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# Series 

## [Time-series](time-series.html)
A series of posts related to the analysis of time-series.  

* introduce the 4 statistical moments 
* develop concepts on auto-correlation, stationarity and random-walk
* time-series decomposition
* ARIMA and families

## [Probability](probability.html)
A series of posts centered on basic probability concepts essentials for the study of quantitative finance. 

## [Risk and Portfolio](risk-portfolio.html)
A series of posts related to risk-management in portfolio construction. 

## [Quant - Part 1](quant-part1.html)
A series of posts when starting quant finance. Basic mathematical concepts and related code in R and Python when starting quantitative finance.  

## [Quant - Part 2](quant-part2.html)
A series of posts on some introductory concepts of stochastic calculus.  

## [Quant - Part 3](quant-part3.html)
A series of posts on the Black-Schole Equation and derivative pricing.

## [Machine Learning - Part 1](machine-learning-part1.html)
A series of posts on machine learning algorithms with a quant finance lens. 

* KNN
* linear regression
* Kmeans 

## [Machine Learning - Part 2](machine-learning-part2.html)
A series of posts on machine learning algorithms that focuses on trees, bagging and boosting.  

# Posts