A jump diffusion model for spot electricity prices and market price of risk

We construct a jump-diffusion model with seasonality, mean-reversion, time-dependent jump intensity and heteroskedastic disturbance for electricity spot prices, while keeping the analytical tractability of futures prices. We find that the jump component plays a considerably larger role than the diffusion component in the variance of spot prices. Moreover, the jump intensity is much higher during summer and winter. We also explore the seasonal market price of risk (MPR) with different maturities, from one month to five months. Our results show that the diffusion risk and the jump risk are priced quite differently.     

Turbulent transport processes in a plasma as a diffusion process with random time

It is proposed to apply the statistical analysis of the increments of fluctuating particle fluxes to analyzing the probability characteristics of turbulent transport processes in plasma. Such an approach makes it possible to analyze the dynamic probability characteristics of the process under study. It is shown that, in the plasmas of the L-2M stellarator and the TAU-1 linear device, the increments of local fluctuating particle fluxes are of stochastic character and that their distributions are scale mixtures of Gaussians. In particular, for TAU-1, the increments have the Laplacian distribution (which is a scale mixture of Gaussians with an exponential mixing distribution). This implies that the rate of flux variations is a diffusion process with random time. It is shown that the characteristic growth (damping) time of fluctuations is one order of magnitude shorter than their characteristic correlation time. Physical mechanisms that may be responsible for the random character of the growth (damping) of fluctuations are discussed.     

Asset price dynamics in a financial market with heterogeneous trading strategies and time delays

In this paper we present a continuous time dynamical model of heterogeneous agents interacting in a financial market where transactions are cleared by a market maker. The market is composed of fundamentalist, trend following and contrarian agents who process market information with different time delays. Each class of investors is characterized by path dependent risk aversion. We also allow for the possibility of evolutionary switching between trend following and contrarian strategies. We find that the system shows periodic, quasi-periodic and chaotic dynamics as well as synchronization between technical traders. Furthermore, the model is able to generate time series of returns that exhibit statistical properties similar to those of the S&P 500 index, which is characterized by excess kurtosis, volatility clustering and long memory.     

A simplified quasi-Gaussian random process model based on non-linearity

The non-Gaussian response of a simple polynomial non-linear element to Gaussian excitation is investigated, and correlation functions and spectral densities up to the fourth order are established in terms of the second order correlation function and spectral density of the excitation. Suitable choice of excitation and non-linearity parameters then permits the response to be used, either in analysis as a well-described near-Gaussian random process, or as a good approximate model of any given near-Gaussian random process.     

Long-Time tails in a random diffusion model

Letw = {w(x)xZ^d} be a positive random field with i.i.d. distribution. Given its realization, letX _t be the position at timet of a particle starting at the origin and performing a simple random walk with jump rate w^–1(X_t). The processX={X _t:t0} combined withw on a common probability space is an example of random walk in random environment. We consider the quantities _t =(d/dt) E (X _t ² –M ^–1 t and _t(w) = (d/dt)E_w(X _t ² – M^– 1t). Here E_w. is expectation overX at fixedw and E = E_w (dw) is the expectation over bothX andw. We prove the following long-time tail results: (1) lim_t t^d/2_t= V²M^d/2–3(d/2)^d/2 and (2) lim_t t^d/4 _st(w)= Z_s weakly in path space, with {Z_s:s>0} the Gaussian process with EZ_s=0 and EZ_rZ_s= V²M^d/2–4(d)^d/2 (r + s)^–d/2. HereM and V² are the mean and variance of w(0) under . The main surprise is that fixingw changes the power of the long-time tail fromd/2 tod/4. Since , with ₀ the stationary measure for the environment process, our result (1) exhibits a long-time tail in an equilibrium autocorrelation function.     

The price impact asymmetry of institutional trading in the Chinese stock market

The asymmetric price impact between the institutional purchases and sales of 32 liquid stocks in the Chinese stock market in 2003 is carefully studied. We analyze the price impact in both drawup and drawdown trends with consecutive positive and negative daily price changes, and test the dependence of the price impact asymmetry on the market condition. For most of the stocks, institutional sales have a larger price impact than institutional purchases, and a larger impact of institutional purchases exists only in a few stocks with primarily increasing tendencies. We further study the mean return of trades surrounding institutional transactions, and find that the asymmetric behavior also exists before and after institutional transactions. A new variable is proposed to investigate the order book structure, and it can partially explain the price impact of institutional transactions. A linear regression for the price impact of institutional transactions further confirms our finding that institutional sales primarily have a larger price impact than institutional purchases in the bearish year 2003.     

