Trading behavior in S&P 500 index futures

This article examines the determinants of trading decisions and the performance of trader types, in the context of the E-Mini S&;P 500 futures and S&;P 500 futures markets. Speculators and small traders tend to follow positive feedback strategies while hedgers dynamically adjust positions in response to market returns. Such strategies apparently reverse during the 2008–09 financial crisis. Investor sentiment and market volatility play an important role in determining the net trading position of traders across the sample period. While all trader types are better at foreseeing market upturns, an out-of-sample test suggests that speculators and small traders have some predictive ability for short-term market returns.     

The Limits of Investor Behavior

Many models use noise trader risk and corresponding violations of the Law of One Price to explain pricing anomalies, but include a storage technology in perfectly elastic supply or unlimited asset liability. Storage allows aggregate consumption risk to differ from exogenous fundamental risk, but using aggregate consumption as a factor for asset returns can make noise trader risk superfluous. Using (i) limited asset liability and limited storage withdrawals, or (ii) an endogenous locally riskless interest rate eliminates violations of the Law of One Price. Our main results use only budget equations and market clearing, and require virtually no assumptions about behavior.     

Glued to the TV: Distracted Noise Traders and Stock Market Liquidity

In this paper, we study the impact of noise traders’ limited attention on financial markets. Specifically, we exploit episodes of sensational news (exogenous to the market) that distract noise traders. We find that on “distraction days,” trading activity, liquidity, and volatility decrease, and prices reverse less among stocks owned predominantly by noise traders. These outcomes contrast sharply with those due to the inattention of informed speculators and market makers, and are consistent with noise traders mitigating adverse selection risk. We discuss the evolution of these outcomes over time and the role of technological changes.     

Technical trading,monetary policy,and exchange rate regimes

The paper extends and empirically tests the noise trader exchange rate model of Jeanne and Rose (2002). We introduce technical trading in the exchange market as a source of noise and explicitly incorporate monetary and exchange rate policy. With these modifications, it is possible to directly test the model's prediction of an U-shaped relation between exchange trend and volatility. We find strong empirical evidence supporting the implications of the model. As a corollary, we develop a measure of excess exchange rate volatility and categorize exchange rate regimes based on the de facto behavior of the exchange rates.     

Market or limit orders?

In this paper we investigate the problem of optimal order placement of an asset listed on an exchange using both market and limit orders in a simple model of market dynamics. We seek to understand under which settings it is optimal to place limit or market orders. Limit orders typically lower transaction costs but increase the risk of incomplete order execution, whereas market orders typically have higher transaction costs but are guaranteed to be executed. Rather than considering order book dynamics to determine if a limit order is executed we rely on price dynamics for this. We look at implementation shortfall in this setup with market impact of trading and propose a dynamic program to find the optimal placement of both market and limit orders for risk-neutral and risk-averse traders. With this we find a bound on the expected cost of trading and show that a trader who behaves optimally should always expect to pay less to trade less. We then solve the dynamic program numerically and examine optimal order placement strategies. We find that the decision between market and limit orders is sensitive to price volatility, risk aversion, and trading costs.     

Market making, prices, and quantity limits

This article develops a model of spread and depth setting underasymmetric information where the equilibrium depth is proportionallymore sensitive than the spread to changes in the degree of informationasymmetry. The analysis uses a one-period model in which a risk-neutral,monopolistic market maker faces a price-sensitive liquiditytrader and a better informed trader who is alternatively riskneutral and risk averse. The equilibrium depth can take valuesranging from 0 to infinity, depending on the information asymmetry,the asset volatility, and the strength of the liquidity demand,while the spread remains positive and finite.     

Technical trading,monetary policy,and exchange rate regimes

The paper extends and empirically tests the noise trader exchange rate model of Jeanne and Rose (2002). We introduce technical trading in the exchange market as a source of noise and explicitly incorporate monetary and exchange rate policy. With these modifications, it is possible to directly test the model's prediction of an U-shaped relation between exchange trend and volatility. We find strong empirical evidence supporting the implications of the model. As a corollary, we develop a measure of excess exchange rate volatility and categorize exchange rate regimes based on the de facto behavior of the exchange rates.     

