# Financial Econometrics MFE MATLAB Introduction. Kevin Sheppard University of Oxford

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1 Financial Econometrics MFE MATLAB Introduction Kevin Sheppard University of Oxford October 21, 2013

2 Kevin Sheppard 2

3 Contents Introduction i 1 Getting Started 1 2 Basic Input and Operators 5 3 Functions 9 4 Accessing Elements in Matrices 13 5 Program Flow 15 6 Logical Operators 17 7 Importing Data into MATLAB 19 8 Graphics 21 3

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6 pd = pwd cd PATH\WHERE\YOU\PUT\THE\TOOLBOX\ addtopath -silent cd(pd) This will add the MFE toolbox to your path each time you open MATLAB. ii

7 Lesson 1 Getting Started This lesson covers: Launching MATLAB Launching the editor Creating a startup file Launching MATLAB To launch MATLAB, select Start>Programs>MATLAB>R2013a>MATLAB R2013a. 1 When MATLAB opens, a window similar to figure 1 should be present, although the contents of the panes may vary. Problem 1 (Launching MATLAB). Open MATLAB on your terminal. Launch the Editor Once MATLAB is up and running, launch the editor. There are two methods to accomplish this task Enter edit in the command window Use the menu via File>New>M-File. The editor should appear similar to figure 1.2. Problem 2 (Launch the Editor). Open the editor using one the methods above. Once the editor is open, create a file with the following contents: x = exp(1) y = log(x) and save it as lesson1.m. Go to the command window and enter lesson1. The command window should show x = y = 1 1 The version may be different depending on what OUCS is distributing. 1

8 Figure 1.1: Basic MATLAB Window. The standard setup has four pains. 1: The command window, 2: Current Directory, 3: Workspace and 4: Command History Problem 3 (Edit an Existing File). Next, close the editor by either clicking on the X in the top right corner or selecting File>Close Editor. A specific file can be opened in the editor by entering edit filename in the command window. To verify this works, try the following: >> edit lesson1 Exercises Exercise 1. Explore alternative views of the MATLAB desktop by changing the configuration using the Desktop menu. 2

9 Figure 1.2: The editor. 3

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11 Lesson 2 Basic Input and Operators This lesson covers: Manually inputting data in scalars, vectors and matrices Basic mathematical operations Saving and loading data August 2013 prices (closing prices) for the S&P 500 EFT (SPY), Apple (AAPL) and IBM (IBM) are listed in table 2.1. Problem 4 (Input scalar data). Create 3 variables, one labeled SPY, one labeled AAPL and one labeled IBM that contain the August 1 price of the name. For example, to enter the IBM data, >> IBM = IBM = Problem 5 (Semicolon (;)). Re-enter the data in the previous task but this time use a semicolon (;) to suppress output. Verify that the value is correct by entering the ticker symbol alone on the command prompt (and without a semicolon). For example, >> IBM = ; >> IBM IBM = Problem 6 (Input a Row Vector). Create row vectors for each of the days in Table 2.1 named AugXX where XX is the numeric date. For example, >> Aug01 = [ ]; Problem 7 (Input a Column Vector). Create column vectors for each of the ticker symbols in Table 2.1 named IBM, MSFT and HPQ, respectively. For example, >> IBM = [194.84;194.19;194.53;190.04;188.56;187.93;187.82;189.09;188.42;187.53;185.79]; 5

12 Prices in August 2013 Date SPY Price AAPL Price IBM Price Aug Aug Aug Aug Aug Aug Aug Aug Aug Aug Aug Table 2.1: S&P 500 SPDR (SPY), Apple (AAPL) and IBM (IBM) price data for the first half of August Problem 8 (Input a Matrix). Create a matrix named prices containing Table 2.1. A matrix is just a column vector containing row vectors. For example,the first two days worth of data are >> prices = [ ; ]; Problem 9 (Construct a Matrix from Row and Column Data). Create a second matrix named pricesrow from the row vectors previously entered such that the results are identical to returns. For example, the first two days worth of data are >> pricessrow = [Aug01;Aug02]; Create a third matrix named pricescol from the 3 column vectors entered such that the results are identical to prices >> pricescol = [SPY APPL IBM]; Verify that all three matrices are identical by entering >> pricescol - prices >> pricesrow - prices and that all elements are 0. Problem 10 (Saving Data). Save all data to a file named myfirstmat. Next save only the returns matrix, prices, to a file named pricesonly. >> save myfirstmat >> save pricesonly prices Verify that your data was saved by clearing all variables using >> clear all and then loading the files using the load command. Problem 11 (Addition and Subtraction). Add the prices of the three series together. Add the prices in Aug01 to the prices of IBM. What happens? 6

