SIGNALREVEAL

CREATE INVESTMENT SIGNALS USING MACHINE LEARNING ALGORITHMS

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SignalReveal - Create Investment Signals with Machine Learning

MODULAR & READY-TO-USE MACHINE LEARNING ENGINE

 

SignalReveal is a fully modular Machine Learning engine to create signals and investment strategies from any traditional market, alternative, or proprietary dataset.

Its models and Python source code are fully transferred to clients.

This powerful tool accelerates data analysis and provides techniques to protect against overfitting, all with a transparent, no black box approach.

KEY FUNCTIONALITIES

Alternative Data Sets Evaluation & Integration

Rapidly and rigorously evaluate any structured dataset and integrate it with other datasets

Modular Machine Learning Pipelines

Build predictive machine learning pipelines to identify sources of alpha and limit the risk of overfitting

Signal & Trading Strategy Creation 

Build predictive indicators and complete trading strategies for any asset class or use case

ADVANCED TECHNOLOGIES

A transparent & standardized Machine Learning methodology to help you gain time.

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Data Pre-Processing

  • Alternative Data
  • Market Data
  • Quantitative factors
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Features Engineering

  • Explanatory & target features
  • Correlations & Stationarity
  • Discriminating importance
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Modeling

  • Dimension Reduction
  • Machine Learning & Quantitative Models
  • Temporal Cross-Validation
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Strategy Calibration

  • Models combination & interpretation
  • Backtesting
  • Stability checks

WORKING WITH SESAMm

1. Documentation

Get access to technical documentation & Notebooks to evaluate SignalReveal.

2. Workshop

Dive deeper with our team and ask your technical questions during a Discovery Workshop.

3. Code Delivery

Receive SignalReveal’s Python source code, documentation & Notebooks for each module.

4. Training & Support

Training, support and versioning are included. Be operational in just a few days.

USE CASE

Model Selection Notebook Sample

Features include:

  • Dimension reduction;
  • Cross-validation;
  • Graphical model selection.

Notebook sample: model selection with SignalReveal for a long-only and long-short equity use case combining alternative and market data.

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Use case SignalReveal notebook sample preview

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