An Empirical Analysis of Quoted Depths of NYSE and Amex Stocks

In this study, we find strong intertemporal/cross-sectional correlations between quoted depths and various security characteristics for a sample of stocks listed on the NYSE and Amex. Our empirical results indicate that although specialists are generally unable to discern insider trading as it occurs, they cope with insider trading by posting smaller depths for stocks with a greater tendency of insider trading. Empirical evidence also indicates that specialists/limit order traders quote smaller depths for riskier stocks to limit potential losses to better-informed traders. In addition, we find that specialists/limit order traders quote larger depths for stocks with greater trading volume, larger market capitalization, and higher competition. Overall, our findings suggest that depths are an important means through which specialists and limit order traders deal with the adverse selection problem, order processing problem, and competition.     

Daily income target effects: Evidence from a large sample of professional commodities traders

We provide evidence of rational reference-dependent preferences in the proprietary trading of professional traders. We find increased trading effort and risk taking by traders following morning losses. Further analysis provides no evidence of a deterioration in trading performance subsequent to losses, as neither risk-adjusted performance nor trade execution appear to be negatively affected by prior losses. The evidence supports the existence of rational reference-dependent preferences in the form of trader daily income targets: these professional traders exhibit increased work effort subsequent to abnormal morning losses. The evidence is inconsistent with the alternative explanation of costly loss aversion.     

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.     

What do retail FX traders learn?

What is the benefit of experience? Using data from a leading trading platform we find no evidence that retail FX traders learn to trade better, but they do appear to learn about their innate abilities as traders and respond appropriately. In particular, following an unsuccessful trading day, they are more likely to cease trading, to trade smaller amounts and to trade less frequently. These effects are stronger for younger and less experienced traders who might be expected to have more to learn than older, more experienced traders. As regards learning through experience, surprisingly we find that more seasoned traders demonstrate a slight decline in performance once we account for the endogenous decision to cease trading, and even very experienced traders consistently lose money.     

Neoclassical finance,behavioral finance and noise traders: A review and assessment of the literature

While mainstream neoclassical finance ignores the role played by noise traders, a significant amount of empirical evidence is available to show that noise traders are active market participants and that their participation gives rise to market anomalies. Unlike neoclassical finance, behavioral finance allows for market inefficiency on the grounds that market participants are subject to common human errors that arise from heuristics and biases. In this paper we review the literature on the behavior of noise traders and analyze the consequences of their presence in the market, starting with a distinction between neoclassical finance and behavioral finance. We identify the market anomalies that provide evidence for the tendency of markets to trade at irrational levels, demonstrate how noise trading is related to some market fundamentals, and describe the models used to quantify noise trader risk.     

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.     

Individual Investors and Volatility

We show that retail trading activity has a positive effect on the volatility of stock returns, which suggests that retail investors behave as noise traders. To identify this effect, we use a reform of the French stock market that raises the relative cost of speculative trading for retail investors. The daily return volatility of the stocks affected by the reform falls by 20 basis points (a quarter of the sample standard deviation of the return volatility) relative to other stocks. For affected stocks, we also find a significant decrease in the magnitude of return reversals and the price impact of trades.     

Retail investor attention and the limit order book: Intraday analysis of attention-based trading

We are the first to examine how intraday changes in retail investor attention, measured by hourly Google searches, affect trading activity and informativeness of trades. High levels of Google search activity are followed in the next hour by more intensive trading in all stocks. The increased trading activity is initiated by retail investors as evidenced by the reduced size of new orders. After googling a company, retail investors do not become informed in the traditional sense; rather, they act as noise traders, who mistake noise for information, as their orders are picked off by truly informed traders.     

WHO ARE THE NOISE TRADERS?

Closed‐end funds often trade at a discount to net asset value. Previous research suggests that the positive correlation in discounts is associated with investor sentiment that causes systematic mispricing by noise traders. We use a newly available sample of daily fund valuations to examine the relation between intraday trading activity and discount changes. Contrary to the assumption that retail investors are noise traders, we find no relation between discount changes and the order‐flow imbalances of individual investors. Large daily discount changes are associated with institutional trading, and this may reflect the price inelasticity of closed‐end fund shares.     

An intertemporal capital asset pricing model with heterogeneous expectations

This paper extends the intertemporal capital asset pricing model (ICAPM) to integrate the heterogeneous trading behavior of three groups of investors; rational utility maximizers, positive feedback, or momentum, traders, and fundamental traders. Using several contemporary fundamental factors to proxy for the latter of these investors’ trading patterns, the interaction of these three groups of investors is explored in the G-7 markets using monthly stock market prices. There is no evidence that positive feedback traders are present in the sample data. Fundamental traders are however observable. This finding suggests that although positive feedback traders may drive stock prices in the short-run, as is typically observed in higher frequency data, fundamental traders likely play a role in pushing prices back to their fundamental value in the longer-run.     

