Microstructure Theory Research Articles

Trading Strategies and Market Microstructure: Evidence from a Prediction Market

We examine transaction-level data from Intrade's 2012 presidential winner market for the entire two-year period for which trading occurred. The data allow us to compute key statistics, including volume, transactions, aggression, directional exposure, holding duration, margin, and profit for each of 6,300 unique trader accounts. We identify a diverse set of trading strategies that constitute a rich market ecology. These range from arbitrage-based strategies with low and fleeting directional exposure to strategies involving large accumulated positions in one of the two major party candidates. Most traders who make directional bets do so consistently in a single direction, unlike the information traders in some canonical models of market microstructure. We present evidence suggestive of manipulation by a single large trader, and consider the possible motives for such behavior. Broader implications for the interpretation of prices in financial markets and the theory of market microstructure are drawn.

Realized Volatility Forecasting in the Presence of Time-Varying Noise

Observed high-frequency financial prices can be considered as having two components, a true price and a market microstructure noise perturbation. It is an empirical regularity, coherent with classical market microstructure theories of price determination, that the second moment of market microstructure noise is time-varying. We study the optimal, from a finite-sample forecast mean squared error (MSE) standpoint, frequency selection for realized variance in linear variance forecasting models with time-varying market microstructure noise. We show that the resulting sampling frequencies are generally considerably lower than those that would be optimally chosen when time-variation in the second moment of the noise is unaccounted for. These optimal, lower frequencies have the potential to translate into considerable out-of-sample MSE gains. When forecasting using high-frequency variance estimates, we recommend treating the relevant frequency as a parameter and evaluating it jointly with the parameters of the forecasting model. The proposed joint solution is robust to the features of the true price formation mechanism and generally applicable to a variety of forecasting models and high-frequency variance estimators, including those for which the typical choice variable is a smoothing parameter, rather than a frequency.

Liquidity Provision in a Limit-Order Market: The Case of the Tunisian Stock Exchange

This paper examines the dynamics of buy and sell liquidity provision in the Tunisian stock exchange (B.V.M.T.) and uses high frequency data from a reconstructed limit order book. As an order driven market, The BVMT relies on limit order submissions to supply liquidity and ensure exchanges. Using an Autoregressive Conditional Duration Model, the focus was on the time dimension of the trading process. Applying a parsimonious methodology to the most liquid stocks traded in continuous session, we found that renewal frequency of liquidity supply depends on the state of the market which is characterized by three types of variables: pre-transaction variables such as spread, depth, limit order imbalance, and transitory volatility, post-transaction variables such as realized volatility, traded volume, order satisfaction rate, pre-opening variables such as opening volume, opening-closing volatility. Our results confirm the microstructure theory predictions: Asymmetric information discourages liquidity provision. Traders consume liquidity when it is abundant. They, also supply liquidity when an immediate transaction is expensive. However, traders are more attentive to order volatility than to limit order satisfaction rate.

Simulation of Vibration Isolation by Shape Memory Alloy Springs Using a Microstructural Model of Shape Memory Alloy

A vibroisolation of a payload connected to a vibrating housing by two helical shape memory alloy (SMA) elements is considered. A microstructural theory is used for the simulation of the mechanical behavior of the SMA. The simulations have shown that the resonant frequency and the mitigation of the external vibrations depend on the shape memory alloy state. The maximum reduction of the acceleration amplitude for harmonic excitation is reached when the SMA is in the martensitic pseudoplastic state or in the two-phase state. Variation of temperature allows changing the resonance frequency and thus escaping from resonance. The acceleration of the payload at impact is the smallest when the SMA elements are in the pseudoelastic state.

