Determinants of bid and ask quotes and implications for the cost of trading

Financial transaction costs are time varying. This paper proposes a model that relates transaction cost to characteristics of order flow. We obtain qualitatively consistent model results for different stocks and across different time periods. We find that an unusual excess of buyers (sellers) relative to sellers (buyers) tends to increase the ask (bid) price. Hence, the ask and bid components of spread change asymmetrically about the efficient price. For a fixed order imbalance surprise these effects are muted when unanticipated total volume is high. Unexpected high volatility in the transaction price process tends to widen the spread symmetrically about the efficient price. Our findings are consistent with predications from market microstructure theory that the cost of market making should depend on both the risk of trading with better-informed traders and inventory risk. We also find that order flow surprises have a significant impact on the efficient price and can also explain a substantial amount of persistence in the volatility of the efficient price. This dependence does not violate the efficient market hypothesis since the surprises, by definition, are not predictable.     

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.     

Tobin tax and market depth

This paper investigates—on the basis of the Cont–Bouchaud model—whether a Tobin tax can stabilize foreign exchange markets. Compared to earlier multi-agent studies, this paper explicitly recognizes that a transaction tax-induced reduction in market depth may increase the price responsiveness of a given order. We find that the imposition of a transaction tax may still achieve a triple dividend: (1) exchange rate fluctuations decrease, (2) currencies are less mispriced and (3) central authorities raise substantial tax revenues. However, if the price impact function is too sensitive with respect to market depth, stabilization may turn into destabilization.     

The Price of Immediacy

This paper models transaction costs as the rents that a monopolistic market maker extracts from impatient investors who trade via limit orders. We show that limit orders are American options. The limit prices inducing immediate execution of the order are functionally equivalent to bid and ask prices and can be solved for various transaction sizes to characterize the market maker's entire supply curve. We find considerable empirical support for the model's predictions in the cross-section of NYSE firms. The model produces unbiased, out-of-sample forecasts of abnormal returns for firms added to the S&P 500 index.     

Quote setting and price formation in an order driven market

This paper models quote setting and price formation in a non-intermediated, order driven market where trading occurs because investors differ in their share valuations and the advent of news that is not common knowledge, and tests the model using transaction data on individual stocks in the ParisBourse CAC40 index. As an extension of Foucault (1999), we show that the size of the spread is a function of the differences in valuation among investors and of adverse selection. Both GMM estimation of the model parameters and empirical evidence on spread behavior as the relative proportion of buyers and sellers in the market changes, provide strong support for the model. Our analysis yields further insight into the dynamic process of price formation and into the market clearing process in an order driven market.     

So who gains from a small tick size?

We investigate the relation between price discreteness and the number of dealers in a dealer market. We present a model featuring a finite number of dealers competing in prices for supplying liquidity to a forthcoming market order. We find that a decrease in tick size benefits dealers and tends to hurt investors when the number of dealers for a stock is small. In contrast, a decrease in tick size hurts dealers and benefits investors when the number of dealers is large. This result yields several new empirical implications relating a change in tick size to entry and exit of dealers, order aggressiveness and transaction rates.     

银行间债券市场价格发现功能研究

交易机制会对市场的价格发现功能造成影响。本文基于银行阃债券市场的高频数据,利用VAR模型和脉冲响应,对做市商市场的运行情况进行检验,发现:存货效应和信息不对称对价格发现均有显著影响,而后者的影响更大;交易行为显著正相关,但对价格水平无任何影响;交易价格对新信息的反应速度较快。不存在滞后调整。总体来看,《全国银行间债券市场做市商规定》的出台前后,市场质量无明显改善,这与现行的做市商制度有很大关系。     

订单型操纵的新发展及监管

本文考察了一类新的操纵类型——订单型操纵及其监管。研究发现,对于订单型操纵而言,订单提交频率较高且撤单速度非常快,以避免成交风险;申报买入笔数很多且提交订单额度巨大,但成交笔数极少;买入申报撤单量占该股票当日市场买入总申报比例极高。进一步,操纵者选择的股票往往具有低股价和小市值的特征;操纵行为对价格和流动性仅有短暂的影响。比较发现,中国和美国订单型操纵在制度上存在差异。本文研究对于如何在中国更好地加强这一类新型操纵的监管有着借鉴意义。     

Investment strategies in the long run with proportional transaction costs and a HARA utility function

We consider an agent who invests in a stock and a money market in order to maximize the asymptotic behaviour of expected utility of the portfolio market price in the presence of proportional transaction costs. The assumption that the portfolio market price is a geometric Brownian motion and the restriction to a utility function with hyperbolic absolute risk aversion (HARA) enable us to evaluate interval investment strategies. It is shown that the optimal interval strategy is also optimal among a wide family of strategies and that it is optimal also in a time changed model in the case of logarithmic utility.     

