Stock Forecasting

Step 1 β€” Pick an industry (avg 1-month change)

Step 2 β€” Pick a company

History
30 days

Last close

β€”

1M change

β€”

Volatility

β€”

Sharpe

β€”

Max drawdown

β€”

Forecast confidence

β€”

Price

How the forecast works (plain English)

We fit a classic time-series model (ARIMA) to past prices and extend the trend 30 business days out; the shaded band is the 95% confidence interval β€” wider means less sure. It cannot predict news, results or events. To judge trust, we replay history: hide the last 30 days, forecast them, and measure how far off we were. High = clearly better than assuming tomorrow equals today Β· Medium = about the same as that guess Β· Low = ignore the projection.

AI Insight (AI-generated, educational only)

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Forecast reliability: β€”

Recent anomalies (unusual daily moves)

Step 3 β€” Read the market (chosen industry)

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Who's winning? return, last 30 days, % β€” β˜… = market index

Is the reward worth the risk? top-right = high return, low volatility (best)

How far from the top? distance below 52-week high, % β€” dip candidates on the right

Above or below trend? distance from 50-day average, % β€” green = uptrend

Ranking (by 1-month change β€” click a company to inspect)

#Ticker Industry1M % VolSharpe Forecast trust

Head-to-head growth of 100 invested β€” pick up to 3

Do they move together? correlation of daily returns β€” click a company to compare

Least related β€” diversifiers (lowest correlation, across all industries)

    Moves together (highest correlation, across all industries)

      What do these words mean? (30-second guide)