Factors
Momentum · US equities

Risk-Adjusted Momentum Factor — US

Risk metrics for periods of 50, 100 & 200 days

product_id risk_adjustment_momentum_factor_us · 4800+ stocks · daily refresh · since 2003-01-01 · 4 data columns · API/CSV

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Overview

Risk-adjusted momentum is similar to price momentum, except this factor takes into account the level of risk involved. This is done primarily because of the popularity of the momentum factor during periods of high volatility, and by taking into account volatility, we mitigate the momentum factor from suffering from swift changes in market direction.

Data Highlights

  • For low-risk and high reward investors, when adjusting for risk the top performing portfolio (Q_10) generates strong annual returns and cumulative return, while simultaneously showing a lower correlation to the market and the highest Sharpe ratio.
  • When looking at all risk-adjusted momentum factors, all factors out-perform the maximum drawdown of the market, and again have a lower correlation to the market. This is while demonstrating strong cumulative return and annual returns.

Performance

Statistics

MetricQ1Q2Q3Q4Q5Q6Q7Q8Q9Q10SPY
CAGR10.98%10.58%8.38%8.71%9.50%10.06%10.18%9.73%10.31%11.26%9.37%
Cumulative Return1088.39989.22576.10626.79762.93873.78900.77807.18928.601161.23678.46
Annual Volatility28.60%21.93%20.34%18.71%16.86%16.92%15.69%14.63%13.34%12.29%14.47%
Sharpe0.500.570.500.540.620.650.700.710.810.930.69
Calmar0.160.170.140.150.180.190.220.220.250.270.18
Max Drawdown-69.71%-62.23%-61.59%-56.53%-53.39%-53.57%-46.62%-44.35%-40.89%-41.10%-52.56%
Omega1.561.601.501.561.641.671.731.741.852.051.68
Sortino0.860.950.780.840.950.991.071.061.221.441.04
Skew0.970.580.09-0.05-0.34-0.48-0.53-0.82-0.84-0.86-0.61
Kurtosis8.414.883.954.252.833.482.664.243.443.161.40
Tail1.211.071.051.041.041.121.091.101.151.260.99
Value At Risk-0.12-0.09-0.09-0.08-0.07-0.07-0.07-0.06-0.05-0.05-0.06
Alpha0.79%1.28%-0.44%0.39%1.67%2.15%2.76%2.92%4.14%5.84%0.00%
Beta1.631.331.261.161.061.070.990.900.800.691.00

Data through 2026-10-26

Comparison

Statistics · Q1

MetricRisk Adjusted Momentum 50Risk Adjusted Momentum 100Risk Adjusted Momentum 200Risk Adjusted Momentum Combined
CAGR10.98%13.97%14.53%11.28%
Cumulative Return1088.392130.542409.741166.82
Annual Volatility28.60%28.07%28.41%28.81%
Sharpe0.500.600.620.51
Calmar0.160.200.210.16
Max Drawdown-69.71%-68.36%-69.79%-69.33%
Omega1.561.661.691.58
Sortino0.861.091.100.88
Skew0.971.261.041.01
Kurtosis8.417.305.928.34
Tail1.211.421.141.26
Value At Risk-0.12-0.12-0.12-0.12
Alpha0.79%3.49%3.76%0.98%
Beta1.631.601.651.64

Data through 2026-10-26

Data

Risk-adjusted momentum factors are available for all the tradable stock equities on the US stock exchanges, including major securities markets such as NYSE, Nasdaq and Dow Jones Industrial.

Coverage · top 10 sectors

SectorCountTypeStart date
Finance1,133Equities2003-01-01
Health Technology775Equities2003-01-01
Technology Services392Equities2003-01-01
Electronic Technology387Equities2003-01-01
Producer Manufacturing304Equities2003-01-01
Consumer Services286Equities2003-01-01
Non-Energy Minerals237Equities2003-01-01
Energy Minerals223Equities2003-01-01
Commercial Services223Equities2003-01-01
Industrial Services194Equities2003-01-01

Delivery & access

Risk-adjusted momentum factors are calculated daily for thousands of stocks.

This data is available via API and CSV download.

Sample data

Documentation

Approach

Risk-adjusted momentum uses a rolling analysis of time series model: 50 days, 100 days, and 200 days. This estimates the coefficients over a rolling window and scaled by the 200 days rolling volatility.

Factors evaluated

In addition to considering price and return, risk-adjusted momentum takes into consideration a volatility scale.

  • ·- Period = 50, it was adjusted by the 50 rolling days of standard deviation - Period = 100, it was adjusted by the 100 rolling days of standard deviation - Period = 200, it was adjusted by the 200 rolling days of standard deviation - Combined risk-adjusted momentum

Methodology

We applied the aforementioned risk-adjusted momentum metrics to a universe of the largest 500 US equities by market capitalization and ranked each stock on its risk-adjusted momentum factor. We then divided the universe into 10 quantiles of stocks, with the top quantile (Q_10) representing stocks with the highest value of that factor and the bottom quantile (Q_1) representing the lowest value of that factor.

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