The impact of algorithmic trading on the market quality in the stock exchange of Thailand
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2019
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2562
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eng
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235 leaves
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National Institute of Development Administration. Library and Information Center
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Pavinee Hassavayukul (2019). The impact of algorithmic trading on the market quality in the stock exchange of Thailand. Retrieved from: https://repository.nida.ac.th/handle/662723737/6419.
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The impact of algorithmic trading on the market quality in the stock exchange of Thailand
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Abstract
This dissertation aims to study how the rising algorithmic trading activities in
the Stock Exchange of Thailand affects the market quality. I conducted three researches
to investigate the impact of algorithmic trading. One is on the impact of algorithmic
trading on volatility. Second is on the effect of algorithmic trading on liquidity and third
is on the relationship between algorithmic trading and price efficiency. Furthermore, I
introduced two new algorithmic trading proxies, namely, algorithmic trading initiated
by institutional and foreign investors to investigate the effect of algorithmic trading
initiated by these two investors on the market quality.
The first research demonstrates how algorithmic trading affects stock volatility
in the Stock Exchange of Thailand. The study is based on SET100 stocks from March
to December 2016. I implemented the OLS regression to establish the relationship
between algorithmic trading and volatility and the two-stage least square regression and
the Granger causality test to verify the causal relationship. I showed that on average,
algorithmic trading proxy is associated and has a causal relationship with negative
volatility. However, individually, algorithmic trading proxy is related to positive
volatility. Similarly, algorithmic trading initiated by institutional and foreign investors
lower realized and range-based volatility. During the volatile period, algorithmic
trading decreases range-based volatility. There is no evidence that algorithmic trading
affects realized volatility in the volatile period.
The second research investigates the relationship between algorithmic trading
and liquidity. In general, I found that algorithmic trading deteriorates liquidity by widening effective spread and lowering share turnover in the short run and reducing
liquidity ratio in the long run. I confirmed the result by using the two-stage least square
and showed that algorithmic trading causes liquidity to decrease by enlarging effective
spread and shrinking share turnover. Information asymmetry is used to explain this
phenomenon. An increase in algorithmic trading imposes adverse selection cost onto
other investors, causing them to decrease their participation. Algorithmic trading
initiated by foreign investors has more profound effect on deteriorating short-run
liquidity while algorithmic trading initiated by institutional has more profound effect
on decreasing long-run liquidity. During the volatile period, algorithmic trading also
associates with lowering liquidity for all measures. The slope coefficient of algorithmic
trading during volatile period is higher than during the whole sample except for the
share turnover. Therefore, algorithmic traders have less effect on lowering share
turnover during the volatile period than during the entire period.
The third research determines whether the rise of algorithmic trading enhances
price efficiency. There is no evidence that algorithmic trading influences price
efficiency. However, when probing further, I found that algorithmic trading initiated by
institutional and foreign investors and their interaction terms decrease pricing error,
facilitating price efficiency. Furthermore, algorithmic trading initiated by foreign
investors has a larger effect on augmenting price efficiency. During the volatile period,
algorithmic trading, on the contrary, decreases price efficiency and enlarges price
errors.
Finally, this dissertation investigates the effect of algorithmic trading on market
quality in detail and provides insightful conclusion for policymakers, regulators and
investors in order to regulate or react to the increase in algorithmic trading strategies in
the Stock Exchange of Thailand.
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Thesis (Ph.D. (Business Administration))--National Institute of Development Administration, 2019