Arbitraging Arbitrageurs

This paper develops a theory of strategic trading in markets with large arbitrageurs. If arbitrageurs are not well capitalized, capital constraints make their trades predictable. Other market participants can exploit this by trading against them. Competitors may find it optimal to lend to arbitrageurs that are financially fragile; additional capital makes the arbitrageurs more viable, and lenders can reap profits from trading against them for a longer time. The strategic behavior of these market participants has implications for the functioning of financial markets. Strategic trading may produce significant price distortions, increase price manipulation, and trigger forced liquidations of large traders.     

Market efficiency and learning in an artificial stock market: A perspective from Neo-Austrian economics

An agent-based artificial financial market (AFM) is used to study market efficiency and learning in the context of the Neo-Austrian economic paradigm. Efficiency is defined in terms of the “excess” profits associated with different trading strategies, where excess is defined relative to a dynamic buy and hold benchmark in order to make a clean separation between trading gains and market gains. We define an Inefficiency matrix that takes into account the difference in excess profits of one trading strategy versus another (signal) relative to the standard error of those profits (noise) and use this statistical measure to gauge the degree of market efficiency. A one-parameter family of trading strategies is considered, the value of the parameter measuring the relative informational advantage of one strategy versus another. Efficiency is then investigated in terms of the composition of the market defined in terms of the relative proportions of traders using a particular strategy and the parameter values associated with the strategies. We show that markets are more efficient when informational advantages are small (small signal) and when there are many coexisting signals. Learning is introduced by considering “copycat” traders that learn the relative values of the different strategies in the market and copy the most successful one. We show how such learning leads to a more informationally efficient market but can also lead to a less efficient market as measured in terms of excess profits. It is also shown how the presence of exogeneous information shocks that change trader expectations increases efficiency and complicates the inference problem of copycats.     

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.     

Hidden Liquidity: Some New Light on Dark Trading

Using a laboratory market, we investigate how the ability to hide orders affects traders’ strategies and market outcomes in a limit order book environment. We find that order strategies are greatly affected by allowing hidden liquidity, with traders substituting nondisplayed for displayed shares and changing the aggressiveness of their trading. As traders adapt their behavior to the different opacity regimes, however, most aggregate market outcomes (such as liquidity and informational efficiency) are not affected as much. We also find that opacity appears to increase the profits of informed traders but only when their private information is very valuable.     

An empirical investigation of large trader market manipulation in derivatives markets

Using account-level transaction data in options and futures markets, we investigate the existence of market manipulation, which is the ability of large traders to trade strategically, impacting prices and making abnormal profits. First, large trader’s option positions have a quantity impact on the underlying asset’s price. Second, large traders generate significantly positive alphas from trading options and futures. Among the different investor types, proprietary dealers generate the largest positive alphas. Third, these abnormal returns are consistent with strategic trading and cross-market manipulation. The evidence supports market manipulation across the options and futures markets, but not within the futures market itself.     

Covered interest arbitrage profits: The role of liquidity and credit risk

We study the profitability of Covered Interest Parity (CIP) arbitrage violations and their relationship with market liquidity and credit risk using a novel and unique dataset of tick-by-tick firm quotes for all financial instruments involved in the arbitrage strategy. The empirical analysis shows that positive CIP arbitrage deviations include a compensation for liquidity and credit risk. Once these risk premia are taken into account, small arbitrage profits only accrue to traders who are able to negotiate low trading costs. The results are robust to stale pricing and the nonsynchronous trading occurring in the markets involved in the arbitrage strategy.     

Strategic Trading When Agents Forecast the Forecasts of Others

We analyze a multi-period model of trading with differentially informed traders, liquidity traders, and a market maker. Each informed trader's initial information is a noisy estimate of the long-term value of the asset, and the different signals received by informed traders can have a variety of correlation structures. With this setup, informed traders not only compete with each other for trading profits, they also learn about other traders' signals from the observed order flow. Our work suggests that the initial correlation among the informed traders' signals has a significant effect on the informed traders' profits and the informativeness of prices.     

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.     

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.     

Learning to be overconfident

We develop a multiperiod market model describing both the processby which traders learn about their ability and how a bias inthis learning can create overconfident traders. A trader inour model initially does not know his own ability. He infersthis ability from his successes and failures. In assessing hisability the trader takes too much credit for his successes.This leads him to become overconfident. A trader's expectedlevel of overconfidence increases in the early stages of hiscareer. Then, with more experience, he comes to better recognizehis own ability. The patterns in trading volume, expected profits,price volatility, and expected prices resulting from this endogenousoverconfidence are analyzed.     

