About

This worksheet is your warm-up exercises to getting started with some R for finance, based on examples from the book. It is also your getting started with problems solving (no R required) and expressing your methods/answers using proper mathematical symbols and representations.

Setup

Remember to always set your working directory to the source file location. Go to ‘Session’, scroll down to ‘Set Working Directory’, and click ‘To Source File Location’. Read carefully the below and follow the instructions to complete the tasks and answer any questions. Submit your work to RPubs as detailed in previous notes.

Note

For clarity, tasks/questions to be completed/answered are highlighted in red color (color visible only in preview mode) and numbered according to their particular placement in the task section. Type your answers outside the red color tags!

Quite often you will need to add your own code chunk. Execute sequentially all code chunks, preview, publish, and submit link on Sakai following the naming convention. Make sure to add comments to your code where appropriate. Use own language!

Any sign of plagiarism, will result in dissmissal of work!


Task 1: Charting Stock Time Series

This task follows the book’s R Example 1.1/p. 8 also exhibited in the R-Labs section R Labs1 from the book’s website (*). In order to work with R in finance we need to first install the package quantmod that allows us to retrieve financial data and conduct various statistical analysis.

# Require will load the package only if not installed 
# Dependencies = TRUE makes sure that dependencies are install
if(!require("quantmod",quietly = TRUE))
  install.packages("quantmod",dependencies = TRUE, repos = "https://cloud.r-project.org")

##### 1A) Insert in the code chunk below the rest of the code to calculate and chart the time series for stock GE. Follow the example in the book. Add comments, where appropriate, explaining what the particular line(s) of code is/are executing/solving for.

library("quantmod")
##retrieve historical price data for General Electric Co. from Yahoo Finance
getSymbols('GE',src='yahoo', from="2000-01-01", to="2009-12-30")
[1] "GE"
##to see headers of file (OHLCV type)
names(GE)
[1] "GE.Open"     "GE.High"     "GE.Low"      "GE.Close"    "GE.Volume"   "GE.Adjusted"
## extract Adjusted Close
geAdj = GE$GE.Adjusted["2000-01-01/2000-01-20"]
##compute max, min and mean
max(geAdj); min(geAdj); mean(geAdj)
[1] 28.06313
[1] 26.23787
[1] 27.1946
## draw a chart
chartSeries(GE)

 
##to save data to your disk use
saveRDS(GE,file="GE.rds")

Task 2: Comparing Performance of Stocks Time Series

This follows the book’s example 1.3.4 R Lab/p. 34 also R Labs 1 from the book’s website (*).

##### 2A) Insert the code chunk to chart instead the performance of Value Line Index VLIC (sort of benchmark), and four other stocks of your choice over a time period dating back one year from present date.

library("quantmod")
symbols=c('^VLIC','AMZN','FB','T','MSFT')
getSymbols(symbols,src='yahoo',from="2012-02-01",to="2013-02-01")
[1] "VLIC" "AMZN" "FB"   "T"    "MSFT"
 #obtain adjusted closed
VLICad = VLIC$VLIC.Adjusted; AMZNad= AMZN$AMZN.Adjusted;
  FBad=FB$FB.Adjusted; Tad=T$T.Adjusted;
  MSFTad = MSFT$MSFT.Adjusted
 #compute cumulative sum (cumsum) of daily returns (Delt)
 #Remove first term of the series, with [-1,], since cumsum is not defined for it.
vl = cumsum((Delt(VLICad)*100)[-1,])
amzn = cumsum((Delt(AMZNad)*100)[-1,])
fb = cumsum((Delt(FBad)*100)[-1,])
t = cumsum((Delt(Tad)*100)[-1,])
msft = cumsum((Delt(MSFTad)*100)[-1,])
 
###range of values for the plot
lim = c(min(vl,amzn,fb,t,msft),max(vl,amzn,fb,t,msft))
###the plot
plot(vl,main="",ylim=lim,xlab="dates",ylab="% benefits")

lines(amzn,col="green"); lines(fb,col="red")

lines(t,col="violet"); lines(msft,col="yellow")

legend(x="topleft",cex=0.4,c("VLIC","AMZN","FB","T","MSFT"),
   lty=1, col=c("black","green","red","violet","yellow"))

##### 2B) Write the mathematical form/representation, using proper math symbols, to describe the formula being calculated and plotted in the code

\[R_{t}= \sum_{t=1}^{n}\frac{P_{t}}{P_{t-1}}-1\]

##### 2C) Write a paragraph, in your own words, comparing the stock performances based on your assessment of the companies general business and their valuation vis-a-vis the market overall performance, and pertinent econonomical factors.

