centralbank.Rmd

---
title: "central bank"
author: "qiufei"
date: "2016-06-08"
output: 
  html_document: 
    fig_height: 7
    fig_width: 9
    keep_md: yes
    number_sections: yes
    theme: readable
    toc: yes
---

```{r setup,Message=FALSE,echo=FALSE,include=FALSE,warning=FALSE}

# load needed packages
library(knitr)
opts_chunk$set(Message=FALSE,echo=FALSE)
library(ggplot2)
library(reshape2)
library(Quandl)
Quandl.api_key("9iGeZZoG6Vc46rfs1AgJ")
library(pdfetch)
library(quantmod)
options("getSymbols.warning4.0"=FALSE)
library(scales)
library(plyr)
library(dplyr)
options(warn=-1)          #suprress warning globally
## the default is
## options(warn=0)

```

# 人民银行资产负债表规模增速与cpi的关系 #

物价指数环比增速与央行资产负债表的增速高度相关.


```{r balanc sheet}
#这里的quandl code代码最好用双引号，也是官方的做法。以前这里单引号在ubuntu下是运行通过了的，但是在mac上不行。mac下必须要用双引号。
codes = c('PBCHINA/REP_04.11','NBSC/A01030101_M')
names = c('date','pbc.asset','cpi')
pbc = Quandl(codes)
colnames(pbc) = names

## drop those NA observations
pbc2 = filter(pbc,date>'2005-12-31')
## get growth rate
## 这里的ROC函数来自TTR包，前面加在quandmod包的时候，会自动加载TTR包。
pbc2[,2] = ROC(pbc2[,2],type = 'discrete')*100
pbc2[,3] = pbc2[,3] - 100


qfplot = function(dat,title){
    inter = melt(dat,id = 'date')
    ggplot(inter,aes(x = date,y = value,color = variable,shape = variable))+
        geom_line()+
        geom_point()+
        ggtitle(title)}
qfplot(pbc2,'人行资产增速与CPI环比增速之间的关系')


```