关于墨尔本论文代写-现金流成分持续性的研究和预测，存在一些基于上下文的变量影响持续性(taste & Wilson, 2016;Lo等，2017)。然而，普遍接受的标准是，与权责发生制成分相比，现金流成分更持久。Cheng和Hollie(2005)进行了一项研究，评估未来现金流预测中现金流成分的持久性。在他们的工作中，他们评估了六个关键组成部分，即现金流、销售产品的成本、这类产品的经营费用、利息和税收。作者使用了一种回归分析方法，将上一个时期的现金周期与当前年度进行回归。在此基础上，进行了现金流量预测模型和总现金流量预测模型的比较。关于持久性的假设是，只有当产生现金流的活动发生变化时，现金流组件持久性才会发生变化，这意味着如果活动本身不发生变化，那么这些组件也一定不会发生变化(Richardson et al.， 2005;Hanlon, 2005)。
A similar persistence should also be observed across all the cash flow components that were identified by researchers. Only when cash flow persistence is thus defined, then it will be possible for the company to make use of forecast models and better investment options. However, in terms of persistent the authors observed that cash flow from sales of goods, the cost in goods sold, the expenses of operations seemed to have better persistence in comparison with cash flows for other expenses (Cheng & Hollie, 2005). It was identified that cash flow with respect to taxes did not have any form of persistence and this has been observed in other research works, too (Cheng & Hollie, 2005; Lundholm, and Myers, 2002)
The same research was conducted with respect to accrual components. The persistence regression model applied for cash flow analysis was used here. It was established that the cash flow persistence was much higher than that of accruals and therefore cash flows might do a better job of predicting earning performance (Cheng & Hollie, 2005). However, in research works instead of using cash flow analysis alone, it was deemed better to make use of accrual components as well, as accrual components enhanced performance (Dechow & Dichev, 2002; Dechow, 1994).
Research Method and Model
The research regression model in the work of Cheng & Hollie (2005), article titled ‘The Persistence of Cash Flow Components into Future Cash Flows’, the variables as defined in the work of Lundholm & Myers (2002) and the variables defined in the work of Francis et al (2005) are used here. The model from the journal will be replicated to construct a regression model. Samples of data within the last 10 years for around 30 companies would be used. In this data, APR data is analyzed for the given sample. The samples would be collected from Compustat US.
Future earning= A+B(accurals)+error
Future earning=A+B(cash flow)+error
In this model, the important variables are future annual returns, accounting quality based on Francis et al 2005, abnormal accruals, credit ratings, etc. These variables are used for the analysis. The work of Lundholm and Myers, (2002) emphasizes key understanding on why some earnings component reflect well when being used as predictors and why others don’t. Their research highlighted how better information disclosures will result in better earnings predictions. While the reporting of cash flows and accruals have a positive influence in prediction, they can be considered as being accurate only when firms reveal credible information. The regression equation from the study was applied in this work.
The Rt value where t stands for the year is the measurement of buy and hold return for that year. The measurement of the Rt value is basically done for a time period of 12 months and the calculations ends just three months before the fiscal year end. The value Xt once again is calculated for year t. It is the income for all common shareholders as calculated for the year t, the values are considered with deflation by market value. Dt is the AIMR rating for firm.