SPX Statistical Mean-Reversion — Independent Replication

Replication of "How a Simple Statistics Strategy beats 95% of Retail Traders" (Royal Trader Substack, 2026-08-26) with rigorous Python + free data.
^GSPC daily · Yahoo Finance (free) 56 years 10% sizing · pyramiding cost + regime + walk-forward checks

Strategy rules (from the article)

Entry
Close after
≤ −2% day
Exit
Fixed N bars
Size / trade
10%
Pyramiding
On
Edge claimed
>60% WR

Buy the index at the close of any day whose open-to-close move is ≤ −threshold (2% primary); sell after a fixed holding period of N bars. Rationale: big intraday down-moves mean unexpected forced selling; market makers absorb and hedge, driving short-term mean reversion (a statistical cousin of the "VIX Rule of 16").

Replication results — 5 article configurations

$100 start · 10% sizing per signal · pyramiding on · zero costs (as the article assumed). Equity marked-to-market daily.

Config Thresh % Hold Trades Win % PF Avg win % Avg loss % Max DD % Total % B&H %

Article vs replication

Side-by-side for the five configurations. Win rates / PF / returns come in lower than the article; max drawdowns line up well once the equity simulation is correct.

Config Trades (us) Trades (art) WR % (us) WR % (art) PF (us) PF (art) MaxDD % (us) MaxDD % (art) Total % (us) Total % (art)

Equity curves — strategy vs buy & hold

The edge is real but modest: at 10% sizing the strategy earns single-digit CAGR while deploying little capital most of the time. Buy & hold dwarfs it — as expected for a diversifier, not a wealth builder.

Robustness checks (not in the article)

Cost sensitivity — 2% / 7d

Cost (bps/side)TradesWin %PFTotal %

Edge survives 10 bps/side, erodes at 20 bps/side. Typical retail round-trip ≈ 5–10 bps — fine for a daily strategy.

Per-decade breakdown — 2% / 7d

DecadeTradesWin %Avg ret/trade %Cum P&L ($)

Edge is not consistent across decades: 1980s lost money, 1970s was a coin flip, and the bulk of gains concentrated in the 2000s (dot-com crash + GFC volatility).

Alternative execution assumptions — 2% / 7d

VariantTradesWin %PFMax DD %Total %

Result is robust to execution assumptions. Notably, no-pyramiding gives the best risk-adjusted profile (PF 1.66, DD −3.4%) — pyramiding is not the source of the edge.

Walk-forward — IS 70% → OOS 30%

Enhancement analysis — can we squeeze more out?

Battery of enhancements tested on the base 2%/7d and 2%/24d configs (56y, zero costs). Full detail in results/enhancement_analysis.csv, combos in enhancement_combos.csv, out-of-sample validation in enhancement_isoos.csv.

1. Freshness — entry lag (2%/7d)

The edge decays fast as the signal ages. Buy the signal-day close; waiting kills the return.

EntryWin %PFTotal %MaxDD %Trades

2. Full enhancement battery (2%/7d)

TestVariant Win %PF Total %MaxDD %Trades

Key: 3% profit target is the single best, robust enhancement on the 7d hold. VIX filter rows use the 1990+ overlap window; the Rule-of-16 rationale does not help. Stops (trailing/ATR) hurt; vol-sizing halves DD at a proportional return cost; cooldown is a risk lever.

3. Combos — 7d & 24d

VariantHoldTrades Win %PF MaxDD %Total %

The 24d trend-filtered config (close > 200d SMA) is the risk-adjusted star — at the cost of trade count and crisis-year returns. An 8% profit target on 24d improves the unfiltered long-hold profile.

4. Out-of-sample validation (IS 70% → OOS 30%)

VariantIS PFOOS PF OOS WR %OOS Total %OOS DD %OOS n

The top enhancers are not overfits — they hold or improve out of sample. See the table for IS vs OOS profit factor, win rate, and drawdown.

Verdict

The edge is real but weaker than advertised. Every configuration wins 56–63% of trades with PF 1.3–1.9 over 56 years — "better than a coin flip" holds. But the article overstates win rates by ~5–8 pts, profit factor by ~30–40%, and total returns by ~2×. Max drawdowns were roughly right once the equity simulation was done correctly.
It is a diversifier, not a standalone strategy. At 10% sizing it returns single-digit CAGR and captures almost none of the secular upside. The concentration of edge in crisis decades (2000s) suggests it's partly a volatility-regime premium rather than a structural mispricing. Use as a hedge against gap-down days alongside other systems — exactly the author's own framing.

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