Informed traders and limit order markets

We consider a dynamic limit order market in which traders optimally choose whether to acquire information about the asset and the type of order to submit. We numerically solve for the equilibrium and demonstrate that the market is a “volatility multiplier”: prices are more volatile than the fundamental value of the asset. This effect increases when the fundamental value has high volatility and with asymmetric information across traders. Changes in the microstructure noise are negatively correlated with changes in the estimated fundamental value, implying that asset betas estimated from high-frequency data will be incorrect.     

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.     

The strategic specialist and imperfect competition in a limit order market

The empirical literature suggests that the limit order book contains information that might be used by the specialist to his own advantage. I develop a model where there is a strategic specialist who competes against a limit order book and has information about supply. The presence of a strategic specialist in an imperfectly competitive limit order book market induces non-monotonicity of market indicators with respect to the variance of liquidation value. Moreover, the existence of private information about supply significantly affects market performance as it induces, among other effects, lower market liquidity. Finally, this model suggests another link between Kyle’s (1985, 1989) [Kyle, A., 1985. Continuous auctions and insider trading. Econometrica 53, 1315–1336, Kyle, A., 1989. Informed speculators with imperfect competition. Review of Economic Studies 56, 317–356] and Glosten and Milgrom’s (1985) [Glosten, L., Milgrom, P., 1985. Bid, ask and transaction prices in a specialist market with heterogeneously informed markets. Journal of Financial Economics 14, 71–100] models by allowing for strategic behaviour of the specialist.     

A factor analysis approach to measuring European loan and bond market integration

By using an existing and a new convergence measure, this paper assesses whether bank loan and bond interest rates are converging for the non-financial corporate sector across the euro area. Whilst we find evidence for complete bond market integration, the market for bank loans remains segmented, albeit to various degrees depending on the type and size of the loan. Factor analysis reveals that rates on large loans and small loans with long rate fixation periods have weakly converged in the sense that, up to a fixed effect, their evolution is driven by common factors only. In contrast, the price evolution of small loans with short rate fixation periods is still affected by country-specific dynamic factors. There are few signs that bank loan rates are becoming more uniform with time.     

A market-clearing role for inefficiency on a limit order book

Limit order markets with stationary dynamics attract equal volumes of market orders and uncanceled limit orders, equalizing the supply and demand for liquidity and immediacy. To maintain this balance, market orders must share any benefit obtained by limit order traders from more efficient trading conditions, such as better order queuing policies. Therefore an efficient market places a low price on immediacy, producing small bid–ask spreads. Furthermore, when price-discreteness leads to a mainly constant spread, cutting the price tick raises surplus. This is modeled with a stochastic sequential game, using stationarity considerations to bypass direct analysis of traders’ intricate market forecasts.     

Undisclosed orders and optimal submission strategies in a limit order market

Reserve orders enable traders to hide a portion of their orders and now appear in most electronic limit order markets. This paper outlines a theory to determine an optimal submission strategy in a limit order book, in which traders choose among limit, market, and reserve orders and simultaneously set price, quantity, and exposure. We show that reserve orders help traders compete for the provision of liquidity and reduce the friction generated by exposure costs. Therefore, total gains from trade increase. Large traders always benefit from reserve orders, whereas small traders benefit only when the tick size is large.     

Stock market bubbles, inflation and investment risk

This paper proposes an autoregressive regime-switching model of stock price dynamics in which the process creates pricing bubbles in one regime while error-correction prevails in the other. In the bubble regime the stock price depends negatively on inflation. In the error-correction regime it depends on the price-dividend ratio. We find that the probability of regime-switch depends on exogenous inflation and lagged price. The model is consistent with Shleifer and Vishny's theoretical noise trader and arbitrageur model and Modigliani's inflation illusion phenomenon. The results emphasize the importance of inflation and the price-dividend ratio when assessing investment risk.     

Option-implied volatility factors and the cross-section of market risk premia

The main goal of this paper is to study the cross-sectional pricing of market volatility. The paper proposes that the market return, diffusion volatility, and jump volatility are fundamental factors that change the investors’ investment opportunity set. Based on estimates of diffusion and jump volatility factors using an enriched dataset including S&P 500 index returns, index options, and VIX, the paper finds negative market prices for volatility factors in the cross-section of stock returns. The findings are consistent with risk-based interpretations of value and size premia and indicate that the value effect is mainly related to the persistent diffusion volatility factor, whereas the size effect is associated with both the diffusion volatility factor and the jump volatility factor. The paper also finds that the use of market index data alone may yield counter-intuitive results.     

