Details, Data and Methodology

Tokyo Stock Exchange (TSE) is the second largest equity market of the world in terms of market capitalization. The exchange follows a “continuous auction” trading mechanism without any market maker or specialists. This is one of the oldest and most developed equity markets of the world with a long history of price limit rules. Price limit rules for individual stocks traded in this exchange do not allow placing bid and ask quotes beyond daily price limits but trading on a security can still

Sample Selection Bias

Table 5 reports the comparison of volatility persistence between the frequent limit hitter group (i.e. stocks that hit daily price limit at least 5 times over the entire sample period) and the group of stocks reaching at least 60%, 70%, 80% or 90% of daily price limit but not hitting the price limit on the days when the stocks of limit hit group hit their daily price limits. The average volatility persistence values reflect very high persistence of volatility for all the groups. Average

Summary and Conclusion

This study investigates the impact of price limit rules on volatility of security prices in Tokyo Stock Exchange over a period of 5 years from January 2001 to December 2005. We propose a modification to widely used methodology of Kim and Rhee (1997) by applying propensity score matching technique, in order to reduce the possible sample selection bias of the existing methodology. Using the modified methodology, we provide new evidences of efficacy of price limit rules in equity markets. Results

References (33)

  • X. Li et al.

    Propensity score matching and abnormal performance after seasoned equity offerings

    J. Empir. Financ.

    (2006)
  • R. Bildik et al.

    Effects of price limits on volatility: evidence from the Istanbul Stock Exchange

    Emerg. Markets. Financ. Trade

    (2004)
  • W.S. Choi et al.

    Price limits and limit order flow: evidence from the Korean Stock Exchange

    Rev. Pac. Basin Financ. Mark. Policies

    (2000)
  • J. Conrad et al.

    When is bad news really bad news?

    J. Financ.

    (2002)
  • M.J. Cooper et al.

    Changing names with style: mutual fund name changes and their effects on fund flows

    J. Financ.

    (2005)
  • S.S. Deb et al.

    Flexible price limits: the case of Tokyo Stock Exchange

    J. Int. Financ. Mark. Inst. Money

    (2012)
  • Cited by (15)

    • Price limit changes and market quality: Evidence from China

      2022, Finance Research Letters
      Citation Excerpt :

      We construct three measurements of market quality using the high frequency trading data: liquidity, volatility and information asymmetry. Following Deb et al. (2017) and Lien et al. (2019), we control for a set of firm characteristics likely to affect market quality. The control variables in this paper are as follows: Stock price (Price), which is the logarithm of the stock price in a day; Asset value (AssetValue), which is the logarithm of the total market value; Logarithm of the daily number of transactions (Tradenum); Return of the stock (Return); Daily turnover (Turnover), which is the trading volume divided by the total number of outstanding shares; Systematic risk (Beta) and the unsystematic risk (Nonsysrisk), which are estimated based on the capital asset pricing model using data from the last 250 trading days; Price-to-book ratio (PB), which is daily price divided by the net asset value.

    • The cooling-off effect of price limits in the Chinese stock markets

      2018, Physica A: Statistical Mechanics and its Applications
      Citation Excerpt :

      Deb et al. provided new evidence on the effectiveness of the price limit trading rule with the data from the Tokyo Stock Exchange over a period of 5 years from January 2001 to December 2005. They concluded that the price limit trading rule works quite efficiently for lower limit hits as there is no evidence of volatility spill-over [11]. Our data come from RESSET (http://resset.cn/), which includes all A-share stocks traded on the Shanghai Stock Exchange and the Shenzhen Stock Exchange.

    • An Agent-Based Model for the Impact of Price Limit Changes on Market Quality

      2022, International Journal of Information Technology and Decision Making
    View all citing articles on Scopus
    1

    http://people.unisa.edu.au/Petko.Kalev.

    View full text