Saturday, July 21, 2012

20 hours online course on MATLAB for Financial Engineering / Quants

20 Hours Course On MATLAB For Financial Engineering @Wiziq.com


Class TopicDuration
1
Introduction To Programming in MATLAB
2 Hours
2
Introduction To Quant Corporate Finance
2 Hours
3
Data Handling & Visualization in MATLAB
2 Hours
4
Five MATLAB Toolboxes for Finance
2 Hours
5
Fixed Income
2 Hours
6
Financial Time Series
2 Hours
7
Distributions & VAR
2 Hours
8
Portfolio Optimization
2 Hours
9
Black Scholes & Monte Carlo
2 Hours
10
Revision
2 Hours


Course highlights:
  • Useful for financial analysts, accountants & others to perform analysis.
  • Requires no programming knowledge - if you use word, you can use MATLAB.
  • Demo class can be registered as per convenience.
  • Course consists of 35-40% live classes.
  • Scheduling of doubt clearing class as per convenience.

Key points about the course:
  1. Requires absolutely no knowledge of programming.
  2. Highly flexible and tailored as per needs of individual.
  3. Sensitization on derivative, quant, fixed income, portfolio, VAR modelling.
  4. Gives introduction to all features of MATLAB in Finance.
  5. Provide introduction about all Quantitative roles in Finance.
  6. Helpful for passing FRM, CFA, BAT exams.
  7. Prepares for Master level studies in Finance or career change.
  8. Right mix of data handling, scripting, mathematical skills.
  9. Helpful for technical analysis.
  10. Contains right blend of learning and practice (Ratio 6:4).

Course Link:

To know more about the platform, you can also join our free course on wizIQ:

http://www.wiziq.com/course/708-CFA-Classes-Discussions-Study-Group-for-Self-Prep


Course agenda in detail:

Class 1:

  • Utility of course.
  • How it takes you beyond excel.
  • Comparison of MATLAB-SAS-R-Excel/VBA.

Class 2:
  • Matrix, types of data.
  • Types of array/matrix/data types/vector arrays etc.
  • Reducing and selecting of Matrix.
  • Looping for data handing in Excel.
  • Movement and arrays of data.
  • Data management or data cleaning or data optimization skills used in MATLAB.
  • Loop for data correction like addressing blank or data types management.
  • Data cleaning, data modifications, data arrays, struct, rating matrix, selection of elements from rating matrix.
Class 3:
  • Array handling & how to manage Data for Quant Finance.
  • Preparing Data For Final Analysis of Algorithmic Trading & VAR Computations.
  • Reading Data from SQL Database & Linking the System.
  • MATLAB Database Toolbox.
  • Making Chart.
Class 4:
  • Statistical Toolbox.
  • Symbolic computation toolbox.
  • Fixed income. 
  • Econometrics (Monte Carlo).
  • Derivatives.
Class 5:
  • Financial Terms Used.
  • Basics of all Terms.
  • Generic Knowledge About the industry - Spreads Changing, Bank Rating Consumer, Shorting CDS, Cause & Role of Goldman or Greece Crisis.
Class 6:
  • Box Cox Transformation Method.
  • Ito Process.
  • ARCH GARCH.
  • Stochastic Volatility. 
Class 7:

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

Class 8:

  • Statistical Modelling.
  • VAR Modelling.
  • Risk Assessment.
  • FRM Level 2 Library.
  • FRM Level 2 Terms in MATLAB.
  • Statistics Toolbox.
  • Copula.
Class 9:
  • Scenario & Sensitivity Analysis.
  • Portfolio Optimization.
  • Asset Liability Management.
  • Monte Carlo.
  • Algorithmic Trading.
Class 10:

Revision Class - Thorough Review of studied areas & doubt clearing session.


Books recommended:
  • MATLAB Basics and Beyond (This book has lot of graphics and data type forms).
  • MATLAB Primer.
Topics for Advanced MATLAB:
  • Functions overloading.
  • Random generation.
  • Matrix manipulation.
  • Advanced indexing.
  • Dimension expansion.
  • User input.
  • Inline functions.
  • Newton Raphson.
  • Call Function input.
  • Call Function.
  • Array Slicing.
  • Mesh grids.
  • Sums & cumulative products.
  • Loop: manipulate/do while vs. while/switch cases, while loop, when to use which.


MATLAB CFA overlap:
  • Fixed Income (80%)
  • Derivatives (80%)
  • Quant (100%)
  • Portfolio (70%)

Youtube Videos:




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/demo.html




Uploaded by Shivgan on WizIQ Tutorials



Links To some of the Recordings:



Contact Us

Course Teacher: Shivgan Joshi (shivgan@qcfinance.in/shivgan3@gmail.com).

Course Manager: Arpit (arpit@qcfinance.in).



ONE ON ONE CLASSES ALSO AVAILABLE ON REQUEST.



One on One Customized Training:
qcfinance.in believes in personalized touch so that our clients are completely satisfied with our service. In this regard, we offer One on One Customized Training to our clients.
These Trainings are provided on request by our clients & are customized according to their individual needs.
The course structure & timings for these training are highly flexible, classes are scheduled as per the convenience of our clients.
We have four to five teachers specialized in different areas of MATLAB, and our teachers can be reached on flexible timings. Our teachers have also recorded their videos which are uploaded on the course.

Contact Us for More details: info@qcfinance.in



Modules Under Development:


Monte Carlo methods for Equity Projections (MATLAB for Equity Research in Investment Banking), where the main focus is on revenue growth and then growing other things in a custom way. Other things that increases the complexity of models is decisions such as (what to do with extra cash: repo, dividend  debt reduction, etc). Robust environment of MATLAB with lots of predefined functions help the analysis very easy. 

http://www.mathworks.in/help/finance/portsim.html.


Step 1: Returns.

Step 2: Correlations.
Step 3: Random number.
Step 4: Running simulation.


Quantitative Game theory applications in MATLAB, where the search is for Nash Equilibrium and finding out the best strategy that work given what would happen at each path. The area is niche and involves cooperative and non cooperative games. 


13 comments:

  1. Toolbox class is easy

    ReplyDelete
  2. http://www.learneconometrics.com/pdf/MCstata/MCstata.pdf

    ReplyDelete
  3. Please start course on Quant Equity. This could inculude quant index, beta computations, different style of index, equity derivatives, importance of volume traded, value grwoth differences, emerging and developed markets relations, how idnex are made, using ric ticker, etc equity database research, etc.


    Corproate quant fiance will be another important area.

    ReplyDelete
  4. This comment has been removed by a blog administrator.

    ReplyDelete
  5. Symbolic computation, database, optimization, statistical, other. I tried to put my hands on polynomials, optimization, integration and differentiation .

    Is this the class composition for 5 and 6? How to study that? are there presentations online?

    ReplyDelete
  6. Portfolio Optz is common for both so you can make a viode that will cover both, part 1 common part 2implemenation on matlab..

    Black Sholes and Monte Carlo could be make comon for both on the ground of FM and derivaitives optiosn.

    ReplyDelete
  7. link all videos to the playlist and embed the play list

    use one page or array fiel to mvoe aehad

    ReplyDelete
  8. More things on simplest of simplest program Arpit.
    Stat, Econometrics, Symbolic and Optz.
    Data structure programs
    Looping programs.
    inputing outputing value manually from matlab.

    ReplyDelete
  9. questiosn on indexing.

    ReplyDelete
  10. study gie part 2 for all tings that are common in all toolbix.

    ReplyDelete
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