FINIO MODEL / FINANCIAL PROBABILITY

One forecast.
Many financial
questions.

Finio turns market data into probabilistic forecasts you can question.

Generate one forecast for an asset and ask about returns, outperformance, drawdowns, volatility, and more, all from the same probabilistic view.

FINIO MODELv0.3 / BETA
NVDAONE FORECAST, MANY QUESTIONS
What is the chance NVDA beats SPY over 20 trading sessions?

EXAMPLE FORECASTHISTORICAL ARCHIVE

55.7%

Chance NVDA beats SPY over the next 20 trading sessions.

55.7%
Inspect scored source rows ↗
About this example

SAME FORECAST: v03-NVDA-2026-07-07. The archive key is not a saved live forecast ID. Each answer is a recorded model probability, not an observed outcome. No per-query training. This preview makes no production requests.

TRY FINIO

Start with an asset.

Choose a model, then generate your forecast in the live workspace.

MODEL EVOLUTION

Three generations.
One direction: measurable progress.

From a fixed event classifier to reusable statistical forecasts and a learned distribution. Each generation expands the questions you can ask.

Model evolution, not a performance chart.

v0.1HISTORICAL

Historical classifier.

The original classifier estimates the chance of a positive return over five trading sessions.

One symbol · one event · five sessions

View v0.1 →Historical model card ↗
v0.2EXPERIMENTAL

Reusable statistical forecast.

A statistical model samples paired stock and SPY paths from recent historical returns.

Returns · SPY comparison · risk · ranges

View v0.2 →Inspect v0.2 evidence ↗
v0.3BETA / LEARNED

Learned probabilistic model.

A frozen learned model generates stock and SPY scenarios. Additional questions reuse the same forecast.

Returns · SPY comparison · risk · ranges

Run v0.3 →Inspect v0.3 evidence ↗

These are research estimates, not buy or sell advice. v0.3’s Beta label comes from its historical release criteria; it does not establish live predictive accuracy.

Open the original v0.1 live classifier

v0.1 / HISTORICAL BASELINE

Original v0.1 live model

A fixed five-trading-session positive-return estimate. Successful requests create a public record. Pending means no outcome has been recorded.

Use a US stock symbol such as AAPL or NVDA. Five sessions means trading days, excluding market closures. Each successful request creates a public prediction record.

A live request creates a production prediction record.

HOW FINIO WORKS

A forecast you can question.
An answer you can measure.

v0.2 and v0.3 reduce one reusable scenario distribution into probabilities for supported financial events.

01 / ONE FORECAST

Model the market state.

Generate paired asset and SPY scenarios from completed-session market data. The forecast stays fixed while you ask questions.

02 / MANY QUESTIONS

Change the question.

Explore return direction and thresholds, SPY outperformance, daily-close drawdown, volatility and supported return ranges over 1-20 trading sessions.

03 / MEASURABLE ANSWERS

Get a probability.

A supported question becomes a typed event. Finio counts the modeled paths that satisfy it, with no additional forecast generation or training.

04 / REALITY GRADES THE MODEL

Return to the record.

Saved predictions carry timestamps and model versions. Later recorded outcomes can be evaluated separately from simulations and historical tests.

FINIO MODEL EVIDENCE

We measure our claims
across model generations.

Three model generations. A measurable progression from fixed-task classification to reusable, learned forecasts.

Historical forecast records2,305
Unique assets evaluated293
Event decision records17,283
Model generations3

Archive scope across v0.1, v0.2 and v0.3. Row-backed totals cover v0.2 and v0.3 only; supplied v0.1 figures are kept separate. Records count each model, asset, origin and question once. Shared market cases across versions remain separate model records, not independent trials. Assets are counted once across versions.

v0.1 / HISTORICAL

Original fixed-task model

One question. One horizon.

23,774 held-out samples

Supplied figures. Primary Brier 0.251623; constant baseline 0.251618. Row artifacts unavailable here; excluded from archive totals.

