<p>The closest you can get to data on this is the CME Commitment of Trader reports.
<a href="http://www.cmegroup.com/tools-information/quikstrike/commitment-of-traders-agricultural.html" rel="nofollow noreferrer">link to CME page</a></p>

<p>The report breaks down the position sizes in futures based on the reporting segment of client (e.g., commodity producers).</p>

<p>Based on my experience, it is hard to relate the changes in positioning to price changes. (I used to look at an earlier version of the report, which divided participants into “commercial”/“non-commercial” entities.) You can always look at historical data and tell a story why the price changed, but that methodology has little predictive power (you just change your story).</p>

<p>At the minimum, you need to specify what market you are interested in. Crude oil trades differently than bonds, which trade differently than equities. </p>

<p>Also, market structure matters. An exchange where all participants trade as equals is different than where there are market makers. In a market dominated by market makers, prices are literally set by the market makers. The question then becomes: why do market makers change their prices? (If you had an exact answer to that question, you would make a fortune as a trader.)</p>

<p>My experience is in fixed income, and it is safe to say that the bulk of price movements are associated with the release of economic data (although this was not the case during the Financial Crisis). Since prices typically jump immediately on the release of data, there is no way to associate any group with the price change - posted prices are changed without any transactions taking place. Fixed income prices are a mixture of exchange prices (Treasury bond futures) and market making (exotic derivatives).</p>

<p>My understanding of the energy markets is that commodity data releases have a similar effect. That is, prices are often adjusted based on news about consumption and production, not just the act of buying/selling by the end users/producers themselves. This should be expected, as energy commodities can generally be stored, and so commodities can be moved in/out of storage if the prospects for future supply/demand change. (Electricity was an exception for storage, although storage technology there is improving.)</p>

CC BY-SA 3.0
2018-01-31T17:08:58.130Z
2018-01-31T17:08:58.130Z
Brian Romanchuk
<p>You have a nice idea going on there, I suggest you transform this thing into a research. If you are familiar with Econometrics, you can take data related to specific thing, in your case a commodity and analyze how much of it was traded between individual buyers and how much between institutional investors.  </p>

<p>Based on the results of the tests you run, you would then be able to base your conclusions on hard evidence.</p>

CC BY-SA 3.0
2018-01-23T09:51:00.940Z
2018-01-23T09:51:00.940Z
Kir'Shara
<p>If (for example) a heavily traded asset like crude oil has a price move of x, how much of that is influenced by functional buyers/sellers and how much by speculators?</p>

<p>Let's say x is +100, there are 8 speculators who bought 1 each and a big petrol station who bought 92. The price move is experienced by the speculators but heavily moved primarily by the petrol station. </p>

<p>I know it will never be possible to know the exact distribution (unless you can see all orders and know who made them?) but is there a model to describe this?</p>

<p>Would the 'functional buyer/seller' be what microeconomics calls 'business owner'. And 'speculator' the 'buyers' and 'sellers'?</p>

<p>Although it might be easier to classify all market participants as 'buyers' and 'sellers' if looking to model trending markets it may be good to incorporate how much of price change was heavily social. </p>

CC BY-SA 3.0
2018-01-23T21:09:40.353Z
As has been answered already this could be a fun study or exercise - I guess it will depend heavily on the asset. For example in Oil or Gas (which is primarily sold as futures), the security will very often have “switched hands” many times before expiration and delivery - which would add to the “speculations” side, where the final buyer (who actually ends up getting the oil/gas delivered) will be the “functional” buyer. I haven’t studied it, but my got feeling would be that speculators will outweigh the functional buyers a lot for many commodities. Don’t know about other securities.
ssn
CC BY-SA 3.0
2018-01-31T12:17:34.603Z
Although you can find natural buyers/sellers in some markets, anything that is traded on an exchange features traders that will go either way. They will set prices on any number of factors, including released data. There’s not going to be a simple mechanical model for price determination, as otherwise those traders can use it to make a fortune.
Brian Romanchuk
CC BY-SA 3.0
2018-03-03T18:59:15.703Z
Think about it:  The weather bureau predicts a big blizzard coming in 3-4 days so you run to the store for toilet paper.  The first 3 stores you check are sold out.  The 4th still has it but they've doubled the price.
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<microeconomics><supply-and-demand><asset-pricing><price-theory>
How much of an assets price change is due to speculators and functional buys/sellers
cardycakes
# How much of an assets price change is due to speculators and functional buys/sellers

(Asked by: username_0 on 2018-01-23)

If (for example) a heavily traded asset like crude oil has a price move of x, how much of that is influenced by functional buyers/sellers and how much by speculators?

