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443
Operating system profiling via latency analysis
 In Proceedings of the 7th Symposium on Operating Systems Design and Implementation (ACM SIGOPS
, 2006
"... Operating systems are complex and their behavior depends on many factors. Source code, if available, does not directly help one to understand the OS’s behavior, as the behavior depends on actual workloads and external inputs. Runtime profiling is a key technique to prove new concepts, debug problems ..."
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Cited by 37 (14 self)
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Operating systems are complex and their behavior depends on many factors. Source code, if available, does not directly help one to understand the OS’s behavior, as the behavior depends on actual workloads and external inputs. Runtime profiling is a key technique to prove new concepts, debug problems, and optimize performance. Unfortunately, existing profiling methods are lacking in important areas—they do not provide enough information about the OS’s behavior, they require OS modification and therefore are not portable, or they incur high overheads thus perturbing the profiled OS. We developed OSprof: a versatile, portable, and efficient OS profiling method based on latency distributions analysis. OSprof automatically selects important profiles for subsequent visual analysis. We have demonstrated that a suitable workload can be used to profile virtually any OS component. OSprof is portable because it can intercept operations and measure OS behavior from userlevel or from inside the kernel without requiring source code. OSprof has typical CPU time overheads below 4%. In this paper we describe our techniques and demonstrate their usefulness through a series of profiles conducted on Linux, FreeBSD, and Windows, including client/server scenarios. We discovered and investigated a number of interesting interactions, including scheduler behavior, multimodal I/O distributions, and a previously unknown lock contention, which we fixed. 1
Tiebout/TaxCompetition Model
 Journal of Public Economics, August
"... delivery of the gax gene inhibits vessel stenosis in a rabbit ..."
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Cited by 25 (0 self)
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delivery of the gax gene inhibits vessel stenosis in a rabbit
The effects of marketmaking on price dynamics
, 2006
"... This paper studies marketmakers, agents responsible for maintaining liquidity and orderly price transitions in markets. Marketmakers include major firms making markets on global stock exchanges, as well as software agents that run behind the scenes on novel electronic markets like prediction marke ..."
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Cited by 23 (5 self)
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This paper studies marketmakers, agents responsible for maintaining liquidity and orderly price transitions in markets. Marketmakers include major firms making markets on global stock exchanges, as well as software agents that run behind the scenes on novel electronic markets like prediction markets. We use a sophisticated model of marketmaking to build richer agentbased models of markets and show how these models can be useful both in understanding properties of existing markets and in predicting the impacts of structural changes. For example, we show how competition among marketmakers can lead to significantly faster price discovery following a jump in the true value of an asset. We also show that myopic profitmaximization, apart from leading to poor market quality, is suboptimal even for a monopolistic marketmaker. This observation leads to an interesting characterization of the marketmaker’s explorationexploitation dilemma as a tradeoff between price discovery and profittaking.
Statistical Analysis of Financial Networks
, 2005
"... Massive datasets arise in a broad spectrum of scientific, engineering and commercial applications. In many practically important cases, a massive dataset can be represented as a very large graph with certain attributes associated with its vertices and edges. Studying the structure of this graph is e ..."
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Cited by 22 (1 self)
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Massive datasets arise in a broad spectrum of scientific, engineering and commercial applications. In many practically important cases, a massive dataset can be represented as a very large graph with certain attributes associated with its vertices and edges. Studying the structure of this graph is essential for understanding the structural properties of the application it represents. Wellknown examples of applying this approach are the Internet graph, the Web graph, and the Call graph. It turns out that the degree distributions of al these graphs can be described by the powerlaw model. Here we consider another important application  a network representation of the stock market. Stock markets generate huge amounts of data, which can be used for constructing the market graph reflecting the market behavior. We conduct the statistical analysis of this graph and show that it also folliws the powerlaw model. Moreover, we detect cliques and independent sets in this graph. These special formations have a clear practical interpretation, and their analysis allows one to apply a new data mining technique of classifying financial instruments based on stock prices data, which provides a deeper insight into the internal structure of the stock market.
Normal modified stable processes
, 2001
"... This paper discusses two classes of distributions, and stochastic processes derived from them: modified stable (MS) laws and normal modified stable (NMS) laws. This extends corresponding results for the generalised inverse Gaussian (GIG) and generalised hyperbolic (GH) or normal generalised inverse ..."
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Cited by 22 (4 self)
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This paper discusses two classes of distributions, and stochastic processes derived from them: modified stable (MS) laws and normal modified stable (NMS) laws. This extends corresponding results for the generalised inverse Gaussian (GIG) and generalised hyperbolic (GH) or normal generalised inverse Gaussian (NGIG) laws. The wider framework thus established provides, in particular, for added flexibility in the modelling of the dynamics of financial time series, of importance especially as regards OU based stochastic volatility models for equities. In the special case of the tempered stable OU process an exact option pricing formula can be found, extending previous results based on the inverse Gaussian and gamma distributions.
2001, “Power laws of wealth, market order volumes and market returns,” Physica A
"... Using the Generalised Lotka Volterra (GLV) model adapted to deal with muti agent systems we can investigate economic systems from a general viewpoint and obtain generic features common to most economies. Assuming only weak generic assumptions on capital dynamics, we are able to obtain very specific ..."