View v0.1 history →

v0.2 / EXPERIMENTAL

Reusable statistical forecast

One forecast. Many questions.

1,157 historical forecasts

Primary Brier 0.249858. Positive 5-session return; AAPL benchmark proxy for other events.

View v0.2 evidence →

v0.3 / BETA

Learned probabilistic model

Shared learned asset and SPY distribution.

1,148 historical forecasts

Primary Brier 0.246779. Positive 5-session return; actual SPY benchmark for other events.

View v0.3 evidence →

Row-backed evaluation period: 2026-07-02 to 2026-10-29. Scores, baselines and protocols stay per model; these snapshots are not a head-to-head ranking. No overall predictive edge is established. Prospective production totals require an audited export.

Inspect the original v0.1 model card and historical figures

These figures were supplied by Finio. The underlying v0.1 evaluation artifacts are absent from this checkout, so they could not be independently reproduced here.

MODEL SPECIFICATION / v0.1 HISTORICAL

finio-model-v0.1

Shared cross-asset classifier

HISTORICAL BASELINE
Primary horizon
5 trading days
Training securities
295
Training samples
314,234
Held-out samples
23,774
Training period
Jan 2022 – Jun 2026
Held-out period
Jul 2026 – Oct 2026
KNOWN LIMITATION

Historical testing has not yet demonstrated a meaningful predictive edge.

Inspect historical evaluation METRICS + BASELINES
Historical held-out evaluation · finio-model-v0.1
MeasureModelBaseline
Accuracy49.84%49.16% momentum
Brier score0.2516230.251618 constant

299 dataset securities; 295 training securities. Lower Brier is better. The model's Brier score is slightly worse than the constant baseline. These historical results do not establish predictive edge. Figures supplied by Finio; evaluation artifacts are not hosted in this website repository.

BUILD WITH FINIO

Financial-event probabilities.
In your software.

Add versioned forecasts to an app, agent or research workflow. Generate one distribution, then ask multiple typed questions without rebuilding the forecasting stack.

01 One reusable forecast

02 Structured probability answers

03 Saved records and evidence

View API metadata ↗

Public experimental endpoints. Successful requests create public records. Availability and data permissions require separate verification.

Versioned contracts and saved records

v0.3 uses /api/v3; v0.2 uses /api/v2. POST /forecasts creates a forecast, POST /queries answers a typed question, and GET /forecasts/:id or /predictions/:id retrieves saved evidence.

Original v0.1: POST https://api.tryfinio.com/v1/predict with {"symbol":"NVDA","horizon":"5d"}. Its fixed-event contract and ledger are separate.

v0.2 API metadata ↗
v0.3 / JAVASCRIPT / REAL API CONTRACT
One forecast, then a question
const base = 'https://tryfinio.com/api/v3';
const post = async (route, body) => {
  const response = await fetch(base + route, {
    method: 'POST',
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify(body)
  });
  if (!response.ok) throw new Error('Request failed');
  return response.json();
};

const forecast = await post('/forecasts', {
  asset: 'NVDA'
});
const answer = await post('/queries', {
  forecast_id: forecast.forecast_id,
  query: {
    horizon: 20,
    event: { metric: 'outperformance',
      operator: '>', value: 0 }
  }
});
console.log(answer.probability);

The example asks whether NVDA outperforms SPY after 20 trading sessions. No response value is invented. Asking another supported question reuses forecast.forecast_id.

FINIO ON IPHONE / COMPANION APP

Take your research
with you.

The Finio iPhone app brings market research, learning and simulated portfolios into a companion interface.

The web model exposes explicit forecast versions and evidence. App signal scores and AI projections are distinct outputs and do not imply that every screen uses v0.3.

Finio Learn with lessons and topicsFinio iPhone practice portfolio with simulated holdings
Original app captures. Historical, simulated portfolio data.

FORECAST → QUESTION → MEASURE

Give your next question
a probability.

Run the model Build with the API →