澳洲墨尔本大学论文代写：债券收益
在本文中，对8个静态经济科学因素进行了计算，并计算了后续的Ludvigson和Ng(2009,2010)。我们倾向于提出统计数据，除了利率统计之外，我们还保留了外汇，以拥有纯粹的宏观因素(Geert,2007)。经济科学知识领域位于世界的主要角落。
结果和发现
总结债券收益方测量数据在表1,表,以及大纲宏观变量的统计测量面板b意味着债券利润广场升级发展中除了数字平方衡量队伍通过之前的研究(柯西,罗伯特,2010)。而未来的债券回报从2到5年债券投资一年时间,非常讨厌的,大概由于结合到来的11个月,一个月分享的相关因子进行国库券的收益量下降很多更快的初始值的谎言从0级相关因素。23至0.55(Geert,2007)。
他的问题，平均的大小，期的问题，以及隐藏的问题的平方，都是与初始的顺序相关系数系数，从0.85开始到0.96(Jiang,Yisong,2005)。大尺度因素表现出较少的相关因素，并包括少数假设为负的部分。表a对与风险溢价方差(Geert,2007)一起，将不合格的自相关因子与所有预报员变量联系在一起。显然，平方衡量的3个因素被认为是受害收益或债券的回归数据，CP，平方度量与从0的完全自相关的方法非常相关。32至0.72。风险溢价差异并不十分极其相关的其他因素除了绑定大小是-0.33,因此最初的宏单元,Ludvigson毫微克(2009)因为真正的问题由于其自相关系数升高过程真正的生产力以及雇佣。
澳洲墨尔本大学论文代写：债券收益
In this paper, the eight static economic science factors has also been calculated subsequent Ludvigson and Ng (2009, 2010). We tend to bring up to date the statistic and that we keep out the exchange in addition to interest rate statistic so as to possess unadulterated macro factors (Geert, 2007). The economic science knowledge area lies in the main from world just round the corner.
Results and Findings
Summing up data for the bond proceeds square measure in Table one, sheet A, as well as outline statistics for the macro variables in Panel B. The mean bond profits square measure escalating in the midst of development in addition to the numbers square measure in procession through preceding studies (Corsi, Roberto, 2010). whereas future bond returns from 2 to five year bonds for a one year investment period that are extremely importunate, presumably owing to the combining arrival horizon of eleven months, the correlation factor perform for the one month sharing amount returns of the Treasury bills drops a lot of quicker with values of initial order correlation factors that lies from zero.23 to 0.55 (Geert, 2007).
he CP issue, size of the mean, the issue of the period, as well as the concealed issue square measure all extremely unrelenting with initial order correlation factor coefficients starting from 0.85 to 0.96 (Jiang, Yisong, 2005). The large scale factors exhibit less correlation factors, and include few parts that assumed to be negative. Table a pair of information the unqualified autocorrelation factor with all the forecaster variables together with risk premium variance (Geert, 2007). Obviously, the 3 factors that square measure considered victimization yields or bond come back data, CP, square measure fairly extremely related to by means of total autocorrelations that lies from zero.32 to 0.72. The risk premium variance isn’t terribly extremely related to with the other factors apart from the mean bound size that is -0.33, and therefore the initial macro element, that Ludvigson and nanogram (2009) make because the real issue owing to its elevated autocorrelation factor with procedures of genuine productivity as well as employ.
