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We study the returns of stock prices and show that in the context of data from Bombay stock exchange there are groups of stocks that remain moderately correlated for up to 3 days. We use the delay correlations to identify these groups of stocks. In contrast to the results of same-time correlation matrix analysis, the groups in this case do not appear to come from any industry segments. We present our results using the closing prices of 326 significant stocks of Bombay stock exchange for the period 1995 to 2005. [ABSTRACT FROM AUTHOR]

So far econophysics has given contributions in four areas of economics: financial markets, wealth and income distribution, industrial economics (firms' size distribution, growth rates) and, more recently, networks analysis. According to Gallegati et al., 2006, there are some weakness in the approach: a lack of awareness of work that has been done within economics itself; resistance to more rigorous and robust statistical methodology; the belief that universal empirical regularities can be found in many areas of economic activity; the theoretical models which are being used to explain empirical phenomena. The paper raised a lively debate (see e.g. Ball, 2006). [ABSTRACT FROM AUTHOR]

Generalisation of the El Farol bar problem to that of many bars here leads to the Kolkata restaurant problem, where the decision to go to any restaurant or not is much simpler (depending on the previous experience of course, as in the El Farol bar problem). This generalised problem can be exactly analysed in some limiting cases discussed here. The fluctuation in the restaurant service can be shown to have precisely an inverse cubic behavior, as widely seen in the stock market fluctuations. [ABSTRACT FROM AUTHOR]

We show the existence of a first best incentive compatible mechanism for the queueing model that satisfies identical preferences lower bound. We call this mechanism the FB′ mechanism. We also show that for the queueing model, either with three agents or with four agents, the FB′ mechanism is the only first best incentive compatible mechanism that satisfies identical preferences lower bound. [ABSTRACT FROM AUTHOR]

We consider an R&D race between two symmetric firms. The game consists of two stages. In the first stage, firms non-cooperatively decide upon their levels of investment in R&D which, in turn, determine the Poisson probabilities of their subsequent sucesses. In the second stage, they engage in a Nash bargaining game to share their knowledge. We show that the firms over-invest and earn lower profits if knowledge sharing is possible compared to the situation where it is not. Hence, before the first stage, if the firms are given the option of precommitting to no knowledge sharing, they will do so and be better off. The society, of course, would be better off with full knowledge sharing. [ABSTRACT FROM AUTHOR]

Almost all societies, once they attain a certain level of complexity, exhibit inequality in the income of its members. Hierarchical stratification of social classes may be a major contributor to such unequal distribution of income, with intra-class variation often being negligible compared to inter-class differences. In this paper, examples from different historical periods, such as 10th century Byzantium and the Mughal empire of India in the 15th century, and different kinds of organizations, such as a criminal gang in the USA and Manufacturing & IT Services companies in India, are shown to suggest a causal relation between the hierarchical structure of social organization and the observed income inequality in societies. Proceeding from the assumption that income inequality may be a consequence of resource flow in a hierarchically structured social network, we present a model to show that empirically observed long-tailed income distribution can be explained through a process of division of assets at various levels in a hierarchical organization. [ABSTRACT FROM AUTHOR]

Revision and extension of a paper, ‘U.S. wage income since 1961: the perceived inequality trend', presented to the annual meetings of the Population Association of America, March-April 2005, Philadelphia, Pennsylvania, USA. On-line at: http://paa2005.princeton.edu/download.aspx?submission ID=50379. [ABSTRACT FROM AUTHOR]

Scientific collaboration network gives a nice description for communications among scientists. In order to show the status of the research in Econophysics, we have collected papers in Econophysics and constructed a network of scientific communication to integrate idea transportation among econophysicists by collaboration, citation and personal discussion. Inspired by scientific collaboration networks, especially our empirical analysis of econophysicists network, an evolutionary model for weighted networks is proposed. The model shows the scale-free phenomena in degree and vertex weight distribution. The results of short term evolution are consistent well qualitatively with the empirical results. [ABSTRACT FROM AUTHOR]

A first analysis of the Italian system of banks and firms was carried out using an approach based on network theory. The emerging architecture of this economic network shows peculiar behaviors. Big banks are creditors of many firms; among these, big firms are financed by several banks. On the contrary, small firms are preferentially financed by small banks, covering very often the entire credit they need. [ABSTRACT FROM AUTHOR]

