Searcharxiv⌕ Search

arXiv subjects

Taisei Kaizoji

Publications and source records attributed to Taisei Kaizoji.

At least 19 recordsLinked to original sources

Mechanism of information transmission from a spot rate market to crypto-asset markets

We applied the SVAR-LiNGAM to illustrate the causal relationships between the spot exchange rate, and three crypto-asset exchange rates, Bitcoin, Ethereum, and Ripple. It was notable that the causal order, the EUR_USD spot rate->Bitcoin->Ethereum->Ripple, was obtained by this approach. All the instantaneous effects were strongly positive. Moreover, it was notable that Bitcoin can influence the EUR_USD spot rate positively with a one-day time lag.

q-fin.ST↗

Fat Tails in Financial Return Distributions Revisited: Evidence from the Korean Stock Market

This study empirically re-examines fat tails in stock return distributions by applying statistical methods to an extensive dataset taken from the Korean stock market. The tails of the return distributions are shown to be much fatter in recent periods than in past periods and much fatter for small-capitalization stocks than for large-capitalization stocks. After controlling for the 1997 Korean foreign currency crisis and using the GARCH filter models to control for volatility clustering in the returns, the fat tails in the distribution of residuals are found to persist. We show that market crashes and volatility clustering may not sufficiently account for the existence of fat tails in return distributions. These findings are robust regardless of period or type of stock group.

q-fin.GN↗

Zipf's law for share price and company fundamentals

We statistically investigate the distribution of share price and the distributions of three common financial indicators using data from approximately 8,000 companies publicly listed worldwide for the period 2004-2013. We find that the distribution of share price follows Zipf's law; that is, it can be approximated by a power law distribution with exponent equal to 1. An examination of the distributions of dividends per share, cash flow per share, and book value per share - three financial indicators that can be assumed to influence corporate value (i.e. share price) - shows that these distributions can also be approximated by a power law distribution with power-law exponent equal to 1. We estimate a panel regression model in which share price is the dependent variable and the three financial indicators are explanatory variables. The two-way fixed effects model that was selected as the best model has quite high power for explaining the actual data. From these results, we can surmise that the reason why share price follows Zipf's law is that corporate value, i.e. company fundamentals, follows Zipf's law.

econ.GN↗

Toward Economics as a New Complex System

The 2015 Nobel Prize in Economic Sciences was awarded to Eugene Fama, Lars Peter Hansen and Robert Shiller for their contributions to the empirical analysis of asset prices. Eugene Fama [1] is an advocate of the efficient market hypothesis. The efficient market hypothesis assumes that asset price is determined by using all available information and only reacts to new information not incorporated into the fundamentals. Thus, the movement of stock prices is unpredictable. Robert Shiller [2] has been studying the existence of irrational bubbles, which are defined as the long term deviations of asset price from the fundamentals. This drives us to the unsettled question of how the market actually works. In this paper, I look back at the development of economics and consider the direction in which we should move in order to truly understand the workings of an economic society.

econ.GN↗

Stock Market Market Crash of 2008: an empirical study of the deviation of share prices from company fundamentals

The aim of this study is to investigate quantitatively whether share prices deviated from company fundamentals in the stock market crash of 2008. For this purpose, we use a large database containing the balance sheets and share prices of 7,796 worldwide companies for the period 2004 through 2013. We develop a panel regression model using three financial indicators--dividends per share, cash flow per share, and book value per share--as explanatory variables for share price. We then estimate individual company fundamentals for each year by removing the time fixed effects from the two-way fixed effects model, which we identified as the best of the panel regression models. One merit of our model is that we are able to extract unobservable factors of company fundamentals by using the individual fixed effects. Based on these results, we analyze the market anomaly quantitatively using the divergence rate--the rate of the deviation of share price from a company's fundamentals. We find that share prices on average were overvalued in the period from 2005 to 2007, and were undervalued significantly in 2008, when the global financial crisis occurred. Share prices were equivalent to the fundamentals on average in the subsequent period. Our empirical results clearly demonstrate that the worldwide stock market fluctuated excessively in the time period before and just after the global financial crisis of 2008.

