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I am looking for a simple way to estimate price time series of downstream products based on price of the main "raw" commodity.

For example, would like to estimate a price for wheat flour based on available wheat price data and wheat per unit weight flour conversion factor.

Some cursory googling seems to suggest that there is no standard way to do this. How would a quant go about such a task?

Incidentally, if anyone knows of a source for readily available flour price data, please let me know.

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    $\begingroup$ I would start with a linear regression, to see how well that works. $\endgroup$ – noob2 Feb 6 '17 at 15:11
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This is a typical issue in physical commodities trading and I don't think you'll find free sources for such prices because it's precisely some firm's business to talk to market participant and perform surveys in order to come up with an approximate.

As suggested by noob2, what I've seen in the industry is usually a regression, but you need at least historical data to perform this.

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In my mind, there is no obvious way how to do this. The price of the processed good will be be AT LEAST the cost of the raw material plus the cost of labour for processing plus the cost of other goods that are inputs to the process (energy etc.). A linear regression of the price of the finished good with respect to prices of the inputs will allow you to get rid of labour cost dependence and other price dependencies. However on top of this you expect to see a markup that is driven by demand for the finished good.

As a simple example take a power plant: The price of power will be the cost of fuels plus the cost of labour plus a production margin. The latter will fluctuate over time as a function of supply/demand

In other words, in many cases you will not gain much insight without supply/demand modelling

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