i am looking for some articles on how to identify and estimate utility functions in the stock market.

My own search results yielded some papers by Blackburn and Ukhov https://www.researchgate.net/publication/228137635_Estimating_Preferences_Toward_Risk_Evidence_from_Dow_Jones

and by Jakusch https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2845871 What do you think about their approach?

As far as i understand for the Blackburn-Ukhov paper you need to make a strong assumption regarding the marginal investor, which is always a different individual for each point in time and asset, where for the Jakusch paper, you need individual level trading data plus some fancy machine learning ..of which i'm not sure whether this makes sense as it havent been published anywhere.

Im also not sure whether the methodology in the latter is correct as it ignores the dynamic optimization of an individual. Would you mind to comment on this?

Thanks a lot for your replies :-) Thomas

  • 1
    $\begingroup$ "how to identify and estimate utility functions in the stock market" 1. whose utility function? 2. utility function regarding what good space? 3. based on what data do you want to estimate it? $\endgroup$
    – Giskard
    Feb 7 at 12:48
  • 1
    $\begingroup$ @Giskard Thanks for your comment. Yes, its a good question: i thought about any kind of data that is publicly available such as order book data or price quotes, which (forgive my stupid thoughts about this) perhaps can be used to construct some sort of hypothetical aggregate portfolio (e.g. odd number trades=retail investors, even number trd.=institutional traders) to figure out which utility function (the dominat group of investors that currently the price of a stock) dominates currently. Dont know whether this makes sense.. Please pm me for some more background on this if you like $\endgroup$
    – T123
    Feb 7 at 12:54


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