Abstract
On the negative side, price limits are criticized for increasing stock price volatility and hindering the price discovery process. On the positive side, price limits are argued to give panicky investors additional time to reassess their judgments and thus provide an opportunity for correcting the element of overreaction in pricing stocks. This study analyzes the effectiveness of price limits in Borsa Istanbul by utilizing a propensity-matched control sample in addition to the traditional benchmarks used in the literature. Similar to recent research, we find strong evidence that price limits lead to increased and persistent price volatility and decreased liquidity. We also provide evidence that price limits interfere with the price discovery process. Results show that smaller stocks with larger volatility and higher trading volume are more likely to experience limit hits. Furthermore, the difference in the findings from the matched control sample and the traditional benchmarks points out the importance of accounting for firm- and market-related characteristics when analyzing the effect of price limits.
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Notes
Another study by Bildik and Elekdag (2004) claim that price limits have no conclusive effect on the volatility of the stock market; however, in this study, the authors use daily stock returns and do not provide comparisons between limit-hitting and non-limit-hitting stocks. These attributes of the methodology do not make it possible to draw conclusions about the effect of price limits on the volatility of stocks traded on Borsa Istanbul.
In order to check the validity of our algorithm, it was used to generate price boundaries for the 2005–2013 period. Boundaries obtained from the algorithm exactly match the actual upper and lower price boundaries provided by Borsa Istanbul for that period.
In order to classify the sample firms into the size versus book-to-market matrix, first all firms are sorted independently based on their market value of equity and book-to-market values as of December 31st of each year. Next, the bottom 35 % from the size (book-to-market) sort are classified as small (low), the middle 30 % from the size (book-to-market) sort are classified as medium (medium), and the top 35 % from the size (book-to-market) sort are classified as large (high). The firms at the intersection of these independent size and book-to-market classes are placed in the appropriate cells on the matrix. Likewise, for the momentum classification, each month sample firms are sorted based on their past 11-month returns with a one-month lag and the bottom 30 % are classified as losers, the middle 40 % are classified as neutrals, and, the top 30 % are classified as winners.
The non-limit-hitting firms are the ones that do not experience any price limit hits during the 21-day window constructed around each limit hit event.
The BIST-100 index is made up of the first 100 of the largest market capitalization and most liquid stocks traded on Borsa Istanbul.
In Borsa Istanbul, hitting a price limit does not automatically trigger a circuit breaker during our sample period.
In results not reported, when volatility is measured as the logarithm of the ratio of the highest price to the lowest price in a session, the DiD estimator is significantly positive for both the lower and upper limit hits. This definition of volatility is known as the Grossman volatility measure (Grossman 1988).
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Danışoğlu, S., Güner, Z.N. Do price limits help control stock price volatility?. Ann Oper Res 260, 129–157 (2018). https://doi.org/10.1007/s10479-016-2317-y
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DOI: https://doi.org/10.1007/s10479-016-2317-y