Momentum — Turnover II

Momentum — Turnover II

More advanced second stage of previously performed research pertaining application of turnover and momentum-based trading strategies in connection with portfolio optimization for holding periods between trades back tested on historical data with a set of simplifying assumptions. Quantitative analysts Marko Malling, Noah Åkesson and Jaroslavs Grigoluns incorporated methods of equal risk contribution for securities determined by the automated momentum- capturing mechanism based on purchase/hold/sale signals and their interpretation. Computer self-trading algorithm was tested on the relevant S&P 500 historical constituent equity data ranging from 2000 up till 2020 with a one-day frequency.

Set of momentum strategies were utilized based on crossovers of moving averages of varying time-length and their derivatives in the form of double and triple exponential ones as well as separate data clustering methods, namely static percentile attribution and Jenk’s natural breaks. The strategy used in the research generates long and short trading signals when certain predetermined logical conditions and indicator requirements are fulfilled. Target profit and stop- loss levels for each signal were added as well as limitations on the size of each transaction linked with equal risk contribution approach.

To read the full report, please see attached PDF below.