# Tag Info

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I'd put this down as a comment, but don't have the reputation to do so. There is (or at least used to be) a two part MOOC course over at Coursera by one of the developers of QuantSoftware Toolkit. This is not an endorsement of the course or the software, just a statement of fact (for the record, I did do a part of the course, but found it too simplistic and ...

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Start with: http://www1.nyse.com/pdfs/closings.pdf which covers all closings through 2011 then use the following... 2012/2013: http://www1.nyse.com/press/1294398514465.html Weather related closures happened on Monday, Oct. 29, 2012 and Tuesday, Oct. 30, 2012. (http://markets.nyx.com/nyse/trader-updates/view/11507) 2014/2015: ...

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I would say it could be short for annual turnover (precent/portfolio) Higher portfolio turnover often means higher transaction costs. The definition is usually the lesser of all buys and sells in a year divided by the average monthly NAV of the strategy. (Morningstar) Be aware that turnover numbers come in all colors and flavors and can in or exclude ...

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I think you need to ask your question differently to get better answers than mine. Your Black Scholes part has two problems. First positive infinity should be negative infinity. Second, you are assuming zero dividends in Black Scholes but you are assuming a possibly positive div yield q in the CEV part. If the div yield q is sufficiently positive in the ...

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From how you outlined your solution, you are computing the mean variance portfolio with minimum risk and with target return $\overline{r}$. I'd say that you are solving an optimization using Lagrange multiplier method given the values of matrix A. $\lambda$ and $\mu$ are the Lagrande multipliers: these parameters measure the sensitivity of the Lagrange ...

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You can download the time series of e.g. S&P500 prices from NYSE, then their dates should well represent approximately the real NYSE trading days.

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