Noise trader risk: Evidence from the Siamese twins

This paper provides new evidence regarding the magnitude and nature of noise trader risk. I examine returns for two pairs of “Siamese twin” stocks: Royal Dutch/Shell and Unilever NV/PLC. These unusual pairs of fundamentally identical stocks provide a unique opportunity to investigate two facets of noise trader risk: (1) the fraction of total return variation unrelated to fundamentals (i.e., noise), and (2) the short-run risk borne by arbitrageurs engaged in long-short pairs trading. I find that about 15% of weekly return variation is attributable to noise. Noise trader risk has both systematic and idiosyncratic components, and varies considerably over time. The conditional volatility of long-short portfolio returns ranged from 0.5% to over 2.75% per week during the 1989–2003 sample period. Noise trader risk was especially high around the failure of Long-Term Capital Management in 1998 and during the collapse of the technology bubble in 2000. I conclude that noise trader risk is a significant limit to arbitrage.     

Strategic Trading in a Dynamic Noisy Market

This paper studies a dynamic model of a financial market with a strategic trader. In each period the strategic trader receives a privately observed endowment in the stock. He trades with competitive market makers to share risk. Noise traders are present in the market. After receiving a stock endowment, the strategic trader is shown to reduce his risk exposure either by selling at a decreasing rate over time or by selling and then buying back some of the shares sold. When the time between trades is small, the strategic trader reveals the information regarding his endowment very quickly.     

Information, Trading Demand, and Futures Price Volatility

We examine the relation between futures price volatility and trading demand by type of trader in the Standard & Poor's (S&P) 500-stock index futures market. We find that volatility covaries negatively with signed speculative demand shocks but is positively related to signed hedging demand shocks. No significant relation between volatility and demand shocks for small traders is found. Our results suggest that changes in positions of large hedgers destabilize the market, whereas changes in positions of large speculators stabilize volatility. Consistent with models with asymmetrically informed traders, we find that large speculators are likely to possess superior forecasting ability, large hedgers behave like positive feedback traders, and small traders are liquidity traders.     

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.     

The role of private information in return volatility,bid–ask spreads and price levels in the foreign exchange market

Trading volume and order flow have both been closely associated with informed trader activity in the market microstructure literature. Using theory that explains regular intraday patterns in trading data, we transform these two variables into proxies for private information and examine their relationships with bid–ask spreads and return volatility. We use a unique and unusually rich high-frequency intraday dataset from the world's largest financial market, namely, the electronic inter-dealer spot foreign exchange market. Our analysis takes account of institutional features peculiar to this order-driven market. Our empirical results strongly affirm our theoretical understanding of how these markets work. They also reveal how the structure of the inter-dealer spot FX market affects exchange rate volatility. Finally, we also explore how private information contributes to the evolution of prices.     

印花税调整对股票价格影响的实证研究

印花税下调在短期内对大盘股指产生显著影响,但这种影响随时间的推移而逐渐减弱;税率下调对沪市和深市单只股票具有冲击效应,个股产生正的超额收益;税率下调对两市的大盘波动性产生显著影响,刺激了"噪声交易者",在短期内产生了噪声效应。目前印花税仍然存在一些不足,建议:拓宽税基,改双向征税为单向征税,尽快开征股票交易税。     

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.     

Does knowing the volatility states affect the market risk premium?

Mayfield (J Financ Econ 73:465–496, 2004) has devised a method for estimating the market risk premium, based on a variant of Merton’s ICAPM wherein volatility is specified as a two-state Markov process. In this study, we assess Mayfield’s key assumption that investors know the current volatility state with certainty, via empirical testing of the assumption of exogenous Markov-switching in Mayfield’s model. We detect strong evidence of endogenous switching. This indicates that investors infer the current volatility state, as opposed to simply observing it. We also find that the risk premium estimates are affected by the switching type.     

Stock market volatility, excess returns, and the role of investor sentiment

Using the Investors' Intelligence sentiment index, we employ a generalized autoregressive conditional heteroscedasticity-in-mean specification to test the impact of noise trader risk on both the formation of conditional volatility and expected return as suggested by De Long et al. [Journal of Political Economy 98 (1990) 703]. Our empirical results show that sentiment is a systematic risk that is priced. Excess returns are contemporaneously positively correlated with shifts in sentiment. Moreover, the magnitude of bullish (bearish) changes in sentiment leads to downward (upward) revisions in volatility and higher (lower) future excess returns.     

