Monthly Weakness

by Ordertune · part of Institutional Alpha

Seasonal mean reversion, short only
Risk elevated

Monthly Weakness is a short-side seasonal model that trades a recurring window each month in which stocks tend to soften. It only trades while the broader market is in a downtrend and covers within days. In rising markets it stays flat, so it can go months without a trade. Short selling needs a margin account at Alpaca.

Universe: Nasdaq100
Holding period: a few trading days
Order types: market, limit

€479

Institutional Alpha bundle · 25 strategies · per month, net

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Orders go to your own Alpaca account. You set the position size and approve each order until you switch to automatic.

6 Oct 2000 to 3 Nov 2026 · 6,774 trading days

Strategy level

What to expect from the strategy as a whole, measured on the daily return series.

Annual return (CAGR): +4.0%; per year over the full history
Volatility: 8.3%; annualized
Max drawdown: −25.2%; peak to trough
Sharpe ratio: 0.50; risk-free 0%, annualized
Sortino ratio: 0.73; downside deviation only
MAR ratio: 7.06; return ÷ max drawdown

Equity curve

Growth over the full history on a logarithmic scale, so every year weighs the same. The figure that counts here is the annual return above.

Drawdown

How far the value stood below its previous high on each day. Deep or long dips are what an investor has to sit through.

Monthly returns

Compounded from daily returns, net of costs. Year compounds the months shown; an empty cell lies outside the range. ^*Partial month.

Year	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec	Year
2026	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%^*	no data	0.0%^*
2025	0.0%	0.0%	−2.4%	+8.7%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	+6.1%
2024	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%
2023	−2.6%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	−2.6%
2022	0.0%	−0.8%	+3.8%	0.0%	+13.4%	−4.3%	0.0%	0.0%	+0.1%	+8.8%	0.0%	+1.7%	+23.9%
2021	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%
2020	0.0%	0.0%	+2.1%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	+2.1%
2019	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%
2018	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	−1.1%	+6.6%	+5.5%
2017	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%
2016	+2.9%	+6.3%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	+9.4%
2015	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	−0.7%	0.0%	0.0%	0.0%	−0.7%
2014	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	−3.5%	0.0%	0.0%	−3.5%
2013	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%
2012	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	−0.5%	0.0%	−0.5%
2011	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	+0.2%	−0.7%	−3.1%	0.0%	0.0%	−3.6%
2010	0.0%	0.0%	0.0%	0.0%	0.0%	+1.4%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	+1.4%
2009	+5.9%	0.0%	−3.6%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	+2.1%
2008	+13.1%	−2.9%	−1.7%	0.0%	0.0%	+2.7%	+3.8%	0.0%	+6.4%	+14.3%	0.0%	0.0%	+40.0%
2007	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	−1.9%	0.0%	0.0%	+6.6%	0.0%	+4.5%
2006	0.0%	0.0%	0.0%	0.0%	0.0%	+0.5%	+0.7%	0.0%	0.0%	0.0%	0.0%	0.0%	+1.2%
2005	0.0%	0.0%	0.0%	0.0%	−1.1%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	−1.1%
2004	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	+1.9%	0.0%	−0.6%	0.0%	0.0%	+1.3%
2003	0.0%	−6.2%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	−6.2%
2002	+5.8%	+2.0%	0.0%	+1.7%	−6.5%	+11.1%	+10.4%	−5.7%	+3.7%	+1.8%	0.0%	0.0%	+25.3%
2001	+10.7%	0.0%	+4.9%	−6.3%	0.0%	+6.3%	+3.8%	+1.8%	+6.3%	−2.0%	0.0%	0.0%	+27.3%
2000	no data	no data	no data	no data	no data	no data	no data	no data	no data	−17.8%	+5.9%	0.0%	−12.9%

Trade level

Closed trades with an exit inside the range.

Win rate: 60.2%; 221 of 367 closed trades
Avg win: +6.3%; per winning trade
Avg loss: −5.6%; per losing trade
Profit factor: 1.70; gross wins ÷ gross losses
Avg holding: 3d; entry to exit, calendar days
Trades: 367; closed in the range

Closed trades, last 90 days

No trade closed in the last 90 days.

Daily return series 6 Oct 2000 to 3 Nov 2026, supplied by the provider. The provider has not marked a live start, so treat the full series as a backtest: simulated results are a hypothesis, not a promise. Past performance does not predict future returns. Your own results depend on your position sizes, fills and costs.