q-fin.GN↗

Modeling of Stock Returns and Trading Volume

In this study, we investigate the statistical properties of the returns and the trading volume. We show a typical example of power-law distributions of the return and of the trading volume. Next, we propose an interacting agent model of stock markets inspired from statistical mechanics [24] to explore the empirical findings. We show that as the interaction among the interacting traders strengthens both the returns and the trading volume present power-law behavior.

q-fin.ST↗

Full characterization of the fractional Poisson process

The fractional Poisson process (FPP) is a counting process with independent and identically distributed inter-event times following the Mittag-Leffler distribution. This process is very useful in several fields of applied and theoretical physics including models for anomalous diffusion. Contrary to the well-known Poisson process, the fractional Poisson process does not have stationary and independent increments. It is not a Lévy process and it is not a Markov process. In this letter, we present formulae for its finite-dimensional distribution functions, fully characterizing the process. These exact analytical results are compared to Monte Carlo simulations.

math.PR↗

Non-Stationary Chaos

A new type of deterministic chaos for a system described by iterative two-dimensional maps is reported. The series being generated by the original map has an average upward trend while the first difference, which is the series of changes from one period to the next, exhibits chaotic behavior through period doubling bifurcation. Furthermore, step-wise time series appears as the values of the bifurcation parameter are large, and the first difference of the time series exhibits intermittent chaos.

nlin.CD↗

Effect of changing data size on eigenvalues in the Korean and Japanese stock markets

In this study, we attempted to determine how eigenvalues change, according to random matrix theory (RMT), in stock market data as the number of stocks comprising the correlation matrix changes. Specifically, we tested for changes in the eigenvalue properties as a function of the number and type of stocks in the correlation matrix. We determined that the value of the eigenvalue increases in proportion with the number of stocks. Furthermore, we noted that the largest eigenvalue maintains its identical properties, regardless of the number and type, whereas other eigenvalues evidence different features.

q-fin.ST↗

The Effects of Market Properties on Portfolio Diversification in the Korean and Japanese Stock Markets

In this study, we have investigated empirically the effects of market properties on the degree of diversification of investment weights among stocks in a portfolio. The weights of stocks within a portfolio were determined on the basis of Markowitz's portfolio theory. We identified that there was a negative relationship between the influence of market properties and the degree of diversification of the weights among stocks in a portfolio. Furthermore, we noted that the random matrix theory method could control the properties of correlation matrix between stocks; this may be useful in improving portfolio management for practical application.

q-fin.PM↗

Volatility return intervals analysis of the Japanese market

We investigate scaling and memory effects in return intervals between price volatilities above a certain threshold $q$ for the Japanese stock market using daily and intraday data sets. We find that the distribution of return intervals can be approximated by a scaling function that depends only on the ratio between the return interval $τ$ and its mean $<τ>$. We also find memory effects such that a large (or small) return interval follows a large (or small) interval by investigating the conditional distribution and mean return interval. The results are similar to previous studies of other markets and indicate that similar statistical features appear in different financial markets. We also compare our results between the period before and after the big crash at the end of 1989. We find that scaling and memory effects of the return intervals show similar features although the statistical properties of the returns are different.

q-fin.ST↗

Group dynamics of the Japanese market

We investigated the network structures of the Japanese stock market through the minimum spanning tree. We defined grouping coefficient to test the validity of conventional grouping by industrial categories, and found a decreasing in trend for the coefficient. This phenomenon supports the increasing external influences on the market due to the globalization. To reduce this influence, we used S&P500 index as the international market and removed its correlation with every stock. We found stronger grouping in this measurement, compared to the original analysis, which agrees with our assumption that the international market influences to the Japanese market.

