TRADING SIGNALS

OUR SERVICE

We deliver a monthly report including trading signals for all major asset classes. Results are presented to the client during dedicated meetings.  Our signal are extrapolated from:

  •  Options
  •  Technical Analysis
  • Sentiment indicators
  • A.I. predictive models
  • Crash Alpha models
  •  Contagion models

MUCH MORE THAN MACHINE LEARNING

Forecasting financial time series is much more than putting some technical indicators inside a neural network.

Forecasting is effective only when ALL these components are properly developed:

  1. Predictors
  2. Data-Mining
  3. Predictive Models
  4. Backtesting
abstract-3629844_1280-min

OUR SCIENTIFIC APPROACH

PREDICTORS

One of the most neglected rules of financial forecasting is “GARBAGE IN-GARBAGE OUT”.

We dedicate more time to building a reliable set of powerful predictors than anything else.

Among distinguishing our long list of financial predictors into 5 main subsets:

  • Option Based
  • Spread Based
  • Technical
  • Economical
  • Microstructural

DATA MINING

Usually, there are thousands of candidate predictors for a given predictive model.

Consequently, data-mining procedures must be employed to select a more manageable number of predictors:

  • Clustering
  • Feature Selection
  • Anomaly Detection
  • Dimensionality Reduction

Data-Mining is not complete without an econometric analysis of the predictors and the model’s outputs.

PREDICTIVE MODELS

We employ a broad range of predictive models, from simple linear support vector machines to more complex deep reinforcement learning.

We build our models starting from TensorFlow2, and then we adapt the new features to include findings of the most recent academic publications in the field.

In the range of models we propose, we include the innovative field of Meta-Learning.

No predictive model is operational before passing through a rigorous backtesting procedure to avoid over-fitting.