Machine Learning: LVQ-based Strategy

LVQ-based Strategy (FX and Crypto)


Learning Vector Quantization (LVQ) can be understood as a special case of an artificial neural network, more precisely, it applies a winner-take-all learning-based approach. It is based on prototype supervised learning classification task and trains its weights through a competitive learning algorithm.


Initialize weights
Train for 1 to N number of epochs
- Select a training example
- Compute the winning vector
- Update the winning vector
Classify test sample

The LVQ algorithm offers a framework to test various indicators easily to see if they have got any *predictive value*. One can easily add cog, wpr and others.
Note: TradingViews's playback feature helps to see this strategy in action. The algo is tested with BTCUSD /1Hour.

Warning: This is a preliminary version! Signals ARE repainting.
***Warning***: Signals LARGELY depend on hyperparams (lrate and epochs).

Style tags: Trend Following, Trend Analysis
Asset class: Equities, Futures , ETFs, Currencies and Commodities
Dataset: FX Minutes/Hours+++/Days
リリースノート: Minor fix.
リリースノート: Minor edit.
リリースノート: Added signal reversal. Some assets and TFs require inverting the signal. Mind this is the work in process.

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