Credit Stocks Derivatives Finance CFA FRM Course: Free Classes ...

50 hours course in MATLAB for Finance

By Shivgan Joshi (shivgan3@gmail.com)

Course is divided into 15 classes:

1. Intro to MATLAB; comparison with SAS, R and other tools; jobs

2. Functions, data handling, Array, structures,

3. Advanced data manipulation, graphics display

4. Financial applications: FI, portfolio and Fin Time series

5. Financial terms that are used

6. Black schools, Ito, other quant finance theories

7. Financial time series terms and data prep

8. Financial time series advanced functions

9. FRM 2 book 1 ( risk )

10. FRM 2 book 2 (credit risk)

11. Portfolio optimization and analysis of measures

12. Monte Carlo simulation

13. Technical Analysis, Algorithmic trading and MATLAB

14. CMT and Algo trading

15. Revision, practice and doubt session

Class one agenda:

Utility of Course

How it takes your beyond excel

Comparison of MATALB SAS R Excel/VBA

1. As far as the comparison goes, R vs MATLAB, MATLAB is much easier and the only reason people do R in west is because R is free and MATLAB is very expensive.

2. As per my knowledge R and SAS are not so much user friendly, although when it comes to hardcore data handling SAS is much much better. MATLAB is good for easier applications.

Three job profiles:

1. Bond spreads, CDS, fixed income etc (M)

2. VAR, PoD, bond portfolio, companies bond, trading data and VAR for that, etc (G)

3. Data cleaning for Time series, other data cleaning and optimizations (E)

Class 2

Matrix, types of data,

1. Types of array / matrix / data types / vector arrays etc

2. Reducing and selecting of Matrix

3. Looping for data handing in Excel

4. Movement and arrays of data

5. Data management or data cleaning or data optimization skills used in matlab

6. Loop for data correction like addressing blank or data types management

7. Data cleaning, data modifications, data arrays, struct, rating matrix, selection of elements from rating matrix, banks internal rating and pod computations, post that you made

Struct http://www.mathworks.in/help/techdoc/ref/struct.html

1. For those who have not done Programming before the logical flow like For statement becomes the first Hurdle

2. Regression using MATLAB

3. Symbolic computations

4. Making Chart: Polyval(c,x) to make the long elements that can be then used for making chart

5. Different way to make different type of matrix, like equal, incremental etc

6. Matrix division vs Element by element division

Class three

1. There was array handing, and how to manage data for Quant Finance

2. Preparing data for final analysis for: Algo trading & VAR computations

3. Reading Data from SQL Database and linking the system (advanced and out of scope), MATLAB Database toolbox

4. Making Chart: Polyval(c,x) to make the long elements that can be then used for making chart

Book Recommended:

1. MATLAB Basics and Beyond; This book has lot of graphic and graphics and data type forms.

2. MATLAB Primer

Class four:

Five area of MATLAB you need to master

1. StatisticalToolbox

2. Symbolic computation toolbox

3. Fixed income

4. Econometrics (Monte Carlo)

5. Derivatives

Class 5

Financial terms used Basics of all terms

1. Black Scholes, Monet Carlo, Stochastic Calculus, Greeks, Decision Tree, Regression

2. Structured Financial Products:, CDS, CDO, MBS (Fixed income from CFA L2/FRM L2)

Generic Knowledge about the industry needed:

1. Data -- Inter-phasing -- Output

2. Spreads changing

3. Bank Rating Consumer

4. Shorting CDS

5. Causes and Role of Goldman on Greece Crisis

Class six FTS:

Time Series terms:

1. Box Cox transformation method

2. Ito process

3. ARCH GARCH

4. Stochastic Volatility

Class 7

1. Normalizing and making data relevant by Data cleaning (playing with matrix) example for financial times series

Class 9 & 10

Statistical modelling, variance-covariance modelling, value at risk modelling, regular risk reporting (hot spot reports, concentration reports), risk assessment and style analysis of money managers, term structure modelling, rich cheap analysis

FRM L2 library: PD, LGD, Downgrade, Credit Rating Methodologies

FRM Level 2 terms in MATLAB Stat toolbox:

1. Copula

2. Modelling Tail Data with the Generalized Pareto Distribution

3. Modelling Data with the Generalized Extreme Value Distribution

4. Bayesian Analysis for a Logistic Regression Model

5. Weibull distribution

Class 11

1. Scenario & Sensitivity Analysis, Portfolio Optimization, Asset liability management

Class 12

Monte Carlo

Class 13 & 14

Algorithmic trading

1. Trading MATLAB and importance of Visualization

2. Commodity trading in MATLAB

Class 15

Revision

References:

References
http://www.mathworks.in/help/techdoc/ref/struct.html
http://www.mathworks.in/help/techdoc/ref/size.html
http://www.mathworks.in/help/techdoc/ref/f16-42340.html
http://www.mathworks.in/products/matlab/demos.html?file=/products/demos/shipping/matlab/nddemo.html

Source: http://stockcreditfinancecfa.blogspot.com/2012/07/50-hours-course-in-matlab-for-finance.html

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