Daily Rates Of Return Research Articles

Prediction of index futures returns and the analysis of financial spillovers—A comparison between GARCH and the grey theorem

This paper adopts the GM(1, 1) model to predict the rates of return of nine major index futures in the American and Eurasian markets. In a further step, by means of local grey relational analysis and by employing the GM(1, N) model for the first time, the variation relatedness and the main influencing factor among the above mentioned targeted markets is determined. Then, a comparison between GARCH/TGARCH and the grey theory with regard to predictive power is conducted. The findings reveal that the GARCH/TGARCH model performs better than the GM(1, 1), including the optimal α method, in terms of forecasting capabilities. Meanwhile, it is also found that GARCH and spillover effects indeed exist. Moreover, GM(1, N) also reveals that the daily rate of return of the Dow Jones index futures has the most influence on the rates of return of the other index futures.

Financial Valuation of the German Model: The Negative Relationship Between Ownership Concentration and Stock Market Returns, 1997–2001

Believed to be a robust alternative to Anglo-American market capitalism, the virtues of the German model are increasingly disputed as doubts are raised about its long-term prospects. At the core of the German model is a system of corporate governance that is characterized by concentrated ownership and cross-holdings of stocks among related firms and their financial service providers. When combined with workers’ representation on corporate supervisory boards, concentrated ownership is thought to encourage a longer-term competitive and investment strategy. Using a unique data set on German corporate voting rights and insights gleaned from intensive interviews with German and international financial institutions, we analyze daily stock market prices from 1997 to 2001, testing for the value attributed to concentrated ownership by financial markets. We show that financial markets discount ownership concentration in ways that are consistent with Anglo-American conceptions of shareholder value, rather than with the logic of the German model. There is a significant negative relationship between ownership concentration and the average daily rate of return (as measured by closing stock market prices). This is an important finding for firms in the DAX100 and is the most pronounced for firms in the DAX30. Implications of these findings for the continued significance of distinctive regional systems of accumulation are considered in the final sections.

Rules extraction in short memory time series using genetic algorithms

Data mining is performed using genetic algorithm on artificially generated time series data with short memory. The extraction of rules from a training set and the subsequent testing of these rules provide a basis for the predictions on the test set. The artificial time series are generated using the inverse whitening transformation, and the correlation function has an exponential form with given time constant indicative of short memory. A vector quantization technique is employed to classify the daily rate of return of this artificial time series into four categories. A simple genetic algorithm based on a fixed format of rules is introduced to do the forecasting. Comparing to the benchmark tests with random walk and random guess, genetic algorithms yield substantially better prediction rates, between 50% to 60%. This is an improvement compared with the 47% for random walk prediction and 25% for random guessing method.

Evolution in dynamic linkages across daily national stock indexes

This article investigates how dynamic linkages among the daily rates of return of eight national stock indexes have evolved since 1972. A dynamic simultaneous equations model is estimated to describe the contemporaneous and lead/lag relationships across national equity markets over three different years: 1972, 1980, and 1987. Results reveal growing market interdependence within the same geographical region over time. While there are many significant intermarket relationships within the same 24-hour period, there are few significant lagged responses across markets beyond 24 hours. This suggests a high degree of international market efficiency. Furthermore, Japan's market influence has been growing to rival that of the USA.

Evidence of Nonlinearity in Daily Stock Returns

This article applies a newly developed statistical technique to time series of daily rates of return of 15 common stocks. The technique involves estimating the bispectrum of the observed time series. The bispectrum is defined as the double Fourier transform of the third-order cumulant function. If the process generating rates of return is linear with independent innovations, then the skewness of the bispectrum will be constant. The article describes a test that can detect nonconstant skewness in the bispectrum. Hence if the test rejects constant skewness, a nonlinear process is implied. As a consequence, the test can distinguish between white noise and purely random noise. The results suggest that daily stock returns are generated by a nonlinear process.

A Comparison of the Stable and Student Distributions as Statistical Models for Stock Prices

There has been a great deal of discussion about the statistical distribution of rates of return on common stocks. At an early stage the prevalent belief was that distributions of rates of return on common stocks were adequately characterized by the normal distribution. This belief seemed to be consistent with the pioneering work of Bachelier.1 It was also observed, however, that empirical distributions of such returns had more kurtosis (i.e., fatter tails) than that predicted by the normal distribution. The evidence provided by Mandelbrot and Fama suggested that one could explicitly account for the observed fat tails by using the symmetric-stable distribution.2 This article considers another family of symmetric distributions that can also account for the observed fat tails of returns distribution. This alternative is the Student (or t) distribution. It will be indicated that this alternative model has implications for empirical and theoretical work that are quite different from those of the symmetric-stable model. The descriptive validity of the Student model, relative to that of the symmetric-stable model, will be assessed using actual daily rates of return. This article is organized as follows: Section II describes the prop-