An empirical analysis of the dynamic relationship between mutual fund flow and market return volatility

We study the dynamic relation between aggregate mutual fund flow and market-wide volatility. Using daily flow data and a VAR approach, we find that market volatility is negatively related to concurrent and lagged flow. A structural VAR impulse response analysis suggests that shock in flow has a negative impact on market volatility: An inflow (outflow) shock predicts a decline (an increase) in volatility. From the perspective of volatility–flow relation, we find evidence of volatility timing for recent period of 1998–2003. Finally, we document a differential impact of daily inflow versus outflow on intraday volatility. The relation between intraday volatility and inflow (outflow) becomes weaker (stronger) from morning to afternoon.     

Information demand and stock market volatility

We study information demand and supply at the firm and market level using data for 30 of the largest stocks traded on NYSE and NASDAQ. Demand is approximated in a novel manner from weekly internet search volume time series drawn from the recently released Google Trends database. Our paper makes contributions in four main directions. First, although information demand and supply tend to be positively correlated, their dynamic interactions do not allow conclusive inferences about the information discovery process. Second, demand for information at the market level is significantly positively related to historical and implied measures of volatility and to trading volume, even after controlling for market return and information supply. Third, information demand increases significantly during periods of higher returns. Fourth, analysis of the expected variance risk premium confirms for the first time empirically the hypothesis that investors demand more information as their level of risk aversion increases.     

Testing conditional asset pricing models: An emerging market perspective

The CAPM as the benchmark asset pricing model generally performs poorly in both developed and emerging markets. We investigate whether allowing the model parameters to vary improves the performance of the CAPM and the Fama–French model. Conditional asset pricing models scaled by conditioning variables such as Trading Volume and Dividend Yield generally result in small pricing errors. However, a graphical analysis reveals that the predictions of conditional models are generally upward biased. We demonstrate that the bias in prediction may be the consequence of ignoring frequent large variation in asset returns caused by volatile institutional, political and macroeconomic conditions. This is characterised by excess kurtosis. An unconditional Fama–French model augmented with a cubic market factor performs the best among some competing models when local risk factors are employed. Moreover, the conditional models with global risk factors scaled by global conditioning variables perform better than the unconditional models with global risk factors.     

Mean reversion in stock market prices: New evidence based on bull and bear markets

In this paper we test whether mean reversion in stock market prices presents a different behavior in bull and bear markets. We date the US bull and bear periods using Bry and Boschan (1971) algorithm. We examine the order of integration in the S&P 500 stock market index covering a daily period from August 1929 to December 2006 in bull and bear phases. Our results indicate the existence of different episodes of mean reversion, which mainly correspond to bull market periods.     

Options, short-sale constraints and market efficiency: A new perspective

This paper undertakes a new investigation of the potential for options to mitigate short-sale constraints. I find that option introduction alleviates 79% of the price adjustment efficiency disparity between short-sale constrained and unconstrained stocks in relation to negative news. No significant improvement in adjustment efficiency is found in response to positive information. These results are robust to controls for endogeneity biases associated with the option introduction selection process. Further, I find evidence that post-option improvement in efficiency is similar in relation to private and public information. This suggests that short-sale constraint effects stem, at least in part, from an irrational, optimism bias or another behavioral source as suggested theoretically by Miller (1977). Collectively, these results suggest that options act as an effective substitute to short-sales, significantly contributing to the informational efficiency of the market.     

Liquidity and market efficiency

Short-horizon return predictability from order flows is an inverse indicator of market efficiency. We find that such predictability is diminished when bid-ask spreads are narrower, and has declined over time with the minimum tick size. Variance ratio tests suggest that prices were closer to random walk benchmarks in the more liquid decimal regime than in other ones. These findings indicate that liquidity stimulates arbitrage activity, which, in turn, enhances market efficiency. Further, as the tick size decreased, open-close/close-open return variance ratios increased, while return autocorrelations decreased. This suggests an increased incorporation of private information into prices during more liquid regimes.     