Dynamic structure factor in a random diffusion model

Let {X _t:0} denote random walk in the random waiting time model, i.e., simple random walk with jump ratew ^–1(X _t), where {w(x):x^d} is an i.i.d. random field. We show that (under some mild conditions) theintermediate scattering function F(q,t)=E ₀ (q^d) is completely monotonic int (E ₀ denotes double expectation w.r.t. walk and field). We also show that thedynamic structure factor S(q, w)=2 ₀ cos(t)F(q, t) exists for 0 and is strictly positive. Ind=1, 2 it diverges as 1/||^1/2, resp. –ln(||), in the limit 0; ind3 its limit value is strictly larger than expected from hydrodynamics. This and further results support the conclusion that the hydrodynamic region is limited to smallq and small such that ||D |q|², whereD is the diffusion constant.     

Analytic study of a model of diffusion on random comb-like structures

Summary An analytic study of a model of diffusion on random comb-like structures in which a bias field may or not exist along the backbone is presented. First, when no bias is present, the method allows to compute in an exact manner, for any given disordered structure, the asymptotic behaviour at large time of the probability of presence of the particle at its initial site and on the backbone, and of the particle position and dispersion. The expressions of these quantities are shown to coincide asymptotically with those derived in simple ?mean-field? treatments. The results for any given sample do not depend on the particular configuration (self-averaging property). When a bias field is present along the backbone, one can also compute directly in an exact manner the asymptotic behaviour at large time of the disorder average of the probability of presence of the particle at its initial site. As for the particle position and dispersion, they can be computed in a periodized system of arbitrary periodN. The corresponding quantities for the random system can then be obtained by taking the limitN→∞. As a result, in both cases the behaviours strongly depend on the distribution of the lengths of the branches. With an exponential distribution transport is normal while anomalous drift and diffusion may take place for a power law distribution (when long branches are present with sufficiently high weights). Paper presented at the I International Conference on Scaling Concepts and Complex Fluids, Copanello, Italy, July 4–8, 1994. Laboratoire associé au C.N.R.S. (U.A. no. 17) et aux Universités Paris VII et Paris VI.     

Quantitative evaluation of nonlinear diffusion for isotropic random flow

The projection operator method is applied to isotropic random flow field. This application derives a model of a time correlation function with no assumption, and allows for quantitative evaluations of the nonlinear diffusion near initial time. We confirm that for wide range of Reynolds number, the model exhibits good agreement with the results calculated by the direct numerical simulation near the initial time. It is concluded that the projection operator method is useful to exhibit quantitatively the dependence of the nonlinear diffusion on the Reynolds number.     

Quantum mechanics as a classical diffusion process

A direct construction is provided showing that the classical expectation value for the energy of a particle executing a classical diffusion process is equivalent to the quantum mechanical form with a Hamiltonian structured like that for a charged particle in an electromagnetic field.     

Two-state random walk model of diffusion. 2. Oscillatory diffusion

Continuing our study of interrupted diffusion, we consider the problem of a particle executing a random walk interspersed with localized oscillations during its halts (e.g., at lattice sites). Earlier approaches proceedvia approximation schemes for the solution of the Fokker-Planck equation for diffusion in a periodic potential. In contrast, we visualize a two-state random walk in velocity space with the particle alternating between a state of flight and one of localized oscillation. Using simple, physically plausible inputs for the primary quantities characterising the random walk, we employ the powerful continuous-time random walk formalism to derive convenient and tractable closed-form expressions for all the objects of interest: the velocity autocorrelation, generalized diffusion constant, dynamic mobility, mean square displacement, dynamic structure factor (in the Gaussian approximation), etc. The interplay of the three characteristic times in the problem (the mean residence and flight times, and the period of the ‘local mode’) is elucidated. The emergence of a number of striking features of oscillatory diffusion (e.g., the local mode peak in the dynamic mobility and structure factor, and the transition between the oscillatory and diffusive regimes) is demonstrated.     