Let's say x is +100, there are 8 speculators who bought 1 each and a big petrol station who bought 92. The price move is experienced by the speculators but heavily moved primarily by the petrol station.

I know it will never be possible to know the exact distribution (unless you can see all orders and know who made them?) but is there a model to describe this?

Would the 'functional buyer/seller' be what microeconomics calls 'business owner'. And 'speculator' the 'buyers' and 'sellers'?

Although it might be easier to classify all market participants as 'buyers' and 'sellers' if looking to model trending markets it may be good to incorporate how much of price change was heavily social.

**Tags:** microeconomics, supply-and-demand, asset-pricing, price-theory
> **Comments:**
> **username_1**: As has been answered already this could be a fun study or exercise - I guess it will depend heavily on the asset. For example in Oil or Gas (which is primarily sold as futures), the security will very often have “switched hands” many times before expiration and delivery - which would add to the “speculations” side, where the final buyer (who actually ends up getting the oil/gas delivered) will be the “functional” buyer. I haven’t studied it, but my got feeling would be that speculators will outweigh the functional buyers a lot for many commodities. Don’t know about other securities.  
> **username_2**: Although you can find natural buyers/sellers in some markets, anything that is traded on an exchange features traders that will go either way. They will set prices on any number of factors, including released data. There’s not going to be a simple mechanical model for price determination, as otherwise those traders can use it to make a fortune.  
> **username_3**: Think about it:  The weather bureau predicts a big blizzard coming in 3-4 days so you run to the store for toilet paper.  The first 3 stores you check are sold out.  The 4th still has it but they've doubled the price.  

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## 2 answers

### Answer by username_2 on 2018-01-31. Score: 0

The closest you can get to data on this is the CME Commitment of Trader reports.
[link to CME page](http://www.cmegroup.com/tools-information/quikstrike/commitment-of-traders-agricultural.html)

The report breaks down the position sizes in futures based on the reporting segment of client (e.g., commodity producers).

Based on my experience, it is hard to relate the changes in positioning to price changes. (I used to look at an earlier version of the report, which divided participants into “commercial”/“non-commercial” entities.) You can always look at historical data and tell a story why the price changed, but that methodology has little predictive power (you just change your story).

At the minimum, you need to specify what market you are interested in. Crude oil trades differently than bonds, which trade differently than equities.

Also, market structure matters. An exchange where all participants trade as equals is different than where there are market makers. In a market dominated by market makers, prices are literally set by the market makers. The question then becomes: why do market makers change their prices? (If you had an exact answer to that question, you would make a fortune as a trader.)

My experience is in fixed income, and it is safe to say that the bulk of price movements are associated with the release of economic data (although this was not the case during the Financial Crisis). Since prices typically jump immediately on the release of data, there is no way to associate any group with the price change - posted prices are changed without any transactions taking place. Fixed income prices are a mixture of exchange prices (Treasury bond futures) and market making (exotic derivatives).

My understanding of the energy markets is that commodity data releases have a similar effect. That is, prices are often adjusted based on news about consumption and production, not just the act of buying/selling by the end users/producers themselves. This should be expected, as energy commodities can generally be stored, and so commodities can be moved in/out of storage if the prospects for future supply/demand change. (Electricity was an exception for storage, although storage technology there is improving.)


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### Answer by username_4 on 2018-01-23. Score: 0

You have a nice idea going on there, I suggest you transform this thing into a research. If you are familiar with Econometrics, you can take data related to specific thing, in your case a commodity and analyze how much of it was traded between individual buyers and how much between institutional investors.

Based on the results of the tests you run, you would then be able to base your conclusions on hard evidence.


---

