07. Forecast Future stock Prices

PRDTM2-787 AI Trading C4 L3 Vid7 Forecast Future Stock Prices

Understanding Stock Price Predictions with GBM

The forecast function of the GBM class allows users to predict future stock prices by utilizing known model parameters. Here's how it works:

  • Stock Price Forecasting

    • Function uses the formula relating initial stock price, S_0, to future price, S_t.
    • Assumes a log-normal distribution for future prices.
    • Calculates expected future price for given time t.
  • Calculating Confidence Intervals

    • Determines two price points, Alpha and Beta, for a specific confidence level.
    • These points define the expected range for S_t.
    • Uses the properties of normal distribution for calculations.
  • Function Implementation

    • Computes the mean and standard deviation of the stock price ratio.
    • Determines critical values for forming confidence intervals.
    • Outputs a dictionary with the prediction and interval values.

This method is applicable for long-term predictions and requires validation with historical and scenario-based simulated data. Subsequent lessons will focus on building the simulate function for further analysis.

You have calibrated a geometric Brownian motion to historical stock prices. The parameters are mu = 0.4, sigma = 0.5. The current stock price is $100. What is the expected stock price in 1.5 years?

SOLUTION: 182.21