
Abstracts
Talk
Modeling microstructure noise using point processes
Emmanuel Bacry
(Ecole Polytechnique, France)
Abstract:
Hawkes processes (mutually exciting processes) are used to build a model for tickbytick timeseries.
We show how this model accounts for the stylized facts of the microstructure noise, namely the socalled signature plot and the Epps effect.
Talk
Network analysis of exchange data: Interdependence drives crisis contagion
David Matesanz Gómez
(University of Oviedo, Spain)
Abstract:
In this paper we detect the linear and nonlinear comovements presented on the real exchange rate in a group of 28 developed and developing countries that have suffered currency and financial crises during 15 years. We have used the matrix of Pearson correlation and Phase Synchronous (PS) coefficients and an appropriate metric distance between pairs of countries in order to construct a topology and hierarchies by using the Minimum Spanning Tree (MST). In addition, we have calculated the MST cost and global correlation coefficients to observe the comovements dynamics along the time sample. By comparing Pearson and phase synchronous information we address a new methodology that can uncover meaningful information on the contagion economic issue and, more generally, in the debate around interdependence and/or contagion among financial time series. Our results suggest some evidence of contagion in the Asian currency crises but this crisis contagion is due to previous and stable interdependence.
Talk
The origin of correlation in order flow and the market impact of large orders
Fabrizio Lillo
(University of Palermo, Italy)
Abstract:
A well known empirical fact in the microstructure of financial markets is that order flow is time correlated. It has recently been shown that the time series of order flow displays long memory property. The origin of this correlation, and more generally of the phenomenon termed "diagonal effect" by Biais, Hillion, and Spatt (1995), has been attributed either to herding or to persistence in trading of investors. By using trading data of market members we show that the latter is the most relevant cause. More specifically, order splitting, i.e. the practice of dividing a large order and to trade it incrementally, explains a large fraction of the time correlation. We discuss and measure empirically the effect of long memory on market impact of large orders. We finally suggest an impact model that reproduces the empirical results.
Talk
On high frequency covariation and leadLag estimation
Mathieu Rosenbaum
(Ecole Polytechnique, France)
Abstract:
Market participants usually agree that certain pairs of assets share a leadlag effect, in the sense that the lagger (or follower) price process is correlated to the leader (or driver) price process, with some temporal delay. We investigate in this talk the question of estimating covariation and leadlag effect from high frequency data. In particular, we propose estimation strategies which are robust to the asynchronicity of the data and the presence of microstructure noise.
Talk
Persistent collective trend in stock markets
Ingve Simonsen
(NTNU, Norway)
Abstract:
Talk
Agent dynamics in kinetic models for wealth exchange
Arnab Chatterjee
(The Abdus Salam ICTP, Italy)
Abstract:
We will discuss the dynamics of individual agents in some kinetic models of wealth exchange, particularly, the models with savings. For the model with uniform savings, agents perform simple random walks in the wealth 'space'. On the other hand, we observe ballistic diffusion in the model with distributed savings. There is also an associated skewness in the gainloss distribution which explains the steady state behavior in such models.
Talk
A Meanfield model for Reproducing the "Stylized Facts" of Financial Markets
Sitabhra Sinha
(Institute of Mathematical Science, India)
Abstract:
Recently, we have proposed a meanfield model that reproduces all the wellknown stylized facts of financial markets by considering agents interacting only indirectly with each other, via the market price dynamics. Not only is the powerlaw tail behavior of price return and volume captured, but the volatility clustering (as reflected in the slow decay of the autocorrelation of volatility) and multifractal properties are also reproduced. We discuss an analytical approach in understanding the origin of the powerlaw tail of the return distribution from the longtailed behavior of the distribution of number of trading agents. We also discuss empirical evidence from the Indian financial market about to the nature of the trading volume and number of trades distributions.
