mlfinlab.labeling.tail_sets

Labeling Tail Sets.

Method based on: “Nonlinear support vector machines can systematically identify stocks with high and low future returns”

Module Contents

Classes

TailSetLabels

Tail set labels are a classification labeling technique introduced in the following paper: Nonlinear support vector

class TailSetLabels(prices, n_bins, vol_adj=None, window=None)

Tail set labels are a classification labeling technique introduced in the following paper: Nonlinear support vector machines can systematically identify stocks with high and low future returns. Algorithmic Finance, 2(1), pp.45-58.

A tail set is defined to be a group of stocks whose volatility-adjusted return is in the highest or lowest quantile, for example the highest or lowest 5%.

A classification model is then fit using these labels to determine which stocks to buy and sell in a long / short portfolio.

get_tail_sets()

Computes the tail sets (positive and negative) and then returns a tuple with 3 elements, positive set, negative set, full matrix set.

The positive and negative sets are each a series of lists with the names of the securities that fall within each set at a specific timestamp.

For the full matrix a value of 1 indicates the volatility adjusted returns were in the top quantile, a value of -1 for the bottom quantile.

Returns:

(tuple) Positive set, negative set, full matrix set.