There are some things impossible to quantify. The deliciousness of your grandma's cookies, or how exciting it is to train a neural network, for example. But financial markets are made of numbers - among other things. They should be measurable, quantifiable. Nobody said it would be easy. But we dare.

AI case study: Long/Short Strategy
A new way to train neural networks: the Forward-Forward algorithm
Unlocking Wealth and Diversification: The Powerful Advantages of Investing in Conglomerate Stocks
Clustering Forex Market
Financial Statements Effect
Linking Impact in Divergence Attribution II
Value vs Growth: adversaries or complementary strategies?
How to detect outliers in a set of financial time series?
Ranking aggregation using genetic algorithms
German Idealism meets Modern Finance: a dialectical approach to understanding risk
Financial Machine Learning pitfalls: it’s levioosa, not leviosaa
Gamma Squeeze: How does it affect stock prices?
EURUSD impact in 2022
Generative Adversarial Networks: A rivalry that strengthens
Risk contribution in portfolio management
On the origins of Bayesian statistics
Yield curve modeling
Behavioral Equilibrium Exchange Rate (BEER)
Annualizing volatility
How earnings reports affect stocks?
Building a sector rotation strategy based on Fed’s interest rate policy
ESG 2022: “greenwashing” or alpha source?
Doubling Down: Double Deep Q-networks for trading
Why bother with unbiasedness?
Beyond linear II: the Unscented Kalman Filter
MOIC: Investing Holy Grail
Causality: interest rates and fixed income assets
Sell in May and go away… Just won’t go away
Look-through Hedging: Optimising Currency Overlay
Valuation Multiples or Multiples Analysis
Analyzing U.S. election cycle seasonality in the S&P 500
Self-organizing maps for an investment strategy
What is the difference between Passive Hedging and Active Hedging?
Debt/Equity vs Debt/EBITDA
On the origins of some stochastic processes
From theory to practice: Challenging the market using MPT-based investment strategy
Optimization problems with non-continuous restrictions
Forming Inflation expectations
Penn effect and its impact on GDP
Hierarchical clustering: explanation and classification
How to Increase Factor Definition Robustness
Dali’s Whiskers: How To Improve a Boxplot
Achieving a well-diversified portfolio based on Graph Theory
Random Forest on Financial Ratios as an Investment Strategy
Measuring uncertainty in time series data
Finding the Probability Distribution Implied in Option Prices
Transformers: is attention all we need in finance? Part II
Mutual Fund Returns vs Investor Returns
Hedging cash flows
Predicting NASDAQ price using news
In the pursuit of the Perfect Portfolio: Modern Portfolio Theory
TF-IDF: summarising news with python
Black-Litterman Sector Allocation
What is the intrinsic value of a company?
What is inflation?
Linking Impact in Divergence Attribution
What Is The Difference Between Time-Weighted and Money-Weighted Returns?
Analyzing S&P 500 Constituents Returns by Sector
Self-organizing maps for clustering
FX Hedging – Execution Timing Lags
Volatilities and Correlations of Cross Rates, a Geometrical Understanding
Transformers: is attention all we need in finance? Part I
P/E vs P/B vs P/S
On the origins of the normal distribution
Will the Fed ruin my S&P500 investments?
Markov chain as market predictor
What moves the market?
Moving Abroad: Can We Optimize FX Conversions?
Factor contribution
Hedged Share Class: from theory to practice
Optimizing implicitly using genetic algorithms
Purchasing Power Parity
Are FX Swaps Mispriced?
Beyond linear: the Extended Kalman Filter
The risk of investing: An exploration on SPDR Sector ETFs
What is a Short Squeeze?
Implementing a RNN with numpy
Improving crypto investing with Reinforcement Learning
Automating cryptocurrencies investment
Concepts of Entropy in Finance: Transfer entropy
Linking Attribution Factors
Different methods for mitigating overfitting on Neural Networks
Reducing data dimensionality using PCA
What cannot be hedged
What is Mutual Information?
In Search of Lost Covered Interest Parity
4 simple ways to label financial data for Machine Learning
Detecting turning points
SigCWGAN, a new generation GAN architecture for Time Series Generation.
Salary factor
Second chances with momentum
Improving time series animations in matplotlib (from 2D to 3D)
Reinforcement Learning for Trading
Fundamental shifts in factors, are they here to stay?
Decision Trees: Gini vs Entropy
Does low volatility anomaly work in funds?
Deflated Sharpe Ratio (how to avoid been fooled by randomness)
Dream team: Combining classifiers
Clustering S&P500 using Fully Convolutional Autoencoders
FX Swap pricing and the mystery of Covered Interest Parity
Currency Hedging Valuation: A Money Weighted Approach
An Introduction to Time Series Signatures
Kelly criterion: Part 2
Introduction to NLP: Sentiment analysis and Wordclouds
The secret sauce that makes Deep Learning frameworks so powerful
Finance Factors Coordination? Cascade Selection
What is the difference between Extra Trees and Random Forest?
Variational autoencoder as a method of data augmentation
Probabilistic Sharpe Ratio
What is the difference between parameters and hyperparameters?
Can neural networks predict the stock market just by reading newspapers?
Understanding Neural Networks (with Graphs)
Hedging an Option through the Black-Scholes model in discrete time
A primer on embedded currency risk
The other way around: from correlations to returns
Predicting the fall:  Revisiting the “Forecasting VIX peaks” experiment.
Is robustness an ally?
Create your own Deep Learning framework using Numpy
Factor Exposure: The Turn of The Screw
Have you tried to calculate derivatives using TensorFlow 2?
