Advanced Excel and VBA for Financial Modeling

12 Hours

Deal Price$10.00

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$19.99

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Advanced Excel and VBA for Financial Modeling

$10.00$19.9949% OFF

50 Lessons (12h)

You, This Course and Us
Promo_CareerInFintech3:16
Introducing Risk management
Risk Management - Slides and Source Code
Introduction12:30
Factor Risk Models10:26
Case Studies12:52
Mean Variance11:52
Correlations12:58
Outlining an Approach to Risk Management
Overall Approach12:53
Portfolio Mean Variance9:24
Factor Models9:17
Factor Variance Calc10:29
VaR11:34
VaR - Pros and Cons10:28
RIsk Modeling in Excel/VBA
Yahoo Finance10:33
Returns10:38
VBA Cov7:36
Factor Regressions10:12
Factor Model Risk5:56
Scenario Risk9:23
Va R Calc6:46
Factor Analysis and PCA
Factor Analysis and the Link to Regression8:05
Factor Analysis and PCA7:02
Basic Statistics Required for PCA
Mean and Variance6:05
Covariance and Covariance Matrices11:47
Covariance vs Correlation3:20
Diving into Principal Components Analysis
The Intuition Behind Principal Components
Finding Principal Components7:12
Understanding the Results of PCA - Eigen Values4:07
Using Eigen Vectors to find Principal Components2:31
When not to use PCA2:26
PCA in Excel
Setting up the data6:52
Computing Correlation and Covariance Matrices3:27
PCA using Excel and VBA5:51
PCA and Regression2:56
Introducing Numerical Optimisation
Optimisation - Slides and Source Code
Introduction6:51
Balance3:33
Framing the Problem8:27
Solving the problem10:19
Applications6:46
PortfolioAllocation5:58
Regression6:57
Gradient Descent5:54
Linear Programming and the Simplex Method
Wyndor7:27
Standard Dual7:04
Micro Econ6:13
Graphical7:37
Simplex Intuition7:47
Simplex Mechanics8:48
Simplex Extensions7:43
Implementing Linear Programming in Excel
Outlining our Approach3:55
Assembling Data3:52
Linear Estimations6:51
Solver5:28
VBA for Covariance5:49
Quadratic Optimization7:30
Understanding Integer Programming
Integer Programming6:03
LP Relaxation4:53
Flaws Naive LP7:00
Applications7:23
Either Or Constraints5:42
Unusual Forms7:18
Implementing Integer Programming in Excel
Integer Constraints4:29
Leverage and Long-bias Constraints3:29
Solver for Integer Programming4:45
Connect the Dots with Linear Regression
Using Linear Regression to Connect the Dots9:06
Two Common Applications of Regression5:26
Extending Linear Regression to Fit Non-linear Relationships2:37
Basic Statistics Used for Regression
Understanding Mean and Variance6:05
Understanding Random Variables11:27
The Normal Distribution9:31
Simple Regression
Setting up a Regression Problem11:38
Using Simple regression to Explain Cause-Effect Relationships4:59
Using Simple regression for Explaining Variance8:09
Using Simple regression for Prediction4:06
Interpreting the results of a Regression7:27
Mitigating Risks in Simple Regression7:58
Applying Simple Regression
Applying Simple Regression in Excel11:57
Multiple Regression
Introducing Multiple Regression7:05
Some Risks inherent to Multiple Regression10:08
Benefits of Multiple Regression3:49
Introducing Categorical Variables7:00
Interpreting Regression results - Adjusted R-squared7:04
Interpreting Regression results - Standard Errors of Co-efficients8:14
Interpreting Regression results - t-statistics and p-values5:34
Interpreting Regression results - F-Statistic2:53
Applying Multiple Regression using Excel
Implementing Multiple Regression in Excel8:54
Logistic Regression for Categorical Dependent Variables
Understanding the need for Logistic Regression9:26
Setting up a Logistic Regression problem6:04
Applications of Logistic Regression9:57
The link between Linear and Logistic Regression8:15
The link between Logistic Regression and Machine Learning4:18
Solving Logistic Regression
Understanding the intuition behind Logistic Regression and the S-curve6:23
Solving Logistic Regression using Maximum Likelihood Estimation10:04
Solving Logistic Regression using Linear Regression5:34
Binomial vs Multinomial Logistic Regression5:23
Applying Logistic Regression
Predict Stock Price movements using Logistic Regression in Excel9:52

Advanced Excel and VBA for Financial Modeling

$10.00$19.9949% OFF

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DescriptionInstructorImportant DetailsRelated Products

Perform Risk Modeling, Optimization, Factor Analysis & Regression with Excel

LoonycornLoonycorn is comprised of two individuals—Janani Ravi and Vitthal Srinivasan—who have honed their respective tech expertise at Google and Flipkart. The duo graduated from Stanford University and believes it has distilled the instruction of complicated tech concepts into funny, practical, engaging courses, and is excited to be sharing its content with eager students.

Description

Excel is a programming language in and of itself. In this power-packed course, you'll use Excel and Visual Basic for Apps (VBA) for some serious financial number-crunching. You'll cover risk modeling, factor analysis, numerical optimization, and linear and logistic regression in your quest to become a competent financial modeler.

Access 50 lectures & 12 hours of content 24/7
Model risk using covariance matrices & historical returns
Understand principal components, Eigen values & Eigen vectors
Apply PCA to explain the returns of a technology stock like Apple
Study various extensions to the Simplex method, including K-of-N constraints & quadratic objective functions
Interpret regression results & avoid common pitfalls

Specs

Details & Requirements

Length of time users can access this course: lifetime
Access options: web streaming, mobile streaming
Certification of completion not included
Redemption deadline: redeem your code within 30 days of purchase
Experience level required: all levels

Terms

Unredeemed licenses can be returned for store credit within 30 days of purchase. Once your license is redeemed, all sales are final.

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