Investor type trading behavior and trade performance: Evidence from the Thai stock market

This paper examines the trading behavior and decomposes the trading performance of foreign, individual and institutional investors as well as proprietary traders in a dynamic emerging stock market, the Stock Exchange of Thailand. Foreign investors follow a positive feedback, momentum strategy and are good short term market timers but have poor security selection performance in poor markets, thus suggesting that they have a macro (market timing) but not a micro (security selection) informational advantage relative to local investors. Institutions and proprietary traders have poor security selection trading performance. Individuals display herding behavior and have fairly good security selection performance, but individual investors appear to compensate proprietary traders for the provision of short term liquidity by proprietary traders, so individuals' security selection gains are canceled out by market timing losses.     

Option trading and individual investor performance

This paper examines the impact of option trading on individual investor performance. The results show that most investors incur substantial losses on their option investments, which are much larger than the losses from equity trading. We attribute the detrimental impact of option trading on investor performance to poor market timing that results from overreaction to past stock market returns. High trading costs further contribute to the poor returns on option investments. Gambling and entertainment appear to be the most important motivations for trading options while hedging motives only play a minor role. We also provide strong evidence of performance persistence among option traders.     

Do Proprietary Algorithmic Traders Withdraw Liquidity during Market Stress?

We investigate the role of proprietary algorithmic traders in facilitating liquidity in a limit order market. Using order‐level data from the National Stock Exchange of India, we find that proprietary algorithmic traders increase limit order supply following periods of both high short‐term stock‐specific volatility and extreme stock price movement. Even following periods of high marketwide volatility, they do not decrease their supply of liquidity. We define orders from high‐frequency traders as a subclass of orders from proprietary algorithmic traders that are revised in less than three milliseconds. The behavior of high‐frequency trading mimics the behavior of its parent class. This is inconsistent with the theory that fast traders leave the market when stress situations arise, although their limit‐order‐supplying behavior becomes weaker when the increase in short‐term volatility is more informational than transitory. Agency algorithmic traders and nonalgorithmic traders behave opposite to proprietary algorithmic traders by reducing the supply of liquidity during stress situations. The presence of faster traders in the market possibly instills the fear of adverse selection in them. We document that the order imbalance of agency algorithmic traders is positively related to future short‐term returns, whereas the order imbalance of proprietary algorithmic traders is negatively related to future short‐term returns.     

Overconfident individual day traders: Evidence from the Taiwan futures market

A specific day-trading policy in Taiwan futures market allows an investigation of the performance of day traders. Since October 2007, investors who characterize themselves as “day traders” by closing their day-trade positions on the same day enjoy a 50% reduction in the initial margin. Because we can identify day traders ex ante, we have a laboratory to explore trading behavior without the contamination of potential behavioral biases. Our results show that the 3470 individual day traders in the sample incur on average a significant loss of 61,500 (26,700) New Taiwan dollars after (before) transaction costs over October 2007–September 2008. This implies that day traders are not only overconfident about the accuracy of their information but also biased in their interpretations of information. We also find that excessive trading is hazardous only to the overconfident losers, but not to the winners. Last, we provide evidence that more experienced individual investors exhibit more aggressive day trading behavior, although they do not learn their types or gain superior trading skills that could mitigate their losses.     

Who is the more overconfident trader? Individual vs. institutional investors

Guided by the Gervais and Odean (2001) overconfident trading hypothesis, we comprehensively investigate the trading behavior of individual vs. institutional investors in Taiwan in an attempt to identify who is the more overconfident trader. Conditional on the various states of the market, on market volatility, and on the risk level of the securities they trade, we find that both individual and institutional investors trade more aggressively following market gains in bull markets, in up-market states, in up-momentum market states, and in low-volatility market states and that only individual investors trade more in riskier securities following market gains. More importantly, we find that individual investors trade more aggressively following market gains in the three conditional states of the market and in high-volatility market states than institutional investors. Also, individual investors trade more in relatively riskier securities following gains than institutional investors. These findings provide evidence that individual investors are more overconfident traders than institutional investors.     

Investor sentiment and feedback trading: Evidence from the exchange-traded fund markets

This paper extends the standard feedback trading model of Sentana and Wadhwani (1992) by allowing the demand for shares by feedback traders to depend on sentiment. Our empirical analysis of three largest Exchange-Traded Fund (ETF) contracts in the U.S. suggests that there is a significant positive feedback trading in these markets and the intensity of which is generally linked to investor sentiment. Specifically, the level of feedback trading tends to increase when investors are optimistic. In addition, we find that the influence of sentiment on feedback trading varies across market regimes. These results are consistent with the view that feedback trading activity is largely caused by the presence of sentiment-driven noise trading. Overall, the findings are important in understanding the role of sentiment in investment behaviour and market dynamics and are of direct relevance to the regulators and investors in ETF markets.     

