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Standard Deviation and Mean
Lotto Number Generator
Playing Card Probability
Monte Carlo Integration
Normal Distribution Random Number Generator
Black-Scholes Option Pricing Model - European Call and Put
Binomial Option Pricing Model
Portfolio Optimization
Multiple Regression
Bootstrap - A Non-Parametric Approach
Multivariate Standard Normal Probability Distribution
Monte Carlo Simulation
New examples will be added on a regular basic, so please do check back.
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Any questions regarding the examples? 
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VBA Project on Finance, Statistics, Economics, and Mathematics Examples
Excel tutorials without using VBA. Examples include bivariate standard normal density function, Black-Scholes option pricing models, forecasting, non-linear regression, frequency distribution with hostogram, Monte Carlo simulation and many more.
This section provides VBA tutorial on small applications.  Examples include compute median and factorial, get option expiration date, sorting, looping, extract unique value and many more.  Also include Simulation Basic Tutorial 101,102 and Excel VBA Basic Tutorial Series.
More Excel VBA
Just Excel (Includes Interactive Web Excel Programs)
Random Number Generator
Chi-Square Distribution, F Distribution, Student-T Distribution, Normal Distribution, Log-Normal Distribution,Log Pearson Type III Distribution,  Gamma DistributionBeta DistributionHypergeometric Distribution, Triangular Distribution,Binomial Distribution, and Multivariate Standard Normal Distribution.
Numerical Searching Methods
Newton-Ralphson, Secant, and Bisection Search Precedures.  Implied Standard Deviation (Volatility).
Option Pricing Models
Option on asset with cash dividend, option on asset with continuous dividend (stock index), option on futures, and option on currency.
Additional Examples for Order (Preview)
Excel VBA Tutorial

This section contains Excel and VBA tutorial examples on various topics in finance, mathematics, statistics and other general issues.  Many advanced topics are included in this section.  To find introductory and intermediate examples please go to the More Excel VBA section.  For Excel examples without VBA please go to the Just Excel section.
You can also  download the selected free sample program files (code protected).
(A 3-part  Excel VBA Basic Tutorial series for beginners has been added in the More Excel VBA section.)
Complete program with source codes available in Package Set 1.
A simple tutorial that shows users on how to compute mean and standard deviation from an array (also a demonstration of creating user-defined functions).
This example involves generating multiple unique random numbers from 1 to 54 with resampling without replacement technique by utilizingsorting one array based on another array.
What is the probability of getting 3 cards with red hearts and two other cards when 5 cards are drawn from a deck? This tutorial simulates an actual scenario. The probability distribution derived from this simulation happens to be a Hypergeometric distribution.
This tutorial shows how to create random numbers from a normal distribution given the standard deviation and the mean, and then computes the confidence interval given the level of significance. Also, a histogram is introduced.
This example uses simulation to find the integral (area under) of a normal distribution curve within a specific interval.
The example computes the European call and put price based on Black-Scholes option pricing models. Cumulative Standard Normal Distribution is also introduced.
The example computes the European call and put price based on Binomial option pricing models. Binomial coefficient is also computed.
This tutorial demonstrates on how to obtain the optimal portfolio (highest return with lowest standard deviation) using Harry Markowitz theory.  The largest Sharpe Ratio is used to determine the optimal set.  The efficient frontier is plotted from the simulated sample.
Using matrix algebra by utilizing the Excel functions such as, MInverse( ) and MMult( ), which performs matrix inversion and matrix multiplication, respectively.
Use resampling with replacement, a probability distribution for the median is created, along with the standard deviation of the median, which cannot be computed under mathematical formula (since there is none).
This example is perhaps the most advanced example so far on this website.  It generates multivariate standard normal distribution deviates from correlated variables and then compute the probability from the given z values.  A numerical procedure, Jocobi search method is used to derive the Eigenvectors and Eigenvalues
This tutorial is two of the most popular tutorials on this site (guess which is the other one?).  By assuming underlying probability distributions (normal, uniform, and truncate normal) of the variables in the profit equation, we get a probability distribution for the profit.  It answers the questions like 'what is the chance that we will loss profit' and 'what is the chance that we will make the X amount of profit.' 
Option Greeks Based on Black-Scholes Option Pricing Model
This tutorial contains option sensitivities (delta, gamma, vega, theta, and rho) formulas and source code.  Option sensitivities are also know as the Greeks.  They measures how sensitive the option price is toward changes in its parameters.  All Greeks are available in user-defined VBA functions and in mathematical formulas.
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Free Sample Download
Free Sample Download
Free Sample Download
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