Account Equity
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Buying Power
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Today's P&L
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Win Rate
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Trades Today
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Signals
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Skipped
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Open Positions
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Cumulative P&L — Today

Open Positions

No open positions.

Manual Trade

Trade Feed (last 20)

No trades yet.

📋 Trade Journal

No executed trades yet.

Trade Journal populates as the bot executes entries. Executed signals and their outcomes appear here.

Executed Trades

Total Trades
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Open
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Wins
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Losses
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Total P&L
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P&L Breakdown — Closed Trades
Win / Loss Split
Filter:

Swing Trade Analysis

Today's Signals

Open Swing Positions

TickerSetupEntryCurrent StopTarget 1Target 2 P&LEnteredHold PlanExpected Exit
No open swing positions

Trade History

DateTickerActionQty PriceStopTarget 1P&LReason
No swing trades yet

Swing Screener

⚡ Momentum Screener

Quantum · AI · Biotech · EV · Space · Crypto-adjacent
⚡ SPECULATIVE — Short-term momentum scoring · MIN SCORE 50 · No MA-stack required
Direction: Setup: Min Score: 50

Performance

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Signal Log

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Manual Tickers Manual

Managed by you. Add or remove anytime — the screener never touches these.

SymbolEnabledOverride rules?

Auto-Screened Tickers Auto · Daily

Top screener tickers by confidence score from each day's screener run. Refreshed every trading day. These are added to the active trading list automatically.

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Global Rules

RISK PRESET: Active: —

Data Providers

Which module gets its data from where. Availability is probed live — a provider with no API key shows as unconfigured, not active. Roles with only one provider have nothing to switch to and say so.

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Bot Controls

Restart Jarvis remotely without needing physical access to the Mac. Restart Bot restarts only main.py (dashboard stays up). Full Restart restarts the bot, dashboard, and Cloudflare tunnel — the dashboard will be unreachable for ~15 seconds while it comes back up.

Per-Ticker Rule Overrides

Leave a field blank to inherit the global value. Only non-blank values are saved as overrides.

✓ Saved

⚙️ Algorithm Management

Both models use strategy_core_adaptive_v2 as the engine. Switching loads different optimized parameters — takes effect on the next trading loop iteration.

V2 uses ADX filter, Fibonacci levels, and relative strength vs SPY
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🧠 Adaptive Learning

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Market Regime

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Learning Progress

Trades logged (10 needed to activate)
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Last optimized: —
Next optimization: —
Active overrides:
None (using base config)

Ticker Heat

Ticker Heat Score Status 5-Day Win Rate
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Signal Intelligence Database

— Trades Logged
— Days of Data
— Last Entry
— · auto-refreshes every 60s

📊 Backtest

Champion Models
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▸ Backtest Output
Trades Taken
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Win Rate
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Total P&L
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Profit Factor
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Max Drawdown
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Signals Gen / Skip
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Gates Fired — Signals Blocked

0
SPY Hard Block
longs blocked
0
Confidence Gate
signals filtered
0
Daily Loss Cap
signals filtered
0
Cooldown
signals filtered
0
Invalid R:R / Size
signals filtered
0
Direction Blocked
signals filtered
0
No Signal (HOLD)
tickers as HOLD
0
Total Evaluated
ticker-bar pairs

Comparison — Actual vs Backtest

Metric Actual (live) Backtest (sim) Δ

Cumulative P&L — Backtest Day

Trade Log

Sort by P&L:

Run a backtest to see trade details.

🧬 Strategy Optimizer

Idle

Research & Promotion

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gate passed
blocked on sessions — needs time, not a better rule
gate failed

How each run has changed things

A run only moves when a new complete session lands. Identical numbers across two runs is the honest answer, not a bug.

RunCandidatesPromotable Best tChange vs previous run

Saved models — out-of-sample check

Each champion was tuned on 5–8 trading days. This replays every model, params frozen, only on days after it was tuned, through backtest.py, then adds the costs the backtest leaves out ($0.01/share + 5 bps per side). Pass = 40+ trades, profit factor ≥ 1.3, ≥ +0.10R per trade after costs, and profitable in at least 2 of 3 periods. Runs in the background (~20 s per model-day); results are cached.
ModelTested onTradesWin % Net $Costs $R / tradePF 3 periods (net $)In-sample $Verdict
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Legacy parameter search — frozen (OPTIMIZER_FREEZE). It maximised win rate and P&L over 10 days and converged on parameters that lost money on their own training window. Kept for reference; the board above replaced it.
WR Model
adaptive_v2_wr
CT=86 · 85.7% WR
Optimise for: Win Rate
P&L Model
adaptive_v2_pnl
CT=84 · $6,978
Optimise for: Total P&L
Trend Aligned
strategy_trend_aligned
CT=75 · ADX=20
Optimise for: Win Rate
Iteration 0 / 12
Days Passing
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Win Rate
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Total P&L
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Per-Day Results

Date W/L P&L Status
Start the optimizer to see results.

Current Params

Waiting for first iteration…

Best Params Found

No best result yet.
⚡ VMC Cipher B Alerts
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📈 Swing Trades

1-hour bars · EMA 7/21 pullback + Range Filter breakout · Multi-week holds
Total Trades
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Win Rate
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Total P&L
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Avg Win
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Avg Loss
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Open Swing Positions

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Trade History

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Latest Signals

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Daily Trade Report

Portfolio Tracker

Long-term holdings · Robinhood & Schwab

Options Desk

Structures chosen by volatility, ranked by expected value per $ risked
Model output — not backtested. Not a recommendation to trade.

Stocks Desk

Trend setups in leaders and laggards, sized by risk and checked against what history says

Alerts

Every Cipher RSI signal, what triggered it, and where the price has gone since

Smart Money

ARK daily trades · Congressional activity · Insider Form 4 buys · 13D/13G filings
FundTickerCompanyDirection WeightChange SharesDate
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PoliticianPartyTickerAsset ActionAmountTrade DateDisclosed
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TickerCompanyInsiderDateFiling
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Filer / FundTickerCompanyTypeDate FiledFiling
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📋 Release Log

Every change made to the Jarvis trading bot — newest first. Revert to any prior algorithm version.
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📊 Stock Research

User Management

Manage who can access the Jarvis dashboard and what they can do.
Username Role Created Status Actions
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My Account