Financial market models with Lévy processes and time-varying volatility

Asset management and pricing models require the proper modeling of the return distribution of financial assets. While the return distribution used in the traditional theories of asset pricing and portfolio selection is the normal distribution, numerous studies that have investigated the empirical behavior of asset returns in financial markets throughout the world reject the hypothesis that asset return distributions are normally distribution. Alternative models for describing return distributions have been proposed since the 1960s, with the strongest empirical and theoretical support being provided for the family of stable distributions (with the normal distribution being a special case of this distribution). Since the turn of the century, specific forms of the stable distribution have been proposed and tested that better fit the observed behavior of historical return distributions. More specifically, subclasses of the tempered stable distribution have been proposed. In this paper, we propose one such subclass of the tempered stable distribution which we refer to as the “KR distribution”. We empirically test this distribution as well as two other recently proposed subclasses of the tempered stable distribution: the Carr–Geman–Madan–Yor (CGMY) distribution and the modified tempered stable (MTS) distribution. The advantage of the KR distribution over the other two distributions is that it has more flexible tail parameters. For these three subclasses of the tempered stable distribution, which are infinitely divisible and have exponential moments for some neighborhood of zero, we generate the exponential Lévy market models induced from them. We then construct a new GARCH model with the infinitely divisible distributed innovation and three subclasses of that GARCH model that incorporates three observed properties of asset returns: volatility clustering, fat tails, and skewness. We formulate the algorithm to find the risk-neutral return processes for those GARCH models using the “change of measure” for the tempered stable distributions. To compare the performance of those exponential Lévy models and the GARCH models, we report the results of the parameters estimated for the S&P 500 index and investigate the out-of-sample forecasting performance for those GARCH models for the S&P 500 option prices.     

Modeling of CPDOs – Identifying optimal and implied leverage

When the subprime crisis started to emerge, collateralized products based on credit default swap (CDS) exposures combined with security features seemed to be a more rational alternative to classic asset backed securities. Constant Proportion Collateralized Debt Obligations (CPDOs) are a mixture of Collateralized Debt Obligations (CDOs) and CPPIs with inverse mechanism. This new asset aims at meeting the investors’ demand for credit derivatives with security enhancements, but to our knowledge quantitative approaches for pricing other than simulation algorithms do not exist yet. CPDOs became famous notably by Standard & Poor’s rating model error which illustrated that closed-form analytical pricing is necessary in order to evaluate and understand complex derivatives. This article aims to shed a light on CPDOs’ specific structural enhancements and mechanisms. We quantify inherent risks and provide a dynamic closed-form pricing formula.     

Centralised order books versus hybrid order books: A paired comparison of trading costs on NSC (Euronext Paris) and SETS (London Stock Exchange)

This article compares the cost of trading large capitalisation equities on the hybrid order-driven segment of the London Stock Exchange and the centralised electronic order book of Euronext. Using samples of stocks matched according to economic sector, free float capitalisation, and trading volume, our study shows that transaction costs are lower on the centralised order book than on the hybrid order book. The presence of dealers outside the electronic order book favours the frequency of large trades, but is associated with higher execution costs for all other trades and higher adverse selection and inventory costs inside the order book.     

Hedge fund portfolio construction: A comparison of static and dynamic approaches

This article studies the impact of modeling time-varying covariances/correlations of hedge fund returns in terms of hedge fund portfolio construction and risk measurement. We use a variety of static and dynamic covariance/correlation prediction models and compare the optimized portfolios’ out-of-sample performance. We find that dynamic covariance/correlation models construct portfolios with lower risk and higher out-of-sample risk-adjusted realized return. The tail-risk of the constructed portfolios is also lower. Using a mean-conditional-value-at-risk framework we show that dynamic covariance/correlation models are also successful in constructing portfolios with minimum tail-risk.     

Common liquidity shocks and market collapse: Lessons from the market for perps

We show how a high degree of commonality in investor liquidity shocks can diminish incentives for intermediaries to keep markets open and lead to market collapse, even without information asymmetry or news affecting fundamentals. We motivate our model using the perpetual floating-rate note market where two years of explosive growth – in which issues by high quality borrowers were placed with institutional investors and traded in a liquid secondary market – were followed by a precipitous collapse when market intermediaries withdrew due to large order imbalances. We shed new light on the trade-off between ownership concentration and market liquidity.     

Stock market liquidity and firm value

This paper investigates the relation between stock liquidity and firm performance. The study shows that firms with liquid stocks have better performance as measured by the firm market-to-book ratio. This result is robust to the inclusion of industry or firm fixed effects, a control for idiosyncratic risk, a control for endogenous liquidity using two-stage least squares, and the use of alternative measures of liquidity. To identify the causal effect of liquidity on firm performance, we study an exogenous shock to liquidity—the decimalization of stock trading—and show that the increase in liquidity around decimalization improves firm performance. The causes of liquidity's beneficial effect are investigated: Liquidity increases the information content of market prices and of performance-sensitive managerial compensation. Finally, momentum trading, analyst coverage, investor overreaction, and the effect of liquidity on discount rates or expected returns do not appear to drive the results.