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.     

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.     

Price limit performance: evidence from transactions data and the limit order book

In recent years, organized stock exchanges with daily price limits adopted wider limits as narrower limits were criticized for jeopardizing market efficiency. This study examines the impact of a wide price limit on price discovery processes, using data from the Kuala Lumpur Stock Exchange. Specifically, examined is the impact of daily price limits on (i) information asymmetry; (ii) arrival rates of informed traders; and (iii) order imbalance. Using both trade-to-trade transaction data and the limit order book, we compile evidence that price limits do not improve information asymmetry, delays the arrival of informed traders, and exacerbates order imbalance. These results suggest that price limits on individual securities do not improve price discovery processes but impose serious costs even when the limit band is as wide as 30%.     

Strategic trading and learning about liquidity

Many practitioners point out that the speculative profits of institutional traders are eroded by the difficulty in gauging the price impact of their trades. In this paper, we develop a model of strategic trading where speculators face such a dilemma because of incomplete information about time-varying market liquidity. Unlike the competitive market makers that they trade against, informed traders do not know the distribution of liquidity (“noise”) trades. Instead, they have to learn about liquidity from past prices and trading volume. This learning implies that strategic trades and market statistics such as informational efficiency are path-dependent on past market outcomes. Our paper also has normative implications for practitioners.     

Whose trades convey information? Evidence from a cross-section of traders

This paper contributes empirically to our understanding of informed traders. It analyzes traders’ characteristics in a foreign exchange electronic limit order market via anonymous trader identities. We use six indicators of informed trading in a cross-sectional multivariate approach to identify traders with high price impact. More information is conveyed by those traders’ trades which—simultaneously—use medium-sized orders (practice stealth trading), have large trading volume, are located in a financial center, trade early in the trading session, at times of wide spreads and when the order book is thin.     

Price Discovery in the Treasury‐Bill When‐Issued Market

When‐issued (i.e., forward) trading in T‐bills yet to be auctioned provides a unique environment for examining price discovery. Because T‐bills are auctioned in a sealed‐bid process, when‐issued traders cannot observe the spot market price. Yet the forward price must ultimately converge on the auction outcome price. Our results indicate that traders in the when‐issued market “discover” the ultimate auction price. Little evidence is found that standard order flow variables contribute to price discovery. Instead, the ability to observe a few trades with relatively small volume in the when‐issued market is sufficient to discover the auction price resulting from the sealed‐bid process.     

Market Statistics and Technical Analysis: The Role of Volume

We investigate the informational role of volume and its applicability for technical analysis. We develop a new equilibrium model in which aggregate supply is fixed and traders receive signals with differing quality. We show that volume provides information on information quality that cannot be deduced from the price statistic. We show how volume, information precision, and price movements relate, and demonstrate how sequences of volume and prices can be informative. We also show that traders who use information contained in market statistics do better than traders who do not. Technical analysis thus arises as a natural component of the agents' learning process.     

On the theory of market information efficiency

This paper discusses the concept of market information efficiency and demonstrates the following: As the number of traders who participate in the market becomes large, the variations in the price of a security caused by the variations in traders' beliefs make the market price vary as if traders all knew the ‘true’ distribution of returns on the security. The empirical implications of the analysis are also explored.     

Are tightened trading rules always bad? Evidence from the Chinese index futures market

This paper investigates the impact of tightened trading rules on the market efficiency and price discovery function of the Chinese stock index futures in 2015. The market efficiency and the price discovery of Chinese stock index futures do not deteriorate after these rule changes. Using variance ratio and spectral shape tests, we find that the Chinese index futures market becomes even more efficient after the tightened rules came into effect. Furthermore, by employing Schwarz and Szakmary [J. Futures Markets, 1994, 14(2), 147–167] and Hasbrouck [J. Finance, 1995, 50(4), 1175–1199] price discovery measures, we find that the price discovery function, to some extent, becomes better. This finding is consistent with Stein [J. Finance, 2009, 64(4), 1517–1548], who documents that regulations on leverage can be helpful in a bad market state, and Zhu [Rev. Financ. Stud., 2014, 27(3), 747–789.], who finds that price discovery can be improved with reduced liquidity. It also suggests that the new rules may effectively regulate the manipulation behaviour of the Chinese stock index futures market during a bad market state, and then positively affect its market efficiency and price discovery function.     

国外高频交易的发展现状及启示

证券市场上的高频交易模式大体上分为四类:订单拆分策略、做市交易策略、定量化交易策略和其他策略。研究发现:(1)高频交易降低了买卖价差,提高了市场流动性,而并没有增加市场波动率,甚至反而可能降低了市场波动率;(2)没有发现高频交易者存在系统性抢单行为(并不排除有特定高频交易者存在此类行为);(3)学术研究认为高频交易有导致市场风险的可能性,但是事件调查大多认为高频交易不是引发市场风险的罪魁祸首。本文认为,对高频交易的监管应该注重抓住重点区别对待,以维护公平、透明、高效的市场秩序。     

Trading performance and market efficiency: Evidence from algorithmic trading

In India, National Stock Exchange directly identifies algorithmic trading participation. Algorithmic traders possess intraday market timing skills. Results are not motivated by extreme short-term signals or transitory price trading. Magnitude of market timing performance in cross-sectional group of traders shows that they earn profit across all the cases, and maximize while providing liquidity. Volume-weighted-average-price decomposition analysis reports algorithmic traders earn profits through intraday market timing performance for five-minute and one-minute intervals, and it is higher compared to short-term market timing performance across all trader groups. Order imbalance and price delay regressions show that algorithmic trading significantly improves price efficiency.     

