1. By Harsh Tiwari

2. 3 Examples of simulations  used in Finance domain

3. Monte Carlo Simulation
This method aims at calculating value of an option where uncertainty coefficient is high
It works on ‘Risk Neutral Valuation’ method
Monte Carlo methods (or Monte Carlo experiments) are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results
Monte Carlo simulation which enables the decision maker to find the most
efficient organisation in a given period of time, considering imprecise time series
of data and also helps with forecasting and estimating the efficiency of
companies in the future for a safe investment
Risk-neutral valuation means that you can value options in terms of their expected payoffs, discounted from expiration to the present, assuming that they grow on average at the risk-free rate.

4. Stochastic Simulation
It traces variables’ evolution that changes randomly with certain probabilities
Outputs are recorded and the projection is repeated with a new set of random values of the variables
In the end, the distribution of the outputs shows the most probable estimates as well as a frame of expectations regarding what ranges of values the variables are more or less likely to fall in
Stochastic simulation framework is applied to perform Bank’s stress testing
It can forecast and assess banks’ capital adequacy, financial fragility and
probability of default.
Stochastic simulations are simulations of a model that is inherently random. An example would be a random number generator, giving you a number between 1 and 6 representing the number of eyes on a die. In other words, you are simulating a random throw of the die by generating a random number.

5. Black-Scholes
The Black-Scholes model is the most popular method for valuing options and can be quite accurate
It relies on fixed inputs (current stock price, strike price, time until expiration, volatility, risk free rates, and dividend yield)
The downside to the Black-Scholes model is that it’s a black box calculator and it doesn’t offer the flexibility required to value options with non-standard features, such as a price reset feature or a mandatory exercise requirement
Black–Scholes equation gives a theoretical estimate of the price of European-style options and shows that the option has a unique price regardless of the risk of the security and its expected return

6. 3 Popular Programming Languages and their Salient Features

7. TIOBE Rating – Popularity of Language
The ratings are based on the number of skilled engineers worldwide, courses, third party vendors

8. Let’s take a look at 3 of them

9. Python
Free and Open
Source
Large standards
library
Easy
Object Oriented
Extensible
Expressive
Portable
Embedded
Dynamically
Typed
The syntax of the language is clean and length of the code is relatively short. It's fun to work in Python because it allows you to think about the problem rather than focusing on the syntax

10. Supports meta-programming
Ruby
Readable Code
Supports meta-programming
OO Script
No indentation issues
Instances
&
Class Variables

11. C++

12. Thanks