13 Problem 12 (Multiplication). Multiply the price of IBM by 2. Problem 13 (Constructing portfolio returns). Set up a vector or portfolio weights ( 1 w = 3, 1 3, 1 ) 3 and compute the price of a portfolio with 1 share of each. Note: Division uses the slash operator (/). Problem 14 (Compute returns). Compute returns using >> returns = diff(log(prices)) which computes the first difference of the natural log of the prices. Mathematically this is r t = ln (P t ) ln (P t 1 ) = ln Additionally, extract returns for each name using >> SPYr = returns(:,1); >> AAPLr = returns(:,2); >> IBMr = returns(:,3) ( Pt P t 1 ) P t P t 1 1. Using the function mean, compute the mean of the three returns series one at a time. For example >> IBMmean = mean(ibmr) Next, compute the mean of the matrix of returns using >> retmean = mean(returns) What is the relationship between these two? Repeat this exercise for the standard deviation (std). Finally, compute the correlation of the matrix of returns (corr). Problem 15 (Summing all elements). Compute the sum of the columns of returns. How is this related to the mean computed in the previous step? Problem 16 (Maximum and Minimum Values). Compute the minimum and maximum values of the columns of returns using the min and max commands. Problem 17 (Rounding Up, Down and to the Closest Integer). Rounding up is handled by ceil, rounding down is handled by floor and rounding to the closest integer is handled by round. Try all of these commands on 100 times returns. For example, >> round(100*returns) Problem 18 (Element-by-Element Multiplication). Mathematical commands in MATLAB obey the rules of matrix algebra. This is why the portfolio returns could be easily computed as above. MATLAB also supports element-by-element operations using the dot operations,.* (multiplication) and./ (division). Multiply the returns of IBM and MSFT together using the dot operator. 7

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15 Lesson 3 Functions This lesson covers: Calling function with more than one input and output Calling functions when some inputs are not used Writing a custom function Begin by clearing all data from the workspace and loading the data in deciles.mat >> clear all >> load deciles This data set contains 2 years of data on the 10 CRSP decile portfolios from The variables are named decxx where XX ranges from 01 (smallest) to 10 (largest). Also included is a variable named date that contains the date in MATLAB date format. Problem 19 (Calling Functions). Functions were used in the previous lesson. Get used to calling functions by computing the mean, std, kurtosis, max, and mean of the 10 portfolios in deciles.mat. Also, explore the help available for calling functions using the help and doc commands. For example, >> help std >> doc std Problem 20 (Calling Functions with 2 Outputs). Some useful functions return 2 or more outputs. One example is sort which will sort a vector or matrix (column-by-column) and returns the sorted data in the first output and the indices of the elements in the second element. Sort the elements of dec01 and dec10. What is the index of the largest and the smallest elements? >> sort(dec10) >> [dec10sorted,dec10indices] = sort(dec10) Problem 21 (Calling Functions with 2 Inputs). Many functions take two or more inputs. Like outputs, the inputs are simply listed in order separated by commas. Use linsapce to produce a series of 11 points evenly spaced between 0 and 1. The help for linspace is listed below. 9