From the chart it is clear that Amazon and AT&T have outperformed the markets upwards of 20% and 40% respectively. This is driven by dominant market share with Amazon’s ability to conitinue to innovate. Additonally, due to strong user growth and growing distribution channels, Amazon had a competitive advantage that led to the outperfomance of the market. AT&T’s ability to expand their services nationwide has helped them to grow their brand image and tap into new customer channels leading to increased revenue. The economies of scale compared to other competitors allows the comaonay to have diversified offerings for various customers. All these factors are drivers of growth and revenue. MSFT underpeformed during 2012-2013 despite strong financials due to investors expectation that the company could not continue to compete or innovate. Additonally, with other players entering the mobile space and Microsoft steering away, investors lost belief in the growth potential. FB had its IPO in 2012 and suffered a big dip despite expectations. However, this is common with IPOs as the market is trying to figure out where to price the stock.

To add math symbols in R Markdown check the link MathinRmd.html. Many other examples are on Google. Following is an example: \(\sum_{n=1}^{10} n^2\). Other, less preferred options, is to neatly handwrite your equations on a paper or use own preferred tools like Microsoft Word, take a clear image capture of your work and include here. Hard to read work will be dismissed.

Below is an example on how to include an image. It is assumed that the image resides in the same folder as the worksheet. Otherwise the path to the folder where the image resides needs to be included in the name referencing below.

Task 3: Problem(s) Solving

This task does not require use of R code. You will however need to type your work here, using proper mathematical symbols and representations, or include a clear image capture of your work.

##### 3A) Solve for 1.3.8 Problem/p. 36.

\[C_u=S_u-K=40-20=20\] \[C=0.8*25 - 11.43 = 8.57\] \[P=C+Ke^{rT}-S_t = 8.57 + 20e^{-0.06}-25=2.6\]

##### 3B) Solve for 1.3.9 Problem/p. 36 \[P+S_t=C+Ke^{rT}\] \[\frac{\partial}{\partial S}(C-P) = \frac{\partial}{\partial S}(S_t-Ke^{rT})\] \[\Delta C-\Delta P = 1\] \[\Delta P = \Delta C + 1\]

*http://computationalfinance.lsi.upc.edu

---
title: "FINC621 Winter 2018-19 Lab Worksheet 01"
author: "Christopher Francis"
date: "November 12,2018"
output:
  html_notebook: default
  pdf_document: default
  html_document: default
subtitle: Exploration of R in Finance (finc621-lab01)
---

### About

This worksheet is your warm-up exercises to getting started with some R for finance, based on  examples from the book. It is also your getting started with problems solving (no R required) and expressing your methods/answers using proper mathematical symbols and representations.

### Setup

Remember to always set your working directory to the source file location. Go to 'Session', scroll down to 'Set Working Directory', and click 'To Source File Location'. Read carefully the below and follow the instructions to complete the tasks and answer any questions.  Submit your work to RPubs as detailed in previous notes. 

### Note

For clarity, tasks/questions to be completed/answered are highlighted in red color (color visible only in preview mode) and numbered according to their particular placement in the task section.  Type your answers outside the red color tags!

Quite often you will need to add your own code chunk. Execute sequentially all code chunks, preview, publish, and submit link on Sakai following the naming convention. Make sure to add comments to your code where appropriate. Use own language!

**Any sign of plagiarism, will result in dissmissal of work!**

--------------

### Task 1: Charting Stock Time Series 

This task follows the book's R Example 1.1/p. 8 also exhibited in the R-Labs section R Labs1 from the book’s website (*). In order to work with R in finance we need to first install the package `quantmod` that allows us to retrieve financial data and conduct various statistical analysis.

```{r}
# Require will load the package only if not installed 
# Dependencies = TRUE makes sure that dependencies are install
if(!require("quantmod",quietly = TRUE))
  install.packages("quantmod",dependencies = TRUE, repos = "https://cloud.r-project.org")
```



<span style="color:red">
##### 1A) Insert in the code chunk below the rest of the code to calculate and chart the time series for stock GE.  Follow the example in the book. Add comments, where appropriate, explaining what the particular line(s) of code is/are executing/solving for.
</span>

```{r}
library("quantmod")
##retrieve historical price data for General Electric Co. from Yahoo Finance
getSymbols('GE',src='yahoo', from="2000-01-01", to="2009-12-30")
##to see headers of file (OHLCV type)
names(GE)
## extract Adjusted Close
geAdj = GE$GE.Adjusted["2000-01-01/2000-01-20"]
##compute max, min and mean
max(geAdj); min(geAdj); mean(geAdj)
## draw a chart
chartSeries(GE)
 
##to save data to your disk use
saveRDS(GE,file="GE.rds")
```

### Task 2: Comparing Performance of Stocks Time Series

This follows the book’s example 1.3.4 R Lab/p. 34 also R Labs 1 from the book’s website (*). 

