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Using Geometric Brownian Motion for Long-Horizon Timber Forecasts

Article Quant Q&A · Author: Umesh Chaudhari
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Summary

The document raises whether Geometric Brownian Motion is suitable for forecasting timber prices over a long horizon. The proposed example is quarterly sawtimber stumpage prices projected ten or fifteen years ahead. The author reports that an Augmented Dickey–Fuller test found the price series non-stationary and interprets this as evidence of a random walk, then asks whether the forecast horizon makes GBM unsuitable.

No response, model specification, forecast, or empirical comparison is provided, so the document offers no conclusion about GBM’s validity for timber or the effects of widening uncertainty bands. Non-stationarity alone does not establish that a series follows a random walk or that GBM is appropriate; the question leaves drift, volatility estimation, structural changes, and alternative models unexamined. It is therefore useful as a model-selection question, not as a forecasting method or result.

Key ideas

  • The document asks whether GBM can support timber price forecasts ten or fifteen years ahead.
  • It reports an ADF test finding non-stationarity and interprets that as a random walk.
  • Non-stationarity alone does not establish a random-walk process or validate GBM.
  • No answer or evidence comparing long-horizon forecasting models is included.

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# Is Geometric Brownian Model suitable for long term price forecast?


# Is Geometric Brownian Model suitable for long term price forecast?












I was thinking of using Geometric Brownian Motion to forecast future prices of timber (say one variable, the stumpage price of sawtimber).

I tested the time series with Augmented Dickey-Fuller test and found the data series as non-stationary which means the series follows a random walk. Then, I went on to use it for price forecast.

However, my professor comes and says we cannot use GBM to forecast future prices that has long horizon.

In my case, I wanted to use quarterly price into 10 years or 15 years into the future. I know GBM is a good model for stock prices for short periods, but is 10 or 15 years too far considering the confidence limits and probable volatility?

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