16 >> help linspace linspace Linearly spaced vector. linspace(x1, X2) generates a row vector of 100 linearly equally spaced points between X1 and X2. linspace(x1, X2, N) generates N points between X1 and X2. For N = 1, linspace returns X2. Class support for inputs X1,X2: float: double, single See also logspace, colon. Overloaded methods: distributed/linspace codistributor2dbc/linspace codistributor1d/linspace codistributed/linspace Reference page in Help browser doc linspace Problem 22 (Calling Functions with Empty Inputs and Outputs). On occasion it is necessary to call a function where some, but not all, inputs are required. One such example is std, which takes the data as its first argument, has a flag for a bias correction as its second argument, and takes the dimension as its third. Compute the standard deviation of each decile, then compute the standard deviation across the individual days (Hint: Down is dim 1, across is dim 2). >> help std std Standard deviation. For vectors, Y = std(x) returns the standard deviation. For matrices, Y is a row vector containing the standard deviation of each column. For N-D arrays, std operates along the first non-singleton dimension of X. std normalizes Y by (N-1), where N is the sample size. This is the sqrt of an unbiased estimator of the variance of the population from which X is drawn, as long as X consists of independent, identically distributed samples. Y = std(x,1) normalizes by N and produces the square root of the second moment of the sample about its mean. std(x,0) is the same as std(x). Y = std(x,flag,dim) takes the standard deviation along the dimension DIM of X. Pass in FLAG==0 to use the default normalization by N-1, or 1 to use N. Example: If X = [ ] then std(x,0,1) is [ ] and std(x,0,2) is [3.0 10

17 Class support for input X: float: double, single 2.0] See also cov, mean, var, median, corrcoef. Overloaded methods: fints/std ProbDistUnivParam/std timeseries/std Reference page in Help browser doc std Problem 23 (Writing a Custom Function). Custom functions will play an important role later in the course when estimating parameters. Construct a custom function that takes two arguments, µ and σ 2 and computes the likelihood function of a normal random variable ( ) f (x ; µ, σ 2 1 ) = exp (x µ)2 2πσ 2 2σ 2 Save this function as normal_likelihood.m and compute the likelihood of x = 0, µ = 0, σ 2 = 1. Exercises Exercise 2 (Custom Function). Write a function named summarystats that will take a single input, x, and return a matrix with 4 columns and as many rows as there were columns in the original data where the columns contain the mean, standard deviation, skewness and kurtosis of x. Exercise 3 (Custom Function). Extend your function in the final task of this lesson to allow for vector values of x, µ, and σ 2 (all the same size). Test your function with >> x=[-3;0;1]; >> mu = [-3;0;2]; >> sigma2=[9 4 1]; 11

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19 Lesson 4 Accessing Elements in Matrices This lesson covers: Accessing specific elements in vectors and matrices Accessing elements in a vector or matrix is a common task. To begin this lesson, clear the workspace, set up a two vectors, y and z, and a 5 5 matrix x using the following commands: >> clear all >> x=1:25; >> x=reshape(x,5,5) x = >> y = 1:5 y = >> z = (1:5) z = These vectors and matrix will make it easy to determine which elements are selected by a command. Problem 24 (Picking an Element out of a Matrix). Select the third element of all three, x, y and z. Next select the 11 th element of x. Finally, using double index notation, select the (1,3) and the (3,1) element of x such as in >> x(1,3) >> x(3,1) 13

20 Which index is rows and which index is columns? Does MATLAB count across first then down or down first then across? Problem 25 (Selecting Entire Rows). Select the 2 nd row of x using the colon (:) operator. Select the 2 nd column of z then y using the same syntax. What happens? Problem 26 (Selecting Entire Columns). Select the 2 nd column of x using the colon (:) operator. Problem 27 (Selecting Specific Rows or Columns). Select the 2 nd and 3 rd columns of x using the colon (:) operator. Select the 2 nd and 4 th rows of x. How can these be combined to select columns 2 and 3 and rows 2 and 4? Exercises Exercise 4 (Selecting Data by Date). Load the data in deciles.mat and construct a matrix containing all of the vectors. How can all returns on a particular day be selected? How can all returns for a particular decile be selected? 14