Day Trader Behavior and Performance: Evidence from Taiwan Futures Market

By using a unique data from the Taiwan futures market to identify each trader’s trading records and focusing on the high-frequency day traders who trade at least 90 days over the sample year, this study closely examines their behaviors and performance. Day traders’ performances are “risk-adjusted” and analyzed to identify behavioral biases and the resulting impact on performance. There is no evidence found that trading too much is detrimental to investment performance. The high-frequency day traders are more aware of the danger of behavioral biases and are as a result less prone to the disposition effect. Contrary to expectations, day traders in my study are shown to be non-loss averse. Most of our sample except for the highest performance quintile follow a momentum strategy.     

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.     

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.     

INFORMATION ASYMMETRY AND OPTIONS TRADING

This paper demonstrates that options trading does not have a uniform impact on the volatility of underlying stocks. Although uninformed traders are able to hedge the risk of underlying stocks by maintaining opposite positions in the options market, informed traders hold outright options positions to capitalize on their information. This hedging behavior tends to reduce noise in the stock market, whereas the speculating behavior tends to generate noise in the stock market. As a result, stocks that were originally volatile, i.e., traded primarily by uninformed traders, will be stabilized by the introduction of options. Conversely, stocks that were more stable become destabilized by options trading.     

Retail investors exonerated: the case of the January effect

We dispel the belief that the January effect is due to retail investor trading. Previous studies suggest that retail investors, affected by behavioural biases and disproportionally invested in small capitalization stocks, are the source of the January effect. Furthermore, the literature regards retail investor trading and the tax‐loss selling hypothesis as essentially the same explanation. We separate tax implications and market capitalization to show that retail traders are not the cause of the January effect. Our study is an important direct test of whether retail trading causes market anomalies.     

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.     

The information content of retail investors’ order flow

In this paper, we provide evidence that the trading activity of small retail investors carries significant genuine information that can be exploited for the short-term out-of-sample forecasting of foreign exchange rates. Our findings are based on a unique dataset of around 2000 retail investors from the OANDA FXTrade electronic trading platform. Our results are consistent with the view that in the foreign exchange market private information is highly dispersed, but can be extracted by observing customer order flow. Previous studies, however, focused on the information content of costumer order flow of dealers in the interbank market, whose clients are themselves large institutional and professional investors. Our study is the first that analyzes a crowd of small retail investors and shows that even the trading activity of these investors contains, on aggregate, important non-public information that can be exploited for short-term exchange rate forecasting. Our findings lead us to conjecture that retail investors (on aggregate) are not pure noise traders but process dispersed information at least partially in a similar way as large institutional investors and hence place their orders accordingly.     

Stock market dynamics with rational liquidity traders

In the Kyle (1985) finite horizon model of stock market dynamics with a trader who holds long-lived information, informed trading intensities rise with time, and the slopes of the equilibrium price schedules fall. This paper shows that this result depends crucially on the irrational liquidity trader assumption. We replace the irrational noise traders with a sequence of rational, risk averse, liquidity traders who receive endowment shocks to their holdings of the risky asset. We demonstrate that unless liquidity traders are sufficiently risk averse, the slope of equilibrium price schedule rises over time, while informed trading intensities fall. In particular, Kyle's result holds only when liquidity traders are so risk averse that they ‘over-rebalance’ their portfolio's holdings of the risky asset, so that their final holdings of the risky asset have the opposite sign of their initial position.     

Pick Your Poison—Fragmentation or Market Power? An Analysis of RegNMS,High Frequency Trading,and Securities Market Structure

The publication of Michael Lewis's has intensified an already contentious debate over high frequency trading (HFT). But the causes that have given rise to HFT are more complicated—and the general economic consequences far more positive—than at least the popular accounts (including Lewis's own) of the book would suggest. While directing much of its attention to the powerful computers and “predatory” potential of HFT, the “media” version of Lewis's book has all but ignored the fundamental driver of such activity: the implementation in 2007 of SEC Regulation NMS, which required all exchanges to direct their orders to the exchanges with the best prices. Before RegNMS, U.S. equity trading was largely dominated by NYSE and Nasdaq. The major exchanges' effective “ownership” of their order flow gave exchange specialists significant edges in trading. RegNMS has resulted in the proliferation of competing stock exchanges, which in turn has dramatically reduced both trading costs and the economic franchise value enjoyed by institutional traders associated with the previously dominant exchanges. The balance of evidence strongly indicates that the cost of trading has declined for retail traders and investors. The big losers have been the previously advantaged wholesale traders. HFT is simply one of the outcomes of the new, more competitive trading environment created by Regulation NMS.     

The turn of the month effect in India: A case of large institutional trading pattern as a source of higher liquidity

We examine (via parametric and non-parametric tests) the turn of the month effect in the returns of various, size-conditioned Indian stock indices, across time, in up and down markets and independent of other seasonal anomalies. We find little support for the payday and the US macroeconomic news announcements hypotheses. Instead, we show that institutional traders (foreign and domestic) significantly increase their trading volumes (on the buying side) at month end, potentially pushing prices up. There is no evidence of a similar behavior on the retail side. We suggest this to be a major cause of the observable TOM effect in India.