1,721,087 research outputs found
A microsimulation of traders activity in the stock market: the role of heterogeneity, agents' interactions and trade frictions
No full textWe propose a model with heterogeneous interacting traders which can explain some of the stylized facts of stock market returns. In the model, synchronization effects, which generate large fluctuations in returns, can arise purely from communication and imitation among traders. The key element in the model is the introduction of a trade friction which, by responding to price movements, creates a feedback mechanism on future trading and generates volatility clustering. The model also reproduces the empirically observed positive cross-correlation between volatility and trading volume
The Impact of Reduced Pre-Trade Transparency Regimes on Market Quality
Full text linkThis paper studies the effects of pre-trade quote transparency on spread, price discovery and liquidity in an artificial limit order market with heterogeneous trading rules. Our agent-based numerical experiments suggest that full quote transparency incurs substantial transaction costs to traders and dampens trading activity in an order-driven market. Our finding reveals that exogenous restriction of displayed depth, up to several best quotes, does not benefit market performance. On the contrary, endogenous restriction of displayed quote depth, by means of iceberg orders, improves market quality in multiple dimensions: it reduces average transaction costs, maintains higher liquidity and moderate volatility, balances the limit order book, and enhances price discovery
A simulation analysis of the microstructure of double auction markets
No full textWe introduce an order-driven market model with heterogeneous agents trading via a central order matching mechanism. Traders set bids and asks and post market or limit orders according to exogenously fixed rules. We investigate how different trading strategies may affect the dynamics of price, bid–ask spreads, trading volume and volatility. We also analyse how some features of market design, such as tick size and order lifetime, affect market liquidity. The model is able to reproduce many of the complex phenomena observed in real stock markets. © 2002 IOP Publishing Ltd
Currency futures volatility during the 1997 East Asian crisis: an application of Fourier analysis
Full text linkWe analyze a recently proposed method to estimate volatility and correlation when prices are observed at a high frequency rate. The method is based on Fourier analysis and does not require any data manipulation, leading to more robust estimates than the traditional methodologies proposed so far. In the first part of the paper, we evaluate the performance of the Fourier algorithm to reconstruct the time volatility of simulated univariate and bivariate models; in the second part, the Fourier method is used to investigate the volatility and correlation dynamics of futures markets over the Asian crisis period, with the purpose of detecting possible interdependencies and volatility transmissions across countries amid a period of financial turmoil
Socioeconomic networks with long-range interactions
No full textWe study a modified version of a model previously proposed by Jackson and Wolinsky to account for communication of information and allocation of goods in socioeconomic networks. In the model, the utility function of each node is given by a weighted sum of contributions from all accessible nodes. The weights, parametrized by the variable δ, decrease with distance. We introduce a growth mechanism where new nodes attach to the existing network preferentially by utility. By increasing δ, the network structure evolves from a power-law to an exponential degree distribution, passing through a regime characterized by shorter average path length, lower degree assortativity, and higher central point dominance. In the second part of the paper we compare different network structures in terms of the average utility received by each node. We show that power-law networks provide higher average utility than Poisson random networks. This provides a possible justification for the ubiquitousness of scale-free networks in the real world. © 2008 The American Physical Society
Macroprudential Capital Buyers in Heterogeneous Banking Networks: Insights from an ABM with Liquidity Crises
Full text linkIn this paper, we study how the effectiveness of macroprudential capital buffers conditional to the systemic-risk assessment of banks responds to the degree of heterogeneity of the financial system. A multi-agent model is employed to build an artificial economy with households, firms, and banks where occasional liquidity crises emerge. The systemic importance of banks is captured by a score-based mechanism reflecting banks' characteristics in terms of size or interconnectedness. We compare three degrees of heterogeneity in the configuration of financial networks related to different banking concentrations in the loan market. The main findings suggest that: (i) reducing the heterogeneity of the banking network stabilizes the economy by itself; (ii) the identification criteria of systemic-important institutions are affected by the heterogeneity of financial networks; it is preferable to apply systemic capital surcharges to the largest banks under high heterogeneity and targeting those most interconnected under low heterogeneity; (iii) the effectiveness of systemic capital buffers is preserved under high heterogeneity when a common asset holding contagion channel is added. However, simple measures based on risk-weighted assets capital ratios appear to be more effective in low heterogeneous systems. Thus, we argue that prudential regulation should account for the characteristics of the banking networks and tune macroprudential tools accordingly
Weighted network analysis of high frequency cross-correlation measures
Full text linkIn this paper we implement a Fourier method to estimate high-frequency correlation matrices from small data sets. The Fourier estimates are shown to be considerably less noisy than the standard Pearson correlation measures and thus capable of detecting subtle changes in correlation matrices with just a month of data. The evolution of correlation at different time scales is analyzed from the full correlation matrix and its minimum spanning tree representation. The analysis is performed by implementing measures from the theory of random weighted networks. © 2007 The American Physical Society
Cross-correlation measures in the high-frequency domain
No full textOn a high-frequency scale the time series are not homogeneous, therefore standard correlation measures cannot be directly applied to the raw data. To deal with this problem the time series have to be either homogenized through interpolation, or methods that can handle raw non-synchronous time series need to be employed. This paper compares two traditional methods that use interpolation with an alternative method applied directly to the actual time series. The three methods are tested on simulated data and actual trades time series
The Impact of Heterogeneous Trading Rules on the Limit Order Book and Order Flows
Full text linkIn this paper we develop a model of an order-driven market where traders set bids and asks and post market or limit orders according to exogenously fixed rules. Agents are assumed to have three components to the expectation of future asset returns, namely-fundamentalist, chartist and noise trader. Furthermore agents differ in the characteristics describing these components, such as time horizon, risk aversion and the weights given to the various components. The model developed here extends a great deal of earlier literature in that the order submissions of agents are determined by utility maximisation, rather than the mechanical unit order size that is commonly assumed. In this way the order flow is better related to the ongoing evolution of the market. For the given market structure we analyze the impact of the three components of the trading strategies on the statistical properties of prices and order flows and observe that it is the chartist strategy that is mainly responsible of the fat tails and clustering in the artificial price data generated by the model. The paper provides further evidence that large price changes are likely to be generated by the presence of large gaps in the book
The role of communication and imitation in limit order markets
No full textIn this paper we develop an order driver market model with heterogeneous traders that imitate each other on different network structures. We assess how imitations among otherway noise traders, can give rise to well known stylized facts such as fat tails and volatility clustering. We examine the impact of communication and imitation on the statistical properties of prices and order flows when changing the networks' structure, and show that the imitation of a given, fixed agent, called 'guru', can generate clustering of volatility in the model. We also find a positive correlation between volatility and bid-ask spread, and between fat-tailed fluctuations in asset prices and gap sizes in the order book. © EDP Sciences, Societa Italiana di Fisica, Springer-Verlag 2009
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