Just talked with Eric about stocks and random walks and thinking machines and split wing politics.<\/p>\n
And, about a little script, portfolio_track.py, I whipped up to expose how a bunch of stocks were doing against “the market”. With the the quantities removed, we have:<\/p>\n
\r\n\r\nSymbol 1yrGain Market-relative\r\n------------------------------------\r\nAEOS 20.9% 5.0% ~ ^GSPC\r\nALDA 74.3% 6.5% ~ ^GSPC\r\nATYT 101.0% 97.3% ~ ^GSPC\r\nAV -32.0% -41.7% ~ ^GSPC\r\nBBBY -41.5% -98.1% ~ ^GSPC\r\nBC -22.3% -30.7% ~ ^GSPC\r\nBSX -23.2% -34.1% ~ ^GSPC\r\nDOW -14.5% -24.2% ~ ^GSPC\r\nEEM 78.4% 61.9% ~ ^GSPC\r\nEGY -45.4% -124.1% ~ ^GSPC\r\nEWY 15.7% -0.8% ~ ^GSPC\r\nFLEX -34.6% -45.5% ~ ^GSPC\r\nFORD -59.2% -107.1% ~ ^GSPC\r\nGM 96.3% 70.3% ~ ^GSPC\r\nGTW 0.0% -47.9% ~ ^GSPC\r\nHD 2.5% -7.2% ~ ^GSPC\r\nJAKK 468.1% 420.2% ~ ^GSPC\r\nKSWS -193.0% -240.9% ~ ^GSPC\r\nLXK -33.5% -47.8% ~ ^GSPC\r\nMMM 4.1% -4.9% ~ ^GSPC\r\nMRK 13.1% 6.0% ~ ^GSPC\r\nMTEX -77.2% -125.1% ~ ^GSPC\r\nNTGR 98.7% 99.3% ~ ^GSPC -\r\nOPTN 89.8% 42.0% ~ ^GSPC\r\nOVTI 86.2% 76.3% ~ ^GSPC\r\nPCAR -4.0% -12.9% ~ ^GSPC\r\nPCL -9.7% -19.4% ~ ^GSPC\r\nPLMD 58.3% 42.5% ~ ^GSPC\r\nPLT 76.9% 61.1% ~ ^GSPC\r\nPXR 52.7% 36.9% ~ ^GSPC\r\nSWK 10.1% 0.3% ~ ^GSPC\r\nTBL 53.9% 44.1% ~ ^GSPC\r\nTDW 127.1% 108.3% ~ ^GSPC\r\nUSG 173.3% 166.7% ~ ^GSPC\r\nVBR 42.9% 26.3% ~ ^GSPC\r\nWDC 401.3% 385.7% ~ ^GSPC\r\nWFR 149.8% 139.0% ~ ^GSPC\r\nWINS -32.4% -99.5% ~ ^GSPC\r\nX 91.0% 80.1% ~ ^GSPC\r\n------------------------------------\r\n^GSPC 12.0%\r\n------------------------------------\r\nAbsolute 52.4%\r\nRelative 40.4% ~ ^GSPC\r\n\r\n<\/pre>\nwhich, bottom line, means that, as of this moment, I’m a stock market genius. Check back in a week or two when the most recently bought stocks, all but one of which are doing badly, really start to clock in.<\/p>\n
There are two possibilities here:<\/p>\n
1) My luck is good.<\/p>\n
2) I don’t know how to keep doing well. Picking these stocks is not a reproducable process.<\/p>\n
BTW, I don’t have some of the stocks listed above any more. Sold a few for various – arrgghh – short term capital gains ’cause they really seemed to be ready to go away. But, checking just now shows that I’m not a genius after all. All but one are up now from their sell price. Oh well.<\/p>\n
To explain the script output columns:<\/p>\n
Symbol – Add it to http:\/\/finance.yahoo.com\/q?s= and you’re good to go.<\/p>\n
1yrGain – Gain or loss, as a percentage of the money, normalized to 1 year. E.g. If a stock were held for a half year and has gained 20% during that time, then the number in this column would be 40%. Eric points out that this number can be really, really misleading. A stock that is held for 1 week for a 1% gain would have a 52% value in this column. Really looks good. But isn’t a big money maker.<\/p>\n
Market-relative – Gain above the market in 1-year-ness. In other words, this is the gain above what the same amount invested in some market average – in this case S&P 500 – would have been.<\/p>\n
Absolute: Raw, 1-year-ness gain overall. This is what most people look at. I don’t consider it interesting, as it’s gotta be considered relative to just sitting back and holding some market tracking “stock” or “fund” or whatever.<\/p>\n
Relative: Overall portfolio gain relative to the “market” index in 1-year-ness terms.<\/p>\n
Interestingly, the only stock held during a period of market loss in this list is NetGear, NTGR. The S&P 500 hasn’t been all that hot this past year. Up 12% for the weighted times that I’ve had stocks in this portfolio isn’t bad, but it’s surprising that it hasn’t dropped a bit during more than one of the periods reflected by each of these holdings.<\/p>\n
These numbers above don’t include dividends and trading costs. If trading costs were included, the bottom line numbers would probably go down a couple percent each. Dividends might bring the numbers right back up, though, as several of these stocks pay out well.<\/p>\n
WARNING to self: The script is pretty untested. I’ve reason to believe that it’s not correct. Too, that is uses end-of-previous-day prices for the “market” is inherently inaccurate, given that most of my trades come at the beginning of the day. Anyway, one thing I’ve learned doing this stock market stuff is that single-digit changes one way or the other are noise. One could argue that larger changes can be noise, too. Consider Google’s run-up. That might be called “crowd noise.”<\/p>\n","protected":false},"excerpt":{"rendered":"
Just talked with Eric about stocks and random walks and thinking machines and split wing politics. And, about a little script, portfolio_track.py, I whipped up to expose how a bunch of stocks were doing against “the market”. With the the … Continue reading