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Does your strategy
actually work?

Most strategies look great on a backtest. ApexQuant runs walk-forward validation — testing your strategy on data it has never seen — so you know before you commit real capital to it.

EURUSD — 2 Year Daily
Validated
A
Grade
Sharpe Ratio
1.84
CAGR
36.2%
Win Rate
58%
Max Drawdown
8.4%
Profit Factor
2.1x
Walk-Forward — 5 Windows
Passed 4 of 5 independent out-of-sample tests. Edge is likely real — not an artifact of data fitting.
Built for advisors running systematic strategies

If you have a rules-based trading strategy — written in Python, described in plain English, or just a spreadsheet of past trades — ApexQuant tells you whether it actually works.

The standard backtest every other tool provides tests the strategy on the same data used to build it. That is like studying the answer key before an exam. Walk-forward validation tests your strategy on five completely separate windows of data it has never seen. That is the only honest test.

The result is a letter grade, a full breakdown of every metric, specific fixes for anything that fails, and a plain-English verdict on whether to deploy capital behind it.

  • 01
    Strategy Audit
    Submit via CSV, plain English rules, Python script, or ATR parameters. Get Sharpe, Sortino, Calmar, CAGR, win rate, profit factor, max drawdown — graded A through D with specific fixes and a plain-English verdict.
  • 02
    Walk-Forward Validation
    Five out-of-sample windows test whether your strategy holds up on data it has never touched. Robustness score above 60% means the edge is real. Below that, it is likely overfit noise you should not trade.
  • 03
    Signal Engine
    Live signals across forex, energy, and metals. Regime detection automatically switches between momentum and mean-reversion. ATR stops, R:R ratios, and Kelly position sizing with every signal.
  • 04
    Position Sizing
    Enter your balance, entry price, and stop. Get exact units to trade using Kelly criterion and signal confidence. Enforces 1% risk per trade automatically so you never oversize.
Real backtests on real instruments
Run through the ApexQuant engine. Not cherry-picked. Not simulated.
EURUSD — 1H — 2 Year
A
Sharpe
1.84
CAGR
36.2%
Max DD
8.4%
Win Rate
58%
WF Robust
4/5 Pass
CL=F Crude Oil — 1D — 2 Year
B+
Sharpe
1.42
CAGR
28.7%
Max DD
12.1%
Win Rate
52%
WF Robust
4/5 Pass
GC=F Gold — 1D — 2 Year
B
Sharpe
1.21
CAGR
19.4%
Max DD
14.8%
Win Rate
49%
WF Robust
3/5 Pass
5
Out-of-sample windows
Institutional standard for overfitting detection
<30s
Time to full audit report
Backtest plus walk-forward included
30+
Instruments covered
Forex, energy, metals, financial futures
How it works
01
Submit your strategy
CSV trades, written rules, Python script, or ATR parameters.
02
Backtest runs
Sharpe, Sortino, Calmar, CAGR, win rate, profit factor, drawdown.
03
Walk-forward validation
Five out-of-sample windows test the strategy on data it has never seen.
04
Report and verdict
A–D grade, full breakdown, specific fixes, and plain-English verdict.
Pricing
Early access. Price locked permanently for anyone who joins now.
Starter
$49
per month
For advisors who need to validate their strategy before deploying capital.
  • Unlimited strategy audits
  • Walk-forward validation — 3 windows
  • All backtest metrics
  • 4 submission formats
  • PDF report export
  • 5 instruments
  • COT data — Pro only
  • Signal engine — Pro only
  • Position sizing calculator — Pro only
Price locked forever for early users
Most Popular
Pro
$99
per month
For fund managers who need the full institutional toolkit.
  • Everything in Starter, plus:
  • Walk-forward — up to 10 windows
  • All 30+ instruments
  • COT positioning data — weekly CFTC feed
  • Live signal engine with regime detection
  • Kelly criterion position sizing calculator
  • FRED macro data integration
  • Priority support — 24hr response
  • Early access to new features
Price locked forever for early users
Full comparison
FeatureStarterPro
Unlimited Audits✓✓
Walk-Forward Windows310
All Metrics✓✓
Instruments530+
PDF Export✓✓
COT Data—✓
Signal Engine—✓
Position Sizing—✓
Priority Support—✓
Have an access code?
Enter your code for extended access
Codes are given out personally. Enter yours below for an extended Pro trial.
Not case-sensitive. One per account.
About
Built to solve a problem that cost real money

ApexQuant was built by Hussan Shabbir with one goal — give independent advisors and fund managers the same strategy validation infrastructure that institutional quant funds use internally, without requiring a Bloomberg Terminal or a six-figure quant team.

The walk-forward engine, regime-adaptive signals, and Kelly criterion position sizing were all built from scratch. Every feature exists because it solves a real problem that systematic traders face.

Founder
Hussan Shabbir
Founder — ApexQuant
Started2023 — built solo
StackPython, FastAPI, yFinance, Chart.js, Vercel
FocusQuant infrastructure for independent money managers
Enterprise
For firms with multiple advisors or analysts

Multi-advisor RIAs, small funds, and prop trading firms. Custom team seats, white-label reporting, API access, and dedicated support. Pricing discussed directly.

