Introduction In this article, we will explore K-Means Clustering: What is K-Means Clustering? Algorithm K-Means Clustering Application: Building a diversified portfolio Jupyter Notebooks are available on Google Colab and Github. For this project, we use several Python-based scientific computing technologies listed below. import time import kneed import requests import numpy as np import pandas as…

Introduction In this article, we are going to cover Neural Networks (NN). Let’s begin by laying down the theoretical foundation of the algorithm. Jupyter Notebooks are available on Google Colab and Github. For this project, we use several Python-based scientific computing technologies listed below. import re import math import numpy as np import pandas…

Introduction In this article, we are going to cover the support-vector machine (SVM) which is an incredibly powerful algorithm that can be used in both classification and regression settings. Let’s begin by laying down the theoretical foundation of the algorithm. Jupyter Notebooks are available on Google Colab and Github. For this…

Introduction In this article, we are going to cover Decision Trees, which are a form of supervised Machine Learning that seek to build a simple set of decision rules to make predictions. Decision Trees are among the most popular machine learning algorithms given their interpretability and simplicity. They can be applied…

Introduction In this article, we are going to cover a simple, yet extremely versatile algorithm called k-nearest neighbors (k-NN). First, we will build intuition about k-NN’s inner workings and then learn how to apply the algorithm to real financial data from AlphaWave Data. We will use fundamental credit data of high…

Introduction Pairs trading is perhaps the earliest form of relative value quantitative trading in equities. Using some modern Machine Learning tools in the pair trading investment process, we will show how to create sensible pairs without using any price data. Certain stocks have highly related price series because they: operate in…

Introduction In developing a Pairs Trading strategy, finding valid, eligible pairs that exhibit unconditional mean-reverting behavior is of critical importance. We walk through an example implementation of finding eligible pairs and then perform a backtest on a selected pair. …

Introduction This example employs several unsupervised learning techniques in scikit-learn to extract the stock market structure from variations in historical close prices. The quantity that we use is the daily variation in close prices because prices that are linked tend to cofluctuate during a day. Jupyter Notebooks are available on Google…

Introduction This article covers regression analysis, which is fundamental to many applications of machine learning and throughout scientific disciplines. We will walk through some of the concepts and then dig into some regression examples using financial data from AlphaWave Data. Jupyter Notebooks are available on Google Colab and Github. For this…