Volatility,Depth, and Order Composition: Evidence from a Pure Limit Order Futures Market

This paper investigates market behaviors (such as volatility, depth, and volume) and order-flow decomposition in a pure limit order futures market, the Taiwan Futures Exchange. The results are different from those in equity markets due to relatively high adverse selection costs in futures markets. We show that a volatility (depth) increase is followed by a depth (volatility) decrease; a market order increase (decrease) subsequently induces higher (lower) volatility; and a limit order increase (decrease) results in more (less) market orders and limit orders. When the upside (downside) volatility rises, buyers decrease (increase) subsequent limit bid orders, and sellers increase (decrease) limit ask orders.     

Relative performance of bid–ask spread estimators: Futures market evidence

The issue of transaction costs is the mainstay of the equity market microstructure. Research in the microstructure of futures markets has lagged behind. A primary reason is that futures exchanges in the U.S. do not record bid–ask quotes, requiring these costs to be imputed from transaction price data. A reliable estimator of bid–ask spreads would significantly enhance microstructure research in futures markets. Unique intraday data from the Sydney Futures Exchange (SFE) that include both transaction prices and bid–ask spreads allow us to compare bid–ask spread estimation techniques proposed in the literature against the benchmark of actual spreads in a futures market, and thus identify the best-performing estimator. To maximize relevance, we impose all the constraints that apply in U.S. futures data to perform our estimations. We find that the four bid–ask spread estimators considered significantly underestimate the actual spreads. However, simple moments-based estimators perform better in predicting spreads.     

To Trade or Not to Trade: The Effect of Broker Search and Discretionary Trading on Securities Market Performance

In this article we examine the interaction of brokerage search with the Bayesian learning behavior of competitive dealers under asymmetric information. We particularly focus on the effects of price search and discretionary trading on the performance of a dealer market. A search process is incorporated into a model in which brokers determine their reservation price and whether to continue their trades. The model enables us to uncover the interrelationships among search cost, bid‐ask spread, and price volatility. We show that both spread revision and price volatility are dependent upon the optimal search process, inventory fluctuation, and search cost. Furthermore, our model predicts a negative relationship between price volatility and liquidity trading volume.     

Relation between bid–ask spread,impact and volatility in order-driven markets

We show that the cost of market orders and the profit of infinitesimal market-making or -taking strategies can be expressed in terms of directly observable quantities, namely the spread and the lag-dependent impact function. Imposing that any market taking or liquidity providing strategies is at best marginally profitable, we obtain a linear relation between the bid–ask spread and the instantaneous impact of market orders, in good agreement with our empirical observations on electronic markets. We then use this relation to justify a strong, and hitherto unnoticed, empirical correlation between the spread and the volatility per trade, with R ²s exceeding 0.9. This correlation suggests both that the main determinant of the bid–ask spread is adverse selection, and that most of the volatility comes from trade impact. We argue that the role of the time-horizon appearing in the definition of costs is crucial and that long-range correlations in the order flow, overlooked in previous studies, must be carefully factored in. We find that the spread is significantly larger on the NYSE, a liquid market with specialists, where monopoly rents appear to be present.     

Short-term market reaction after extreme price changes of liquid stocks

In our empirical study we examine the dynamics of the price evolution of liquid stocks after experiencing a large intra-day price change, using data from the NYSE and the NASDAQ. We find a significant reversal for both intra-day price decreases and increases. Volatility, volume and, in the case of the NYSE, the bid–ask spread, which increase sharply at the event, stay significantly high days afterwards. The decay of the volatility follows a power law in accordance with the `Omori law'. While on the NYSE the large widening of the bid–ask spread eliminates most of the profits that can be achieved by an outside investor, on the NASDAQ the bid–ask spread stays almost constant, yielding significant short-term profits. The results thus give an insight into the size and speed of the realization of an excess return for providing liquidity in a turbulent market.     

Investor behaviour and reaching for yield: Evidence from the sterling corporate bond market

We provide evidence on how corporate bond investors react to a change in yields, and how this behaviour differs in times of market‐wide stress. We also investigate ‘reaching for yield’ across investor types, as well as providing insights into the structure of the corporate bond market. Using proprietary sterling corporate bond transaction data, we show that insurance companies, hedge funds and asset managers are typically net buyers when corporate bond yields rise. Dealer banks clear the market by being net sellers. However, we find evidence for this behaviour reversing in times of stress for some investors. During the 2013 ‘taper tantrum’, asset managers were net sellers of corporate bonds in response to a sharp rise in yields, potentially amplifying price changes. At the same time, dealer banks were net buyers. Finally, we provide evidence that insurers, hedge funds and asset managers tilt their portfolios towards higher risk bonds, consistent with ‘reaching for yield’ behaviour.     

