arXiv subjects

Taisei Kaizoji

Publications and source records attributed to Taisei Kaizoji.

34 records · Page 2Linked to original sources

arXiv2006

Statistical properties of absolute log-returns and a stochastic model of stock markets with heterogeneous agents

This paper is intended as an investigation of the statistical properties of {\it absolute log-returns}, defined as the absolute value of the logarithmic price change, for the Nikkei 225 index in the 28-year period from January 4, 1975 to December 30, 2002. We divided the time series of the Nikkei 225 index into two periods, an inflationary period and a deflationary period. We have previously [18] found that the distribution of absolute log-returns can be approximated by the power-law distribution in the inflationary period, while the distribution of absolute log-returns is well described by the exponential distribution in the deflationary period.\par To further explore these empirical findings, we have introduced a model of stock markets which was proposed in [19,20]. In this model, the stock market is composed of two groups of traders: {\it the fundamentalists}, who believe that the asset price will return to the fundamental price, and {\it the interacting traders}, who can be noise traders. We show through numerical simulation of the model that when the number of interacting traders is greater than the number of fundamentalists, the power-law distribution of absolute log-returns is generated by the interacting traders' herd behavior, and, inversely, when the number of fundamentalists is greater than the number of interacting traders, the exponential distribution of absolute log-returns is generated.

physics.soc-ph↗

arXiv2006

Power law for the calm-time interval of price changes

In this paper, we describe a newly discovered statistical property of time series data for daily price changes. We conducted quantitative investigation of the {\it calm-time intervals} of price changes for 800 companies listed in the Tokyo Stock Exchange, and for the Nikkei 225 index over a 27-year period from January 4, 1975 to December 28, 2001. A calm-time interval is defined as the interval between two successive price changes above a fixed threshold. We found that the calm-time interval distribution of price changes obeys a power law decay. Furthermore, we show that the power-law exponent decreases monotonically with respect to the threshold. Keyword: econophysics, stock price changes, calm time interval, power-laws; PACS: 89.90.+n; 05.40.Df;

cond-mat.stat-mech↗

arXiv2006

A mechanism leading bubbles to crashes: the case of Japan's land markets

In this paper we investigate quantitatively statistical properties of ensemble of {\it land prices} in Japan in the period from 1981 to 2002, corresponding to the period of bubbles and crashes. We find that the tail of the distributions of ensembles of the land prices in the high price range is well described by a power law distribution, $ P(S>x) \sim x^{-α} $, and furthermore that as the power-law exponents $ α$ approached to unity, the crashes of bubbles occurred.

cond-mat.dis-nn↗

arXiv2006

Power law for ensembles of stock prices

In this paper we quantitatively investigate the statistical properties of an ensemble of {\it stock prices}. We selected 1200 stocks traded in the Tokyo Stock Exchange and formed a statistical ensemble of daily stock prices for each trading day in the 5 year period from January 4, 1988 to December 30, 1992. We found that the tail of the complementary cumulative distribution function of the ensembles is accurately described by a power-law distribution with an exponent that moves in the range of $ 1.7 < α< 2.2 $.

cond-mat.stat-mech↗

arXiv2006

Inflation and deflation in stock markets

The aim of this paper is to compare statistical properties of a bubble period with those of the anti-bubble period in stock markets. We investigate the statistical properties of daily data for the Nikkei 225 index in the 28-year period from January 1975 to April 2003, corresponded to the periods of bubbles and anti-bubbles. We divide the time series into two parts, the period of {\it inflation (or bubbles)} from January 1975 to December 2002 and the period of {\it deflation (or anti-bubbles)} from January 1990 to December 2002. We find that the volatility in the inflationary period is approximated by the $q$-exponential distribution with $ q = 1.14 $ while the volatility distribution in the deflationary period is accurately described by an {\it exponential} distribution, that is, the $q$-exponential distribution with $ q \to 1 $. Our empirical findings suggest that the momentous structural changes have occurred at the beginning of 1990 when the speculative bubble was collapsed in the Japan's stock markets. Keywords: econophysics, inflationary period, deflationary period, power law, exponential (Bolztmann-Gibbs) law; PACS 89.90.+n; 05.40.-a;

