OrderDynamics
Institutional Alpha

Panic Shield

by Ordertune · part of Institutional Alpha

  • Trend following, short only
  • Risk elevated

Panic Shield is a short-side trend following model built to protect when markets break. It goes short once selling gains momentum and stays short while the downtrend lasts, on the view that fear feeds on itself. It is rarely active and meant as a hedge for sharp market declines. Short selling needs a margin account at Alpaca.

Universe
Nasdaq100
Holding period
as long as the downtrend lasts
Order types
market, limit

€479

Institutional Alpha bundle · 25 strategies · per month, net

Subscribe to Institutional Alpha

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

5 Oct 2026 to 3 Nov 2026 · 22 trading days

Strategy level

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

Return
0.0%
compounded over the range
Volatility
–
needs 30 days
Max drawdown
0.0%
peak to trough
Sharpe ratio
–
needs 30 days
Sortino ratio
–
needs 30 days
MAR ratio
–
return ÷ max drawdown

Equity curve

Compounded from daily returns, net of costs, rebased to 0% at the start of the selected range.

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.

YearJanFebMarAprMayJunJulAugSepOctNovDecYear
2026no datano datano datano datano datano datano datano datano data0.0%*0.0%*no data0.0%*

Trade level

Closed trades with an exit inside the range.

Win rate
–
0 of 0 closed trades
Avg win
–
per winning trade
Avg loss
–
per losing trade
Profit factor
–
gross wins ÷ gross losses
Avg holding
–
entry to exit, calendar days
Trades
0
closed in the range

Closed trades, last 90 days

No trade closed in the last 90 days.

Daily return series 25 Sep 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.