Market Regime¶

You can find a series of examples on how to create these features in the educational notebooks provided by Quantreo.

import quantreo.features_engineering as fe

KAMA Market Regime¶

The kama_market_regime function generates a market regime indicator based on the relative position of two Kaufman's Adaptive Moving Averages (KAMA): a fast KAMA and a slow KAMA.

This function helps detect bullish or bearish phases by comparing a shorter-term KAMA with a longer-term KAMA:

When the fast KAMA > slow KAMA, the market is in a bullish regime (1).
When the fast KAMA < slow KAMA, the market is in a bearish regime (-1).

Concept This method is inspired by the traditional moving average crossover logic, but with the adaptivity of KAMA smoothing.

The fast KAMA reacts more quickly to price changes due to its shorter parameters, while the slow KAMA filters out market noise over a longer period.

Tip

The choice of l1, l2, and l3 parameters for each KAMA influences both trend reactivity and noise filtering. For trend-following strategies, using l1_fast = 50 and l1_slow = 200 is common, but you can adjust them depending on your timeframe.

FunctionDocstringExample

fe.market_regime.kama_market_regime(df: pd.DataFrame, col: str, 
                                    l1_fast=50, l2_fast=2, l3_fast=30, 
                                    l1_slow=200, l2_slow=2, l3_slow=30)

"""
Compute a market regime indicator based on the difference between two KAMA (fast and slow).

This function calculates two KAMA indicators using different parameter sets (fast and slow).
It then returns a regime signal:
- 1 if fast KAMA is above slow KAMA (bullish)
- -1 if fast KAMA is below slow KAMA (bearish)

Parameters
----------
df : pandas.DataFrame
    DataFrame containing the input price series.
col : str
    Column name on which to apply the KAMA calculation (e.g., 'close').
l1_fast : int, optional
    Efficiency ratio lookback window for the fast KAMA (default is 50).
l2_fast : int, optional
    Fastest EMA constant for the fast KAMA (default is 2).
l3_fast : int, optional
    Slowest EMA constant for the fast KAMA (default is 30).
l1_slow : int, optional
    Efficiency ratio lookback window for the slow KAMA (default is 200).
l2_slow : int, optional
    Fastest EMA constant for the slow KAMA (default is 2).
l3_slow : int, optional
    Slowest EMA constant for the slow KAMA (default is 30).

Returns
-------
pandas.Series
    A Series containing the market regime indicator:
    - 1 for bullish regime
    - -1 for bearish regime
"""

df["kama_trend"] = fe.market_regime.kama_market_regime(df, "close", l1_fast=50, l2_fast=2, l3_fast=30, l1_slow=200, l2_slow=2, l3_slow=30)

📢 For a practical example, check out this educational notebook.