Optimal high-frequency trading with limit and market orders

We propose a framework for studying optimal market-making policies in a limit order book (LOB). The bid–ask spread of the LOB is modeled by a tick-valued continuous-time Markov chain. We consider a small agent who continuously submits limit buy/sell orders at best bid/ask quotes, and may also set limit orders at best bid (resp. ask) plus (resp. minus) a tick for obtaining execution order priority, which is a crucial issue in high-frequency trading. The agent faces an execution risk since her limit orders are executed only when they meet counterpart market orders. She is also subject to inventory risk due to price volatility when holding the risky asset. The agent can then also choose to trade with market orders, and therefore obtain immediate execution, but at a less favorable price. The objective of the market maker is to maximize her expected utility from revenue over a short-term horizon by a trade-off between limit and market orders, while controlling her inventory position. This is formulated as a mixed regime switching regular/impulse control problem that we characterize in terms of a quasi-variational system by dynamic programming methods. Calibration procedures are derived for estimating the transition matrix and intensity parameters for the spread and for Cox processes modelling the execution of limit orders. We provide an explicit backward splitting scheme for solving the problem and show how it can be reduced to a system of simple equations involving only the inventory and spread variables. Several computational tests are performed both on simulated and real data, and illustrate the impact and profit when considering execution priority in limit orders and market orders.     

Liquidity supply in electronic markets

We examine the supply of liquidity by proprietary trading desks and hedge funds (PTDH) versus mutual funds, index funds, and insurance companies (MII) across ten bid (ask) steps of the limit order book. We document that institutional investors simultaneously supply liquidity at multiple prices in the limit order book. We also find that PTDHs are more price aggressive liquidity suppliers than MIIs, consistent with hypothesized responses to observed changes in the cost and risk of non-execution. We investigate whether these findings are robust to fast versus slow markets, the volatility of daily returns, and aggregate depth relative to daily volume.     

Market Microstructure and the Ex-Date Return

This article examines the role of measurement biases, due to order flow effects, in abnormal split ex-day returns. We conjecture that postsplit orders consist of numerous small buyers and fewer larger sellers. This change in order flow causes closing prices to occur more frequently at the ask price, consistent with Maloney and Mulherin (1992) and Grinblatt and Keim (1991) . In addition, this change causes specialists' spreads to increase, perhaps to offset larger average inventories. We examine both NYSE and NASDAQ samples and find that order flow biases can explain approximately 80 percent (48 percent) of the NYSE (NASDAQ) ex-day return.     

Index Options-Futures Arbitrage: A Comparative Study with Bid/Ask and Transaction Data

We can infer from bid/ask quotations and transaction prices that where options contracts are traded under a competitive open‐outcry market‐making system, the options and futures markets are dynamically efficient. Ex‐ante analysis shows that potential arbitrage opportunities disappear within five minutes. Transaction price data understate both the frequency and magnitude of arbitrage opportunities that are signaled by bid/ask quotes. Quotes stale fast, so opportunities are short‐lived and some of the arbitrage opportunities are deceptive. Nonetheless, the evidence suggests that bid/ask quotes provide valuable trading signals to arbitrageurs. Profitability from exploiting the quotes is negatively related to execution delay and execution risk.     

THE DETERMINANTS OF MARKET BID ASK SPREADS ON THE AUSTRALIAN STOCK EXCHANGE: CROSS-SECTIONAL ANALYSIS

Prior research into the cost of trading on the Australian Stock Exchange has identified brokerage fees and the bid-ask spread as significant elements of total transaction costs. While an enormous volume of research has examined the determinants of spreads in US markets, no work has so far addressed the issue for the Australian market-place. Given the importance of spreads as a transaction cost, this work redresses this imbalance and at the same time provides evidence on whether alternative market structures underlying different exchanges give rise to differences in the determinants of spreads. Using prior US research as our benchmark, our results suggest that notwithstanding microstructure differences between the Australian and US exchanges, there are three fundamental determinants of spreads that transcend differences in the market-places. These are the level of trading activity, price volatility and stock price levels. Together these three factors account for up to 94% of the total cross-sectional variation in percentage bid ask spreads on the ASX.     