Microstructural theory and the rheology of concentrated colloidal suspensions

AbstractA theory for the analytical prediction of microstructure of concentrated Brownian suspensions of spheres in simple-shear flow is developed. The computed microstructure is used in a prediction of the suspension rheology. A near-hard-sphere suspension is studied for solid volume fraction $\phi \leq 0. 55$ and Péclet number $Pe= 6\lrm{\pi} \eta \dot {\gamma } {a}^{3} / {k}_{b} T\leq 100$; $a$ is the particle radius, $\eta $ is the suspending Newtonian fluid viscosity, $\dot {\gamma } $ is the shear rate, ${k}_{b} $ is the Boltzmann constant and $T$ is absolute temperature. The method developed determines the steady pair distribution function $g(\mathbi{r})$, where $\mathbi{r}$ is the pair separation vector, from a solution of the Smoluchowski equation (SE) reduced to pair level. To account for the influence of the surrounding bath of particles on the interaction of a pair, an integro-differential form of the pair SE is developed; the integral portion represents the forces due to the bath which drive the pair interaction. Hydrodynamic interactions are accounted for in a pairwise fashion, based on the dominant influence of pair lubrication interactions for concentrated suspensions. The SE is modified to include the influence of shear-induced relative diffusion, and this is found to be crucial for success of the theory; a simple model based on understanding of the shear-induced self-diffusivity is used for this property. The computation of the microstructure is split into two parts, one specific to near-equilibrium ($Pe\ll 1$), where a regular perturbation expansion of $g$ in $Pe$ is applied, and a general-$Pe$ solution of the full SE. The predicted microstructure at low $Pe$ agrees with prior theory for dilute conditions, and becomes increasingly distorted from the equilibrium isotropic state as $\phi $ increases at fixed $Pe\lt 1$. Normal stress differences are predicted and the zero-shear viscosity predicted agrees with simulation results obtained using a Green–Kubo formulation (Foss & Brady, J. Fluid Mech., vol. 407, 2000, pp. 167–200). At $Pe\geq O(1)$, the influence of convection results in a progressively more anisotropic microstructure, with the contact values increasing with $Pe$ to yield a boundary layer and a wake. Agreement of the predicted microstructure with observations from simulations is generally good and discrepancies are clearly noted. The predicted rheology captures shear thinning and shear thickening as well as normal stress differences in good agreement with simulation; quantitative agreement is best at large $\phi $.

Physical-Mechanical Properties and Microstructure Features of Cohesive Soil in the Central South Yellow Sea

Based on microstructure theory and technical method of soil property, the microstructure features of cohesive soil in the central South Yellow Sea were studied. Combined with parameters of physical-mechanical properties, the relation of physical-mechanical properties to particle contact, particle accumulation and pores is studied. The study indicates that soils in this area are mainly cohesive soil including clayey silt, muddy clay and mud. They have three microstructure types: granular link-bond structure, honeycomb structure, and loose matrix structure. Mud and muddy clay are of honeycomb structure and loose matrix structure; they have the characteristics of high water content, high pore ratio, low shear strength, and high compressibility. Clayey silt is of granular link-bond structure;its water content and pore ratio are lower than that of mud and muddy clay. The cohesive soils in this area are a disadvantage for submarine projects and will create direct or potential hazards to structures. During construction in this area, we should avoid or take corresponding measures to improve these soils.

Advances in High Frequency Strategies

This doctoral dissertation, in the field of Mathematical Finance, has received Complutense University-s Ph.D. Prize for the academic year 2011/2012. It is also the author s second Ph.D. dissertation. His first Ph.D.s dissertation was in the field of Financial Economics, and was published in 2003 (https www.educacion.gob.es/teseo/mostrarRef.do ref 295773).Recent legislative changes in the United States (RegNMS) and Europe (MiFID), preceded by substantial technological advances in computation and communication, have been conducive to the proliferation of high frequency trading strategies. About 70 por ciento of the total transacted volume in stocks has been estimated to originate from high frequency operators. In futures markets, that figure is believed to exceed 50%. The goal of this doctoral dissertation is to examine, from a mathematical perspective, how market microstructure theories need to be adjusted to the new high frequency trading framework. Chapter I explains that current market participants follow a volume or transactional clock, as opposed to operating in chronological time. Much of market microstructure theory is built upon the paradigm of chronological time, and must therefore be re-formulated. Our approach generalizes the PIN Theory of Easley and O Hara (1996), by proposing a new estimate of the Probability of Informed Trading based on volume-time sampling, thus consistent with a high-frequency setting. Chapter II demonstrates that returns- volatility is partially caused by order flow toxicity, and that sampling order imbalance in volume-clock has predictive power over that toxicity-induced volatility.Chapter III shows that volume-time order imbalance reached an extreme value two hours before the May 6th 2010 flash crash, and that da-s 10 por ciento price plunge is likely to be the consequence of a liquidity crisis triggered by order flow toxicity.

The Role of Information in the Analysis of Stock Market Prices: Case of Botswana Stock Exchange

The study analyses the price process in the BSE using the microstructure theory that acknowledges imperfect information in the stock market. The paper adopted the standard ACD model of Engle and Russell (1998). The data used in this paper has been sampled by a thinned point process. The model is applied to the actual prices of two stocks traded on the BSE and the evidence in favor of asymmetry information is strong. The study finds that uninformed traders prefer to trade when the market is liquid while informed traders trade only when they believe that they will gain. The assumption of perfect information is found to be unrealistic and preference is given to market microstructure theory. Following Easley and O’Hara (1992) information effects are also empirically relevant to analysis of price process in the stock markets.