cond-mat.stat-mech↗

arXiv2006

Scaling behavior in land markets

In this paper we present an analysis of power law statistics on land markets. There have been no other studies that have analyzed power law statistics on land markets up to now. We analyzed a database of the assessed value of land, which is officially monitored and made available to the public by the Ministry of Land, Infrastructure, and Transport Government of Japan. This is the largest database of Japan's land prices, and consists of approximately 30,000 points for each year of a 6-year period (1995-2000). By analyzing the data on the assessed value of land, we were able to determine the power law distributions of the land prices and of the relative prices of the land. The data fits to a very good degree the approximation of power law distributions. We also found that the price fluctuations were amplified with the level of the price. These results hold for the data for each of the 6 annual intervals. Our empirical findings present the conditions that any empirically accurate theories of land market must satisfy.

cond-mat.stat-mech↗

arXiv2006

A Precursor of Market Crashes

In this paper, we quantitatively investigate the properties of a statistical ensemble of stock prices. We focus attention on the relative price defined as $ X(t) = S(t)/S(0) $, where $ S(0) $ is the initial price. We selected approximately 3200 stocks traded on the Japanese Stock Exchange and formed a statistical ensemble of daily relative prices for each trading day in the 3-year period from January 4, 1999 to December 28, 2001, corresponding to the period in which the {\it internet Bubble} formed and {\it crashes} in the Japanese stock market. We found that the upper tail of the complementary cumulative distribution function of the ensemble of the relative prices in the high value of the price is well described by a power-law distribution, $ P(S>x) \sim x^{-α} $, with an exponent that moves over time. Furthermore, we found that as the power-law exponents $ α$ approached {\it two}, the bubble burst. It is reasonable to assume that when the power-law exponents approached {\it two}, it indicates the bubble is about to burst. PACS: 89.65.Gh; Keywords: Market crashes, Power law, Precursor

physics.soc-ph↗

arXiv2006

Scaling Law for the Distribution of Fluctuations of Share Volume

We show power-scaling behaviors for fluctuations in share volume, which no other studies have so far done. After analyzing a database of the daily transactions for all securities listed on the Tokyo Stock Exchange, we selected 1050 large companies that each had an unbroken series of daily trading activity from January 1975 to January 2002. We found that the cumulative distributions of daily fluctuations in share volumes can be well described by a power-law decay, and that the cumulative distributions for almost all of the companies can be characterized by an exponent within the stable Levy domain. Furthermore, more than 35 percent of the cumulative distributions can be well approximated by Zipf's law, that is, the cumulative distributions have an exponent close to unity.

cond-mat.stat-mech↗

arXiv2006

Power laws and market crashes

In this paper, we quantitatively investigate the statistical properties of a statistical ensemble of stock prices. We selected 1200 stocks traded on the Tokyo Stock Exchange, and formed a statistical ensemble of daily stock prices for each trading day in the 3-year period from January 4, 1999 to December 28, 2001, corresponding to the period of the forming of the internet bubble in Japn, and its bursting in the Japanese stock market. We found that the tail of the complementary cumulative distribution function of the ensemble of stock prices in the high value of the price is well described by a power-law distribution, $ P(S>x) \sim x^{-α} $, with an exponent that moves in the range of $ 1.09 < α< 1.27 $. Furthermore, we found that as the power-law exponents $ α$ approached unity, the bubbles collapsed. This suggests that Zipf's law for stock prices is a sign that bubbles are going to burst. PACS: 89.65.Gh

physics.soc-ph↗

arXiv2005

Grouping in the stock markets of Japan and Korea

We investigated the temporally evolving network structures of the Japanese and Korean stock markets through the minimum spanning trees composed of listed stocks. We tested the validity of conventional grouping by industrial categories, and found a common trend of decrease for Japan and Korea. This phenomenon supports the increasing external effects on the markets due to the globalization of both countries. At last the Korean market are grouped with the MSCI Korea Index, a good reference for foreigners' trading, in the early 2000s \cite{Jung2006}. In the Japanese market, this tendency is strengthened more and more by burst of the bubble in 1990's.

