Try it for Free

Try Our Free Course

No Signup, No Email Required

  • Calculating Forward Prices and Forward Rates in EXCEL
  • Derivatives Terminology Crash Course

  • Duration Convexity- Example
  • Valuing Options- BlackScholes Examples
  • FRM MBA Course – Value at risk dataset

Building Financial Models – Introduction

Building Financial Models – Introduction

Description: An introduction to financial modeling course designed for anyone with an interest in building financial models. The first session reviews the course plan, introduces the concept of design for financial models and the three case studies we will use in the course

Understanding N(d1) & N(d2) – Free Course

Black Scholes, N(d1) and N(d2), Monte Carlo Simulator – Theory and Model Review

Description: The risk training course for understanding risk adjusted probabilities of the Black Scholes equation, N(d1) and N(d2), begins with a power point presentation of the theory setting the foundation for appreciating the difference between N(d1) and N(d2). We start with the Black Scholes European call option formula and move on to primary elements of the underlying process behind the generator function for stock prices, drift and diffusion. We address the concept of risk neutrality and conduct various thought experiments around drift and diffusion to understand their impacts on the plot of stock prices over time. We present three interpretations of the intuition behind the Black Scholes European call option formula and then given a preliminary overview of how to create a Monte Carlo simulation model of the Black Scholes solution in Excel.

Monte Carlo Simulator – Basic Model Walkthrough

Description:In this part we move from our the theory presented in the power point presentation earlier to the practical application of the understanding the difference between N(d1) and N(d2). We given an overview of the Monte Carlo Simulation model built discussing the input cells including the price path generated, the results from the simulation model and the Black Scholes formula, and the results warehouse where results of 30 simulated runs of the model are stored. A brief review of how the simulator can be used to generate and store results and how results could be updated by running multiple iterations.

Understanding N(d1) and N(d2) and Option Exercise using Monte Carlo

Description: After having presented the theory behind the process and a general overview of the various elements of the Monte Carlo simulation model together with the procedure for running the model and updating results in our previous finance videos, we now give a thorough walkthrough of the EXCEL sheet of our Monte Carlo simulation model. We begin with how the results of the payment of exercise price and contingent receipt of stock components of the closed form Black Scholes European call option formula are calculated in the model. Each calculation cell is described in detail, stating precedent and dependent cells, to help with an understanding of:

  • How the model is built,
  • Difference between N(d1) & N(d2),
  • Calculation of the call option value by using Black Scholes formula within the Monte Carlo simulation approach

Pitching for Startups

Pitching for Startups

Description: An introduction to a pitching framework for startups. While elements of a pitch can be classified as an art, there is a process to putting a good effective pitch together. Jawwad Farid walks through ground rules of presenting ideas to investors and making effective sales pitches to customers. How do you get investors and business plan competition judges to take you seriously and make your pitch real and credible? What are some of the things you can do to work with your audience to leave a strong and lasting impression?

Pitching for Startups:
Lesson 2 – Painting your Mona Lisa

Description: Painting your Mona Lisa – Using the customer development framework to build customer personas. The problem is that a large number of pitches start with a customer profile as empty of details as stick figures. Who is this guy, where is he from, what does he feel, how do I find him, what do I say to him, will he bleed when I cut him? Technically speaking what you really want when it comes to your customers profile is to draw a Mona Lisa. Ideally a restored edition that is rich with colors and details. While you are still missing data but at least there is a face in front of you that you can now work with. You can now add details about demographics and profiles (age, education, job role, experiences, social preferences, reading interests, family size, ethnicity, political views, and personal tastes) and any other piece that helps you understand what drives this individual.

Pitching for Startups: Building your
Roadmap to credibility

Description: Your roadmap to credibility is the list of questions you have to ask as well as answer so that your business model can get to the next stage. Starting up, we need a framework or a mind map to build a task list. Jawwad walk through a list of steps you need to follow to make your startup and your pitch real.

Pitching for starting up: Competitive Advantage and competition

Description: In our fourth session we review competition and competitive advantage. Teams are often confused about what is a true competitive advantage. We discuss scale, technology, intellectual property and captive customers. We also discuss the right and the most likely advantage for your startup when you have capital and when you don’t. And link that advantage to your understanding of customers.