HIGH‐FREQUENCY EXCHANGE‐RATE PREDICTION WITH AN ARTIFICIAL NEURAL NETWORK

SUMMARYThis paper examines how market microstructure variables can be used to forecast foreign exchange (FX) rates at frequencies of one to several minutes. We use a unique FX dataset of global inter‐dealer electronic transactions and applied the artificial neural network (ANN) as the predicting model. The immediately preceding bid and ask prices are significant factors in these predictions, which is in keeping with market microstructure theory. These microstructure factors have not been tested in an ANN model before. High‐frequency trading strategies based on the ANN model are shown to be profitable even when transaction costs are included. Copyright © 2012 John Wiley & Sons, Ltd.

Least Squares Inference on Integrated Volatility and the Relationship Between Efficient Prices and Noise

The expected value of sums of squared intraday returns (realized variance) gives rise to a least squares regression which adapts itself to the assumptions of the noise process and allows for joint inference on integrated variance (), noise moments, and price-noise relations. In the iid noise case, we derive the asymptotic variance of the and noise variance estimators and show that they are consistent. The joint estimation approach is particularly attractive as it reveals important characteristics of the noise process which can be related to liquidity and market efficiency. The analysis of dependence between the price and noise processes provides an often missing link to market microstructure theory. We find substantial differences in the noise characteristics of trade and quote data arising from the effect of distinct market microstructure frictions. This article has supplementary material online.

Insider Trading Rules and Price Formation in Securities Markets - An Entropy Analysis of Strategic Trading

This paper addresses the issue of how insider trading rules affect price formation in securities markets and suggests the application of information theory to market microstructure theory. We analyze a variant of Kyle's (1985) setting by simply introducing a more general criterion for informational efficiency borrowed from information theory - namely maximum information transmission. The analysis shows that both the insider's optimal trading strategy and the market price of the risky security depend on the insider trading restriction. Insider trading restrictions are reported to be detrimental to the liquidity of the securities market. We find that a unique insider trading rule exists which implements semi-strong form informational efficiency of the securities market. Alternative restrictions on insider trading give rise to either underreaction or overreaction in securities prices. Too strict insider trading rules are shown to account for excess volatility in securities prices. Contrary to common notion, the uninformed investors are shown to be hurt by too restrictive insider trading rules. We conclude that loose insider trading rules are preferred by the group of investors as a whole.

Study on the Microstructure of Human Articular Cartilage/Bone Interface

For improving the theory of gradient microstructure of cartilage/bone interface, human distal femurs were studied. Scanning Electron Microscope (SEM), histological sections and MicroCT were used to observe, measure and model the microstructure of cartilage/bone interface. The results showed that the cartilage/bone interface is in a hierarchical structure which is composed of four different tissue layers. The interlocking of hyaline cartilage and calcified cartilage and that of calcified cartilage and subchondral bone are in the manner of “protrusion-pore” with average diameter of 17.0 μm and 34.1 μm respectively. In addition, the cancellous bone under the cartilage is also formed by four layer hierarchical structure, and the adjacent layers are connected by bone trabecula in the shape of H, I and Y, forming a complex interwoven network structure. Finally, the simplified structure model of the cartilage/bone interface was proposed according to the natural articular cartilage/bone interface. The simplified model is a 4-layer gradient biomimetic structure, which corresponds to four different tissues of natural cartilage/bone interface. The results of this work would be beneficial to the design of bionic scaffold for the tissue engineering of articular cartilage/bone.

An Empirical Investigation of the Intraday Pattern for Characteristic Variables of Market Microstructure in China Stock Market

Financial market microstructure theory is one of most important new finance branches, which has gradually developed into the most active area in modern microfinance researches. China stock market is an emerging stock market having a special market microstructure. It is of great practical significance to study the market microstructure characteristic in China stock market. The market microstructure characteristic variables such as return, volatility, trading volume, bid-ask spread and duration, are random, but may display some determinant intraday pattern in average sense. In this paper we use the parametric and nonparametric methods to test and explain the intraday patterns and examine the intraday variation in return, return volatility, trading volume, bid-ask spread and financial duration for a sample of 178 stocks traded on the China stock market during 2006 and 2009, especially focuses on the intraday pattern of market microstructure variables and compares the differences among three different periods of rising, falling and adjusting period in Shanghai and Shenzhen stock markets. We find that there is some difference existing among the intraday patterns of market microstructure variables under the three different periods. The stock return is higher in the rising period, though the intraday pattern is U-shaped under three periods. The volatility is higher in the falling period and the intraday pattern is inverse J-shaped. The bidask spread is higher in the rising period and falling period, the intraday pattern is J-shaped. The financial duration is shorter in the rising period and falling period, the intraday pattern is inverse U-shaped. Comparing with the U.S. and U.K. stock markets, there are some clear differences in the intraday patterns of the market microstructure characteristic variables in China stock market.