Talk
Price Impact, Resiliency, and Liquidity fluctuations
Bernd Rosenow
(MPIFKF, Germany)
Abstract:
Buying and selling stocks causes price changes, which are described by the price impact function. To explain the shape of this function, we study the Island ECN orderbook. In addition to transaction data, the orderbook contains information about potential supply and demand for a stock. The virtual price impact calculated from this information is four times stronger than the actual one and explains it only partially. However, we find a strong anticorrelation between price changes and order flow, which strongly reduces the virtual price impact and provides for an explanation of the empirical price impact function.
Using this relation between actual and virtual price impact, we can estimate the market liquidity at a given point in time from the order book and look for the explanation of extremely large price changes. We argue that a large trading volume alone is not a sufficient explanation for large price changes. Instead, we find that a low density of limit orders in the order book, i.e. a small liquidity, is a necessary prerequisite for the occurrence of extreme price fluctuations. Taking into account both order flow and liquidity, large stock price fluctuations can be explained quantitatively.
Talk
Boltzmann and FokkerPlanck Equations modelling Opinion Formation in the Presence of Strong Leaders
MarieTherese Wolfram
(University of Cambridge, UK)
Abstract:
We propose a mathematical model for opinion formation in a society which is built of two groups, one group of ‘ordinary’ people and one group of ‘strong opi nion leaders’. Our approach is based on an opinion formation model introduced by Toscani in 2006 and borrows ideas from the kinetic theory of mixtures of ra reﬁed gases. Starting from microscopic interactions among individuals, we arrive at a macroscopic description of the opinion formation process which is charac terized by a system of FokkerPlanck type equations. We discuss the steady states of this system, extend it to incorporate emergence and decline of opinion leaders, and present numerical results.
Talk
Limit order book market complexity: statistical physics approaches.
François Ghoulmié
(Australian National University, Australia)
Abstract:
I explain the logics and structures of my research project and specify my discoveries during research works in the investment and academic industries. Part of my research consists in building solid theoretical market models that are able to explain the origins of observed statistical regularities in terms of economic behavior of market participants and their interactions: this is a challenging aggregation problem where I explain the behavior of macro variables such as prices and trading volumes, starting from microvariables, i.e. individual agents behavior. In the context of limit order book markets that characterizes the modern electronic functioning of financial markets, I show how in a mean field Ising style market model with novel adaptive modeling of agents behavior, the interaction between heterogeneous trading strategies and market impact lead to the major empirical price properties such as excessive fluctuations in assets returns and to characteristics specific to these markets regarding the profile of the book. By using a BoltzmannGibbs rule for the dynamic asset allocation in the model, I reconcile seemingly contradictory notions in finance, the informational efficiency characterized by the absence of autocorrelation in assets returns and the long memory in market orders buy and sell flows. I finally discuss future directions on these topics.
Talk
Income and Expenditure Distribution: A Comparative Study
Kausik Gangopadhyay
(IIM Kozhikode, India)
Abstract:
An empirical study of the evolution of the consumer expenditure distribution in India during 19832007 has been done in Gangopadhyay, Basu and Ghosh (2009). The National Sample Survey Organization data has the expenditure distribution for the urban and rural sectors. It is found that this distribution is a mixture of two distributions  a lognormal in the lower tail and a Pareto distribution in the higher end. The existing literature has documented the income distribution to have a Pareto tail along with the fact that it is approximately lognormal at the higher end. A comparative analysis of the income distribution and the expenditure distribution is one way to find the consumption decisions of the agents conditional on the income level. We explore various consumption rules from the economics and econophysics literature in this context.
Talk
Quantifying and Modeling Financial Market Fluctuations
Tobias Preis
(Johannes Gutenberg University, Germany)
Abstract:
Financial market fluctuations are characterized by many abrupt switchings on very short time scales from increasing trends to decreasing trends  and vice versa. We find striking scalefree behavior of the time intervals between transactions both before and after the switching occurs. We interpret our findings as being consistent with timedependent collective behavior of financial market participants. We test the possible universality of our result by performing a parallel analysis of transaction volume fluctuations.
