Search results for "Order book"

showing 10 items of 15 documents

Multi-agent-based Order Book Model of financial markets

2006

We introduce a simple model for simulating financial markets, based on an order book, in which several agents trade one asset at a virtual exchange continuously. For a stationary market the structure of the model, the order flow rates of the different kinds of order types and the used price time priority matching algorithm produce only a diffusive price behavior. We show that a market trend, i.e. an asymmetric order flow of any type, leads to a non-trivial Hurst exponent for the price development, but not to "fat-tailed" return distributions. When one additionally couples the order entry depth to the prevailing trend, also the stylized empirical fact of "fat tails" can be reproduced by our …

Hurst exponentStylized factOrder (exchange)Financial marketEconometricsOrder bookEconomicsGeneral Physics and AstronomyAsset (economics)Market trendOrder typeEurophysics Letters (EPL)
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Statistical analysis of financial returns for a multiagent order book model of asset trading

2007

We recently introduced a realistic order book model [T. Preis, Europhys. Lett. 75, 510 (2006)] which is able to generate the stylized facts of financial markets. We analyze this model in detail, explain the consequences of the use of different groups of traders, and focus on the foundation of a nontrivial Hurst exponent based on the introduction of a market trend. Our order book model supports the theoretical argument that a nontrivial Hurst exponent implies not necessarily long-term correlations. A coupling of the order placement depth to the market trend can produce fat tails, which can be described by a truncated Lévy distribution.

Hurst exponentStylized factOrder (exchange)Financial marketLévy distributionOrder bookEconomicsAsset (economics)Market trendMathematical economicsPhysical Review E
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The Dynamics of Quote Prices in an Artificial Financial Market with Learning Effects

2007

In this paper we study the evolution of bid and ask prices in an electronic financial market populated by portfolio traders who optimally choose their allocation strategy on the basis of their views about market conditions. Recently, a growing literature has investigated the consequences of learning about the returns process1. There has been an increasing interest in analyzing what are the implications of relaxing the assumption that agents hold correct expectations. In particular, it has been asked the fundamental question of understanding if typical asset-pricing anomalies (like returns predictability, and excess volatility) can be generated by a learning process about the underlying econ…

Mark to modelMicroeconomicsFinancial economicsfinancial market market volatility learning process copula function portfolio optimizationFinancial marketMarket systemOrder bookPortfolioBusinessPortfolio optimizationVolatility (finance)Market liquidity
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High-Frequency Data

2010

We introduce some of the most common types of high-frequency financial data: tick-by-tick data, trade and quote data, order book data, and market member data. We describe the types of variables that are usually available in the most popular high-frequency financial databases. We discuss the issues related to the handling of these data, including cleaning protocols, timing issues, and issues related to data size. We then briefly consider the issues related to the stylized facts detected in the empirical analysis of high-frequency data. Specifically, we consider (i) the irregular temporal spacing of the events at high frequency and its relevance for the econometric modeling of financial varia…

Market structureEconometric modelStylized factActuarial scienceEconophysicsFinancial marketOrder bookEconomicsRelevance (information retrieval)Market microstructure
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Price-Time Priority and Pro Rata Matching in an Order Book Model of Financial Markets

2011

Using our recently introduced order book model of financial markets we analyzed two different matching principles for order allocation — price-time priority and pro rata matching. Price-time priority uses the submission timestamp which prioritizes orders in the book with the same price. The order which was entered earliest at a given price limit gets executed first. Pro rata matching is used for products with low intraday volatility of best bid and best ask price. Pro rata matching ensures constant access for orders of all sizes. We demonstrate how a multiagent-based model of financial market can be used to study microscopic aspects of order books.

MicroeconomicsActuarial sciencePro rataOrder (exchange)Ask priceMatching principleFinancial marketEconomicsOrder bookVolatility (finance)Limit price
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Diffusive behavior and the modeling of characteristic times in limit order executions

2007

We present an empirical study of the first passage time (FPT) of order book prices needed to observe a prescribed price change Delta, the time to fill (TTF) for executed limit orders and the time to cancel (TTC) for canceled ones in a double auction market. We find that the distribution of all three quantities decays asymptotically as a power law, but that of FPT has significantly fatter tails than that of TTF. Thus a simple first passage time model cannot account for the observed TTF of limit orders. We propose that the origin of this difference is the presence of cancellations. We outline a simple model, which assumes that prices are characterized by the empirically observed distribution …

Physics - Physics and SocietyFOS: Physical sciencesPhysics and Society (physics.soc-ph)Power lawFOS: Economics and businessOrder bookTime to fillLimit (mathematics)Statistical physicsMicrostructureMathematicsQuantitative Finance - Trading and Market MicrostructureEconophysicsLimit order marketEconophysicProbability and statisticsFirst passage timeTrading and Market Microstructure (q-fin.TR)Distribution (mathematics)Physics - Data Analysis Statistics and ProbabilityExponentCensored dataFirst-hitting-time modelGeneral Economics Econometrics and FinanceFinanceData Analysis Statistics and Probability (physics.data-an)
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How does the market react to your order flow?