Market impact measurement of a VWAP trading algorithm

This paper proposes a model for the market impact of algorithmic trades. Usually large orders cannot be executed immediately without significant trading costs. For optimised execution one relies on the help of a VWAP (volume-weighted average price) trading algorithm. It is demonstrated that the VWAP algorithm is the optimal solution of the optimisation problem using the market impact models presented in this paper. The purpose of this work is the empirical market impact analysis of a homogeneous set of algorithmic trades. The underlying data set contains trades resulting from a hedge fund trading strategy. The analysis shows that the participation rate is the most important description variable. Therefore, a linear model and also a concave power law model of the market impact, dependent on the participation rate, are used. The estimated parameters lead to interesting consequences for verifying certain aspects of the market microstructure theory. The results also suggest different behaviour of the various analysed markets. On the one hand the market impact dependency on the participation rate behaves differently for the Japanese market compared to the European, US and Canadian markets. On the other hand, the individualised linear regression results suggest a dependency of the market impact on tick size for the Japanese and US markets.

Price Discovery In The Soybean Futures Market

This paper investigates the price discovery process between the nearby futures prices of soybean, soy meal, and soy oil contracts (Crush constituents) in the U.S. Relationships between these commodities may bear important implications for trading strategies, market inefficiencies, or the derived demand theory. Furthermore, our findings are relevant in light of market microstructure theories, which maintain that the price information disseminates from more liquid contracts. Our VAR and bivariate GARCH model estimates suggest a strong bi-directional causality in Crush futures prices. We also find that while soybean contracts bear the burden of convergence when the spread between soybean and soy meal contract prices widens, this is not true of soybean and soy oil contracts. Furthermore, we show evidence of considerable volatility persistence for the three contracts and volatility spillover between soybean and other Crush constituent futures. The statistical evidence suggests that information arrives in these markets simultaneously. Our findings do not support the derived demand theory.

Least Squares Inference on Integrated Volatility and the Relationship between Efficient Prices and Noise

The expected value of sums of squared intraday returns (realized variance) gives rise to a least squares regression which adapts itself to the assumptions of the noise process and allows for joint inference on integrated volatility (IV), noise moments and price-noise relations. In the iid noise case, we derive the asymptotic variance of the IV and noise variance estimators and show that they are consistent. The joint estimation approach is particularly attractive as it reveals important characteristics of the noise process which can be related to liquidity and market efficiency. The analysis of dependence between the price and noise processes provides an often missing link to market microstructure theory. We find substantial differences in the noise characteristics of trade and quote data arising from the effect of distinct market microstructure frictions.

Optimal Exchange Rates: A Market Microstructure Approach

Motivated by the observation that exchange-rate management resembles market making, we use microstructure theory in order to conduct a welfare analysis of exchange-rate management, including the corner solutions of a free float and a fixed peg. We show that a policy that smoothes out exchange-rate fluctuations needs to trade off the welfare gain due to lower risk exposure of local producers against the trading losses that the policy would generate owing to speculation. We identify the conditions under which exchange-rate management can increase welfare and argue that these conditions are more likely to be satisfied in illiquid markets, mainly small economies and emerging markets. We also explore the role of a Tobin tax (assuming enforceability) in facilitating exchange-rate management.

Geographic proximity and price discovery: Evidence from NASDAQ

We use the NASDAQ market making context to study the role of geographic proximity in the price discovery of a firm's stock. We show that market makers closer to the firm's headquarters spend more time at the inside bid and ask quotes, initiate larger changes in the quotes, and account for greater information share when compared to non-local market makers. Examining a sample of relocating firms, we also find that market makers moving farther away from the firm after relocation experience a reduction in their contributions to price discovery. Our results suggest that some (local) market makers possess superior information relative to other (non-local) market makers and they trade strategically on this information, a finding that challenges the traditional assumptions in market microstructure theory.

Market microstructure: A review from down under

The early automation of the Australian and New Zealand financial markets provided researchers with access to high-frequency data to undertake extensive empirical market microstructure research. We use this anniversary edition of Accounting and Finance to review some of this research and to discuss the development of the Australian and New Zealand markets since their automation. We identify issues currently facing the markets and highlight potential areas for future research. The paper also provides a review of market microstructure theory on inventory control models and asymmetric information models.

On the Correlation Structure of Microstructure Noise: A Financial Economic Approach

We introduce the financial economics of market microstructure into the financial econometrics of asset return volatility estimation. In particular, we use market microstructure theory to derive the cross-correlation function between latent returns and market microstructure noise, which feature prominently in the recent volatility literature. The cross-correlation at zero displacement is typically negative, and crosscorrelations at nonzero displacements are positive and decay geometrically. If market makers are sufficiently risk averse, however, the cross-correlation pattern is inverted. We derive model-based volatility estimators, which we apply to stock and oil prices. Our results are useful for assessing the validity of the frequently-assumed independence of latent price and microstructure noise, for explaining observed cross-correlation patterns, for predicting as-yet undiscovered patterns, and for microstructure-based volatility estimation.