Basic properties of financial markets can be reproduced using a simple model, based on an order book, in which several agents trade an 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 nontrivial Hurst exponent for the price development, but not to “fattailed” 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 Order Book Model.
Talk
Probabilistic approach to anomalous scaling and the dynamics of the Euro/Dollar exchange rate.
A. L. Stella
(University of Padova, Italy)
Abstract:
Novel limit theorems address the asymptotic emergence and the universality of anomalous scaling for the probability density functions of sums of many strongly correlated random variables. The notion of correlated stability implied by these theorems allows to define nonMarkovian, selfsimilar stochastic processes with particularly promising features for the application in finance. Like in many natural phenomena,a basic difficulty in this context is that a process postulated to produce the time evolution of an index has to be validated on the basis of a single historical realization. However, a favorable circumstance conspiring to a successful solution of the problem first posed by Bachelier, is the fact that in some cases one can extract from financial data full ensembles of different histories. Indeed, in this talk I will show that five years of high frequency Euro/Dollar trading records provide a rich enough ensemble of histories, allowing a reliable characterization of the underlying process within a certain time window. Remarkably, the process driving the Euro/Dollar rate turns out to be of the kind one can construct on the basis of the notion of correlated stability implied by the above limit theorems. A careful analysis of various correlators shows that the process is selfsimilar, with dependent incremets obeying a form of timeinhomogeneous scaling. Processes of this kind were recently postulated to underlie also the time evolution of indices which need to be studied on the basis of a single historical series. The perspectives open by these results for the general problem of option pricing will be discussed.
Talk
Capital markets in a closed loop: from empirical facts to high frequency simulations
Charlesalbert Lehalle
(Capital Markets, CA Cheuvreux, France)
Abstract:
The market model presented is well suited to back testing high frequency trading strategies and tactics. It is based on a two layered point of view on the intraday microstructure of the limit order book (LOB).
The first layer (the "macroscopic" layer) mimics investors' high frequency views on the value considered financial instrument. Its kinematics are modelled by stochastic partial derivatives equations obtained via the mien field games (MFG) theory.
The second layer (the "microscopic" layer) is a conditioned high frequency statistical model of the volatility, the bidask spread, the volumes of the price formation process (PFP) and of the frequency and the type of orders sent to the matching engine of the trading platform. It is conditioned by the distance between the state of investors' views and their microscopic realizations in the LOB, inducing a closed loop between the PFP and investors' strategies and tactics.
As a result of this approach, the PFP is allowed to implement some "rare" excursions thanks to the degrees of freedom of the microscopic layer, but the occurrence of such excursions then increase the probability to observe events bringing back the PFP to investors' views thanks to the close loop with the MFGbased macroscopic PDEs.
Talk
High frequency correlation modelling
Nicolas Huth
(France)
Abstract:
We study the features of a high frequency correlation model using correlated Poisson processes with random intensities. The focus is on the Epps effect, lead lag estimation and large scale limits.
Talk
Frederic Abergel
(Ecole Centrale Paris, France)
Abstract :
The modelling of order books is still in its infancy, particularly because the various behaviours of market participants only partially and gradually reveal themselves to the scientist. In this talk, I will present some interesting research avenues that lead to more robust and more accurate models beyond the basic zerointelligence market. I will also present some connections between continuoustime, stochastic price models and their pure jump, discretetime, orderbookbased counterparts.
Talk
Capital structure under opportunistic coalition of stakeholders
Sanjay Banerji
(Essex University, UK)
Abstract :
In this paper, we show that equity financing is the dominant mode of financing in a framework where suppliers of input form alliance with creditors and push the firm towards bankruptcy. Inability to write contracts with suppliers make the firm to use debt to its minimum level. We also show that franchise arrangement with suppliers together with equity financing yields firstbest outcome.