Microstructure-based manipulation: Strategic behavior and performance of spoofing traders

We examine how investors strategically spoof the stock market by placing orders with little chance of being executed, but which mislead other traders into thinking there is an imbalance in the order book. Using the complete intraday order and trade data of the Korea Exchange (KRX) in a custom data set identifying individual accounts, we find that investors strategically placed spoofing orders which, given the KRX's order-disclosure rule at the time, created the impression of a substantial order book imbalance, with the intent to manipulate subsequent prices. This manipulation, which made use of specific features of the market microstructure, differs from previously studied forms of manipulation based on information or transactions. Roughly half of the spoofing orders were placed in conjunction with day trading. Stocks targeted for manipulation had higher return volatility, lower market capitalization, lower price level, and lower managerial transparency. We also find that spoofing traders achieved substantial extra profits. The frequency of spoofing orders decreased drastically after the KRX altered its order-disclosure rule.     

Do market prices reveal the decision models of sophisticated investors?: Evidence from the laboratory

If security prices are fully revealing, then all public information should be reflected in prices, and unsophisticated traders may be able to learn how various types of information affect security valuation by observing prices. A series of laboratory asset markets was conducted to examine whether unsophisticated traders are able to learn to evaluate publicly released information by trading with and observing trades made by a sophisticated trader who knows the valuation implications of the information. We find that unsophisticated traders who participate in an asset market with a sophisticated trader show significant improvement in their ability to use public information on a subsequent price estimation task. Conversely, a control group consisting only of unsophisticated traders shows no improvement. We conclude that market prices convey the sophisticated trader’s private information in a manner that permits unsophisticated investors to learn the stock price implications of a public information release.     

Performance and learning in an ambiguous environment: A study of cryptocurrency traders

We investigate the performance and learning ability of traders in an environment governed by ambiguity, such as the cryptocurrency market. Using a profit decomposition methodology, we find significant cross-sectional and temporal heterogeneity in performance. Traders do not learn to progressively increase the magnitude of returns; however, they are able to improve on their ability to realise profits as a mechanism of adaptation to survive through ambiguity. This adaptation increases as traders progress through their career. Moreover, we find evidence in support of the gambler’s fallacy. We argue that learning in ambiguous environments has limitations, allowing traders primarily to survive.     

Chasing noise

We present a simple model in which rational but uninformed traders occasionally chase noise as if it were information, thereby amplifying sentiment shocks and moving prices away from fundamental values. In the model, noise traders can have an impact on market equilibrium disproportionate to their size in the market. The model offers a partial explanation for the surprisingly low market price of financial risk in the spring of 2007.     

The distribution of information in speculative markets: a natural experiment

We use a unique natural experiment to shed light on the distribution of information in speculative markets. In June 2011, Betfair – a UK betting exchange – levied a tax of up to 60% on all future profits accrued by the top 0.1% of profitable traders. Such a move appears to have driven at least some of these traders off the exchange, taking their information with them. We investigate the effect of the new tax on the forecasting capacity of the exchange (our measure of the market's incorporation of information into the price). We find that there was scant decline in the forecasting capacity of the exchange – relative to a control market – suggesting that the bulk of information had hitherto been held by the majority of traders, rather than the select few affected by the rule change. This result is robust to the choice of forecasting measure, the choice of forecasting interval, and the choice of race type. This provides evidence that more than a few traders are typically involved in the price discovery process in speculative markets.     

Does news travel slowly before a market crash? The role of margin traders

We investigate how investor overconfidence and attention affect market efficiency around the 2015 Chinese stock market crash. We find that the price delay before the crash is about twice the price delay after the crash. Investors become more sensitive to market movements after the crash. Price delays are larger on market down-days than on up-days before the crash, but the differences are insignificant between up- and down-days after the crash, indicating that negative information travels slowly only when investors are overconfident. Margin traders follow market trends and intensify the pyramiding and de-pyramiding effects caused by market sentiment change.     

Trading around macroeconomic announcements: Are all traders created equal?

This paper examines the effects of macroeconomic announcements on equity index markets using high frequency transactions data for the regular and E-mini S&P 500 index futures contracts. For ten types of announcements that significantly affect prices, we analyze the price adjustment process and the trading patterns of exchange locals and off-exchange customers around the announcements. We find a large increase in trading activity immediately after the announcement. The results also show that during this initial surge in trading activity, locals are able to time their trades better than off-exchange traders even when locals do not have the advantage of access to the order flow. The trading strategy followed by exchange locals in the first 20 seconds after the announcement tends to be profitable, while off-exchange traders tend to make losing trades over the same time period. These results lend evidence that local traders tend to react to the macroeconomic information faster than off-exchange traders.     

The Market Evaluation of Information in Directors' Trades

The purpose of this paper is to examine the propensity, characteristics and performance of directors' trades. Consistent with prior research we show that on average, directors outperform the market. However, we also find that there exist a large number of trades which do not share these abnormal share price returns and consequently have little information content. This has important consequences for market participants who use director trading activity as a signal for their own trading strategies. Using different measures of directors' trades based on trade characteristics, we report that purchases by directors are more informative than sales. In addition, the number of directors trading within a twenty day window and the percentage of the directors' holding that is being traded are both important factors in the abnormal share price performance following the trade.     

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.