Monitoring Forecasting Models at Scale
published on Medium, Feb 22nd 2021

Machine Learning and Deep Learning model predictions are used in applications running in your laptop, your desktop, your phone and even in your car or in your home. The list keeps growing as more smart devices enter our homes and lives, like smart vacuums, fridges and anything else you can imagine. Performance monitoring is critical, as it allows to pinpoint issues early, debug and update as needed. Read more
Introducing Predicto Market Outlook
published on Predicto, Feb 14th 2021

Currently, Predicto tracks around 150 stocks, including the entire Nasdaq-100 list. For every single one of those stocks we maintain at least 3 different Deep Learning models, sometimes more based on our experimentation. This means we maintain and occasionally retrain more than 450 models. Read more
Using Predicto - A beginner's guide
published on Predicto, Dec 29th 2020

Photo by simon sun on Unsplash
When first signing up for Predicto, you might be overwhelmed with all the information you are suddenly exposed to. This is normal. You don't have to be a Deep Learning expert to use Predicto but it is important to know its building blocks. Going through this guide will help you understand how to use our platform the right way from Day One! Read more
How to Build your Personal Automated Stock Trading Agent using Deep Learning Forecasts in Python
published on Medium, Dec 8th 2020

Photo by Christopher Burns on Unsplash
After you are done reading this article you will be in a position to setup your own auto stock trader based on Deep Learning forecasting. You are going to achieve this by retrieving the latest stock forecasts from Predicto API and submitting them daily to Alpaca using your own test account. You can be up and running in a couple of hours! Read more
Understanding Deep Learning Forecasts over Time
published on Medium, Nov 10th 2020

Photo by Thomas Bormans on Unsplash
In this post we'll talk about time travel in some way. Forecasting is all about trying to predict what the future holds. But to do that, we need to understand the past first. Not just a still snapshot of the past, but a continuous period of time. We'll present how we are able to visualize our Deep Learning models' "vision" over time, kind of like a movie. Read more
Explaining Financial Deep Learning Forecasts
published on The Startup ‐ Build Something Awesome. on Medium, September 16th 2020
featured on Machine Learning on Medium

We already covered in a previous post, how important it is to deal with uncertainty in financial Deep Learning forecasts. In this post, we’ll attempt a first introduction on how we deal with explainability. Neural networks have been applied to various tasks including stock price prediction. Although highly successfully, these models are frequently treated as black boxes. In most cases we know that the performance on the test data is satisfying, but we do not know why the model came up with a specific output. Read more
Studying news momentum and narratives
published on Medium, July 18th 2020

Photo by Nick Jones on Unsplash
In this post, we want to focus on News momentum and narratives: How narratives form in preparation for a big move. We will see with examples how those narratives are sustained until they fade out or stabilize to a new equilibrium. This idea has been described in Narrative Economics book by Robert Shiller, where he tries to set a foundation on narrative economics and show how stories go viral and can drive major economic events. Read more
Studying volatility, uncertainty and news - Case study #1
published on Medium, June 7th 2020

Photo by Pablo García Saldaña on Unsplash
In this post, we’ll share some of our thoughts on how to study market volatility and news. We’ll give you some pointers on how we at deal with volatility and uncertainty in order to understand risk involved at any given time. This is a continuation of our series of posts about Investing + Deep Learning. Read more
Investing + Deep Learning - an introduction
published on Medium, June 1st 2020

Photo by Hans Eiskonen on Unsplash
In the last few years, Hedge Funds and Financial Institutions have been investing in building strong Data Science and ML/DL teams. It’s no secret in those circles that there is value in using Big and Deep Data to get valuable insights about investment decisions, short term or long term. Read more