BOOTCAMP Market and Counterparty Capital

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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/CA/CFA/FRM/Engineering Background can join this program. Basic knowledge of statistics is recommended but not compulsory

Ans 2. Market risk and counterparty capital charge program focuses on regulatory specific modelling and doesn't require advanced level of math's. Also the entire program is taught in Excel & Python to facilitate easy understanding of all models.

Ans 3. It is a 100% practical program with dozens of case studies, spreadsheet models & python codes. The approach of delivering the concepts is application based to make you a right fit for market risk consulting.

Ans 4. To get certificates you need to complete all topic wise assignments, final project and pass the MCQ based 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. You can schedule your exams anytime after course completion but before the expiration of validity.

Ans 9. Every class is supported by one note files, excel sheet, python files and reading material. All these are available in the course section only.

Ans 10. Letter of Recommendation is virtually delivered within 60 days of passing the exam. LOR’s also mention the details of the final project completed to avail the certificate.

" 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/CA/CFA/FRM/Engineering Background can join this program. Basic knowledge of statistics is recommended but not compulsory

Ans 2. Market risk and counterparty capital charge program focuses on regulatory specific modelling and doesn't require advanced level of math's. Also the entire program is taught in Excel & Python to facilitate easy understanding of all models.

Ans 3. It is a 100% practical program with dozens of case studies, spreadsheet models & python codes. The approach of delivering the concepts is application based to make you a right fit for market risk consulting.

Ans 4. To get certificates you need to complete all topic wise assignments, final project and pass the MCQ based 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. You can schedule your exams anytime after course completion but before the expiration of validity.

Ans 9. Every class is supported by one note files, excel sheet, python files and reading material. All these are available in the course section only.

Ans 10. Letter of Recommendation is virtually delivered within 60 days of passing the exam. LOR’s also mention the details of the final project completed to avail the certificate.