Warrants Rates Of Return And Turnover Of The Empirical Analysis

Warrant as one of the financial derivatives, investors pay a premium to buy, have a right (but not the obligation) in a particular period (or a specific point in time) according to the agreed purchase price to the issuer or selling the underlying securities. Returns and turnover rate as the basis for warrants of the two variables, a static view of previous papers studied the relationship between the returns and turnover, it is clear that this study has certain limitations, to further explore the relationship between them, need to dynamic point of view, from the perspective of time changes. If the relevance of the changes involve the time factor, only the sample correlation coefficient is calculated simply inappropriate, as it ignored the correlation coefficient calculated conditional correlation coefficient changes with the time information.For these reasons, this paper mainly works in three aspects in the following:(1) The paper summarizes the past returns and turnover rate on the links between the two deficiencies at first, before that the research on the return and turnover rate, they used the strictly linear Granger causality test, as They used returns and turnover rate as exogenous variables respectively, so the test results only had a one-way Granger, this paper, using the binary Granger causality test, obtained both turnover and profitability linkage between each other cause and effect relationship.(2) previous studies generally yield the turnover as the exogenous variable, or the introduction of other variables set. This approach does not reflect the turnover and profitability of the mutual interaction between this two factor, mutually causal relationship. In this paper, a binary GARCH (1,1) model, the transaction rate and turnover rate as the GARCH (1,1) model of endogenous variables, the full study linkage relationships between them.(3) Multivariate GARCH model considers the transaction rate and the relationship between returns and turnover rate, based on the introduction of dynamic GARCH model (that is the DCC-GARCH model), taking the residual variability into account, the basic GARCH model predicted to amend, DCC-GARCH (1,1) model can reflect the transaction rate and Turnover change in trend.Main conclusions of this paper are: (1) warrant transactions related to exchange rate relationship between the mutual linkage, not the past, qualitative analysis of the positive relationship.(2) Multivariate GARCH models based solely on financial time series data, low vibration, high hover (the phenomenon of Conditional Heteroskedasticity) characteristics, the multi GARCH to a good deal of financial time series correlation between. (3) relative to the initial binary GARCH models, DCC-GARCH model has its advantages, it takes the conditional heteroscedasticity of the time variation into account, compared with the static GARCH model, described on its relevance, and the estimated value of the forecast will be better.