Paper Trades / APT / APT — May 2025 (v4.0.1 Pythia)
CURRENT · OMNISCIUS v4.0.1 · PYTHIA

APT Aptos Paper Trade

APT — May 2025 (v4.0.1 Pythia) — Simulated live trading results using the v4.0.1 Pythia model.

v4.0.1 Pythia 11 Trades Completed
Walk-forward validated Backtest = Live (bit-identical) Net of fees (0.15% / 0.25%) Forward-look-bias audited

Aptos (APT) is a Layer 1 blockchain built by former members of Meta's Diem project. Using the Move programming language, Aptos focuses on safety, scalability, and user experience. As a newer asset with high institutional backing, APT shows strong trending behavior during market sentiment shifts. Our model tracks its momentum patterns and cross-correlation with other Layer 1 tokens for signal generation.

APT — May 2025 (v4.0.1 Pythia) Performancev4.2 Theros

Aptos (APT) — clean monthly entry, no carry-over from previous months. Net of trading fees (Bitvavo 0.15% + 0.25%).

Sharpe
15.71
Alpha vs B&H
+99.00pp
Risk / Reward
59.04×
B&H Return
-8.32%
Max Drawdown
-1.54%
Avg Drawdown
-3.88%
Sharpe Trend
-3.78
Model
v4.0.1 Pythia
Full Backtest

Side-by-side: model versions

Same coin, same period, same data window — different model. All walk-forward validated. v4.0.1 (Pythia) is the current production model; v4.0 (Itzamná) confirmed the statistical edge across 46 coins; v2.5 is the legacy baseline.

v4.0.1 PYTHIA THIS PAGE
Return
+90.68%
Win Rate
90.9%
Sharpe
15.71
Alpha vs B&H
+99.00pp
Max DD
-1.54%
Avg DD
-3.88%
Risk / Reward
59.04×
Trades
11
v4.0 ITZAMNÁ
Return
+90.31%
▲ +0.37
Win Rate
92.9%
▼ -1.99
Sharpe
0.00
▲ +15.71
Alpha vs B&H
+0.00pp
▲ +99.00
Max DD
-4.77%
▲ +3.23
Avg DD
0.00%
▼ -3.88
Risk / Reward
0.00×
Trades
11
Open v4.0 page →
V2.5.8.3
Return
+52.40%
▲ +38.28
Win Rate
76.5%
▲ +14.41
Sharpe
0.00
▲ +15.71
Alpha vs B&H
+0.00pp
▲ +99.00
Max DD
-0.29%
▼ -1.25
Avg DD
0.00%
▼ -3.88
Risk / Reward
0.00×
Trades
17
Open page →

Δ-arrows on the counterpart cards show this page minus that version. Higher return / WR = better; smaller (less negative) Max DD = better.

APT

APT Monthly Returns (v4.0.1 Pythia)

Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Year Σ
2025 +47.4%
15t
+83.1%
15t
+39.2%
14t
+43.3%
12t
+90.7%
11t
+87.9%
17t
+64.8%
13t
+57.2%
12t
+4,896.7%

All months for APT under this model. Click a cell to drill into that month's trade log. Color intensity = magnitude.

Day-by-day — APT — May 2025 (v4.0.1 Pythia) — compounded daily PnL within this period

Mon
Tue
Wed
Thu
Fri
Sat
Sun
1
2
3
4
5
6
7
8
9
+17.6
10
11
+9.5
12
+1.2
13
+8.8
14
15
16
17
18
+3.7
19
20
+7.1
21
22
23
+13.5
24
+1.1
25
26
+3.3
27
28
-1.5
29
30
+1.1
31
Smart Insights
  • Exceptional return: +90.7% — compound across the full walk-forward window.
  • High win rate: 90.9% — 4 in 5 trades close in profit.
  • Tight risk control: max drawdown only -1.5%.
  • Strongest regime: BULL — avg +9.29% on 4 trades, WR 100%.

Per-regime Breakdownv4.2 Theros

How the model performs across the 4 market regimes detected by Omniscius.

Regime Trades Win Rate Avg PnL Compounded Return Avg Hold
BULL 4 100.0% +9.29% +41.86% 1.3d
BUBBLE 7 85.7% +4.04% +31.05% 19h

Trade Logv4.2 Theros

All 11 trades executed during this paper trade period.

EntryExitEntry PriceExit PricePnLRegimeDuration
$0.00 $0.00 +17.62% BULL 2.5d
$0.00 $0.00 +9.55% BULL 1.3d
$0.00 $0.00 +1.17% BULL 12h
$0.00 $0.00 +8.82% BULL 18h
$0.00 $0.00 +3.70% BUBBLE 13h
$0.00 $0.00 +7.07% BUBBLE 22h
$0.00 $0.00 +13.53% BUBBLE 2.5d
$0.00 $0.00 +1.14% BUBBLE 7h
$0.00 $0.00 +3.27% BUBBLE 1.2d
$0.00 $0.00 -1.54% BUBBLE 3h
$0.00 $0.00 +1.09% BUBBLE 3h

Frequently Asked Questions

What is a paper trade?

A paper trade simulates real signal execution without real money. Each month starts fresh with a clean €10,000 allocation — no carry-over from previous months. This shows exactly what would have happened if you started following signals on day one of that month. View live APT signals →

Are trading fees included?

Yes. All results are net of trading fees based on Bitvavo rates (0.15% entry + 0.25% exit). No slippage is applied. Trading via Bitget (0.1%/0.1%) would improve returns.

How does this relate to the backtest?

Paper trades use the same model and signals as the full backtest. The difference: backtests cover years of data across multiple market cycles, while paper trades show month-by-month performance in recent market conditions. Together they provide a complete picture.

Is the model retrained during the month?

Yes. The Omniscius model is retrained bi-weekly, which means paper trade results reflect the exact same model updates that live subscribers receive. This is not a static backtest — it is a living simulation. Learn about Omniscius →

Start Trading Aptos Smarter

These paper trade results show what our model delivers. Get real-time APT signals with entry, stop-loss, and take-profit on every trade.

90.9% Win Rate +90.7% Return -1.5% Max Drawdown Net of Fees