BOOTCAMP Quant Finance

The QUANT FINANCE includes four all-encompassing, mutually exclusive, core learning courses that cover all of the topics of the BootCamp Lab, plus several refresher topics for preparation purposes.

BOOTCAMP QUANT FINANCE

Topic
1 Class 1 - Functions   39 Class 31 - Discrete to Continuous Models and Intro to Stochastic Calculus
2 Class 2 - Functions Contd   40 Class 32 - Brownian Motion and Ito Calculus with Excel
3 Hands-on session1 - Functions   41 Class 33 - Expectation Pricing - Deriving BSM PDE in Continuous Settings
      42 Class 34 - Options Greeks «
4 Class 3 - Intro to Limits      
5 Class 4 - Differential Calculus   43 Class 35 - Monte Carlo Methods IV - Exotic Option Pricing
      44 Hands-on session7 - MCS Exotic Option Pricing
6 Assignment 1 Functions - Solution Class   45 Class 36 - Monte Carlo Methods V - Pricing the Bermudan Style Options
7 Assignment 2 Limits & Diff - Solution Class      
      46 Class 37 - Finite Difference Method of Option Pricing - I
8 Class 5 - Trigonometry   47 Class 38 - Finite Difference Method of Option Pricing - II
      48 Class 39 - Finite Difference Method - III : Implied Schemes & Fourier Stability Analysis
9 Class 6 - Taylor Series      
10 Class 7 - Integration   49 Class 40 - Markov Models : Stocastic Process & Markov Property
11 Class 8 - Numerical Techniques   50 Class 41 - Markov Chains I
12 Class 9 - Gradient Descent   51 Class 42 - Markov Chains II
13 Hands-on session2 - All Previous Calculus Topics   52 Class 43 - Time Homogeneous Two State Markov Model
      53 Class 44 - Time Homogeneous Multi-State Markov Jump I : Kolmogorov Forward
14 Class 10 - Differential Equation (Part-1) : 1st Order DE & Complex Number   54 Class 45 - Time Homogeneous Multi-state Markov Jump II : Kolmogorov Backward
15 Class 11 - Differential Equation (Part-2) : 2nd Order DE   55 Class 46 - Time Homogeneous Markov Model : Parameter Estimation & Credit Rating Migration
16 Class 12 - Multivariate Functions & Partial Differential Equation(PDE)   56 Class 47 - Time Inhomogeneous Markov Jump
         
17 Class 13 - Linear Algebra (Part-1)   57 Class 48 - Overview of Risk modelling
18 Class 14 - Matrix Algebra (Part-2)   58 Class 49 - Value at Risk I
      59 Class 50 - Value at Risk II
19 Class 15 - Probability Part-1 : Distributions   60 Class 51 - Value at Risk III
20 Class 16 - Probability Part-2 : Distributions   61 "Class 52 - Value at Risk IV : Volatility Models - EWMA ARCH GARCH
21 Class 17 - Probability Part-3 : Normal vs Lognormal Distributions   62 Class 53 - Value at Risk V : Advance GARCH Models
22 Class 18 - Probability Part-4 : Beta & Gamma Dist and Parameter Estimation   63 Class 54 - Value at Risk VI : Historical VaR and EVT and MVT
23 Hands-on session3 - Parameter Estimation   64 Class 55 - Value at Risk VII : Greeks & Option Portfolio
      65 Class 56 - Value at Risk VIII : Properties of Risk Measure and ES
24 Class 19 - Moments   66 Class 57 - Value at Risk IX : PCA
25 Class 20 - Joint Probability   67 Class 58 - Value at Risk X : Backtesting and PLA
26 Class 21 - Copula I - Theory      
27 Class 22 - Copula II   68 Class 59 - Introduction to Interest Rate Asset Class
28 Class 23 - Copula III   69 Class 60 - Interest Rate Asset Class : FRA & IRS
29 Hands-on session4 - Copula I   70 Class 61 - Interest Rate Term Structure : Basics
30 Hands-on session5 - Copula II   71 Class 62 - Short Rate Model & Bond Pricing I
      72 Class 63 - Short Rate Model & Bond Pricing II : Vasicek Model
31 Class 24 - Monte Carlo Methods I   73 "Class 64 - Short Rate Model & Bond Pricing III : CIR ModelHo & Lee Model and Calibration"
32 Class 25 - Monte Carlo Methods II   74 "Class 65 - Hull & White-1 Multi-Factor-Models & HJM Framework "
33 Class 26 - Monte Carlo Methods III   75 Class 66 - Application of HJM & PCA
34 Hands-on session6 - MCS Variance Reduction   76 Class 67 - Valuation of Interest Rate Options : Caplet and Swaption
      77 Class 68 - Option Embedded Bonds
35 Class 27 - General Overview of Financial Instruments & Risks      
36 Class 28 - Discrete Models I   78 Class 69 - CCR : Introduction
37 Class 29 - Option Basics   79 Class 70 - CCR : Margin and Collateral
38 Class 30 - Discrete Models II   80 Class 71 - CCR : Margin Calculation
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.