physics.soc-ph↗

arXiv2005

Comparison of volatility distributions in the periods of booms and stagnations: an empirical study on stock price indices

The aim of this paper is to compare statistical properties of stock price indices in periods of booms with those in periods of stagnations. We use the daily data of the four stock price indices in the major stock markets in the world: (i) the Nikkei 225 index (Nikkei 225) from January 4, 1975 to August 18, 2004, of (ii) the Dow Jones Industrial Average (DJIA) from January 2, 1946 to August 18, 2004, of (iii) Standard and Poor's 500 index (SP500) from November 22, 1982 to August 18, 2004, and of (iii) the Financial Times Stock Exchange 100 index (FT 100) from April 2, 1984 to August 18, 2004. We divide the time series of each of these indices in the two periods: booms and stagnations, and investigate the statistical properties of absolute log returns, which is a typical measure of volatility, for each period. We find that (i) the tail of the distribution of the absolute log-returns is approximated by a power-law function with the exponent close to 3 in the periods of booms while the distribution is described by an exponential function with the scale parameter close to unity in the periods of stagnations.

physics.soc-ph↗

arXiv2003

Intermittent chaos in a model of financial markets with heterogeneous agents

In this paper we study the price dynamics in a simple model of financial markets with heterogeneous agents. We concentrate on how increases in the total number of active traders influences fluctuations of asset prices. We find that a curious route to chaos is observed when the total number of [active traders] increases. Particularly, we show that {\it intermittent chaos} [1] of price fluctuations is observed as the total number of trader increases.

nlin.CD↗

arXiv2003

Speculative bubbles and fat tail phenomena in a heterogeneous agent model

The aim of this paper is to propose a heterogeneous agent model of stock markets that develop complicated endogenous price fluctuations. We find occurrences of non-stationary chaos, or speculative bubble, are caused by the heterogeneity of traders' strategies. Furthermore, we show that the distributions of returns generated from the heterogeneous agent model have fat tails, a remarkable stylized fact observed in almost all financial markets.

nlin.CD↗

arXiv2002

Growth and Fluctuations of Personal Income

Pareto's law states that the distribution of personal income obeys a power-law in the high-income range, and has been supported by international observations. Researchers have proposed models over a century since its discovery. However, the dynamical nature of personal income has been little studied hitherto, mostly due to the lack of empirical work. Here we report the first such study, an examination of the fluctuations in personal income of about 80,000 high-income taxpayers in Japan for two consecutive years, 1997 and 1998, when the economy was relatively stable. We find that the distribution of the growth rate in one year is independent of income in the previous year. This fact, combined with an approximate time-reversal symmetry, leads to the Pareto law, thereby explaining it as a consequence of a stable economy. We also derive a scaling relation between positive and negative growth rates, and show good agreement with the data. These findings provide the direct observation of the dynamical process of personal income flow not yet studied as much as for companies.

cond-mat.dis-nn↗

arXiv2002

Dynamics of price and trading volume in a spin model of stock markets with heterogeneous agents

The dynamics of a stock market with heterogeneous agents is discussed in the framework of a recently proposed spin model for the emergence of bubbles and crashes. We relate the log returns of stock prices to magnetization in the model and find that it is closely related to trading volume as observed in real markets. The cumulative distribution of log returns exhibits scaling with exponents steeper than 2 and scaling is observed in the distribution of transition times between bull and bear markets.

cond-mat.stat-mech↗

arXiv2000

Speculative bubbles and crashes in stock market: an interacting-agent model of speculative activity

We present an interacting-agent model of speculative activity explaining bubbles and crashes in stock markets. We describe stock markets through an infinite-range Ising model to formulate the tendency of traders getting influenced by the investment attitude of other traders. Bubbles and crashes are understood and described qualitatively and quantitatively in terms of the classical phase transitions. The results of estimation the parameters of the model using the actual financial data (the bubble and the subsequent crash in the Japanese stock market in 1987-1992) show that the good quality of the fits, as well as the consistency of the values of the parameters.

cond-mat.stat-mech↗