Dijkstra algorithm
Learn all about the Dijkstra algorithm! Dijkstra algorithm is one of the greedy algorithms to find the shortest path in a graph or matrix....
Mathematics and Econometrics
Learn the practical applications of mathematics and econometrics in finance. This series of blogs covers time series analysis, portfolio management, probability distribution, econometrics and many mathematical models.
Grokking Linear Regression Analysis in Finance
Getting under the hood of linear regression where we demystify the jargon regularly encountered on the topic. Let’s dive in!...
Introduction to Central Limit Theorem: Examples, Calculation, Statistics in Python
This blog introduces you to the Central Limit Theorem (CLT) and explains its importance with the help of examples in Python. The concepts of samples and sampling distribution are also covered in this article....
Autoregression: Model, Autocorrelation and Python Implementation
In this article, you will learn all about the autoregression and AR Model to forecast time series and its Python implementation....
Stationarity in Time Series Analysis Explained using Python
In this article, you will learn about the stationary series, how to detect stationarity and convert a non-stationary series into a stationary series....
Kurtosis & its Application in Risk Evaluation
This blog discusses the concept of kurtosis and its application in understanding the risk profiles of financial securities besides common misconceptions regarding its calculation and interpretation....
Markov Model - An Introduction
In this post, we will learn about Markov Model and review two of the best known Markov models namely the Markov Chains, and the Hidden Markov Model (HMM)....
Random Walk: Introduction, GBM, Simulation
Random walk describes a path taken by an object which is seemingly random, or unpredictable. We will see what is a simple random walk and create a simulation for the closing price of a stock....
All About Time Series: Analysis and Forecasting
Learn about Time Series Data Analysis and its applications in Python. Learn types, components, decomposing, forecasting, calculating, plotting and validating Time Series....