We develop complex networks that represent activities in the economy. The network in this study is constructed from firms and the relationships between firms, i.e., shareholding, interlocking directors, transactions, and joint applications for patents. Thus, the network is regarded as a multigraph, and it is also regarded as a weighted network. By calculating various network indices, we clarify the characteristics of the network. We also consider the dynamics of firms in the production space that are characterized by capital stock, employment, and profit. Each firm moves within this space to maximize their profit by using controlling of capital stock and employment. We show that the dynamics of rational firms can be described using a ridge equation. We analytically solve this equation by assuming the extensive Cobb-Douglas production function, and thereby obtain a solution. By comparing the distribution of firms and this solution, we find that almost all of the 1,100 firms listed on the first section of the Tokyo stock exchange and belonging to the manufacturing sector are managed efficiently. [ABSTRACT FROM AUTHOR]

Bilateral trade relationships in the international level between pairs of countries in the world give rise to the notion of the International Trade Network (ITN). This network has attracted the attention of network researchers as it serves as an excellent example of the weighted networks, the link weight being defined as a measure of the volume of trade between two countries. In this paper we analyzed the international trade data for 53 years and studied in detail the variations of different network related quantities associated with the ITN. Our observation is that the ITN has also a scale invariant structure like many other real-world networks. [ABSTRACT FROM AUTHOR]

During the last few years various models of networks [1,2] have become a powerful tool for analysis of complex systems in such distant fields as Internet [3], biology [4], social groups [5], ecology [6] and public transport [7]. Modeling behavior of economical agents is a challenging issue that has also been studied from a network point of view. The examples of such studies are models of financial networks [8], supply chains [9, 10], production networks [11], investment networks [12] or collective bank bankrupcies [13, 14]. Relations between different companies have been already analyzed using several methods: as networks of shareholders [15], networks of correlations between stock prices [16] or networks of board directors [17]. In several cases scaling laws for network characteristics have been observed. [ABSTRACT FROM AUTHOR]

The financial markets started to be computerized due to development and spread of the Information and Communication Technology (ICT) in early 1990s. As the result rapid development and spread of electrical trading systems occurred all over the world. Moreover advance of processing speed of computers and capacity of storages leads to accumulation of activity records of market participants, high frequency financial data. By utilizing the high frequency financial data one can observe behavior of the market participants with high resolutions and analyze a large amount of data enough to quantify them in the statistically significant. [ABSTRACT FROM AUTHOR]

There has been an explosion in the number of models proposed for understanding and interpreting the dynamics of financial markets. Broadly speaking, all such models can be classified into two categories: (a) models which characterize the macroscopic dynamics of financial prices using time-series methods, and (b) models which mimic the microscopic behavior of the trader population in order to capture the general macroscopic behavior of prices. Recently, many econophysicists have trended towards the latter by using multi-agent models of trader populations. One particularly popular example is the so-called Minority Game [1], a conceptually simple multi-player game which can show non-trivial behavior reminiscent of real markets. Subsequent work has shown that - at least in principle - it is possible to train such multi-agent games on real market data in order to make useful predictions [2-5]. However, anyone attempting to model a financial market using such multi-agent trader games, with the objective of then using the model to make predictions of real financial time-series, faces two problems: (a) How to choose an appropriate multi-agent model? (b) How to infer the level of heterogeneity within the associated multi-agent population? [ABSTRACT FROM AUTHOR]

We model the logarithm of the price (log-price) of a financial asset as a random variable obtained by projecting an operator stable random vector with a scaling index matrix $$ \underline{\underline E} $$ onto a non-random vector. The scaling index $$ \underline{\underline E} $$ models prices of the individual financial assets (stocks, mutual funds, etc.). We find the functional form of the characteristic function of real powers of the price returns and we compute the expectation value of these real powers and we speculate on the utility of these results for statistical inference. Finally we consider a portfolio composed of an asset and an option on that asset. We derive the characteristic function of the deviation of the portfolio, $$ \mathfrak{D}_t^{(\mathfrak{t})} $$, defined as a temporal change of the portfolio diminished by the the compound interest earned. We derive pseudo-differential equations for the option as a function of the log-stock-price and time and we find exact closed-form solutions to that equation. These results were not known before. Finally we discuss how our solutions correspond to other approximate results known from literature,in particular to the well known Black & Scholes equation. [ABSTRACT FROM AUTHOR]