q-fin.ST↗

The market efficiency in the stock markets

We study the temporal evolution of the market efficiency in the stock markets using the complexity, entropy density, standard deviation, autocorrelation function, and probability distribution of the log return for Standard and Poor's 500 (S&P 500), Nikkei stock average index, and Korean composition stock price index (KOSPI). Based on the microscopic spin model, we also find that these statistical quantities in stock markets depend on the market efficiency.

physics.soc-ph↗

Waiting times between orders and trades in double-auction markets

In this paper, the survival function of waiting times between orders and the corresponding trades in a double-auction market is studied both by means of experiments and of empirical data. It turns out that, already at the level of order durations, the survival function cannot be represented by a single exponential, thus ruling out the hypothesis of constant activity during trading. This fact has direct consequences for market microstructural models. They must include such a non-exponential behaviour to be realistic.

physics.soc-ph↗

Stylized Facts in Internal Rates of Return on Stock Index and its Derivative Transactions

Universal features in stock markets and their derivative markets are studied by means of probability distributions in internal rates of return on buy and sell transaction pairs. Unlike the stylized facts in log normalized returns, the probability distributions for such single asset encounters encorporate the time factor by means of the internal rate of return defined as the continuous compound interest. Resulting stylized facts are shown in the probability distributions derived from the daily series of TOPIX, S & P 500 and FTSE 100 index close values. The application of the above analysis to minute-tick data of NIKKEI 225 and its futures market, respectively, reveals an interesting diffference in the behavior of the two probability distributions, in case a threshold on the minimal duration of the long position is imposed. It is therefore suggested that the probability distributions of the internal rates of return could be used for causality mining between the underlying and derivative stock markets. The highly specific discrete spectrum, which results from noise trader strategies as opposed to the smooth distributions observed for fundamentalist strategies in single encounter transactions may be also useful in deducing the type of investment strategy from trading revenues of small portfolio investors.

cs.IT↗

Response of Firm Agent Network to Exogenous Shock

This paper describes an agent-based model of interacting firms, in which interacting firm agents rationally invest capital and labor in order to maximize payoff. Both transactions and production are taken into account in this model. First, the performance of individual firms on a real transaction network was simulated. The simulation quantitatively reproduced the cumulative probability distribution of revenue, material cost, capital, and labor. Then, the response of the firms to a given exogenous shock, defined as a sudden change of gross domestic product, is discussed. The longer tail in cumulative probability and skewed distribution of growth rate are observed for a high growth scenario.

physics.soc-ph↗

An interacting-agent model of financial markets from the viewpoint of nonextensive statistical mechanics

In this paper we present an interacting-agent model of stock markets. We describe a stock market through an Ising-like model in order to formulate the tendency of traders getting to be influenced by the other traders' investment attitudes [1], and formulate the traders' decision-making regarding investment as the maximum entropy principle for nonextensive entropy. We demonstrate that the equilibrium probability distribution function of the traders' investment attitude is the {\it q-exponential distribution}. We also show that the power-law distribution of the volatility of price fluctuations, which is often demonstrated in empirical studies, can be explained naturally by our model which is based on the collective crowd behavior of many interacting agents.

physics.soc-ph↗

Re-examination of the size distribution of firms

In this paper we address the question of the size distribution of firms. To this aim, we use the Bloomberg database comprising multinational firms within the years 1995-2003, and analyze the data of the sales and the total assets of the separate financial statement of the Japanese and the US companies, and make a comparison of the size distributions between the Japanese companies and the US companies. We find that (i) the size distribution of the US firms is approximately log-normal, in agreement with Gibrat's observation (Gibrat 1931), and in contrast (ii) the size distribution of the Japanese firms is clearly not log-normal, and the upper tail of the size distribution follows the Pareto law. It agree with the predictions of the Simon model (Simon 1955). Key words: the size distribution of firms, the Gibrat's law, and the Pareto law

physics.soc-ph↗