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- Adrian A Dr, Victor M Yakovenko
- 2004

Outline • Formulation of the problem • Description of the model: multiplicative Brown-ian motion with stochastic volatility • Exact solution of the model • Analytical analysis in several asymptotic limits

- Adrian Dr, Victor M Yakovenko
- 2000

Using tax and census data, we demonstrate that the distribution of individual income in the USA is exponential. Our calculated Lorenz curve without fitting parameters and Gini coefficient 1/2 agree well with the data. From the individual income distribution, we derive the distribution function of income for families with two earners and show that it also… (More)

The terms highlighted in bold in Sec. I refer to other articles in this Encyclopedia. This paper reviews statistical models for money, wealth, and income distributions developed in the econophysics literature since late 1990s.

- A Christian Silva, Victor M Yakovenko
- 2005

– Personal income distribution in the USA has a well-defined two-class structure. The majority of population (97–99%) belongs to the lower class characterized by the exponential Boltzmann-Gibbs (" thermal ") distribution, whereas the upper class (1–3% of population) has a Pareto power-law (" superthermal ") distribution. By analyzing income data for… (More)

- Adrian A Dr, Victor M Yakovenko, P L Garrido, J Marro
- 2002

In this short paper, we overview and extend the results of our papers [1, 2, 3], where we use an analogy with statistical physics to describe probability distributions of money, income, and wealth in society. By making a detailed quantitative comparison with the available statistical data, we show that these distributions are described by simple exponential… (More)

- A Christian Silva, Richard E Prange, Victor M Yakovenko, V M Yakovenko
- 2004

We study the probability distribution of stock returns at mesoscopic time lags (return horizons) ranging from about an hour to about a month. While at shorter microscopic time lags the distribution has power-law tails, for mesoscopic times the bulk of the distribution (more than 99% of the probability) follows an exponential law. The slope of the… (More)

- A Christian Silva, Victor M Yakovenko
- 2002

We compare the probability distribution of returns for the three major stock-market indexes (Nasdaq, S&P500, and Dow-Jones) with an analytical formula recently derived by Dr˘ agulescu and Yakovenko for the Heston model with stochastic variance. For the period of 1982–1999, we find a very good agreement between the theory and the data for a wide range of… (More)

- A Christian Silva, Victor M Yakovenko, V M Yakovenko
- 2007

We present an empirical study of the subordination hypothesis for a stochastic time series of a stock price. The fluctuating rate of trading is identified with the stochastic variance of the stock price, as in the continuous-time random walk (CTRW) framework. The probability distribution of the stock price changes (log-returns) for a given number of trades… (More)

- Anand Banerjee, Victor M Yakovenko, T Di, Matteo
- 2006

We analyze the data on personal income distribution from the Australian Bureau of Statistics. We compare fits of the data to the exponential, log-normal, and gamma distributions. The exponential function gives a good (albeit not perfect) description of 98% of the population in the lower part of the distribution. The log-normal and gamma functions do not… (More)