APEX · Backtest Engine

// run summary 2024-01-01 → 2024-12-31 · 252 trading days

filter trades by entry-bar pattern

Total Return +34.7% ▲ vs SPY: +18.2%

Sharpe Ratio 2.41 benchmark: 1.08

Max Drawdown -8.3% duration: 14d

Win Rate 67.4% 714 / 1,059 trades

Profit Factor 2.08 ▲ above target

equity curve

+$34,712 MDD $8,300

trade p&l distribution 252 trades

avg win +$312 avg loss -$150

trade log 7 recent

Time	Symbol	Side	Qty	Entry	Exit	P&L	Status

risk metrics healthy

Sharpe Ratio2.41

Sortino Ratio3.18

Calmar Ratio4.18

Max Drawdown-8.3%

VaR (95%)-$2,140

Expectancy / trade$0

Avg R multiple+0.00R

Exposure Limit Usage

Long

62%

Short

28%

Drawdown

83%

// robustness underwater curve and execution-cost sensitivity

drawdown underwater trough —

slippage stress PF @ 3t —

Adverse	Profit Factor	Return %	Net $	Winners

// monte carlo · walk-forward bootstrap on trade order · 1000 iterations

monte carlo equity fan P(profit) —

P(profit)—

5th pct $—

95th pct $—

Med MDD—

Worst MDD—

Iters—

walk-forward windows — windows

#	Range	N	Return	PF	WR	MDD

// attribution where does P&L come from?

time of day (entry hour ET) — buckets

day of week — days

exit reason — reasons

regime breakdown — regimes

// stability streak control + rolling risk-adjusted return

streak analysis current —

Max Win Streak—

Max Loss Streak—

Current—

rolling sharpe (10 trades) window 10

// strategy comparison click any row to switch strategy

all strategies on this dataset — strategies

Key	Strategy	N	Return	WR	PF	MDD	Sharpe	Expect/T	Status	Run

// data feeds last built —

Source CSV—

Bars / Footprintmes_bars.csv · mes_footprint.csv (frozen, 12mo, Databento MDP3)

Generated at—

Build commandpython build_dashboard.py --all