Tick Size and Informed Trading: Evidence from the Taiwanese Stock Market

We adopt the Sandås model for order-book equilibrium to examine informed trading on the Taiwanese stock market, a purely order-driven call-auction market. We find that adverse-selection cost is low for well-known stocks with high liquidity and low volatility, but cost is high for monitoring the order books of those stocks. Our empirical results show that the impact of adverse selection is greatest at the beginning of each trading day and that informed traders engage in stealth trading, supporting the stealth trading hypothesis. Finally, with the special tick size rules on the market, both adverse-selection cost and monitoring cost decline as tick size decreases.

Dark Pool Trading and Information Acquisition

Theory suggests that dark pools may facilitate or discourage information acquisition. We find that more dark pool trading leads to greater information acquisition. We measure information acquisition using stock price dynamics around earnings announcements. To overcome endogeneity concerns, we exploit a large exogenous decrease to dark pool trading that results from the implementation of the Security and Exchange Commission’s (SEC’s) Tick Size Pilot Program. The results cannot be explained by lit venue liquidity, algorithmic trading, or informational efficiency. A battery of additional tests, such as documenting a shift in SEC EDGAR searches, supports the information acquisition interpretation.

Tick Size and Price Reversal after Order Imbalance

It is well known that intraday returns tend to reverse the following intraday period, conditional on excess buying pressure on the bid or ask side. This suggests that liquidity providers “overreact” to order imbalance (OIB) by initially altering quotes so much that a negative autocorrelation is seen in mid-price returns. We investigate under which circumstances this behavior is most common. Specifically, it seems the tick size augments “OIB-reversal”. However, if the tick size is binding for much of the trading day, it has the opposite effect of censoring such reversals. In addition, if market liquidity is high, the reversal becomes more frequent.

Estimating the effect of transaction costs using tick-size as a proxy

A method is proposed for estimating the effect of transaction costs on volatility, using the tick-size as proxy. The method follows three steps: 1) collect only the cases where the tick-size changes from one regime to another, 2) estimate the effect with and without the order book size, and 3) use local data on tick-size and volatility, but instruments from international markets. The first step handles stationarity and dependence. The second step is used to infer the effect of a symmetric transaction cost as tick-size is a revenue and not a cost for liquidity providers. A regression with and without the order book may therefore indicate how much this asymmetry is likely to affect the result. The third step handles endogeneity. The method is applied on intraday data from the Norwegian Stock Exchange (OSE). The results show that both the tick-size and inferred transaction costs seems to have surprisingly little impact on volatility.

Dark Trading and Post-Earnings-Announcement Drift

Both theory and evidence are mixed regarding the impact on prices of trading on “dark” venues partially exempt from National Market System requirements. Theory predicts that price discovery improves as dark venues siphon noisy uninformed trades, but increased adverse selection reduces liquidity. Empirical studies, which focus on intraday inefficiency, also find contradictory results. We extend that literature to investigate the impact of dark trading on a long-standing inefficiency based on under-reaction to quarterly earnings. We study a randomized controlled trial created by the “trade-at” rule of the Securities and Exchange Commission’s Tick Size Pilot Program that exogenously shocks dark trading. We supplement that with ordinary least squares and two-stage least squares regressions on a more representative Compustat/Center for Research in Security Prices sample. All our results suggest that under-reaction increases with dark trading, consistent with reduced liquidity limiting arbitrage. We contribute to the literature on dark trading and inefficient processing of accounting disclosures, highlighting the role of advances in trading technology. This paper was accepted by Brian Bushee, accounting.

Impact of COVID-19 on Performance Evaluation Large Market Capitalization Stocks and Open Innovation

This research is an event study that evaluates the performance of large market capitalization shares using a performance model that is adjusted to risks due to the COVID-19 outbreak. The study measured the performance of large market capitalization stocks which represented each tick size on the Indonesian Stock Exchange during the COVID-19 pandemic using the Sharpe Index, the Treynor Ratio, and Jensen’s Alpha. The sample selection used a purposive sampling technique and 24 stocks were selected as samples in the study. We used the daily closing price of stocks, the Indonesia composite index, and average risk-free rate return (BI rate). By using Jensen’s Alpha, this study found that FREN was the highest beta with a value of 1.8189, indicating that the index was an effective and well-diversified stock. FREN is low priced and the highest market capitalization stock in its tick size (third tier stocks). Jensen’s Alpha is good for measuring the performance of large capitalization and low-priced stocks. There are eight stocks that always have negative values in each method of measuring stock performance, which indicates that these stocks underperformed during COVID-19.