 Paper代写：GARCH模型由数学方程和定义构成

Paper代写 ：GARCH模型由数学方程和定义构成

{Ft} =由W，增广螺母集生成

Wi =的冲击

Paper代写 ：GARCH模型由数学方程和定义构成

This is one of the important part of this study to formulate the required and best model that is capable of handling this much data and is able to do the time series analysis. With help of the various methods as discussed above, the GARCH model was finalized. This was finalized because it is one of the best method or model to analyse or regress the financial time series data and characterize (Gurarda et al., 2016). This model is also applied because in the collected data above for 50 Chinese listed companies, there are lot number data points which were there in a series such that the variance for the error term or the innovation it actually the function which is related to the overall size of the error taken during the previous time periods.

Paper代写 ：GARCH模型由数学方程和定义构成

This was the reason for choosing GARCH model as the best suitable method with three different models for this study to provide the required results or outputs form the given data. The model is constructed with mathematical equations and definitions as below:
Let us consider that this economy is a continuous time pure exchange with finite horizon T. If there is any uncertainty in economy, then it can be actually represented with the help of the filtered probability space , F,Ft, P, with F=FT on which is defined a two dimensional Brownian motionW=(Wa, Wi).
Whereas,
{Ft} = Generated by W, augmented nut sets
Wa=Agreegrate consumption shock
Wi= idiosyncratic shock
Normally, the value which is obtained from the idiosyncratic shock is used when doing the assessment of the pricing in case of a small firm which is embedded in the economy. After this it is also important to consider such a firm which has equity and debt in its overall capital structure under the overall simple assumption that the debt is complete free from the risk, so that any changes in the firm valuation are entirely led by change in stock value of the company (Xu& Wang, 1999).