Value at Risk (VaR) Portfolio Risk Model

This project is a simple implementation of a portfolio risk model using Value at Risk (VaR) parametric method. It uses historical market data and statistical measures to estimate potential losses in a stock portfolio over a fixed time horizon. The VaR is a single number that indicates the likehood of losing 'X' percent of capital given a confidence interval and at any given trading session.

Overview

The project builds an equity portfolio from NSE and evaluates its risk using:

• Historical log returns
• Portfolio variance (covariance matrix)
• Parametric Value at Risk (VaR)
• Multi-day risk scaling
• Visual distribution of returns

It helps simulate how much a portfolio can lose under normal market conditions with a given confidence level.

How it works

The calculation of the VaR requires the calculation of the portfolio's standard deviations as a pre-requisite.This method uses statistical approach and follow a normal distribution:

• Calculate mean and standard deviation

• Use Z-score for chosen confidence level

• Calculate VaR using:

                VaR = μ - (Z * σ)
  

This method assumes that:

• Returns follow a normal distribution
• Market conditions remain stable
• Volatility is constant over the period

---

Visualisation

The histogram below shows the distribution of portfolio returns. It helps in understanding how returns are distributed around the mean and where potential losses lie.

---