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Cited by 21 (2 self)
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Using the Generalised Lotka Volterra (GLV) model adapted to deal with muti agent systems we can investigate economic systems from a general viewpoint and obtain generic features common to most economies. Assuming only weak generic assumptions on capital dynamics, we are able to obtain very specific predictions for the distribution of social wealth. First, we show that in a ’fair ’ market, the wealth distribution among individual investors fulfills a power law. We then argue that ’fair play ’ for capital and minimal sociobiological needs of the humans traps the economy within a power law wealth distribution with a particular Pareto exponent α ∼ 3/2. In particular we relate it to the average number of individuals L depending on the average wealth: α ∼ L/(L − 1). Then we connect it to certain power exponents characterising the stock markets. We obtain that the distribution of volumes of the individual (buy and sell) orders follows a power law with similar exponent β ∼ α ∼ 3/2. Consequently, in a market where trades take place by matching pairs of such sell and buy orders, the corresponding exponent for the market returns is expected to be of order γ ∼ 2α ∼ 3. These results are consistent with recent experimental measurements of these power law exponents ([Maslov 2001] for β and [Gopikrishnan et al. 1999] for γ).
Critical Overview of AgentBased Models for Economics
, 1101
"... Summary. — We present an overview of some representative AgentBased Models in Economics. We discuss why and how agentbased models represent an important step in order to explain the dynamics and the statistical properties of financial markets beyond the Classical Theory of Economics. We perform a ..."
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Cited by 20 (2 self)
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Summary. — We present an overview of some representative AgentBased Models in Economics. We discuss why and how agentbased models represent an important step in order to explain the dynamics and the statistical properties of financial markets beyond the Classical Theory of Economics. We perform a schematic analysis of several models with respect to some specific key categories such as agents ’ strategies, price evolution, number of agents, etc. In the conclusive part of this review we address some open questions and future perspectives and highlight the conceptual importance of some usually neglected topics, such as nonstationarity and the selforganization of financial markets. 1.
Topological identification in networks of dynamical systems,” Automatic Control
 IEEE Transactions on
, 2010
"... Abstract—The paper deals with the problem of reconstructing the topological structure of a network of dynamical systems. A distance function is defined in order to evaluate the “closeness” of two processes and a few useful mathematical properties are derived. Theoretical results to guarantee the cor ..."
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Cited by 17 (2 self)
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Abstract—The paper deals with the problem of reconstructing the topological structure of a network of dynamical systems. A distance function is defined in order to evaluate the “closeness” of two processes and a few useful mathematical properties are derived. Theoretical results to guarantee the correctness of the identification procedure for networked linear systems with tree topology are provided as well. Finally, the application of the techniques to the analysis of an actual complex network, i.e. to high frequency time series of the stock market, is illustrated. I.
Scale Invariance and Universality of Economic Fluctuations
, 2000
"... In recent years, physicists have begun to apply concepts and methods of statistical physics to study economic problems, and the neologism "econophysics" is increasingly used to refer to this work. Much recent work is focused on understanding the statistical properties of time series. One r ..."
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Cited by 16 (0 self)
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In recent years, physicists have begun to apply concepts and methods of statistical physics to study economic problems, and the neologism "econophysics" is increasingly used to refer to this work. Much recent work is focused on understanding the statistical properties of time series. One reason for this interest is that economic systems are examples of complex interacting systems for which a huge amount of data exist, and it is possible that economic time series viewed from a different perspective might yield new results. This manuscript is a brief summary of a talk that was designed to address the question of whether two of the pillars of the field of phase transitions and critical phenomena  scale invariance and universality  can be useful in guiding research on economics. We shall see that while scale invariance has been tested for many years, universality is relatively less frequently discussed. This article reviews the results of two recent studies  (i) The probability distribution of stock price fluctuations: Stock price fluctuations occur in all magnitudes, in analogy to earthquakes  from tiny fluctuations to drastic events, such as market crashes. The distribution of price fluctuations decays with a powerlaw tail well outside the Lévy stable regime and describes fluctuations that differ in size by as much as eight orders of magnitude. (ii) Quantifying business firm fluctuations: We analyze the Computstat database comprising all publicly traded United States manufacturing companies within the years 19741993. We find that the distributions of growth rates is different for different bins of firm size, with a width that varies inversely with a power of firm size. Similar variation is found for other complex organizations, including country size, university research budget size, and size of species of bird populations.
A Random Matrix Theory Approach To Financial CrossCorrelations
, 2000
"... It is common knowledge that any two #rms in the economy are correlated. Even #rms belonging to di#erent sectors of an industry may be correlated because of "indirect" correlations. How can we analyze and understand these correlations? This article reviews recent results regarding crosscor ..."
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Cited by 15 (0 self)
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It is common knowledge that any two #rms in the economy are correlated. Even #rms belonging to di#erent sectors of an industry may be correlated because of "indirect" correlations. How can we analyze and understand these correlations? This article reviews recent results regarding crosscorrelations between stocks. Speci#cally, we use methods of random matrix theory (RMT), which originated from the need to understand the interactions between the constituent elements of complex interacting systems, to analyze the crosscorrelation matrix C of returns. We analyze 30min returns of the largest 1000 US stocks for the 2year period 19941995. We #nd that the statistics of approximately 20 of the largest eigenvalues (2%) show deviations from the predictions of RMT. To test that the rest of the eigenvalues are genuinely random, we test for universal properties such as eigenvalue spacings and eigenvalue correlations, and demonstrate that C shares universal properties with the Gaussian orthogonal ensemble of random matrices. The statistics of the eigenvectors of C con#rm the deviations of the largest few eigenvalues from the RMT prediction. We also #nd that these deviating eigenvectors are stable in time. In addition, we quantify the number of #rms that participate signi#cantly to an eigenvector using the concept of inverse participation ratio, borrowed from localization theory. c 2000 Published by Elsevier Science B.V. All rights reserved.