Futures Market Sentiment and Institutional Investor Behavior in the Spot Market: The Emerging Market in Taiwan

This paper investigates whether and how futures market sentiment and stock market returns heterogeneously affect the trading activities of institutional investors in the spot market in Taiwan. Our empirical results suggest that foreign investors are net sellers whenever futures market sentiment is bullish and net buyers when investor sentiment is bearish. The two types of domestic institutional investors have poor sentiment timing abilities and the price-pressure effect may account for the behavioral differences among institutional investors. In addition, all three institutional investors are momentum traders. Nevertheless, the momentum trading of foreigners is consistent with an information-based model and that of two local institutional investors, as behavior-based models suggest. This indicates that the same trading momentum strategy can lead to different outcomes for different investors, and both information- and behavior-based momentum trading can exist contemporaneously in the Taiwanese stock market.     

Earnings Announcements: Good News for Institutional Investors and Short Sellers

In this paper, we consider the trading behavior of institutional investors and short sellers around earnings announcements. The results suggest that institutional investors, and to a lesser extent short sellers, successfully anticipate earnings news. In the period immediately after the earnings announcement, both types of traders are active in the market and trade in response to the earnings announcement. In particular, short sellers are quick to increase their short positions when a company releases bad news. Institutional traders also trade in response to the news; however, they take longer to react.     

Momentum,Reversal, and Uninformed Traders in Laboratory Markets

We report the results of three experiments based on the model of Hong and Stein (1999) . Consistent with the model, the results show that when informed traders do not observe prices, uninformed traders generate long‐term price reversals by engaging in momentum trade. However, when informed traders also observe prices, uninformed traders generate reversals by engaging in contrarian trading. The results suggest that a dominated information set is sufficient to account for the contrarian behavior observed among individual investors, and that uninformed traders may be responsible for long‐term price reversals but play little role in driving short‐term momentum.     

Does proprietary day trading provide liquidity at a cost to investors?

Capitalizing on the special case of Malaysia in which proprietary day traders (PDTs) are mandated to boost liquidity and the recent availability of trading data, this paper empirically examines the liquidity effect of proprietary day trading. Using daily data spanning October 2012 to June 2018, we find evidence that PDTs' trade volume is associated with higher aggregate liquidity in the Malaysian stock market, which can be attributed to the theoretical channel of intense competition among informed traders. However, such improved liquidity comes at a cost to investors, as proprietary day trading is found to be associated with higher conditional volatility and conditional skewness of closing percent quoted spreads. The former is due to the exchange-imposed immediacy for PDTs to close their open positions, whereas the latter can be attributed to the exclusive rights granted to PDTs to engage in intraday short selling.     

Prospect theory and trading patterns

Reference dependence, loss aversion, and risk seeking for losses together comprise the preference-based component of prospect theory that sets its value function apart from the standard risk-aversion model. Using an elasticity analysis, we show that this distinctive preference component serves to underpin negative-feedback trading propensities, but cannot manifest itself in behavior directly or holistically at the individual-choice level. We then propose and demonstrate that the market interaction between prospect-theory investors and regular CRRA investors allows this preference component to dominate in equilibrium behavior and hence helps to reestablish the intuitive link between prospect-theory preferences and negative-feedback trading patterns. In the model, the interaction also reconciles the contrarian behavior of prospect-theory investors with asymmetric volatility and short-term return reversal. The results suggest that prospect-theory preferences can lead investors to behave endogenously as contrarian noise traders in the market interaction process.     

Intraday trading volume and international spillover effects

The objective of this paper is to explore whether lagged trading activity in one market contributes to the return and volatility process in other markets, using 5-min concurrent data from German and British equity market. Our results lend support to our initial premise that if international investors have access to the same information set as domestic traders, then after observing foreign trading activity, market makers adjust prices to reflect their expectation of the security value, conditional upon all available information, including prior trades. Our findings clearly indicate that intraday trading volume contains predictive power for cross-border return and volatility processes. Moreover, these volume effects are found to be asymmetric in the sense that the impact of positive volume changes upon foreign stock market volatility is greater than is the impact of negative changes.     

The price discovery role of day traders in futures market: Evidence from different types of day traders

Using proprietary account-level transaction data in the futures market where day traders are self-declared ex ante, this study investigates whether day traders enhance price discovery at the market level. From a natural classification of day traders, we find that heterogeneous day traders have differential effects on price discovery. Self-declared day traders, who benefit from low margin requirement, do not improve price discovery measured by information share. In contrast, non-declared traders, who are not self-declared as day traders, improve price discovery. Their positive impacts on price discovery are particularly significant during periods of high volatility and arrival of new information. Overall, a margin stimulating policy may encourage more day trading, but may also attract overconfident investors, especially inexperienced ones, and who do not enhance price discovery.     

