Friday, August 23, 2013

MOOC

I will be running a MOOC (massively online) class this fall. Follow the link for information. The class will roughly parallel my PhD asset pricing class. We'll run through most of the "Asset Pricing" textbook. The videos are all shot, now I'm putting together quizzes... which accounts for some of my recent blog silence.

So, if you're interested in the theory of academic asset pricing, or you've wanted to work through the book, here's your chance. It's designed for PhD students, aspiring PhD students, advanced MBAs, financial engineers, people who are working in industry who might like to study PhD level finance but don't have the time, and so on. It's not easy, we start with a stochastic calculus review!  But I'm emphasizing the intuition, what the models mean, why we use them, and so on, over the mathematics.

19 comments:

  1. is there any pre-requisite coursework aspiring participants should review before the class starts?

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    1. The course site describes (or will describe!) all that.

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  2. Rao Aiyagari used to tell a story about intuition in which (in his story) Lucas would give the punchline: "F the intuition. Just give me the equations and I'll make up my own intuition." Which sounds right to me. There's lot of good stuff in your book, but I hope you give them E(mr) = 1 over and over again. It's a rare topic that has such a clean unifying theme.

    Cheers.

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    1. Intuition and equations work best when they act as checks on each other. Equations can confirm intuition. Intuition can act as a test of the correctness of the equations. If intuition and equations disagree, then you have work to do.

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  3. In the industry and have no interest in pursuing a full-time PhD, but your class would interest me. I assume a finance degree + MBA + CFA would position me to understand the material, assuming I can recall my calculus?

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    1. You can hold an MBA and CFA (level...?) and not remember calc? What's the point in getting advance degrees and certificates if you can't do that math. Do you even know what your financial models are telling you?!

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    2. Just my 2 cents: I dont believe CFA and MBA would help in any way...

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  4. Great news, looking forward to it. Is there any chance that you'll do something similar with your 35150 Investments class at some point?

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  5. Thank you very much for doing this. I will probably take your course. I read the syllabus and it was not clear if we should but your textbook.
    Anyway, these are great news, thank you

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  6. I got a B+ in Real Analysis. Do you think I'm qualified for this course??

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  7. Thank you Prof. Cochrane, I've been looking forward to this class ever since its first preview was released on coursera. A month ago, I asked quite a few of my Carnegie Mellon professors about where to begin if I'm interested in learning about quantitative alpha strategies, and they all suggested your book Asset Pricing. And here we have you teaching that course yourself. I'm in luck.

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  8. Thank you, thank you, thank you!

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  9. I just enrolled, I'm really looking forward to take the course.

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  10. Are you going to follow the book (which I just happen to have but had no time to look at yet...)?

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    1. Yes. We basically march through about half the book. An online version will be available through coursera.

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  11. Folks (and Prof Cochrane, of course)

    This was a GREAT course (it's not formally finished yet - we still have what I assume will be an absolute bear of a final).

    If you're up for it, you MUST enrol for this, the next time it's offered.

    I particularly like the week 8 portfolio lectures (week 7 - Bonds - was great but I screwed the pooch on extending Vasicek by going one step too far and entering the discrete time formula - with phi* - instead of the continuous time version: what was I thinking?)

    As a former mutual fund analyst I lol'd hard when Prof Cochrane said "Knowing 'sigma-inverse-mu' does not make you smarter than average": so true, and yet operationally that's the mindset, isn't it?

    This course really did inspire me to pick up the threads of my PhD, which I suspended in 2000. No joke - next week I'm off down to my nearest university (where an old mate is head of the school of economics and finance) to see if they won't let me enrol (and, fingers crossed, give me another scholarship).

    Funnily enough, the entire gist of my topic was that individual stock (and asset-class) covariances and expected returns are not time-stable - they depend on expected economic outcomes ("state variables", if you will): I proposed to use a multisector, intertemporal computable GE model plus some 'scenario-based stochastic simulation' to forecast industry-level expected returns and covariances... and form portfolios from there. I presented preliminary results in 1997 in a Masters seminar, and they went over OK: by 1999 I had 200 pages but had lost all momentum. Now that my former mentor is building a new CGE model for the US State Dept ("USAGE"), my approach will be able to be applied outside of the Australian context (since the only large-scale multi-sector CGE model that existed in 1995 was MONASH - with GTAP as a global analogue).

    But enough about me...

    To Prof Cochrane directly: thank you for making this course available to anyone who turned up. You don't need me to tell you that you're a sensational instructor, but I'll say it anyhow. Your passion for the discipline leaps out of the screen - and using your famous "dot-dot-dot operator" to make students grind through the algebra is a very very good idea. Your participation in the Hangouts was genuinely "above and beyond the call of duty". Thanks again, and all the very best to you and yours.

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  12. When are you offering this course again? I would love to take it.

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    1. January 2015. Much expanded. Working on new videos now!

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