Transaction costs, trading volume, and the liquidity premium

In a market with one safe and one risky asset, an investor with a long horizon, constant investment opportunities and constant relative risk aversion trades with small proportional transaction costs. We derive explicit formulas for the optimal investment policy, its implied welfare, liquidity premium, and trading volume. At the first order, the liquidity premium equals the spread, times share turnover, times a universal constant. The results are robust to consumption and finite horizons. We exploit the equivalence of the transaction cost market to another frictionless market, with a shadow risky asset, in which investment opportunities are stochastic. The shadow price is also found explicitly.     

Optimal hedging in an extended binomial market under transaction costs

We develop an approach to optimal hedging of a contingent claim under proportional transaction costs in a discrete time financial market model which extends the binomial market model with transaction costs. Our model relaxes the binomial assumption on the stock price ratios to the case where the stock price ratio distribution has bounded support. Non-self-financing hedging strategies are studied to construct an optimal hedge for an investor who takes a short position in a European contingent claim settled by delivery. We develop the theoretical basis for our optimal hedging approach, extending results obtained in our previous work. Specifically, we derive a no-arbitrage option price interval and establish properties of the non-self-financing strategies and their residuals. Based on the theoretical foundation, we develop a computational algorithm for optimizing an investor relevant criterion over the set of admissible non-self-financing hedging strategies. We demonstrate the applicability of our approach using both simulated data and real market data.     

An empirical study of portfolio-balance and information effects of order flow on exchange rates

We propose a simple structural model of exchange rate determination which is inspired by the analytical framework recently forward by Bacchetta and van Wincoop (2006) and allows us to disentangle the portfolio-balance and information effects of order flow on exchange rates. We estimate this model employing an innovative transaction data-set that covers all indirect foreign exchange transactions completed in the USD/EUR market via EBS and Reuters between August 2000 and January 2001. Our results indicate that the strong contemporaneous correlation between order flow and exchange rates is largely due to portfolio-balance effects. This result also appears to carry through the four FX intervention events that appear in our sample.     

Optimal Refunding Strategies, Transaction Costs, and the Market Value of Corporate Debt

The primary purpose of this paper is to consider both qualitatively and quantitatively the effects of refunding transaction costs and interest rate uncertainty on optimal refunding strategies and the market value of corporate debt. A dynamic model of corporate bond refunding with transaction costs is developed that simultaneously solves for the optimal refunding strategy, the value of the refunding call option, the value of the bond liability to the firm, and the market (investor) value of the fixed-rate contract. We provide examples in which the price of the callable bond does exceed the call price, and we examine whether or not typical levels of refunding costs are sufficient to explain the magnitude and duration of frequently observed premiums on callable corporate bonds.     

透明度变化对股票市场投资者委托单提交行为和交易成本影响研究

基于2003年12月8日沪深交易所交易前市场透明度改革背景,本文利用一家营业部的投资者报价和交易数据,研究同一个机构投资者和散户投资者在透明度改革前后委托单提交激进程度的变化,以及这种变化对其完成交易的成本的影响。我们发现,透明度改革前后,机构投资者的委托单提交激进程度都显著大于散户投资者的委托单提交激进程度。透明度增加以后,机构投资者的委托单激进程度显著减少,而散户投资者的委托单提交激进程度增加。同时发现,透明度增加以后,机构投资者通过分拆委托单,增加交易次数,导致完成交易的时间增加,但价格影响力基本没有变化,散户投资者的成交时间和价格影响力有显著改善。     

The effect of option transaction costs on informed trading in the options market around earnings announcements

We investigate the effect of option market transaction costs (a form of market imperfection) on the ability of option implied volatility-based measures to predict future stock returns and volatility around quarterly earnings announcements. We find that the predictability is significantly stronger for firms with lower option relative bid-ask spreads. The effect is more pronounced around positive rather than negative earnings news. We find no significant effect of option transaction costs around randomly chosen dates when there is no clustering of major information events. Trading strategies based on option market predictors and transaction costs earn monthly abnormal returns of 1.39% to 1.91%.     

