watch short videos + how to implement machine intelligence into trading apps

get up and running fast + minimal code to get started

Use Cases + Browse Python code

How does SliceMatrix-IO work?

AP_Multi_Bubble.png

Machine Intelligence Models & Pipelines

There are 2 core innovative concepts that allows users to build powerful machine learning with minimal code:

1. The Analytical Pipeline(AP) can be thought of as assembly lines of code which can train machine learning models. AP’s are reusable, meaning you can use the same AP to train multiple machine learning models using different input data.

2. The Model
The model are where the real magic happens. After the Pipeline trains a Model, the Model live’s on SliceMatrix-IO(beta)’s machine learning infrastructure in the cloud. That means you can access your model after you create it in a distributed fashion. You can also train models in parallel subject to your usage plan’s request / throttling limits.

GLOBAL COVERAGE

SliceMatrix offers a monthly subscription to the platform's powerful machine intelligence tools and solutions. With SliceMatrix-IO(beta) access your models 24/7 any where around the world.Choose from 1 of 4 data centers distributed around the world. Why choose one over the other? One word: latency, the closer your programs are to your data center, the faster you will receive responses from SliceMatrix-IO. In the end its all about performance. You can also choose multiple data centers in one subscription.

Use Machine Intelligence to identify hedge ratios

 

Real World use case

As any good pairs trader will tell you, hedge ratios are liable to change over time. One way to combat this problem is to use a rolling window of regressions: i.e. constantly updating your hedge ratio with a trailing window of data. The problem is this method is guaranteed to fail over time as you're always looking backwards, averaging what has happened in the past as your best guess of the future hedge ratio.

But a superior method is to employ a dynamic linear model such as the Kalman Filter (KF). The KF is the optimal model for estimating the parameters of linear gaussian models such as pairs trading.

 

List of SliceMatrix-IO Machine Intelligence Models

*please note that this is not an exhausive list- models are continuously being added.