Sitemap - 2026 - Engineering Alpha
My Key Takeways From Zuckerman's The Men Who Solved the Market
Hybrid Models Combine Signal Processing and Machine Learning
Online Filters Create Causal Features: Forecasting with Exponential Smoothing
Wavelets Reveal Changes: Causal Forecasting with Haar Features
Fourier Methods Reveal Cycles: Causal Forecasting with the Discrete Fourier Transform
The Most Dangerous Thing in Trading, and How to Avoid It
Kâs Synapse: A Simple Way to Read Market Structure Without Guesswork
A Proper Introduction to Market Microstructure
LLMs in Market Forecasting - A Quantitative Research Primer
How I Forecast Financial Markets
The Regression Method Almost Nobody Uses
Astrology and Trading - The Myth Debunked
Deep Learning Can Forecast Time Series. It Just Often Doesnât Beat the Boring Stuff.
PCA in Time Series: Finding Structure in a Moving World
How to Beat Loss Aversion - A Professional Trader's Way
A Day in a Hedge Fund Analyst's Shoes
Let's Apply Kalman Filter on Time Series
Wavelets for Market Forecasting - Are They Any Good?
New Time Series Forecasting Technique - All You Need to Know
Simple Machine Learning Models for Time Series - The Tweedie Regression
Why RSI Works Sometimes and What That Actually Means
The Myth of Precision in Technical Analysis
Why Most âEdgesâ Are Just Poorly Measured Noise
Detecting Chart Patterns with Numerical Templates and a Random Walk Price Series
The Triple Parabolic Trading Technique
Let's Create a Moving Pivot Points Overlay Indicator
Understanding Hidden Markov Models
Wavelet Transform Modulus Maxima For Time Series Analysis
I Built a Quantitative Research Platform for Markets. Today It Goes Public
More Forgotten Quantitative Research Skills
Exotic Market Patterns Simplified VI - NR7 Pattern
I Hid a Small Pattern in Data and Ran ML Models to Find It
Kernel Ridge Regression in Practice
Variational Mode Decomposition - An Elegant Tool for Time Series
The Forgotten Skill in Quantitative Research
Mastering Time Series Classification With Random Forests
Seeing the Market Through Weight and Intent
Zigzaging Our Way Through Time Series Regression
The Most Dangerous Thing in Trading, and How to Avoid It
Why Support and Resistance Work (and When They Donât)
The Truth About Machine Learning in Trading
Creating Synthetic Data for Strategy Testing
A Deep Learning Model Built for Tabular Data
Time Warping the Market Simplified
Stop Judging Reversal Strategies the Wrong Way
The BiasâVariance Tradeoff in Time Series Forecasting
Stationarity Explained Without Math Anxiety
Why Time Series Is Not Just Regression With Time
Forecasting with SARIMAX: What It Is and Why It Matters
Understanding Wavelet Transforms
The Signature Transform: A Practical Introduction for Time Series
DBSCAN in Time Series: Finding Regimes, Motifs, and Weird Stuff
My Key Takeaways from Machine Trading by Ernest Chan
Proper Risk Management: The Skill That Actually Keeps You in the Game
Autoencoders, Explained From Scratch
PCA in Time Series: Finding Structure in a Moving World
The Extrema Precision Index (EPI): A Different Way to Judge Forecasts
Technical Analysis: A New Data-Driven Approach and a NEW Book!
The Squeeze Momentum Indicator
Why Most Moving Average Signals Are Arbitrary
Sequential Pattern Averaging Regressor - Presenting my New Model
Monte Carlo Simulation - All You Need to Know
Purging and Embargo - Two Tricks That Stop Time Series Models From Lying to You
What Working in Counterparty Risk Taught Me - Technically and Human-wise
The 3 Mistakes Killing Most Retail Traders
HoltâWinters Exponential Smoothing: Forecasting When Patterns Repeat
DLinear Model - A Revolution in Simplicity With Forecasting Time Series
My Key Takeways From Marcos Lopez De Prado's Machine Learning for Asset Managers
A Primer on Support Vector Machines in Python
What is Stochastic Gradient Descent and How to Use it With Time Series?
Astrology and Trading - The Myth Debunked
Beyond Linear Regression - L1 & L2 Regularization From Scratch
Simple Machine Learning Models for Time Series - The Tweedie Regression
My Key Takeways From Marcos Lopez De Prado's Advances in Financial Machine Learning
What is Huber Loss in Financial Machine Learning
Quantile Regression - A Different Solution for a Known Problem
An In-Depth Guide to Gaussian Process Regression
Multi-Step Forecasting With Fourier Transform in Python
Using the t-Statistic to Validate Your Trading Results
What is the Deflated Sharpe Ratio?
Overfitting in Layman's Terms and How to Avoid it
Predicting Time Series With Partial Least Squares (PLS) Regression in Python
Classification vs Regression in Financial Time Series
The Cross-Correlation Function to Understand Predictability
K's Synapse - A New Multi-Purpose Technical Indicator
Creating a Simple RSI-Based Market Regime Detector
Simple Machine Learning Models for Time Series - The Tweedie Regression