The impact of competition and information on intraday trading

In a dynamic model of financial market trading multiple heterogeneously informed traders choose when to place orders. Better informed traders trade immediately, worse informed delay – even though they expect the market to move against them. This behavior generates intraday patterns with decreasing spreads, decreasing probability of informed trading (PIN), and increasing volume. We predict that policies that foster market entry improve the welfare of uninformed traders and lead to increased market participation by incumbent traders. Technological advances that lead to better signal processing also encourage market participation and increase volume but at the expense of uninformed traders’ welfare.     

Dual Trading in Futures Markets

With dual trading, brokers trade both for their customers and for their own account. We study dual trading and find that customers who are less likely to be informed have higher expected profits with dual trading while customers who are more likely to be informed have higher expected profits without dual trading. We also examine the effects of frontrunning. We test the major empirical implications of our model. Consistent with the model, dual traders earn higher profits than non-dual traders, and customers of dual-trading brokers do better than customers of non-dual-trading brokers.     

Expiration day effects and market manipulation: evidence from Taiwan

In this study, we analyze the expiration day effects of index futures on the cash market in Taiwan, and find that both volatility and trading volume are higher on the final settlement days than on other trading days. We also calculate the volume of open interest for the final settlement of index futures contracts relating to different classes of traders, as well as the profits they earn from their open interest positions. We find that proprietary traders exhibit superior performance whereas foreign investors achieve the worst returns. Our empirical results support the view that the expiration day effects in the Taiwan futures market are at least partially attributable to attempts at ‘marking the close’.     

Strategic insider trading in foreign exchange markets

Inside traders are well-documented to leverage private idiosyncratic information for personal gain in centralized exchanges such as stock markets. Evidence is rare, however, for decentralized and fragmented over-the-counter markets with microstructure properties that make them particularly vulnerable to stealth trading. The 2015 criminal conviction of Hill and Kamay for foreign exchange insider trading is the first in over-the-counter markets. We analyze their actions to show the complex, strategic decision-making of insiders even in opaque markets where they run a low risk of detection and prosecution: they trade when the market is most sensitive to local information, carefully choose and time their trades to minimize the risk of confounding information disclosures that may affect their profits, as well as act during high noise trading to mask their trades. Our results are consistent with evidence on insider trading in stock markets. We highlight the limitations of regulatory control in over-the-counter markets where technology-based surveillance methods are ineffective, while reinforcing the importance of whistleblowers in detecting and preventing insider trading.     

Information dissemination by insiders in equilibrium

This paper generates an equilibrium explanation for partial disclosure of information by an insider to privileged associates. In our model, prices are set by competitive market makers in anticipation of trading volume, but not affected by the actual number of trades. Liquidity demand is not perfectly inelastic, but rather liquidity traders are sensitive to trading costs through a reservation price. Because profits from liquidity traders are bounded, the feasibility of an equilibrium depends on the balance between the number of associates, the precision of information and the number of liquidity traders. Partially, rather than fully, disclosing information alters this balance by limiting the informational advantage of individual associates. If the number of associates is exogenous, partial disclosure prevents market failure. If the insider chooses the number of associates, partial disclosure allows him to serve more associates but still increase total associate profits.     

Multimarket trading and market liquidity

When a security trades at multiple locations simultaneously,an informed trader has several avenues in which to exploit hisprivate information. The greater the proportion of liquiditytrading by 'large' traders who can split their trades acrossmarkets, the larger is the correlation between volume in differentmarkets and the smaller is the informativeness of prices. Weshow that one of the markets emerges as the dominant locationfor trading in that security. When informed traders can usetheir information for more than one trading period, the timelyrelease of price information by market informed traders expectto make subsequently at other locations. Markets makers, competingto offer the lowest cost of trading at their location, consequentlydeter informal trading by voluntarily making the price informationpublic and by 'cracking down' on insider trading.     

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。     

A Characterization of the Daily and Intraday Behavior of Returns on Options

The daily and intraday behavior of returns on Chicago Board Options Exchange options is examined. Option returns contain systematic patterns even after adjusting for patterns in the means and variances of the underlying assets. This is consistent with the hypothesis that informed trading in options can make the order flow in the options market informative about the value of the underlying asset, making options nonredundant. The intraday patterns in adjusted option return variances are further consistent with a model of strategic trading by informed and discretionary liquidity traders.     

Price reversal,transaction costs,and arbitrage profits in the real estate securities market

This paper studies the return reversals of exchange traded real estate securities using an arbitrage portfolio approach. Using the approach, we find that there exist significant return reversals in such securities. These return reversals could be exploited by arbitrage traders if trading costs can be ignored. However, the arbitrage profits disappear after deducting trading costs and taking into account the implicit cost of bid-ask spread. Thus, the real estate securities market is efficient at weekly intervals in the sense that one could not exploit the price reversals via some simple trading rules.     

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.