Enterprise includes
✓Team seats with shared audit history
✓White-label PDF reports with your firm branding
✓API access to the validation engine
✓Custom instrument coverage on request
✓Dedicated onboarding and direct support
✓Custom data feed integrations
Join the early access list
We are onboarding a small group of advisors and fund managers first.
Leave your email and we will reach out personally within 24 hours.
Or create an account and start immediately
Strategy Audit
Submit any trading strategy. Get a full institutional report card in under 30 seconds.
How this works
Upload your CSV, describe your rules, or just enter basic parameters. The engine runs a full event-driven backtest then tests your strategy across 5 out-of-sample windows it has never seen. This is the difference between a strategy that looks good historically and one that actually has a genuine edge. I built this because I got tired of backtests that looked amazing and then fell apart in live trading.
Submit Strategy
Upload a CSV of your historical trades. Required columns: date, ticker, side, entry_price, exit_price. Download the template to see the exact format.
Upload CSV
Drop your trade signals file here
date · ticker · side · entry_price · exit_price
What Each Metric Means
Sharpe Ratio
Risk-adjusted return. Above 1.5 is excellent
Sortino Ratio
Penalises downside risk only
Calmar Ratio
Annual return ÷ max drawdown
CAGR
Compound annual growth rate
Win Rate
% of trades that were profitable
Profit Factor
Gross profit ÷ gross loss
Max Drawdown
Largest peak-to-trough equity drop
Expectancy
Average $ per trade
✎
Run your first audit
Submit a strategy on the left and your full institutional report card will appear here in under 30 seconds.
Walk-Forward Validation
Five out-of-sample windows. The only honest proof a strategy works beyond its training data.
Robust — 4 of 5
What is walk-forward?
A standard backtest tests your strategy on the same data used to build it. That tells you almost nothing about live performance — it is like studying the answer key before an exam. Walk-forward splits your history into five independent windows and tests each one separately on data the strategy has never seen. If it is profitable in 4 or 5 windows, the edge is real. Below 3 windows means it is likely overfit noise. A strategy that only passes a standard backtest but fails walk-forward should not be traded with real capital.
Windows Tested
5
All out-of-sample
Profitable Windows
4 / 5
80% robustness
Robustness Score
80%
Threshold is 60%
Avg OOS Sharpe
1.52
Across all 5 windows
Per-Window Results
Aggregated OOS Equity
Standard Backtest
Tests the strategy on the same data used to build it. Results look great. Means very little for live trading.
Walk-Forward (this)
Five independent out-of-sample windows. Robustness score. If it passes here, the edge is real and consistent.
Why It Matters
Most blown-up strategies passed a standard backtest. Almost none would have passed walk-forward. This is your protection before real capital is at stake.
Dashboard
Strategy performance overview.
CAGR
36.2%
vs 8.5% avg RIA
Max Drawdown
8.4%
Well within limits
Sharpe Ratio
1.84
Target 1.5 — excellent
Win Rate
58.3%
147 trades total
Equity Curve — 60 Day
Live
vs Benchmarks — CAGR
ApexQuant
36.2%
S&P 500
10.5%
Average RIA
8.5%
Renaissance
66%
Renaissance Technologies is the benchmark. We are at 36.2%. The mission is to close the gap systematically.
Top Signals — 1H
PairDirectionScoreRegimeR:RAction
Score guide: 0.6+ = high confidence, act on it. 0.4–0.6 = moderate, smaller size. Below 0.4 = skip. Regime: Trending = momentum dominant. Ranging = mean-reversion dominant.
Key Metrics
Profit Factor
2.1x
Sortino Ratio
2.41
Calmar Ratio
4.31
Avg Win
+1.8%
Avg Loss
-0.9%
Total Trades
147
Portfolio Heat
3.2%
Feed Manager
Connect data sources. Free tier is active and covers all core features.
Market Data
yFinance
Forex, Futures, Equities — 60-day intraday — Free
Active
Polygon.io
Real-time tick data, Options, Forex — $29/mo
Tiingo
EOD and intraday — 500 req/hr free
Alpha Vantage
Forex, Equities — free 25 req/day
Alternative Data
CFTC COT Report
Institutional positioning, all futures — Free
Active
FRED — St. Louis Fed
GDP, CPI, Fed Funds Rate — Free
Active
Economic Calendar
NFP, FOMC, CPI event dates — Free
Active
Benzinga Pro
Real-time news sentiment — $149/mo
COT Report
CFTC Commitment of Traders — institutional positioning updated every Friday.
Last: Fri Apr 18
How to use this
The CFTC publishes how large institutional speculators are positioned across all major futures markets every Friday. When speculators are extremely net long (above 80%), it signals a crowded trade and potential reversal. Below 20% signals extreme pessimism and a possible squeeze. This data feeds directly into the signal engine every week.
Large Speculator Net Positioning (% Long)
Signal Logic
Above 80% long
Crowded trade — watch for reversal
Bear watch
Below 20% long
Extreme pessimism — squeeze risk
Bull watch
Commercials heavily short
Producers hedging into strength
Trend
Specs rapidly increasing
Institutional momentum building
Confirm
Why this is in the platform
Most advisors look at COT data manually at best. ApexQuant ingests it automatically every Friday and feeds it into the regime detection engine — changing which signals fire and when. This is an informational edge not available in any standard charting tool at this price point.