21 Lesson 5 Program Flow This lesson covers: for loops Nested loops Problem 28 (Basic For Loops). Construct a for loop to sum the numbers between 1 and N for any N. A for loop that does nothing can be written N = 10; for i=1:n end Problem 29 (Compute a compound return). The compound return on a bond that pays interest annually at rate r is given by T c r t = (1 + r ) = (1 + r ) T i =1 Use a for loop compute the total return for 100 invested today for 1,2,...,10 years. Store this variable in a 10 by 1 vector cr. Problem 30 (Simulate a random walk). (Pseudo) Normal random variables can be simulated using the command randn(n,m ) where N and M are the dimensions of the desired random numbers. Simulate 100 normals in a 100 by 1 vector and name the result e. Initialize a vector p containing zeros using the function zeros. Add the 1 st element of e to the first element of p. Use a for loop to simulate a process y i = y i 1 + e i When finished plot the results using >> plot(y) Problem 31 (Nested Loops). Begin by clearing the workspace and loading deciles.mat. Begin by adding 1 to the returns to produce gross returns. 1 Use two loops to loop both across time and across the 10 deciles to compute the total compound return. For example, if only interested in a single series, this 1 A gross return is the total the value in the current period of 1 invested in the previous period. A net return subtracts the original investment to produce the net gain or loss. 15

22 cr=zeros(size(dec01)); gr = 1 + dec01; cr(1) = 1+dec01(1); T=10; for t=2:t cr(t)=cr(t-1)*gr(t); end would compute the cumulative return. When finished, plot the cumulative returns using plot(cr). After finishing this assignment, have a look at doc cumsum and doc cumprod. Exercises Exercise 5. Simulate a 1000 by 10 matrix consisting of 10 standard random walks using both nested loops and cumsum. Plot the results. If you rerun the code, do the results change? Why? 16

23 Lesson 6 Logical Operators This lesson covers: Basic logical operators Compound operators Mixing logic and loops all and any Begin by clearing all data and loading the data in deciles.mat Problem 32 (Basic Logical Statements). For decile 1 and decile 10, count the number of elements that are < 0, 0 and exactly equal to 0. Next count the number of times that the returns in decile 5 are greater, in absolute value, that 2 times the standard deviation of the returns in that decile. Problem 33 (Compound Statements). Count the number of times that the returns in both decile 1 and decile 10 are negative. Next count the number of times that the returns in deciles 1 and 10 are both greater, in absolute value, that 2 times their respective standard deviations. Problem 34 (Logical Statements and for Loops). Use a for loop along with an if statement to simulate an asymmetric random walk of the form y i = y i 1 + e i + I [ei <0]e i where I [ei <0] is known as an indicator variable that takes the value 1 if the statement in brackets is true. Plot y. Problem 35 (Selecting Elements using Logical Statements). For decile 1 and decile 10, select the elements that are < 0, 0 and exactly equal to 0. Next select the elements where both deciles are less than 0. Problem 36 (Using find). Use find to select the index of the elements in decile 5 that are negative. Next, use the find command in its two output form to determine which elements of the decile return matrix are less than -2%. 17

24 Exercises Exercise 6 (all and any). Use all to determine the number of days where all of the decile returns were negative. Use any to compute the number of days with at least 1 negative return and with no negative returns (Hint: use negation ( )). 18

25 Lesson 7 Importing Data into MATLAB This lesson covers: Preparing data for import Importing data Converting dates Begin by clearing all data from the workspace. Problem 37 (Formatting Data in Excel for Import). Format the return data contained in excel.xls for import into MATLAB and save the file as excel_for_import.xls. The Excel file can be downloaded from Problem 38 (Importing Data). Import the file created in the previous step and save the data to excel_imported.mat. Problem 39 (Converting Dates). Convert the dates imported in the previous step using x2mdate. Exercises Exercise 7 (Practice). Getting data into and out of MATLAB is very important for your success in the computing portion of the course. Practice on the file excel_practice.xls which is available on the website, 19

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27 Lesson 8 Graphics This lesson covers: Basic plotting Editing plots Subplots Histograms Begin by clearing all data from the workspace and loading the data in hf.mat. This data set contains highfrequency price for IBM and MSFT on a single day and times in MATLAB format. Problem 40 (Basic Plotting). Plot the series labeled IBMprice which contains the price of IBM. Add a title and label the axes. Use the interactive tool to add markers and remove the line. Problem 41 (Subplot). Create a 2 by 1 subplot with the price of IBM in the top subplot and the price of MSFT in the bottom subplot. Problem 42 (Plot with Dates). Plot the price of IBM against the series IBMdate. Use datetick to reformat the x-axis. Problem 43 (Histogram). Produce a histogram of MSFT returns (Hint: you have to produce the Microsoft returns first). 21

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