financial-time-series

To calculate time-series momentum signals from financial price data, compute historical returns, apply de-trending for stationarity, and generate TSMOM or multi-scale momentum indicators to capture trend directions across assets.

Volatility targeting in portfolio construction normalizes risk across assets by scaling position sizes according to target volatility, ensuring consistent risk exposure and generating risk-adjusted portfolio returns across diverse futures.

Yes, you can use time-series momentum for futures backtesting by applying TSMOM signals and MACD-based indicators to price series, then evaluating portfolio performance with risk controls specific to futures handling.

The best way to build a momentum-driven trading strategy with risk controls is to combine multi-scale momentum signals with volatility targeting, constructing a portfolio that systematically manages risk exposure across assets.

MACD works with time-series momentum strategies by serving as a supplementary signal generator alongside TSMOM, capturing momentum shifts across different time horizons to enhance portfolio construction and trend identification.

You should not use time-series momentum for portfolio construction when asset price series lack clear trends or stationarity cannot be achieved through de-trending, as momentum signals require directional continuity to generate valid returns.