The Systems Scorecard

In 2022, a year in which US stocks and bonds fell together, the oldest trading system in this book had one of its best years. The SG Trend Index, which tracks large trend-following managers, gained 27.3%; Dunn Capital's World Monetary and Agriculture programme gained 60.24%, Campbell's Fund Trust 36.01% (audited, net of fees) and Aspect Diversified 40.46% (companion's profiles). A balanced fund holding 60% stocks and 40% bonds, Vanguard's VBINX, lost 17.0% (net of fund fees), and a public risk-parity fund lost 22.8%. In the same years the fastest-growing trade among US individuals was selling and buying S&P 500 options on their day of expiry, whose share of SPX volume rose from about 47% in 2024 to a record 66.2% in July 2026 (Cboe). The research catalogue behind this book grades the first, time-series momentum across diversified futures, A, and selling same-day options for premium D/F.

The two grades sum up what the catalogue found. It documents 118 trading systems in 13 families, from covered calls to machine-learning bots, and grades each on the evidence that it makes money after costs for the people who use it. Four earn an A, and three of those four are A only for the firms that run them. One A is available to anyone who can hold a diversified futures portfolio and wait out a lean decade. Most systems sit in the middle, in grades that mean "real but modest, decayed, or paid for with crash risk", and a large minority, most of them sold to individual traders, have no credible evidence or credible evidence against them.

This chapter puts the catalogue's grades in one view. It explains how the grades were set and what they do not mean, sets out which systems make money, for whom and at what risk, lists what the evidence does not support, and shows with a stylized calculation why most grades cannot be raised by a few more years of results. It closes with the question each chapter has asked of its cases: which factor of the edge equation does each part of the scorecard turn on?