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I would like to build a model to predict capital calls and distributions of a private equity fund. The first question is: does any of you can address me towards the state of art for it? also machine learning approaches are more than welcome (so far I have only found papers using ito's calculus, or other deterministic simple methods). In particular I would like to link/correlate the output to the market and economic situation.

The second question is: in order to build the model I need data on some private equity funds (for training the model), however they are costy, so are you aware of any free database which I could be using?

I was also thinking that if no database/data is available I could approach it but generating fake funds by using a Montecarlo simulation but I am not sure this would be reliable.

Thanks

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As to the theory, I would recommend “Illiquid Alternative Asset Fund Modeling” by Dean Takahashi and Seth Alexander of the Yale Endowment.

You’re right that private equity fund data often sits behind paywalls. I’d recommend checking out the public pensions, however, since they tend to provide a lot of disclosure about their investments since they are subject to FOIA requests (CalPERS Example). You may have luck submitting your own FOIA requests for the actual call and distribution dates and amounts. That should get you a good sample of data for major funds.

Generating your own data via Monte Carlo might be good for testing your code & framework but it would have zero predictive value since it’s just random data.

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  • $\begingroup$ Thanks for you information. 2 questions pls. Is the CalPERS data accessible only by those enrolled to the pension scheme or they are available also for researchers? in order to submit the data request, should I simply email them or there is a more strict procedure? $\endgroup$
    – Luigi87
    Apr 6 at 7:33
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    $\begingroup$ Probably email. Would be interested if you share link to whatever you find. $\endgroup$
    – cpage
    Apr 8 at 0:19

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