Talk
An econophysics approach to stock market volatility: Evidence from seven countries
Sónia R. Bentes
(ISCAL, Portugal)
Abstract :
The intricate character of stock markets has always intrigued both scholars and practioners alike. One major issue in this debate has been the different patterns evidenced by the volatility of stock market returns. Since the traditional approach, based on the Financial Theory, are not fully satisfactory we apply a different one that relies on the concept of entropy. To shed some light into this matter we shall clarify that the concept of entropy was originally introduced in 1865 by Clausius in the context of thermodynamics and, since then, several formulations have been constructed. Although the debate generated over its meaning, it is generally understood as measure of disorder, uncertainty, ignorance, dispersion or even lack of information. In order to perform our analysis we compare the results of three different entropy measures: Shannon, Renyi and Tsallis entropy with traditional statistical measures like the standard deviation, the root mean square percentage error (RMSPE) and the coefficient of variation (CV). For our purpose, we shall basically focus on the behaviour of seven stock market indexes: TSX 60 (Canada), CAC 40 (France), DAX 30 (Germany), MIB 30 (Italy) NIKKEI 225 (Japan), FTSE 100 (UK) and S&P 500 (USA) for a comparative analysis between the approaches mentioned above. The results are however mixed.
Talk
Correlation Statistics in Foreign Exchange & Stock Markets
Bikas K. Chakrabarti
(Saha Institute of Nuclear Physics, India)
Abstract :
We will study some emeprical correlations in several Foreign Exchange mrkets and also in some Stock (inedex) markets. We will comapre the observations with those recently observed in sesmic activities of the earth.
Measuring Financial Inclusion: An Axiomatic Approach
Satya R. Chakravarty
(Indian Statistical Institute, India)
Abstract :
In this paper we clearly demonstrate that the axiomatic measurement approach developed in the human development literature can be usefully applied to the measurement of banking financial inclusion. A conceptual framework for aggregating data on financial services in different dimensions is developed. The index of financial inclusion we suggest allows calculation of percentage contributions made by different dimensions to the overall level of inclusion. This in turn enables us to identify the dimensions of inclusion that are more/less susceptible to overall inclusion and hence to isolate the dimensions that deserve attention from a policy perspective.
Talk
Random Matrix Theory and Covariance Estimation
Jim Gatheral
(Merill Lynch and New York University, USA)
Abstract :
In this talk, we explain Random Matrix Theory and show how to apply it to reduce the noise in estimates of the covariance matrix of stock returns. After formulating a general recipe for cleaning sample covariance matrices, we work through a particular example, comparing the outof sample performance of the cleaned matrix to that of the sample covariance matrix and a covariance matrix derived from a factor model respectively.
Talk
Economic Risk Capital Measure – Credit Crisis & beyond
Chitro Majumdar
(Rsquare Temigroup Nordic, Finland)
Abstracts :
We also consider the crosscorrelation between changes in CDS prices and stock returns for evidence that information is revealed first in the CDS market with respect to recent credit turmoil. We would expect to observe insiders exploiting information in the CDS market when there is significant negative information. Our motivation is why to differentiate between shadow price and fundamental price of credit risk we provide an integrated, unifying framework for assessing the accuracy of VaR forecasts. The correlation independent model of product to be priced and we measure Gaussian copula model to access the default time simulation. The key is to get an efficient implementation that gives accurate risk numbers. Finally our motivation is to compare the macro correlation adjustments, Economic Capital is calculated for each risk type and loss situation that attracts Economic Capital is reframed as an option beyond the world credit crisis.
Talk
Two agent allocation problems and the first best
Manipushpak Mitra
(Indian Statistical Institute, India)
Abstract :
We consider a general class of two agent allocation problems and identify the complete class of first best allocation rules. By first best allocation rules we mean allocation rules for which we can find efficient, strategyproof and budget balanced mechanisms. We show that the only first best allocation rules are the fixed share allocation rules. An allocation rule is a fixed share allocation rule if the share of each agent is fixed under all states of the world.
Talk
Fabrizio Pomponio
(Ecole Centrale Paris, France)
Abstract :
This talk focuses on statistics of important events occuring in limit order books : multiple limits trades. Those are big trades that consume strictly more than the liquidity oﬀered on the ﬁrst order book limit. Investors who use multiple limits trades choose not to wait for the order book to be reﬁlled with new liquidity at the ﬁrst limit. Based on those particular trades, we will try to characterize leadlag relation between US and EU equity markets.