Visualising ETFs with UMAP
Generating OHLC bars with Generative Adversarial Networks
Autoencoder based outlier detection in FOREX
Dimensionality reduction method through autoencoders
Mitigating overfitting on  Trading Strategies
What is the difference between feature extraction and feature selection?
Awesome data visualizations
Towards the Risk-Free Curve: Logarithmic vs. Arithmetic Returns
Trick or treat. It’s Halloween!
Mitigating overfitting on Financial Datasets with Generative Adversarial Networks
An age prediction solution applied to rank returns
Encoding financial texts into dense representations
What is the difference between Deep Learning and Machine Learning?
Geometrical evaluation of Generative Adversarial Networks
An intuition behind currency risk
Outliers detection with autoencoder, a neural network
Graph Theory in portfolio analysis. Part I
Generating Financial Series with Generative Adversarial Networks Part 2
A Matter of Scale: Returns and Volatility
From the Neuron to the Net
Classification of Market Regimes
Learning to Rank with TensorFlow
Understanding the shape of data (II)
Fundamental Manifoldness
Generating Financial Series with Generative Adversarial Networks
Ranking Quality
Fixed income from interest rates’ point of view
Mutual Funds… A walk through history
Portfolio weightlifting (II)
Portfolio weightlifting (I)
Factor investing in the currency market
Omega ratio, the ultimate risk-reward ratio?
Asset Migrations
More examples in Financial Visualisation
Group Funds with the Sun
Deep Reinforcement Trading
Estimating the probability of something that never happened
Understanding the shape of data
Volcano escape with Gradient Descent
Synthetic prices… and burgers
Creating our own S&P 500 Momentum ETF
Scaling/ normalisation/ standardisation: a pervasive question
The Benford law and the Zipf law
Erratic correlation: an illustration through Chord diagrams
Value at Risk or Expected Shortfall
Evening class imbalance before the war
Backtesting algorithms… with Python!
10 Reasons for loving Nearest Neighbors algorithm
Hierarchical Risk Parity
To be or not to be (correlated)
Bootstrapping time series data
Biclustering time series
Improving data diversity. Synthetic Financial Time Series Generator
Monkey quants & sector rotation
The Elo system
Isolation forest: the art of cutting off from the world
Quantitative clustering with Machine Learning
Demystifying the Hurst exponent
Diversity is the ultimate diversification strategy
The magic of Fibonacci numbers
Survivorship bias: an investment decision trap
The Kelly criterion
Correlation with prices or returns: that is the question
How do stock market prices work?
When distance is the issue
Cointegration in Economy: a long-term relationship
The lazy or intelligent fund manager
Forecasting S&P 500 using Machine Learning
Hierarchical clustering of Exchange-Traded Funds
Dropout in feed-forward neural networks
Fibonacci retracement and extensions
Asset allocation with constraints using Backtracking
Copulas: an alternative in risk measurement
Risk Parity in Python
The herd effect in financial markets
Markov chains
Portfolio risk control: risk parity vs. inverse volatility
World connections using financial indexes
The Kalman filter
This is why Machine Learning boosts your brain
Neural networks
Foreseeing the future: a user’s guide
Stochastic portfolio theory, revisited!
“Past performance is no guarantee of future results”, but helps a bit
Playing with Prophet on financial time series (again)
Interviewing prices: don’t settle for less
The Simpson Paradox
Seeing the market through the trees
Shift or stick? Should we really ‘sell in May’?
What to expect when you are the SPX
K-Means in investment solutions: fact or fiction
Lévy Flights. Foraging in a finance blog. Part II
How to… use bootstrapping in portfolio management
What is the difference between Artificial Intelligence and Machine Learning?
Playing with Prophet on financial time series
Dual momentum analysis
Random forest: many are better than one
Non-parametric estimation
Classification trees in Matlab
Using Multidimensional Scaling on financial time series
Applying genetic algorithms to define a trading system
Graph theory: connections in the market
Lévy flights. Foraging in a finance blog
Data cleansing & data transformation
Principal component analysis
Comparing ETF sector exposure using Chord Diagrams
Learning with kernels: an introductory approach
SVM versus a monkey. Make your bets.
Clustering: “Two’s company, three’s a crowd”
Euro Stoxx Strategy with Machine Learning
Visualizing Fixed Income ETFs with T-SNE
Hierarchical clustering, using it to invest
Lasso applied in portfolio management
Markov switching regimes say… bear or bullish?
Exploring extreme asset returns
Playing around with future contracts
“K-Means never fails”, they said…
What is the difference between Bagging and Boosting?
BETA: Upside Downside
Outliers: looking for a needle in a haystack
Autoregressive model in S&P 500 and Euro Stoxx 50
“Let’s make a deal”: from TV shows to identifying trends
Machine Learning: a brief breakdown
Approach to dividend adjustment factor calculation
Are low-volatility stocks expensive?
Predict returns using historical patterns
Stock classification with ISOMAP
Could the Stochastic Oscillator be a good way to earn money?
Central limit theorem: visual demonstration
Sir Bayes: all but not naïve!
Returns clustering with k-Means algorithm
Correlation and cointegration
Dynamic Markowitz Efficient Frontier
Confusion matrix & MCC statistic
Performance and correlated assets
Reproducing the S&P500 by clustering
Size effect anomaly
Predicting gold using currencies
Inverse ETFs versus short selling: a misleading equivalence
Seasonality systems
Using decomposition to improve time series prediction
In less of a Bayes haze…
In a Bayes haze…
Volatility of volatility. A new premium factor?