Execution in an aggregator

An aggregator is a technology that consolidates liquidity—in the form of bid and ask prices and amounts—from multiple sources into a single unified order book to facilitate ‘best-price’ execution. It is widely used by traders in financial markets, particularly those in the globally fragmented spot currency market. In this paper, I study the properties of execution in an aggregator where multiple liquidity providers (LPs) compete for a trader’s uninformed flow. There are two main contributions. Firstly, I formulate a model for the liquidity dynamics and contract formation process, and use this to characterize key trading metrics such as the observed inside spread in the aggregator, the reject rate due to the so-called ‘last-look’ trade acceptance process, the effective spread that the trader pays, as well as the market share and gross revenues of the LPs. An important observation here is that aggregation induces adverse selection where the LP that receives the trader’s deal request will suffer from the ‘Winner’s curse’, and this effect grows stronger when the trader increases the number of participants in the aggregator. To defend against this, the model allows LPs to adjust the nominal spread they charge or alter the trade acceptance criteria. This interplay is a key determinant of transaction costs. Secondly, I analyse the properties of different execution styles. I show that when the trader splits her order across multiple LPs, a single provider that has quick market access and for whom it is relatively expensive to internalize risk can effectively force all other providers to join her in externalizing the trader’s flow thereby maximizing the market impact and aggregate hedging costs. It is therefore not only the number, but also the type of LP and execution style adopted by the trader that determines transaction costs.     

Have European Stocks become More Volatile? An Empirical Investigation of Idiosyncratic and Market Risk in the Euro Area

We examine the dynamics of idiosyncratic risk, market risk and return correlations in European equity markets using weekly observations from 3515 stocks listed in the 12 euro area stock markets over the period 1974–2004. Similarly to Campbell et al. (2001) , we find a rise in idiosyncratic volatility, implying that it now takes more stocks to diversify away idiosyncratic risk. Contrary to the US, however, market risk is trended upwards in Europe and correlations are not trended downwards. Both the volatility and correlation measures are pro‐cyclical, and they rise during times of low market returns. Market and average idiosyncratic volatility jointly predict market wide returns, and the latter impact upon both market and idiosyncratic volatility. This has asset pricing and risk management implications.     

Last look

In over-the-counter markets, a trader typically sources indicative quotes from a number of competing liquidity providers, and then sends a deal request on the best available price for consideration by the originating liquidity provider. Due to the communication and processing latencies involved in this negotiation, and in a continuously evolving market, the price may have moved by the time the liquidity provider considers the trader’s request. At what point has the price moved too far away from the quote originally shown for the liquidity provider to reject the deal request? Or perhaps the request can still be accepted but only on a revised rate? ‘Last look’ is the process that makes this decision, i.e. it determines whether to accept—and if so at what rate—or reject a trader’s deal request subject to the constraints of an agreed trading protocol. In this paper, I study how the execution risk and transaction costs faced by the trader are influenced by the last look logic and choice of trading protocol. I distinguish between various ‘symmetric’ and ‘asymmetric’ last look designs and consider trading protocols that differ on whether, and if so to what extent, price improvements and slippage can be passed on to the trader. All this is done within a unified framework that allows for a detailed comparative analysis. I present two main findings. Firstly, the choice of last look design and trading protocol determines the degree of execution risk inherent in the process, but the effective transaction costs borne by the trader need not be affected by it. Secondly, when a trader adversely selects the liquidity provider she chooses to deal with, the distinction between the different symmetric and asymmetric last look designs fades and the primary driver of execution risk is the choice of trading protocol.     

The optimal bid-ask price strategies of high-frequency trading and the effect on market liquidity

We propose a model for determining the optimal bid-ask spread strategy by a high-frequency trader (HFT) who has an informational advantage and receives information about the true value of a security. We employ an information cost function that includes volatility and the volume of the asset. Subsequently, we characterize the optimal bid-ask price strategies and obtain a stable bid-ask spread. We assume that orders submitted by low-frequency traders (LFTs) and news events arrive at the market with Poisson processes. Additionally, our model supports the trading of the two-sided quote in one period. We find that more LFTs and a higher exchange latency both hurt market liquidity. The HFT prefers to choose a two-sided quote to gain more profits while cautiously chooses a one-sided quote during times of high volatility. The model generates some testable implications with supporting empirical evidence from the NASDAQ-OMX Nordic Market.