Talk
Abhirup Sarkar
(Indian Statistical Institute, India)
Abstract :
The purpose of the paper is to investigate the desirability of free trade in agricultural goods when production is uncertain. It is shown that though production uncertainity tends to reduce the standard gains from trade, free trade is desirable compared to antarky if comparative advantage effects are sufficiently strong. A restricted trade regime is also located which is always better than antarky.
Talk
"Market making" behaviour in an electronic order book and its impact on the bidask spread
Ioane Muni Toke
(Ecole Centrale Paris, France)
Abstract :
It has been suggested that marked point processes might be good candidates for the modelization of financial highfrequency data. A special class of point processes, Hawkes processes, has been the subject of various investigations in the financial community. In this paper, we propose to enhance a basic order book simulator with limit and market orders arrival times following mutually (unsymmetrically) exciting Hawkes processes. Modelization is based on empirical observations verified on several markets. We show that this simple feature enables a much more realistic treatment of the bidask spread of the simulated order book.
Poster
Multi Scale Entropy analysis of the sectoral indices of Indian Stock Market
Durga Prasad Bisen
(Pt.Ravishankar Shukla University Raipur, India)
Abstract :
There has been considerable interest in quantifying the complexity of the time series of price variations exhibited by stock markets. Different methods have been developed for this purpose. Traditional entropy based algorithms quantify the regularity of the time series. Entropy increases with disorder ,however , an increase in entropy may not always be with increase in dynamic complexity. The traditional algorithms may generate misleading results because the algorithms are based on single time scale .However, the multiscale entropy approach measures the complexity of the system taking into account the multiple time scales. This computational tool can be quite effectively used to quantify the complexity of a given time series. In this paper we study the variation in various sectoral indices of Indian stock market using multiscale entropy analysis (MSE).The sample entropies (SampEn) of different sectoral indices are calculated at different ranges of scales and their MSE profiles are compared at different conditions.
Poster
Study of the Multifractal behavior of NIFTY using Detrended Fluctuation Analysis
Balgopal Sharma
(Govt. Science College Raipur, India)
Abstract :
We apply the Multifractal detrended fluctuation analysis (MFDFA) to investigate the fractal properties of the NIFTY index. The scaling behavior of the time series are investigated using MFDFA approach. The method has recently gained much popularity owing to its simple application and its ability to describe the multifractal structure of a non stationary time series data. We show that the dependence of generalized Hurst exponent h (q) on q demonstrates the multifractal behavior of the index.
Poster
NonIdeal Twophase transition within Multiple Phase Change of Stock Prices and Stock Indices
Kishore Chandra Dash
(Neelashaila Mahavidyalaya, India)
Abstract :
The movement of stock prices is not observed just like the stagnancy of temperature, when phase transition occurs in case of matters. It is observed that movement of stock prices rise or falls up to a certain level and remains almost stagnant with a small variation. There is no sharp level of price from which there is change of phase. Price oscillates around a particular value called as resistance/support level. This can be called as a phase of accumulation. After a few days it transits either upwards or downwards and touches the next level of support/resistance in a very short time compared to the duration of oscillation. Maximum price movements occur in this phase in either direction. In case of matter there is sharp change of phase from one state to another under a given condition of pressure. However in case of stock prices or indices phase change is not sharp. Before breaking into another phase it oscillates around the resistance/support level. So it may be called as nonideal twophase transition. An equation of diffusion coefficient has been derived in the line of Einstein’s determination of diffusion coefficient due to Brownian motion. Diffusion coefficient during the nonideal phase change (pseudo) and ideal phase change (actual) has been discussed. In this paper an attempt has been made to compare stock prices with that of temperature, demand with supply of heat, supply with extraction of heat, ratio of volume of transaction to the change in price with the specific heat and volume transacted during phase transition with latent heat.
