Research Lab
Primary research workspace with price action, key studies, and bias signals.
Price
VWAP
EMA 20
EMA 50
SMA 50
SMA 200
MACD (12, 26, 9)
Price i
Pros: Most direct view of current market value and momentum direction.
Cons: Can be noisy without trend anchors like VWAP/EMA/SMA.
Cons: Can be noisy without trend anchors like VWAP/EMA/SMA.
$0.00 spot
VWAP i
Pros: Tracks institutional price fair value; great for intraday bias.
Cons: Less useful across multi-day horizons; can be noisy in low volume.
Cons: Less useful across multi-day horizons; can be noisy in low volume.
$0.00 anchor: intraday
EMA 20 i
Pros: Responsive to short-term trend shifts; useful for momentum checks.
Cons: Whipsaws in chop; overreacts to single spikes.
Cons: Whipsaws in chop; overreacts to single spikes.
$0.00 trend
EMA 50 i
Pros: Smooths noise while still reacting to trend changes.
Cons: Slower in fast reversals; can lag after sharp moves.
Cons: Slower in fast reversals; can lag after sharp moves.
$0.00 trend
SMA 50 i
Pros: Widely watched mid-term trend filter; good support/resistance proxy.
Cons: More lag than EMA; misses early turns.
Cons: More lag than EMA; misses early turns.
$0.00 trend
SMA 200 i
Pros: Long-term trend anchor; strong regime signal.
Cons: Very laggy; poor for short-term timing.
Cons: Very laggy; poor for short-term timing.
$0.00 trend
MACD i
Pros: Combines momentum + trend; highlights shifts and divergences.
Cons: Lags in fast reversals; false signals in sideways markets.
Cons: Lags in fast reversals; false signals in sideways markets.
0.000 12/26/9
Bias Read i
Pros: Blends VWAP + SMA alignment into a single read.
Cons: Can mask conflicting signals; depends on indicator quality.
Notes: Bias Read blends price vs VWAP, SMA 50, and SMA 200 to summarize trend alignment.
Cons: Can mask conflicting signals; depends on indicator quality.
Notes: Bias Read blends price vs VWAP, SMA 50, and SMA 200 to summarize trend alignment.
Neutral blend
Pro tier required.
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Run Anomaly Scan
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This table shows potential anomalies detected in your portfolio:
- Symbol - Ticker where the anomaly was found.
- Type - What kind of anomaly it is (e.g. drawdown, spike, volume).
- Severity - How important it is (Low, Medium, High).
- Metrics - Extra details used by the model (z-scores, thresholds, etc.).
- Detected At - When the anomaly was identified.
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| Symbol | Type | Severity | Metrics | Detected At |
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