Majority orienting model for the oscillation of market price

The cyclic Lotka-Volterra model in a D-dimensional regular lattice is considered. Entropy production of its nucleus growth mode is investigated by analyzing the time evolution of the family of entropies , with . This family contains as particular case (q = 1) the usual entropic form . The rate of growth of the entropy S _q , for some , is expected to provide non-trivial information about certain complex systems. For the system here considered, it is shown, both numerically and by means of analytical considerations, that a linear increase of entropy with time, meaning finite asymptotic entropy rate, is achieved for the entropic index q _c = 1-1/D, as previously conjectured in the literature. However, although , this relation can be explained in terms of very simple features not directly connected to the complexity of the dynamics. The relation between the characteristic entropic index and lattice dimensionality is shown to be a consequence of the fact that the system soon approaches a steady regime where the nucleus radius grows linearly with time.Received: 8 October 2004, Published online: 14 December 2004PACS: 05.10.Ln Monte Carlo methods - 05.65. + b Self-organized systems - 05.45.-a Nonlinear dynamics and nonlinear dynamical systems     

Fluctuations of trading volume in a stock market

We consider the probability distribution function of the trading volume and the volume changes in the Korean stock market. The probability distribution function of the trading volume shows double peaks and follows a power law, P(V/〈V〉)∼(V/〈V〉)^−α at the tail part of the distribution with α=4.15(4) for the KOSPI (Korea composite Stock Price Index) and α=4.22(2) for the KOSDAQ (Korea Securities Dealers Automated Quotations), where V is the trading volume and 〈V〉 is the monthly average value of the trading volume. The second peaks originate from the increasing trends of the average volume. The probability distribution function of the volume changes also follows a power law, , where V_r=V(t)−V(t−T) and T is a time lag. The exponents β depend on the time lag T. We observe that the exponents β for the KOSDAQ are larger than those for the KOSPI.     

Majority orienting model for the oscillation of market price

The present paper introduces a majority orienting model in which the dealers behavior changes based on the influence of the price to show the oscillation of stock price in the stock market. We show the oscillation of the price for the model by applying the van der Pol equation which is a deterministic approximation of our model.Received: 29 October 2003, Published online: 15 March 2004PACS: 89.65.Gh Economics; econophysics, financial markets, business and management - 05.45.Tp Time series analysis - 02.50.Ey Stochastic processesY. Itoh: Also at The Graduate University for Advanced Studies     

Price dynamics from a simple multiplicative random process model

The existence of stylized facts suggests that there might be `universal' mechanism which drives price evolution on financial markets in general. Based on empirical estimates of 10 major indices, we propose a stylized model of endogenous price formation on an aggregate level whose key issue is that price evolution is driven by the `market's' expectations about future growth rates of investment. The model is a multiplicative random process with a stochastic, state-dependent growth rate which establishes a negative feedback component in the price dynamics which admits some far reaching formal analysis. Generated return trails exhibit statistical properties such as 'volatility clustering', multi scaling, and a non-Gaussian distribution which is in quantitative in agreement with stylized facts from empirical asset returns. Additionally non-equilibrium entropies are also considered. These results suggests that the structure of the model mimicks a mechanism which is essential in driving price dynamics of financial markets in general.     

Structural ion-sound plasma turbulence as a self-similar random process

It is shown that the experimentally investigated structural ion-sound plasma turbulence is a self-similar stationary random process. The self-similarity parameter is determined by two temporal laws: the nonrandom character of the appearance of nonlinear structures (nonlinear ion-sound solitons) in the plasma, and the nonlinear interaction between them. As the distance from the threshold of the ion-sound current instability increases, the self-similar random process approaches a Gaussian random process, but this limit has not been attained experimentally. The possibility of recording superlong time series of the fluctuations of the signal of the plasma process and processing of the time series by the R/S analysis method has made it possible to prove self-similarity of the plasma structural turbulence. Pis’ma Zh. éksp. Teor. Fiz. 70, No. 3, 203–208 (10 August 1999)     

Analysis of price diffusion in financial markets using PUCK model

Based on the new type of random walk process called the potentials of unbalanced complex kinetics (PUCK) model, we theoretically show that the price diffusion in large scales is amplified 2(2+b)^-1 times, where b is the coefficient of quadratic term of the potential. In short time scales the price diffusion depends on the size M of the super moving average. Both numerical simulations and real data analysis of Yen-Dollar rates are consistent with theoretical analysis.