Predicting future volatility
Myalo's Financial Machine Learning Platform
enables volatility forecasts and portfolio creation

Abstract cover for volatility forecasts

Volatility Forecasts

Our adaptive machine learning models are trained and simulated to predict volatility. Signals that can be directly acted upon!

learn more

Model Portfolios

Model portfolios created based on volatility forecasts, trained on our proprietary dataset.
Explore the capabilities!

learn more
Abstract cover for model portfolios
Abstract cover for platform

Platform

Your data, your target, your IP. Coming in 2024.

learn more
Knowledge base

Challenges in Financial Machine Learning

How to avoid Overfitting on Noisy Data

Overfitting in finance occurs when models, highly accurate on historical data, fail with new data due to high complexity. Strategies to combat this include simpler models, cross-validation, feature selection, and out-of-sample testing to ensure real-world adaptability.

Differentiating Between Luck and Skill

Explore the fine line between luck and skill in time series financial forecasting. Learn how walk-forward cross-validation and z-score analysis help differentiate model success due to skill from mere chance, ensuring reliable and accurate market predictions.