This paper uses the Subbotin power exponential family of probability densities to statistically characterize the distribution of price returns in some European day-ahead electricity markets (NordPool, APX, Powernext). We implement a generic non-parametric method, known as Cholesky factor algorithm, in order to remove the strong seasonality and the linear autocorrelation structure observed in power prices. The filtered NordPool and Powernext data are characterized by an inverse relationship between the returns volatility and the price level - approximately a linear functional dependence in log-log space, which properly applied to the Cholesky residuals yields a homoskedastic sample. Finally, we use Maximum Likelihood estimation of the Subbotin family on the rescaled residuals and compare the results obtained for different markets. All empirical densities, irrespectively of the time of the day and of the market considered, are well described by a heavy-tailed member of the Subbotin family, the Laplace distribution. [ABSTRACT FROM AUTHOR]

Prices of commodities or assets produce what is called time-series. Different kinds of financial time-series have been recorded and studied for decades. Nowadays, all transactions on a financial market are recorded, leading to a huge amount of data available, either for free in the Internet or commercially. Financial time-series analysis is of great interest to practitioners as well as to theoreticians, for making inferences and predictions. Furthermore, the stochastic uncertainties inherent in financial time-series and the theory needed to deal with them make the subject especially interesting not only to economists, but also to statisticians and physicists [1]. While it would be a formidable task to make an exhaustive review on the topic, with this review we try to give a flavor of some of its aspects. [ABSTRACT FROM AUTHOR]

We analyze the variations in S&P CNX NSE daily closing index stock values through discrete wavelets. Transients and random high frequency components are effectively isolated from the time series. Subsequently, small scale variations as captured by Daubechies level 3 and 4 wavelet coefficients and modelled by genetic programming. We have smoothened the variations using Spline interpolation method, after which it is found that genetic programming captures the dynamical variations quite well through Padē type of map equations. The low-pass coefficients representing the smooth part of the data has also been modelled. We further study the nature of the temporal variations in the returns. [ABSTRACT FROM AUTHOR]

The cross-correlations between price fluctuations of 201 frequently traded stocks in the National Stock Exchange (NSE) of India are analyzed in this paper. We use daily closing prices for the period 1996-2006, which coincides with the period of rapid transformation of the market following liberalization. The eigenvalue distribution of the cross-correlation matrix, C, of NSE is found to be similar to that of developed markets, such as the New York Stock Exchange (NYSE): the majority of eigenvalues fall within the bounds expected for a random matrix constructed from mutually uncorrelated time series. Of the few largest eigenvalues that deviate from the bulk, the largest is identified with market-wide movements. The intermediate eigenvalues that occur between the largest and the bulk have been associated in NYSE with specific business sectors with strong intra-group interactions. However, in the Indian market, these deviating eigenvalues are comparatively very few and lie much closer to the bulk. We propose that this is because of the relative lack of distinct sector identity in the market, with the movement of stocks dominantly influenced by the overall market trend. This is shown by explicit construction of the interaction network in the market, first by generating the minimum spanning tree from the unfiltered correlation matrix, and later, using an improved method of generating the graph after filtering out the market mode and random effects from the data. Both methods show, compared to developed markets, the relative absence of clusters of co-moving stocks that belong to the same business sector. This is consistent with the general belief that emerging markets tend to be more correlated than developed markets. [ABSTRACT FROM AUTHOR]

Standard economics is based on methodological individualism but this does not imply that the individuals play a crucial role in its models. On the contrary, in such a theory the individual is deprived of authentic subjective characteristics and plays no sizeable role as genuine subject. The so called Homo economicus is just a signpost for given preferences that, however, are generally conceived as exogenous and invariant through time. Therefore, the genuine psychological features of the economic agent do not matter. [ABSTRACT FROM AUTHOR]

