tag:blogger.com,1999:blog-2076691526526730952.post268416090745896684..comments2016-05-30T00:00:10.416-05:00Comments on Travis Vaught: Modern Portfolio Theory - A Python ImplementationTravishttp://www.blogger.com/profile/00720286668168584326noreply@blogger.comBlogger7125tag:blogger.com,1999:blog-2076691526526730952.post-29274523749376611792013-06-10T18:13:03.022-05:002013-06-10T18:13:03.022-05:00Amazing Post! Amazing Bloq ! Friends and me are cu...Amazing Post! Amazing Bloq ! Friends and me are currently very interested in developing something close to this CAPM Project, Travis. Have you already implemented Mikes suggestion of a optimazation or a more recent version? Best wishes from Germany.pecke86https://www.blogger.com/profile/06854467671023338626noreply@blogger.comtag:blogger.com,1999:blog-2076691526526730952.post-21003341031455579462013-01-22T10:46:29.184-06:002013-01-22T10:46:29.184-06:00@JB Thanks for pointing this out...I'll take a...@JB Thanks for pointing this out...I'll take a look and follow up later.Travishttps://www.blogger.com/profile/00720286668168584326noreply@blogger.comtag:blogger.com,1999:blog-2076691526526730952.post-31817142662977184132013-01-21T13:17:03.335-06:002013-01-21T13:17:03.335-06:00I believe you are daily-ifying your volatility inc...I believe you are daily-ifying your volatility incorrectly. You start with rt = 0.5, and say that represents a 50% annual volatility. That's fine. But then you calculate the daily volatility as drt = rt / 252.0. Since volatility scales with the square root of time, it should be drt = rt / math.sqrt(252.0). If you wanted rt and drt to be variance (i.e. the square of volatility), then you could just divide by 252, but that isn't what you say and isn't likely what you meant. Hope this helps.JBhttps://www.blogger.com/profile/14547463940483661304noreply@blogger.comtag:blogger.com,1999:blog-2076691526526730952.post-79087815689282993602011-10-12T17:42:53.707-05:002011-10-12T17:42:53.707-05:00You may be interested in a book called "Stoch...You may be interested in a book called "Stochastic Portfolio Theory" by Dr. Fernholz.ODnoreply@blogger.comtag:blogger.com,1999:blog-2076691526526730952.post-2806787519025407372011-09-02T12:44:55.491-05:002011-09-02T12:44:55.491-05:00The CVXOPT documentation has a portfolio optimizat...The CVXOPT documentation has a portfolio optimization example:<br /><br /> http://abel.ee.ucla.edu/cvxopt/examples/book/portfolio.html<br /><br />It's also fairly easy to do Sharpe ratio optimization with CVXOPT's quadratic programming function.Mikehttps://www.blogger.com/profile/12510015029866121281noreply@blogger.comtag:blogger.com,1999:blog-2076691526526730952.post-2359472299595184492011-09-02T06:39:53.923-05:002011-09-02T06:39:53.923-05:00Chaco's DataLabel does this out of the box for...Chaco's DataLabel does this out of the box for the (x, y) values. I did have to subclass this to get support for arbitrary text in the labels. (see data_point_label.py in the github repo).Travishttps://www.blogger.com/profile/00720286668168584326noreply@blogger.comtag:blogger.com,1999:blog-2076691526526730952.post-86761480247137231562011-09-02T03:59:52.834-05:002011-09-02T03:59:52.834-05:00Nice! What element of Chaco does allow you to drag...Nice! What element of Chaco does allow you to drag'n'drop the labels of the data points? Is that part of chaco_mpt_display?Michaelhttps://www.blogger.com/profile/01401115906766575169noreply@blogger.com