2012

We present an empirical study of the intertwined behaviour of members in a financial market. Exploiting a database where the broker that initiates an order book event can be identified, we decompose the correlation and response functions into contributions coming from different market participants and study how their behaviour is interconnected. We find evidence that (1) brokers are very heterogeneous in liquidity provision -- some are consistently liquidity providers while others are consistently liquidity takers. (2) The behaviour of brokers is strongly conditioned on the actions of {\it other} brokers. In contrast brokers are only weakly influenced by the impact of their own previous ord…

Physics - Physics and SocietyQuantitative Finance - Trading and Market MicrostructureMarket microstructureLimit order marketFinancial marketFOS: Physical sciencesBehavioural financePhysics and Society (physics.soc-ph)Market microstructureMonetary economicsMarket dynamicsFinancial marketFinancial markets microstructure Econophysics stochasti processesTrading and Market Microstructure (q-fin.TR)Market liquidityFOS: Economics and businessCompetition (economics)Empirical researchOrder (exchange)Physics - Data Analysis Statistics and ProbabilityOrder bookBusinessGeneral Economics Econometrics and FinanceData Analysis Statistics and Probability (physics.data-an)FinanceQuantitative Finance
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Price Impact Function of a Single Transaction

2004

Although supply and demand are perhaps the most fundamental concepts in economics, finding any general form for their behavior has proved to be elusive. Here we discuss our recent findings [1] on the price impact function empirically detected in the New York Stock Exchange (NYSE). Our study builds on earlier studies of how trading affects prices [2, 3, 4, 5, 6, 7, 8, 9, 10, 11]. In particular, we look at the short term response to a single trade. This is done by using huge amounts of data and by measuring the market activity in units of transactions rather than seconds, so that we can more naturally aggregate data for many different stocks. This allows us to find regularities in the respons…

Reservation priceOrder (exchange)Stock exchangeFinancial economicsMid priceEconometricsEconomicsOrder bookAggregate dataDatabase transactionSupply and demand
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The adaptive nature of liquidity taking in limit order books

2014

In financial markets, the order flow, defined as the process assuming value one for buy market orders and minus one for sell market orders, displays a very slowly decaying autocorrelation function. Since orders impact prices, reconciling the persistence of the order flow with market efficiency is a subtle issue. A possible solution is provided by asymmetric liquidity, which states that the impact of a buy or sell order is inversely related to the probability of its occurrence. We empirically find that when the order flow predictability increases in one direction, the liquidity in the opposite side decreases, but the probability that a trade moves the price decreases significantly. While the…

Statistics and ProbabilityQuantitative Finance - Trading and Market MicrostructureStatistical Finance (q-fin.ST)Limit order book econophysics market efficiencyfinancial instruments and regulationAutocorrelationFinancial marketQuantitative Finance - Statistical FinanceStatistical and Nonlinear PhysicsProbability and statisticsTrading and Market Microstructure (q-fin.TR)Market liquidityFOS: Economics and businessFlow (mathematics)Order (exchange)risk measure and managementOrder bookEconomicsEconometricsmodels of financial marketStatistics Probability and UncertaintyPredictabilityStatistical and Nonlinear Physic
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Investigation of Simulated Trading — A multi agent based trading system for optimization purposes

2010

Abstract Some years ago, Bachem, Hochstattler, and Malich proposed a heuristic algorithm called Simulated Trading for the optimization of vehicle routing problems. Computational agents place buy-orders and sell-orders for customers to be handled at a virtual financial market, the prices of the orders depending on the costs of inserting the customer in the tour or for his removal. According to a proposed rule set, the financial market creates a buy-and-sell graph for the various orders in the order book, intending to optimize the overall system. Here I present a thorough investigation for the application of this algorithm to the traveling salesman problem.

Statistics and ProbabilitySet (abstract data type)Mathematical optimizationHeuristic (computer science)Computer scienceMulti-agent systemVehicle routing problemFinancial marketOrder bookGraph (abstract data type)2-optCondensed Matter PhysicsTravelling salesman problemPhysica A: Statistical Mechanics and its Applications
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