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Analyst & Quant plans

What happened the last time this setup appeared?

Vantra scans a ticker's own price history for prior sessions with matching technical conditions — then shows forward returns over 7, 30, and 90 sessions.

Not a prediction. Historical context — the same kind of quantitative analysis that institutional desks run manually, automated across the full price history of any ticker.

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Output format

Real output format

Live examples are updated each evening after market close.
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How it works

No data vendors, no ML models, no black boxes. Pure statistical analysis on real OHLCV data.

1
You search a ticker
The engine reads the ticker's full OHLCV price history — typically 5–10 years of daily bars — from real market data.
2
We compute the technical posture
RSI 14, MACD 12/26/9, SMA 200 relationship, and trend direction are computed from today's full price history.
3
We scan every prior session
The engine walks backward through the price history and identifies every prior date where the RSI zone, MACD bias, trend direction, and SMA 200 relationship were all similar to today.
4
We measure what happened next
For each matched session, we look forward and record the price 7, 30, and 90 trading sessions later. We compute the median, average, best, worst, and rate of positive outcomes.
5
You see the historical context
The results show how this specific ticker has historically behaved after technical setups similar to today's — as observational context, not a prediction.
What it is
Historical statistical context from the ticker's own price history
A description of how similar technical setups have resolved, on average, in the past
The same quantitative analysis institutional research desks do manually
Computed fresh from real OHLCV data per ticker per day
What it isn't
A prediction of what this ticker will do
Investment advice or a trading signal
A guarantee that history will repeat
A buy or sell recommendation

Available on Analyst and Quant

Scout plan shows basic indicators. Analyst and Quant unlock the full Historical Pattern Engine.

Scout
$0
·RSI, MACD, CCI
·SMA / EMA stack
·1 pattern signal
·3 lookups/day
Analyst
$19/mo
·Full indicator suite
·Historical Pattern Engine
·25 lookups/day
·Research Desk (5 symbols)
Quant
$49/mo
·Everything in Analyst
·Written research synthesis
·Unlimited lookups
·Research Desk (20 symbols)

Frequently asked questions

How many historical matches are typical?

It depends on the ticker and the specificity of the current conditions. Common setups on liquid stocks like AAPL or SPY might have 30–80 prior matches. Unusual conditions or thinly-traded tickers may have fewer. The match count is always displayed so you can weight the evidence appropriately.

What data does the engine use?

Real OHLCV (Open, High, Low, Close, Volume) daily bar data from public market data providers. No proprietary data, no alternative data feeds. The engine runs on the same data your broker shows you.

How is this different from backtesting?

Traditional backtesting runs a fixed rule on historical data and measures aggregate performance. Vantra's Historical Pattern Engine computes your current conditions dynamically and finds prior dates where those specific conditions existed simultaneously — RSI zone, MACD bias, trend, and SMA200 position all matching. It's condition-specific historical analysis, not a generic strategy backtest.

Is this a trading signal?

No. The Historical Pattern Engine provides observational, statistical context — describing what has happened historically under similar conditions. It does not provide recommendations, ratings, price targets, or any guidance about what action to take. Vantra is a research platform.

Which exchanges are supported?

NYSE, NASDAQ, LSE (UK), XETRA (Germany), Euronext (France), TSE (Japan), HKEX (Hong Kong), NSE (India), TSX (Canada), and ASX (Australia). Use the standard ticker with the appropriate suffix: RELIANCE.NS, VOD.L, 7203.T, etc.

Run it on your next analysis

Free to start. Upgrade to Analyst for the full Pattern Engine.

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No credit card required · Historical context only, not investment advice

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