S&P 100 Index Option Volatility

Using transaction data on the S&P 100 index options, we study the effect of valuation simplifications that are commonplace in previous research on the timeseries properties of implied market volatility. Using an American-style algorithm that accounts for the discrete nature of the dividends on the S&P 100 index, we find that spurious negative serial correlation in implied volatility changes is induced by nonsimultaneously observing the option price and the index level. Negative serial correlation is also induced by a bid/ask price effect if a single option is used to estimate implied volatility. In addition, we find that these same effects induce spurious (and unreasonable) negative cross-correlations between the changes in call and put implied volatility.     

Search Costs,Behavioral Biases,and Information Intermediary Effects

In many markets, buyers, sellers, and their agents have differential information about the quality of heterogeneous assets. We study negotiated transaction prices in the commercial real estate market, which is characterized by heterogeneous assets, illiquidity, and highly segmented local markets, all of which increase the importance of asymmetric information in negotiated pricing outcomes. Using 114,588 industrial, multi-family and office sale transactions that occurred during 1997–2011, we document that distant commercial real estate buyers pay, on average, premiums of 4 % to 15 % relative to local buyers, controlling for individual property characteristics as well as time fixed-effects. We also examine the extent to which the sources of these observed premiums are a product of higher search costs/information asymmetry problems associated with distance (search cost channel) or a result of reference-dependence preference/anchoring based on the price levels in the investors’ local market (behavioral biases channel). Our results suggest the observed price premiums are explained by distant investors who face higher search costs and are at an information disadvantage compared to investors located in closer proximity to the property. In contrast, anchoring plays a more muted role in explaining observed premiums. The use of an intermediary (broker) increases, on average, the acquisition prices of buyers and decreases the disposition prices of sellers by 3 % to 8 %. This result is consistent with the incentive real estate agents have to convince sellers to dispose of their properties too quickly and to convince buyers to search less and therefore pay higher prices.     

Regulation Fair Disclosure and the Cost of Adverse Selection

Regulation Fair Disclosure (FD), imposed by the Securities and Exchange Commission in October 2000, was designed to prohibit disclosure of material private information to selected market participants. The informational advantage such select participants gain is unclear. If multiple “insiders” receive identical information, private information is immediately incorporated in price and each insider has zero expected profit. If, on the other hand, Regulation FD has curtailed the flow of information from firms, private information becomes longer‐lived and more valuable. Hence, market makers will demand increased compensation by widening the adverse selection component of the bid‐ask spread. We identify the cost components of the bid‐ask spread for a sample of NASDAQ stocks surrounding the implementation of Regulation FD. Controlling for other factors affecting the spread, we find that adverse selection costs increase approximately 36% after Regulation FD. We interpret our finding as Regulation FD failing to achieve one of its desired objectives.     

The impact of macroeconomic news on quote adjustments, noise, and informational volatility

We study the impact of the arrival of macroeconomic news on the informational and noise-driven components in high-frequency quote processes and their conditional variances. We decompose bid and ask returns into a common (“efficient return”) factor and two market-side-specific components capturing market microstructure effects. The corresponding variance components reflect information-driven and noise-induced volatilities. We find that all volatility components reveal distinct dynamics and are positively influenced by news. The proportion of noise-induced variances is highest before announcements and significantly declines thereafter. Moreover, news-affected responses in all volatility components are influenced by order flow imbalances.     

Aggressive Orders and the Resiliency of a Limit Order Market

We analyze the resiliency of a pure limit order market by investigating the limit order book (bid and ask prices, spreads, depth and duration), order flow and transaction prices in a window of best limit updates and transactions around aggressive orders (orders that move prices). We find strong persistence in the submission of aggressive orders. Aggressive orders take place when spreads and depths are relatively low, and they induce bid and ask prices to be persistently different after the shock. Depth and spread remain also higher than just before the order, but do return to their initial level within 20 best limit updates after the shock. Relative to the sample average, depths stay around their mean before and after aggressive orders, whereas spreads return to their mean after about twenty best limit updates. The initial price impact of the aggressive order is partly reversed in the subsequent transactions. However, the aggressive order produces a long-term effect as prices show a tendency to return slowly to the price of the aggressive order.We thank Theo Nijman, Erik Theissen, Rob van den Goorbergh, Josef Zechner (editor) and an anonymous referee for valuable comments on an earlier draft as well as seminar participants at the EEA-conference in Venice, the CFS Conference on Market Design in Eltville, CORE, Leuven and Tilburg. The first and last authors gratefully acknowledge financial assistance from FWO-Flanders under contract G.0333.     