‘Complexity' ideas are becoming a hot issue in economics. Originally developed within the natural sciences, complexity theory is now believed by many to be a novel and powerful framework of thought, capable of challenging the fundamental principles sustained by mainstream economics for more than a century. One of its main advocates, David Colander (2000a:31), has written that "Complexity changes everything; well, maybe not everything, but it does change quite a bit in economics". Also, in a recent issue of a popular scientific magazine, it is suggested that complexity ideas "are beginning to map out a radical and long-overdue revision of economic theory" (Buchanan, New Scientist, 2004:35). Indeed, the proliferation of publications, journals, summer schools, and conferences on complexity economics during the past few years can hardly pass unnoticed. [ABSTRACT FROM AUTHOR]

In the recent literature on optimal monetary policy, policymakers are assumed to know the true model of the economy and observe accurately all relevant variables. The sources and properties of economic disturbance are also taken to be known. Uncertainty in this case arises only due to the unknown future realisations of these disturbances. In this context, "uncertainty" means the realisation of an event whose true probability distribution is known. Pure uncertainty, where the state space of outcomes is known but one is unable to assign probabilities, has largely been ignored. In practice, the policymaker's choice is made in the face of tremendous uncertainty about the true structure of the economy, the impact policy actions have on the economy, and even about the current state of the economy. The policymaker is therefore unsure about his model, in the sense that there is a group of approximate models that he also considers as possibly true. Because uncertainty is pervasive, it is important to understand how alternative policies work when the policymaker cannot accurately observe important macro variables or when he employs a model of the economy that is incorrect in unknown ways. [ABSTRACT FROM AUTHOR]

The industrial dynamic literature has shown the existence of some stylized facts regarding firms' distribution among which a very important one, for the reasons discussed in the paper, is the scaling law of firms' size (Axtell, 2001)1. [ABSTRACT FROM AUTHOR]

There is one main theme and correspondingly one formal result in this paper. On the basis of a general characterization of what is formally meant by a ‘complex economy', underpinned by imaginative suggestions to this end in Foley (2003) and in Brock and Colander (2000; henceforth BC), it will be shown that an effective1 theory of economic policy is impossible for such an economy. There is, in addition, also a half-baked conjecture; it will be suggested, seemingly paradoxically, that a ‘complex economy' can be formally based on the foundations of orthodox general equilibrium theory and, hence, a similar impossibility result is valid in this case, too. [ABSTRACT FROM AUTHOR]

Forecasting is a key activity for policy makers. Given the possible complexity of the processes underlying policy targets, such as inflation, output gaps, or employment, and the difficulty of forecasting in real time, recourse is often taken to simple models. A dominant feature of such models is their linearity. However, recent evidence suggests that simple, though non-linear, models may be at least as competitive as linear ones for forecasting macro variables. [ABSTRACT FROM AUTHOR]

How large the non-observed economy (NOE) is and what determines its size in different countries and regions of the world is a question that has been and continues to be much studied by many observers (Schneider and Enste, 2000, 2002)2. The size of this sector in an economy has important ramifications. One is that it negatively affects the ability of a nation to collect taxes to support its public sector. The inability to provide public services can in turn lead more economic agents to move into the non-observed sector (Johnson, Kaufmann, and Shleifer, 1997). When such a sector is associated with criminal or corrupt activities it may undermine social capital and broader social cohesion (Putnam, 1993), which in turn may damage economic growth (Knack and Keefer, 1997; Zak and Knack, 2001). Furthermore, as international aid programs are tied to official measures of the size of economies, these can be distorted by wide variations in the relative sizes of the NOE across different countries, especially among the developing economies. [ABSTRACT FROM AUTHOR]

In free markets workers and firms exchange work for salaries and they have both competing and mutual interests. Workers need to work to get a salary but they are interested in getting as high a salary as possible. Firms need to hire workers but they are interested in paying them as low a salary as possible. At the same time both categories need each other. [ABSTRACT FROM AUTHOR]

We set up agent based models in which agents have low or zero cognitive ability. We examine two quite diverse socio-economic phenomena, namely the distribution of the cumulative size of economic recessions in the United States and the distribution of the number of crimes carried out by individuals. We show that the key macro-phenomena of the two systems can be shown to emerge from the behaviour of these agents. In other words, both the distribution of economic recessions and the distribution of the number of crimes can be accounted for by models in which agents have low or zero cognitive ability. [ABSTRACT FROM AUTHOR]