Emerging Market Equity Prices and Chaos: Evidence from Thailand Exchange

Chaotic deterministic models with sensitive dependence on initial conditions provide a powerful tool in understanding the apparently random movements in financial data. This study examines four financial markets in India, an emerging economy, for possible chaotic behavior. We employ four tests, viz. the BDS test on raw data, the BDS test on pre-filtered data, Correlation Dimension test and the Brock's Residual test. The financial markets considered are the stock market, the foreign exchange market, the money market and the government securities market. The results from these tests provide very weak evidence for the presence of chaos in Indian financial markets.

2006

Chaotic deterministic models with sensitive dependence on initial conditions provide a powerful tool in understanding the apparently random movements in financial data. This study examines four financial markets in India, an emerging economy, for possible chaotic behavior. We employ four tests, viz. the BDS test on raw data, the BDS test on pre-filtered data, Correlation Dimension test and the Brock’s Residual test. The financial markets considered are the stock market, the foreign exchange market, the money market and the government securities market. The results from these tests provide very weak evidence for the presence of chaos in Indian financial markets.

ABAC Journal, 2017

Understanding stock market price fluctuations plays an important role in economic policy and in corporate investment and financing strategies. In recent years, Khantavit and others have investigated the proposition that nonlinear processes studied in Chaos theory play an important role in these fluctuations. This study provides a detailed examination of this hypothesis using data from the Stock Exchange of Thailand (SET) from 1975 to 1999. The study finds that the distribution of the daily return on the SET index is nonnormal and leptokurtic. The results of the study also suggest that non-linear processes play a significant role in stock market behavior

This paper is an attempt to test for nonlinear structure and chaos indicators on the returns of bank stocks listed in Athens Exchange (ATHEX) as well as the indices: ATHEX Composite index, FTSE/ASE 20 and FTSE/ASE mid 40.

2015

Understanding stock market price fluctuations plays an important role in economic policy and in corporate investment and financing strategies. In recent years, Khantavit and others have investigated the proposition that nonlinear processes studied in Chaos theory play an important role in these fluctuations. This study provides a detailed examination of this hypothesis using data from the Stock Exchange of Thailand (SET) from 1975 to 1999. The study finds that the distribution of the daily return on the SET index is non-normal and leptokurtic. The results of the study also suggest that non-linear processes play a significant role in stock market behavior I.

This study tests for the presence of nonlinear dependence and deterministic chaos in the rate of returns series for six Indian stock market indices. The overall result of our analysis suggests that the returns series do not follow a random walk process. Rather it appears that the daily increments in stock returns are serially correlated and the estimated Hurst exponents are indicative of marginal persistence in equity returns. Result from test of independence on filtered residuals suggests that the existence of nonlinear dependence, at least to some extent, can be attributed to the presence of conditional heteroskedasticity. It appears, therefore, that low order GARCH–type models can adequately explain some, but not all, of the observed nonlinear dependence in the data. The existing nonlinearity in the data appears to be multiplicative in nature. Further, we find very little evidence to support the proposition that returns are generated by a chaotic system. Only in two out of six ca...

Ssrn Electronic Journal, 2006

The chaos theory assumes that the returns dynamics are not normally distributed and more complex approaches have to be used to study these time series. In fact, the Fractal Market Hypothesis assumes that the returns dynamics are not independent of the investors' attitudes and represent the result of the interaction of traders who, frequently, adopt different investment styles.

The nonlinearity and accompanying concept, namely the chaos receive great attention from researchers. This study employs nonlinearity and chaos theories to examine the behavior of the Istanbul Stock Exchange (ISE) all share equity indices. The main purpose was to explore the existence or nonexistence of nonlinearity and chaotic behavior in the ISE market. Therefore, the efficient markets' characteristics, which are the random behavior of asset prices and nonlinear chaotic dynamics, were contrasted and the probabilistic and deterministic behaviors of the asset prices were compared. Our results based on BDS, Hinich Bispectral, Lyapunov Exponent and NEGM tests reject the efficient market hypothesis that the index series examined in this study is not random, independent and identically distributed (i.i.d).

This research finds evidence of noisy chaotic properties in the returns of four Dow Jones indices, based on three tests of non-linearity and chaos. The study uses an average of 24,815 data points to correctly simulate chaos in financial time-series. The data consists of the Dow Jones Industrial Average (29,229 observations); Dow Jones Transportation Average (29,121 observations); Dow Jones Utility Average (21,150 observations) and the Dow Jones Composite Average (19,906 observations). The a) Brock, Dechert, and Scheinkman (BDS) test indicates that most of the Dow Jones indices are not iid series, except for the filtered residuals from the GARCH of the Dow Jones Utility Average. The b) rescaled range analysis shows that after scrambling the data, all Hurst exponents are above 0.5, and a trend-reinforcing property, which helps in the conclusion of having a chaotic process. Lastly, the c) correlation dimension analysis complements the initial findings and concludes the presence of a high dimensional noisy chaotic structure in the four Dow Jones indices.

THE 4TH INNOVATION AND ANALYTICS CONFERENCE & EXHIBITION (IACE 2019)

This project is focused on existing of chaos in stock market price. Stock market price is frequently changing in a particular time period. The pattern of stock market price is hard to predict as it is complex and exhibit nonlinear behavior. Due to insufficient chaotic findings for local company in Malaysia, existence of chaos in stock market price of Gamuda Berhad is determined in this project. There are two tests involved in this project which BDS Test and Close Returns Test are mainly used in this project for examining chaos in the stock market price. As for the result, BDS Test results show the rejection of the null hypothesis which means stock market price of Gamuda Berhad is not independent and identically distributed (IID) and Close Returns Test shows the non-chaotic behavior for the data. Therefore, the stock market price of Gamuda Berhad has non-chaotic nonlinearity behavior.