BOOTCAMP Market and CPD Risk

BOOTCAMP MARKET AND CPD RISK

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MARKET AND COUNTERPARTY CAPITAL [175 HOURS]

Sln Topic Details
Module 1 - Risk Foundation
01 Coding in Python 

Data types, CRUD operations

If Else Statements & Loops

Numpy, Pandas, Matplotlib

Regression & Time Series in Python 

Monte Carlo Simulations in Python

02

y = f(x) thinking 

(Excel + Python)

 Taylor Series 

Sensitivity based approaches

Option Greeks

03

Risk Metrics

(Excel + Python)

Formulating VaR & ES (Parametric, Historical, Monte Carlo)

Calculation of VaR & ES for simple instruments (EQ, IR, Fx, Commodity)

Module 2 – Risk Aggregation 
04

Portfolio Mapping 

(Excel + Python)

Systematic VaR

Specific VaR

Factor Models & PCA 

05

Risk Mapping & Aggregation

(Excel + Python) 

Bond Portfolio 

Stock Portfolio

Option Portfolio

Module 3 – FRTB Model
06

Standardised Approach

(Excel + Python)

Delta, Vega, Curvature Charge 

Residual Risk add-on

Default Risk Charge 

07

Advanced Approach 

(Excel + Python)

Expected Shortfall 

Calibrations with stressed periods

NMRF Stress Capital

Default Risk Charge 

08

PnL Attribution & Backtesting 

(Excel + Python)

PL Attribution Tests

Backtesting 

09

Model Validation 

(Excel + Python)

Common checks in model validation 

Review of SR 11-7

Case studies from past 

 
Module 4 – Counterparty Credit Risk 
10

Exposure Modelling 

(Excel + Python)

EE, EPE, EEPE in Python 

Forwards (EQ, IR, Fx)

Swaps (IRS, CCS)

Options (EQ, Caplets)

11

EAD Modelling 

(Excel + Python)

Standardised Approach - CCR

Internal Models Method

12

CVA Capital Charge

(Excel + Python) 

Standardised Approach

Advanced Approach 

13

XVA toolbox

(Excel + Python)

End to end project in python calculating

BCVA, FVA, ColVA, MVA, KVA 

   
ABOUT THE TRAINER

Satya is an IIT and IIM alumni with 8+ years of total work experience spanning across Financial Risk consulting and project management and strategy. Worked as SME and Lead in Various finance, risk, regulatory engagements and complex data migraflon project. Adept in BASEL, FRTB capital calculations, model development and machine learning.

Ans. 1. Anyone with finance background like having studied some level of CFA FRM or actuaries can join this program.

Ans.2. Maths Primers and Python Primers have been included in the program, so no previous experience is expected.

Ans 3. This course is quite long & comprehensive only because we have covered the entire curriculum in 3 parts – theory discussion, visualisations in excel, practical implementation through hands-on session in excel & python

Ans.4. To get certificates you need to complete all topic wise assignments, master project and pass the Final exam.

Ans.5. You can take either 1 year access or lifetime access. Please note that lifetime access is chargeable extra

Ans.6 With this website we have integrated a customized P2T player that will allow you to play encrypted classes. There are no limitations on the number of views. Also the software is compatible with Windows, Mac, Android or iPhone

Ans.7. To interact with the trainer we have a dedicated forum ‘D-forum’. Any questions asked on D-forum are expected to be replied within 24 hours by trainers and team of moderators & experts.

Ans. 8. Presently we are conducting exams in Aug mid and Jan mid. You can choose any of the cohort. In case you are not able to pass the exam in one go, you can re-book at a nominal charge

Ans.9. Every class is supported by One note files, Excel sheets & Python notebooks, Assignments and Quizzes, all these are available in the course section only.

Ans. 10. You get Letter of Recommendation physically delivered to you within 60 days of passing the exam. LOR’s also mention the chosen specialisation with the project details.

" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen>

 

MARKET AND COUNTERPARTY CAPITAL [175 HOURS]

Sln Topic Details
Module 1 - Risk Foundation
01 Coding in Python 

Data types, CRUD operations

If Else Statements & Loops

Numpy, Pandas, Matplotlib

Regression & Time Series in Python 

Monte Carlo Simulations in Python

02

y = f(x) thinking 

(Excel + Python)

 Taylor Series 

Sensitivity based approaches

Option Greeks

03

Risk Metrics

(Excel + Python)

Formulating VaR & ES (Parametric, Historical, Monte Carlo)

Calculation of VaR & ES for simple instruments (EQ, IR, Fx, Commodity)

Module 2 – Risk Aggregation 
04

Portfolio Mapping 

(Excel + Python)

Systematic VaR

Specific VaR

Factor Models & PCA 

05

Risk Mapping & Aggregation

(Excel + Python) 

Bond Portfolio 

Stock Portfolio

Option Portfolio

Module 3 – FRTB Model
06

Standardised Approach

(Excel + Python)

Delta, Vega, Curvature Charge 

Residual Risk add-on

Default Risk Charge 

07

Advanced Approach 

(Excel + Python)

Expected Shortfall 

Calibrations with stressed periods

NMRF Stress Capital

Default Risk Charge 

08

PnL Attribution & Backtesting 

(Excel + Python)

PL Attribution Tests

Backtesting 

09

Model Validation 

(Excel + Python)

Common checks in model validation 

Review of SR 11-7

Case studies from past 

 
Module 4 – Counterparty Credit Risk 
10

Exposure Modelling 

(Excel + Python)

EE, EPE, EEPE in Python 

Forwards (EQ, IR, Fx)

Swaps (IRS, CCS)

Options (EQ, Caplets)

11

EAD Modelling 

(Excel + Python)

Standardised Approach - CCR

Internal Models Method

12

CVA Capital Charge

(Excel + Python) 

Standardised Approach

Advanced Approach 

13

XVA toolbox

(Excel + Python)

End to end project in python calculating

BCVA, FVA, ColVA, MVA, KVA 

   

Satya is an IIT and IIM alumni with 8+ years of total work experience spanning across Financial Risk consulting and project management and strategy. Worked as SME and Lead in Various finance, risk, regulatory engagements and complex data migraflon project. Adept in BASEL, FRTB capital calculations, model development and machine learning.

Ans. 1. Anyone with finance background like having studied some level of CFA FRM or actuaries can join this program.

Ans.2. Maths Primers and Python Primers have been included in the program, so no previous experience is expected.

Ans 3. This course is quite long & comprehensive only because we have covered the entire curriculum in 3 parts – theory discussion, visualisations in excel, practical implementation through hands-on session in excel & python

Ans.4. To get certificates you need to complete all topic wise assignments, master project and pass the Final exam.

Ans.5. You can take either 1 year access or lifetime access. Please note that lifetime access is chargeable extra

Ans.6 With this website we have integrated a customized P2T player that will allow you to play encrypted classes. There are no limitations on the number of views. Also the software is compatible with Windows, Mac, Android or iPhone

Ans.7. To interact with the trainer we have a dedicated forum ‘D-forum’. Any questions asked on D-forum are expected to be replied within 24 hours by trainers and team of moderators & experts.

Ans. 8. Presently we are conducting exams in Aug mid and Jan mid. You can choose any of the cohort. In case you are not able to pass the exam in one go, you can re-book at a nominal charge

Ans.9. Every class is supported by One note files, Excel sheets & Python notebooks, Assignments and Quizzes, all these are available in the course section only.

Ans. 10. You get Letter of Recommendation physically delivered to you within 60 days of passing the exam. LOR’s also mention the chosen specialisation with the project details.