A new estimate of transaction costs

Transaction costs are important for a host of empirical analysesfrom market efficiency to international market research. Buttransaction costs estimates are not always available, or whereavailable, are cumbersome to use and expensive to purchase.We present a model that requires only the time series of dailysecurity returns to endogenously estimate the effective transactioncosts for any firm, exchange, or time period. The feature ofthe data that allows for the estimation of transaction costsis the incidence of zero returns. Incorporating zero returnsin the return-generating process, the model provides continuousestimates of average round-trip transaction costs from 1963to 1990 that are 1.2% and 10.3% for large and small decile firms,respectively. These estimates are highly correlated (85%), withthe most commonly used transaction cost estimators.     

The Impact of Information Diffusion on Comparisons among Various Trading Mechanisms

The information environment and investor order strategy are both important determinants when comparing the market performance of trading mechanisms. However, less is known about what happens when trading mechanisms are compared. In this paper, we link the information environment, trading mechanisms, investor order strategy and market performance to form a model of the securities market. The primary goal of this study is to examine the impact of various call markets in an agency market on liquidity, price volatility and market efficiency under various information regimes. The results indicate that an optimal transaction frequency appears at the trade-off of liquidity, volatility and market efficiency.     

Fractal market time

Ané and Geman (2000) observed that market returns appear to follow a conditional Gaussian distribution where the conditioning is a stochastic clock based on cumulative transaction count. The existence of long range dependence in the squared and absolute value of market returns is a ‘stylized fact’ and researchers have interpreted this to imply that the stochastic clock is self-similar, multi-fractal (Mandelbrot, Fisher and Calvet, 1997) or mono-fractal (Heyde, 1999). We model the market stochastic clock as the stochastic integrated intensity of a doubly stochastic Poisson (Cox) point process of the cumulative transaction count of stocks traded on the New York Stock Exchange (NYSE). A comparative empirical analysis of a self-normalized version of the stochastic integrated intensity is consistent with a mono-fractal market clock with a Hurst exponent of 0.75.     

Arbitrage and Viability in Insurance Markets

Insurance markets are subject to transaction costs and constraints on portfolio holdings. Therefore, unlike the frictionless asset markets case, viability is not equivalent to absence of arbitrage possibilities. We use the concept of unbounded arbitrage to characterize viable prices on a complete and an incomplete insurance market. In the complete market, there is an insurance contract for every possible event. In the incomplete market, risk can be insured through proportional and excess of loss like insurance contracts. We show how the the structure of viable prices is affected by the portfolio constraints, the transaction costs, and the structure of marketed contracts.     

The use of open source internet to analysis and predict stock market trading volume

The objective of this paper is to evaluate the impact of information demand and supply on stock market trading volume. Few studies have demonstrated the role of Google search data in analyzing trading volume activity. In this study, we employ a proxy for information demand which is derived from weekly internet search volume. The latest is from Google Trends database, for 25 of the largest stocks traded on CAC40 index, between April 2007 and March 2014. We use news headlines as a proxy for information supply. We use Garch model to analyze and predict trading volume.The empirical results present new evidences. First, information supply has an impact on trading volume but information demand's impact is much more important. Secondly, by applying MCA to results found, it could be concluded that the impact of public information on transaction volume is conditioned by two elements: the firm and market news disclosure and the second element relates to the characteristics of the market participants, more precisely their news interpretations and their risk aversion. Thirdly, we used Chow structural break test to verify the stability of our model. We found that for securities with structural changes, information demand is the responsible variable of the change in our model. Finally, we found that information variables have a predictive power on transaction volume.This paper contributes to existing literature by incorporating open source internet-based data into the analysis and prediction of transaction volume. Using internet information about the stock market, which has appeared recently as an interesting research for financial empiricists, computer scientists and practitioners, will have a very important utility because quantifying demand and supply of information becomes possible.