<span style="color:red">
##### 2A) Insert the code chunk to chart instead the performance of Value Line Index VLIC (sort of benchmark), and four other stocks of your choice over a time period dating back one year from present date.
</span>
```{r}
library("quantmod")
symbols=c('^VLIC','AMZN','FB','T','MSFT')
getSymbols(symbols,src='yahoo',from="2012-02-01",to="2013-02-01")
 #obtain adjusted closed
VLICad = VLIC$VLIC.Adjusted; AMZNad= AMZN$AMZN.Adjusted;
  FBad=FB$FB.Adjusted; Tad=T$T.Adjusted;
  MSFTad = MSFT$MSFT.Adjusted
 #compute cumulative sum (cumsum) of daily returns (Delt)
 #Remove first term of the series, with [-1,], since cumsum is not defined for it.
vl = cumsum((Delt(VLICad)*100)[-1,])
amzn = cumsum((Delt(AMZNad)*100)[-1,])
fb = cumsum((Delt(FBad)*100)[-1,])
t = cumsum((Delt(Tad)*100)[-1,])
msft = cumsum((Delt(MSFTad)*100)[-1,])
 
###range of values for the plot
lim = c(min(vl,amzn,fb,t,msft),max(vl,amzn,fb,t,msft))
###the plot
plot(vl,main="",ylim=lim,xlab="dates",ylab="% benefits")
lines(amzn,col="green"); lines(fb,col="red")
lines(t,col="violet"); lines(msft,col="yellow")
legend(x="topleft",cex=0.4,c("VLIC","AMZN","FB","T","MSFT"),
   lty=1, col=c("black","green","red","violet","yellow"))
```

<span style="color:red">
##### 2B) Write the mathematical form/representation, using proper math symbols, to describe the formula being calculated and plotted in the code  
</span>

$$R_{t}= \sum_{t=1}^{n}\frac{P_{t}}{P_{t-1}}-1$$


<span style="color:red">
##### 2C) Write a  paragraph, in your own words, comparing the stock performances based on your assessment of the companies general business and their valuation vis-a-vis the market overall performance, and pertinent econonomical factors.
</span>

From the chart it is clear that Amazon and AT&T have outperformed the markets upwards of 20% and 40% respectively. This is driven by dominant market share with Amazon's ability to conitinue to innovate. Additonally, due to strong user growth and growing distribution channels, Amazon had a competitive advantage that led to the outperfomance of the market. AT&T's ability to expand their services nationwide has helped them to grow their brand image and tap into new customer channels leading to increased revenue. The economies of scale compared to other competitors allows the comaonay to have diversified offerings for various customers. All these factors are drivers of growth and revenue. MSFT underpeformed during 2012-2013 despite strong financials due to investors expectation that the company could not continue to compete or innovate. Additonally, with other players entering the mobile space and Microsoft steering away, investors lost belief in the growth potential. FB had its IPO in 2012 and suffered a big dip despite expectations. However, this is common with IPOs as the market is trying to figure out where to price the stock.


To add math symbols in R Markdown check the link [MathinRmd.html]( https://www.calvin.edu/~rpruim/courses/s341/S17/from-class/MathinRmd.html).
Many other examples are on Google. Following is an example: $\sum_{n=1}^{10} n^2$.  Other, less preferred options, is to neatly handwrite your equations on a paper or use own preferred tools like Microsoft Word, take a clear image capture of your work and include here.  Hard to read work will be dismissed. 

Below is an example on how to include an image.  It is assumed that the image resides in the same folder as the worksheet. Otherwise the path to the folder where the image resides needs to be included in the name referencing below.


### Task 3: Problem(s) Solving

This task does not require use of R code.  You will however need to type your work here, using proper mathematical symbols and representations, or include a clear image capture of your work.


<span style="color:red">
##### 3A) Solve for 1.3.8 Problem/p. 36. 
</span>

$$C_u=S_u-K=40-20=20$$
$$C=0.8*25 - 11.43 = 8.57$$
$$P=C+Ke^{rT}-S_t = 8.57 + 20e^{-0.06}-25=2.6$$

<span style="color:red">
##### 3B) Solve for 1.3.9 Problem/p. 36
</span>
$$P+S_t=C+Ke^{rT}$$
$$\frac{\partial}{\partial S}(C-P) = \frac{\partial}{\partial S}(S_t-Ke^{rT})$$
$$\Delta C-\Delta P = 1$$
$$\Delta P = \Delta C + 1$$



*[http://computationalfinance.lsi.upc.edu ](http://computationalfinance.lsi.upc.edu)