Liquidity of emerging markets

Emerging markets are characterized by volatile, but substantial returns that can easily exceed 75% per annum. Balancing these lofty returns are liquidity costs that, using the bid–ask spread as a basis, range from 1% for the Taiwanese market to over 47% for the Russian market. However, the paucity of bid–ask spread information across countries and time requires the use of liquidity estimates in emerging markets even though little is known about the efficacy of these estimates in measuring bid–ask spread costs. Using firm-level quoted bid–ask spreads as a basis, I find that price-based liquidity measures of Lesmond et al. [Review of Financial Studies 12 (1999) 1113] and Roll [Journal of Finance 39 (1984) 1127] perform better at representing cross-country liquidity effects than do volume based liquidity measures. Within-country liquidity is best measured with the liquidity estimates of either Lesmond, Ogden, and Trzcinka or, to a lesser extent, Amihud (2002). Examining the impact of legal origin and political institutions on liquidity levels shows that countries with weak political and legal institutions have significantly higher liquidity costs than do countries with strong political and legal systems, even to the exclusion of legal origin or insider trading enforcement. Higher incremental political risk is associated with a 10 basis point increase in transaction costs, using the Lesmond, Ogden, and Trzcinka estimate, or a 1.9% increase in price impact costs, using the Amihud estimate.     

The Volatility of Bid‐Ask Spreads

This study tests whether the volatility of bid‐ask spreads is positively related to expected returns. After controlling for market‐risk factors, we find that the average risk‐adjusted excess return for stocks in the highest spread volatility quintile is around 50 basis points per month. In a variety of multivariate tests, we find robust evidence of a return premium associated with spread volatility that is both statistically significant and economically meaningful. Our results are robust to controls for a variety of stock characteristics, different tick‐size regimes, and other measures of liquidity volatility.     

More on a statistical analysis of log-periodic precursors to financial crashes

In this paper, we extend the existing empirical evidence on the relationship between the state of the limit order book (LOB) and order choice. Our contribution is twofold: first, we propose a sequential ordered probit (SOP) model which allows studying patient and impatient traders’ choices separately; second, we consider two pieces of LOB information, the best quotes and the book beyond the best quotes. We find that both pieces of LOB information explain the degree of patience of an incoming trader and, afterwards, its order choice. Nonetheless, the best quotes concentrate most of the explanatory power of the LOB. The shape of the book beyond the best quotes is crucial in explaining the aggressiveness of patient (limit order) traders, while impatient (market order) traders base their decisions primarily on the best quotes. Patient traders’ choices depend more on the state of the LOB on the same side of the market, while impatient traders mostly look at the state of the LOB on the opposite side. The aggressiveness of both types of traders augments with the inside spread. However, patient (impatient) traders submit more (less) aggressive limit (market) orders when the depth of the own (opposite) best quote and the length of the own (opposite) side of the book increase. We also find that higher depth away from the best ask (bid) quote may signal that this quote is ‘too low (high)’, causing incoming impatient buyers (sellers) to be more aggressive and incoming patient sellers (buyers) to be more conservative.     

Optimal Portfolio Choices, House Risk Hedging and the Pricing of Forward House Transactions

This paper develops a utility indifference model for evaluating various prices associated with forward transactions in the housing market, based on the equivalent principle of expected wealth utility derived from the forward and spot real estate markets. Our model results show that forward transactions in the housing market are probably not due to house sellers?? and buyers?? heterogeneity, but to their demand for hedging against house price risk. When the imperfections of real estate markets and the risk preferences of market participants are taken into consideration, we are able to show that the idiosyncratic risk premium, which mainly depends on the participants?? risk preferences and the correlation between the traded asset and the real estate, is a remarkable determinant of house sellers?? and buyers?? forward reservation prices. In addition, we also find that the market clearing forward price usually will not converge toward the expected risk-neutral forward price. The sellers?? or buyers?? risk aversion degrees and market powers are also identified to play crucial roles in determining the clearing forward price.