Professional trader discipline and trade disposition

Recent evidence indicates irrational behavior among retail investors. They hold onto losses and sell winners in a manner consistent with the disposition effect. Market professionals often use the term “discipline” to indicate trading strategies that minimize potential behavioral influences. We investigate the nature of trading discipline and whether professional traders are able to avoid the costly irrational behaviors found in retail populations. The full-time traders in our sample hold onto losses significantly longer than gains, but we find no evidence of costs associated with this behavior. The successful floor futures traders in our sample exhibit trading behavior characterized as rational and disciplined. Moreover, measures of relative trading discipline have predictive power for subsequent trading success.     

Front‐Running Scalping Strategies and Market Manipulation: Why Does High‐Frequency Trading Need Stricter Regulation?

Regulators continue to debate whether high‐frequency trading (HFT) is beneficial to market quality. Using Strongly Typed Genetic Programming (STGP) trading algorithm, we develop several artificial stock markets populated with HFT scalpers and strategic informed traders. We simulate real‐life trading in the millisecond time frame by applying STGP to real‐time and historical data from Apple, Exxon Mobil, and Google. We observe that HFT scalpers front‐run the order flow, resulting in damage to market quality and long‐term investors. To mitigate these negative implications, we propose batch auctions every 30 milliseconds of trading.     

Do Behavioral Biases Affect Prices?

This paper documents strong evidence for behavioral biases among Chicago Board of Trade proprietary traders and investigates the effect these biases have on prices. Our traders appear highly loss‐averse, regularly assuming above‐average afternoon risk to recover from morning losses. This behavior has important short‐term consequences for afternoon prices, as losing traders actively purchase contracts at higher prices and sell contracts at lower prices than those that prevailed previously. However, the market appears to distinguish these risk‐seeking trades from informed trading. Prices set by loss‐averse traders are reversed significantly more quickly than those set by unbiased traders.     

Short-selling,margin-trading,and stock liquidity: Evidence from the Chinese stock markets

This paper examines the impacts of two forms of leveraged trading—margin trading and short selling—on the trading liquidity of individual stocks in China. We find that trading liquidity for relevant stocks generally improves after restrictions on leveraged trading are removed. However, margin trading and short selling have opposite impacts on liquidity. During ordinary periods, margin trading benefits liquidity, whereas short selling damages liquidity; however, during market downturns, their roles are reversed. We also provide evidence suggesting that short sellers are informed traders in China and that short selling reduces stock liquidity because of the increased risk of adverse selection faced by uninformed traders.     

Locals, foreigners, and multi-market trading of equities: Intraday evidence from Thailand

We study stock market orders and trades in a developing country, Thailand, where foreign ownership limits partially segment local and foreign investors into two distinct markets. Some foreigners forgo voting rights and distributions to trade on the “local board”, while some locals forgo such benefits and pay a price premium to trade on the “foreign board”. Regardless of nationality, these cross-market traders typically submit orders when liquidity is high, fill orders at relatively beneficial prices, exploit patterns in stock prices across markets, display profitable holding-period returns, and enhance price discovery. This suggests that skilled, informed trading that affects market quality does not depend on trader nationality.     

Can commodity futures be profitably traded with quantitative market timing strategies?

Quantitative market timing strategies are not consistently profitable when applied to 15 major commodity futures series. We conduct the most comprehensive study of quantitative trading rules in this market setting to date. We consider over 7000 rules, employ two alternative bootstrapping methodologies, account for data-snooping bias, and consider different time periods. We cannot rule out the possibility that trading rules compliment some other trading strategy or that some traders may have success using a specific rule on its own, but we do conclusively show that none of these rules beat the market any more than expected given random data variation.     

The trading behavior of institutions and individuals in Chinese equity markets

This paper employs a unique data set to analyze the trading behavior of 4.74 million individual and institutional investors across Mainland China. Results show that groups of individual investors with varying trade values (as proxies for wealth levels) engage in different trading strategies. Chinese institutions are momentum investors, while less wealthy Chinese individual investors at large are contrarian investors. The results also indicate that a small group of wealthiest Chinese individuals tend to behave like institutions when they buy stocks, and behave like less wealthy individuals when they sell. Furthermore, only the trading activities of institutions and of wealthiest individuals can affect future stock volatility, but those of Chinese individual investors at large have no predictive power for future stock returns.