Pitching for Startups – Bringing it all together

Description: In our two part closing session we try and put together everything introduced so far in a complete pitch for a new idea or product. There is a some over lap with the Pitching Case Studies session on this channel.

Pitching for startups – Closing session

Description: In the final session on pitching for startup, Jawwad wraps up the rules and guidelines covered in our six part series by walking through a sample pitch for banking technology.


Following is a list of all the premium courses available under the given categories:

Asset Liability Management
ALM – Crash Course
ALM – Crash Course – EXCEL Examples
Asset Liability Management (ALM) Crash Course – Package
ALM and Capital Adequacy
Building Maturity & Liquidity Profiles for Deposits and Advances
Calibration of CIR Model – EXCEL Example
Duration Convexity – EXCEL Example
Heath Jarrow Merton – HJM 3 – Factor Interest Rate Model
Heath Jarrow Merton (HJM) Interest Rate Model – Package
Principal Component Analysis – PCA – US Treasury Yield Rates
How to construct a Black Derman Toy Model in EXCEL
Black Derman Toy Model Construction – EXCEL Example
Black-Derman-Toy (BDT) Interest Rate Model – Package
How to utilize results of a Black Derman Toy Model
How to utilize results of a Black Derman Toy Model – EXCEL Example
Interest Rate Simulation Crash Course – Package
Interest Rate Simulation Crash Course
Quant Crash Course
Capital Adequacy
Basel III – Liquidity Framework
Basel & ICAAP – Package
ICAAP Sample Report Template & Executive Summary
ICAAP – Credit EXCEL Example
ICAAP – Overview & Core Concepts
Understanding Stress Testing
Coporate Finance
Credit Analysis – First Course
Credit Analysis & Credit Process – Package
Credit Analysis – Financial Institution
Credit Analysis – Financial Institution – EXCEL Example
Corporate Finance – First Course – Includes case study
Credit Process
Introduction to Financial Modelling
Ratio Analysis
Derivative Pricing
Derivative Pricing – Binomial Trees – Efficient Approach
Derivative Pricing – Binomial Trees EXCEL Example
Derivatives Pricing – Package
Derivative Products
Derivative Products – Package
Forward Prices, Forward Rates and Forward Rate Agreements (FRA) – EXCEL Example
Derivatives Terminology Crash Course
Forward Prices, Spot Rates & Forward Rates, Yield-to-Maturity, Forward Rate Agreements (FRA), Forward Contracts and Forward Exchange Rates – PDF
Forward Prices and Forward Rates – Calculation reference & detailed examples
Monte Carlo Simulation – Equity – Exampl
Monte Carlo Simulation – Commodity – Example
Monte Carlo Simulation – Currency – Example
Monte Carlo Simulator with Historical Returns
Monte Carlo Simulation – Package
Option Pricing using Binomial Trees
Option Pricing using Monte Carlo Simulation
Pricing IRS – Module I – Term Structures
Pricing IRS – Module I – Term Structures EXCEL Example
Pricing IRS – Module II – IRS and CCS
Pricing IRS – Module II – IRS and CCS EXCEL Example
Pricing Interest Rate Options – Module III
Pricing Interest Rate Options – Module III EXCEL Example
Pricing Interest Rate Swaps and Interest Rate Options – Package
Pricing Ladder Options using a Monte Carlo Simulator
Selling Derivative Products
Understanding N(d1) & N(d2)
Valuing Options – Black Scholes Example
Valuing Options – Binomial Tree – Traditional Approach – EXCEL Example
Risk Management
Calculating VaR (Value at Risk)
Calculating VaR – Includes case study
Calculating VaR – EXCEL Example
Calculating Value at Risk (VaR) – Package
Collateral Valuation in Credit Risk Management
Calculating VaR for Futures and Options – EXCEL Example
Portfolio Risk Metrics – EXCEL Example
Portfolio VaR – EXCEL Example
Risk Frameworks & Applications – 2nd Edition
Sample Counterparty Limit Proposal
Setting Counterparty Limits
Setting Counterparty Limits – Package
Setting Limits – EXCEL Example
Setting & Linking VaR, Stop loss & PSR Limits
Value at Risk with Liquidity Premium
Start Up
Treasury Products
Crude Oil Mispricing model
Cross Selling Treasury Products
Relative Gold Price model
Treasury Crash Course
Treasury Crash Course – Package
Back to top