Long-only inverse-volatility across the full macro universe

The comparison portfolio for the trend and seasonality strategies: own everything, all the time, with each market sized so it contributes a similar share of the risk. Beating this is the minimum bar.

Conclusion: Control

A benchmark, not a candidate. Held continuously it returned 6.0% a year at 12.5% volatility, with a worst fall of 61.9% over 658 months. Strategies are measured against this.

Figure 1 · Growth of $1

1971–2026 · net of 15bp round-trip costs
What one dollar became, after costs: $26.29 by 2026. Shown against S&P 500, rebased to the same starting dollar.
Return for risk
0.48
range 0.20 to 0.77
Ann. return
6.0%
volatility 12.5%
Max drawdown
61.9%
over 658 months
Beats the search
8.4%
chance, after correction

Method

Hypothesis

Risk-parity long-only benchmark. Any P-series L/S premia strategy above must earn its keep versus just owning this.

Rule

UNIVERSE = futures, FX and equity indices
function positions(bar):
# no signal, no timing: always fully invested
for symbol in UNIVERSE:
w[symbol] = 1 / vol_36m(symbol, bar.prev) # equal risk
return w
# ── execution ────────────────────────────────────────────────────────
COST_PER_TRADE = 15 bps of the notional that changes hands
function on_bar(bar, book):
if not bar.is_month_end:
return # decisions are made monthly only
target = positions(bar) # the rule above
target = scale_to_gross(target, 1.0)
rebalance(book, target, bar)
function scale_to_gross(w, limit):
gross = sum(abs(w)) # total capital at work
if gross == 0:
return w # flat is a valid target
return w * limit / gross # leverage fixed, never implicit
function rebalance(book, target, bar):
for symbol in union(book.symbols, target.symbols):
delta = target[symbol] - book.weight(symbol)
if delta > 0:
buy(symbol, delta, fill = next_bar.close)
else if delta < 0:
sell(symbol, -delta, fill = next_bar.close)
book.charge(COST_PER_TRADE * abs(delta))
# Orders are filled at the next month's close, never the one the decision
# was made on. There is no stop_loss(), take_profit(), limit order or
# position cap: a holding changes only when positions() returns a
# different target at the next month end.

Evaluation

Table 1 · Performance

1971-09 – 2026-06 · 658 months, 658 invested
MeasureValue
Annualised return6.0%
Annualised volatility12.5%
Return for risk taken0.48
95% range0.20 to 0.77
t-statistic3.53
Maximum drawdown61.9%
Hit rate57.9%
Annual turnover0.26×
Return skew(0.80)
Return kurtosis9.05
The range is measured by resampling the history in blocks, so runs of good and bad months stay intact.

Table 2 · Robustness

DiagnosticValueReads asBadOkayYayHmm
Design half (pre-2015)0.47return for risk≤ 00 – 0.40≥ 0.40
Holdout half (2015+)0.74return for risk≤ 00 – 0.40≥ 0.40
Top-5-month share of profit18.7%how much rode on a few months — lower is better≥ 40%25 – 40%< 25%
Top-2-year share of profit16.5%concentration
Distinct trading episodes1how many independent runs this really is< 5050 – 100≥ 100
Chance the edge is real100.0%non-normality corrected
Chance it beats the whole search8.4%chance of beating the whole search by luck
bad/ok boundary is the pre-registered criterion · ok/good is a margin above it, not a criterion · blank where none was registered
The last row asks whether the result would stand out from the hundred-odd ideas tried here, rather than being judged alone.

Table 3 · Net return by calendar year

after costs
+35%-35%
YearNet return
19712.9%
197214.5%
1973(19.1%)
1974(35.3%)
197527.4%
197617.5%
1977(12.2%)
19781.1%
197911.6%
198022.9%
1981(10.2%)
198213.8%
198315.9%
19841.4%
198523.4%
198613.7%
19872.0%
198811.7%
198924.1%
1990(6.8%)
199123.4%
19924.4%
19936.8%
1994(5.1%)
199520.0%
199618.2%
19971.0%
19985.0%
199926.7%
2000(6.0%)
2001(11.8%)
200210.7%
200313.5%
20046.1%
20059.5%
200613.1%
200711.9%
2008(14.5%)
200911.8%
201013.5%
2011(1.7%)
20124.9%
20131.4%
20142.4%
2015(2.0%)
20160.1%
20174.7%
2018(0.9%)
20197.4%
20207.8%
20219.0%
20222.4%
20232.0%
20246.3%
20251.3%
20263.6%

Table 4 · Concentration detail

MeasureValue
Best years1975:+27%, 1999:+27%, 1989:+24%
Worst year1974:-35%

Reference

Instruments

last price and one-month change, live from Yahoo Finance
SymbolNotes
ZW=FChicago SRW Wheat — continuous futures on CBOT, quoted in US cents.
KE=FKC HRW Wheat — continuous futures on CBOT, quoted in US cents.
ZC=FCorn — continuous futures on CBOT, quoted in US cents.
ZS=FSoybeans — continuous futures on CBOT, quoted in US cents.
ZM=FSoybean Meal — continuous futures on CBOT, in USD.
ZL=FSoybean Oil — continuous futures on CBOT, quoted in US cents.
ZR=FRough Rice — continuous futures on CBOT, in USD.
SB=FSugar No. 11 — continuous futures on ICE Futures, quoted in US cents.
KC=FCoffee C — continuous futures on ICE Futures, quoted in US cents.
CC=FCocoa — continuous futures on ICE Futures, in USD.
CT=FCotton No. 2 — continuous futures on ICE Futures, quoted in US cents.
OJ=FOrange Juice — continuous futures on ICE Futures, quoted in US cents.
LE=FLive Cattle — continuous futures on CME, quoted in US cents.
GF=FFeeder Cattle — continuous futures on CME, quoted in US cents.
list truncated in the source record

Sample

1971-09 – 2026-06 · 658 months

Sources

NOAA Physical Sciences Laboratory. Climate indices. ONI, Niño 3.4, MEI v2, DMI, PDO, AMO, TNA, QBO, solar flux. psl.noaa.gov/data/climateindices/list
Queensland Department of Agriculture and Fisheries. Southern Oscillation Index. The Long Paddock. Monthly, 1876–. www.longpaddock.qld.gov.au/soi/soi-data-files
Yahoo Finance. Historical market prices. Adjusted close, month-end. Retrieved with yfinance. finance.yahoo.com

Revision history

RevStageStatusChange
01DraftDirection and criteria fixed before the experiment ran
02TestedControlBenchmark, not scored against the criteria