vbs_redlof

8 ms·

31.
by vbs_redlof 13y ago
This would never happen. The market for programmers and athletes are wildly different (winner take all markets).
32.
by vbs_redlof 13y ago
Please re-read onetwofiveten's explanation. All I've done is paraphrase it. Alpha is just an arbitrary cutoff p-value corresponding to a threshold t-value for a given null hypothesis.
33.
by vbs_redlof 13y ago
You raise an interesting point on 'work'. The value of work is increasingly less atomic in context of a knowledge economy. Ideas, research, art, sports--these are typically either completely ignored or wildly successful. Marginal
34.
by vbs_redlof 13y ago
Not before they trick 641 hipsters into falling in love with them.
35.
by vbs_redlof 13y ago
This is the clearest answer I've read so far. The p-value is the minimum probability of ending up with a test statistic that lies in the rejection region (for a given null hypothesis and critical value).
36.
by vbs_redlof 13y ago
Less wrong, but still off. The p-value is the probability of committing a type-1 error (false positive: we declare X to be president when he really isn't) given a sample and a null hypothesis. P-values are not the 'chances' o
37.
by vbs_redlof 13y ago
P-values are not comparable across different null hypotheses, they are a property of a particular sample given a null hypothesis. You can compare p-values only by making very strong assumptions that the samples come from the same data-gener
38.
by vbs_redlof 13y ago
Lesson learnt from the comments: beware of modelling economics if you have a background in a hard science. As a profession, we are incredibly envious and defensive of our position as the quantitative social science.
39.
by vbs_redlof 13y ago
Maybe Dobelli's ghost writer messed up.
40.
by vbs_redlof 13y ago
Coming from a finance background, calling this measure of startup investor performance "portfolio momentum" is very confusing.
41.
by vbs_redlof 13y ago
I don't want to be an asshole, but…instead of prancing around like you actually know something why not correct what you think is "certainly categorically incorrect".
42.
by vbs_redlof 13y ago
Stachurski's book goes into the underlying theory more deeply with code examples. It's also got a very good/practical introduction into real analysis and measure theory. Great resource for modern computational economics.
43.
by vbs_redlof 13y ago
How do you "stumble" through the PhD system?
44.
by vbs_redlof 13y ago
This book is starting to show it's age, lots of the examples are broken.
45.
by vbs_redlof 13y ago
Share price is up ~6.5% haha.
46.
by vbs_redlof 13y ago
Structural models are more 'insightful' than generative models in machine learning. Econ guys are more interested in Pr(y|x) than reproducing the data. That being said, I really hope computational work gains more traction... this
47.
by vbs_redlof 13y ago
Too bad the font rendering quality is a little subpar compard to the other pdf viewers. Yellow is not an issue: https://code.google.com/p/sumatrapdf/wiki/CommandLineArgumen...
48.
by vbs_redlof 14y ago
Another "mother" http://demonocracy.info/infographics/usa/derivatives/bank_ex...