Topic
1 Class 1 - Functions   39 Class 31 - Discrete to Continuous Models and Intro to Stochastic Calculus
2 Class 2 - Functions Contd   40 Class 32 - Brownian Motion and Ito Calculus with Excel
3 Hands-on session1 - Functions   41 Class 33 - Expectation Pricing - Deriving BSM PDE in Continuous Settings
      42 Class 34 - Options Greeks «
4 Class 3 - Intro to Limits      
5 Class 4 - Differential Calculus   43 Class 35 - Monte Carlo Methods IV - Exotic Option Pricing
      44 Hands-on session7 - MCS Exotic Option Pricing
6 Assignment 1 Functions - Solution Class   45 Class 36 - Monte Carlo Methods V - Pricing the Bermudan Style Options
7 Assignment 2 Limits & Diff - Solution Class      
      46 Class 37 - Finite Difference Method of Option Pricing - I
8 Class 5 - Trigonometry   47 Class 38 - Finite Difference Method of Option Pricing - II
      48 Class 39 - Finite Difference Method - III : Implied Schemes & Fourier Stability Analysis
9 Class 6 - Taylor Series      
10 Class 7 - Integration   49 Class 40 - Markov Models : Stocastic Process & Markov Property
11 Class 8 - Numerical Techniques   50 Class 41 - Markov Chains I
12 Class 9 - Gradient Descent   51 Class 42 - Markov Chains II
13 Hands-on session2 - All Previous Calculus Topics   52 Class 43 - Time Homogeneous Two State Markov Model
      53 Class 44 - Time Homogeneous Multi-State Markov Jump I : Kolmogorov Forward
14 Class 10 - Differential Equation (Part-1) : 1st Order DE & Complex Number   54 Class 45 - Time Homogeneous Multi-state Markov Jump II : Kolmogorov Backward
15 Class 11 - Differential Equation (Part-2) : 2nd Order DE   55 Class 46 - Time Homogeneous Markov Model : Parameter Estimation & Credit Rating Migration
16 Class 12 - Multivariate Functions & Partial Differential Equation(PDE)   56 Class 47 - Time Inhomogeneous Markov Jump
         
17 Class 13 - Linear Algebra (Part-1)   57 Class 48 - Overview of Risk modelling
18 Class 14 - Matrix Algebra (Part-2)   58 Class 49 - Value at Risk I
      59 Class 50 - Value at Risk II
19 Class 15 - Probability Part-1 : Distributions   60 Class 51 - Value at Risk III
20 Class 16 - Probability Part-2 : Distributions   61 "Class 52 - Value at Risk IV : Volatility Models - EWMA ARCH GARCH
21 Class 17 - Probability Part-3 : Normal vs Lognormal Distributions   62 Class 53 - Value at Risk V : Advance GARCH Models
22 Class 18 - Probability Part-4 : Beta & Gamma Dist and Parameter Estimation   63 Class 54 - Value at Risk VI : Historical VaR and EVT and MVT
23 Hands-on session3 - Parameter Estimation   64 Class 55 - Value at Risk VII : Greeks & Option Portfolio
      65 Class 56 - Value at Risk VIII : Properties of Risk Measure and ES
24 Class 19 - Moments   66 Class 57 - Value at Risk IX : PCA
25 Class 20 - Joint Probability   67 Class 58 - Value at Risk X : Backtesting and PLA
26 Class 21 - Copula I - Theory      
27 Class 22 - Copula II   68 Class 59 - Introduction to Interest Rate Asset Class
28 Class 23 - Copula III   69 Class 60 - Interest Rate Asset Class : FRA & IRS
29 Hands-on session4 - Copula I   70 Class 61 - Interest Rate Term Structure : Basics
30 Hands-on session5 - Copula II   71 Class 62 - Short Rate Model & Bond Pricing I
      72 Class 63 - Short Rate Model & Bond Pricing II : Vasicek Model
31 Class 24 - Monte Carlo Methods I   73 "Class 64 - Short Rate Model & Bond Pricing III : CIR ModelHo & Lee Model and Calibration"
32 Class 25 - Monte Carlo Methods II   74 "Class 65 - Hull & White-1 Multi-Factor-Models & HJM Framework "
33 Class 26 - Monte Carlo Methods III   75 Class 66 - Application of HJM & PCA
34 Hands-on session6 - MCS Variance Reduction   76 Class 67 - Valuation of Interest Rate Options : Caplet and Swaption
      77 Class 68 - Option Embedded Bonds
35 Class 27 - General Overview of Financial Instruments & Risks      
36 Class 28 - Discrete Models I   78 Class 69 - CCR : Introduction
37 Class 29 - Option Basics   79 Class 70 - CCR : Margin and Collateral
38 Class 30 - Discrete Models II   80 Class 71 - CCR : Margin Calculation

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.