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Uncommon Returns through Quantitative and Algorithmic TradingWed, 10 Sep 2014 10:56:38 +0000hourly1http://wordpress.com/Comment on About by alphahive
http://quantivity.wordpress.com/about/#comment-3108
Wed, 10 Sep 2014 10:56:38 +0000#comment-3108Where are you? Keep up the good work!
]]>Comment on Why Log Returns by Desempenho e Risco de Estratégias de Investimento | Blog do Dr. Nickel
http://quantivity.wordpress.com/2011/02/21/why-log-returns/#comment-2952
Mon, 25 Aug 2014 02:13:02 +0000http://quantivity.wordpress.com/?p=3018#comment-2952[…] Os log-retornos possuem diversas vantagens com relação aos retornos (ver este post): […]
]]>Comment on Inquiry: Algebraic Geometry and Topology by quantivity
http://quantivity.wordpress.com/2011/10/31/algebraic-geometry-and-topology-inquiry/#comment-2836
Thu, 21 Aug 2014 02:51:06 +0000http://quantivity.wordpress.com/?p=8462#comment-2836Models originating from statistical mechanics, such as spin glass, would appear to meet your three criteria: (1) can be studied in an algebraic geometry / topology setting; (2) applicable to numerous scientific fields, including all three you mention; (3) recent adoption in finance, such as the Bouchaud (2012) paper on Crises and Collective Socio-economic Phenomena.
]]>Comment on Inquiry: Algebraic Geometry and Topology by trentknebel
http://quantivity.wordpress.com/2011/10/31/algebraic-geometry-and-topology-inquiry/#comment-2835
Thu, 21 Aug 2014 02:00:19 +0000http://quantivity.wordpress.com/?p=8462#comment-2835Have you found any other applications of algebraic geometry and topology since you posted this in 2011? (I’m a math student who is lightly exploring finance on the side b/c I prefer to either be totally pure, or explore multiple applied fields (physics, cognitive science, finance…) such that my intuition is still general and not tied to one particular layer of reality.)
]]>Comment on Optimal 10b5-1 Monetization by cyrilrees
http://quantivity.wordpress.com/2011/09/27/optimal-10b51-equity-monetization/#comment-2824
Mon, 18 Aug 2014 21:54:46 +0000http://quantivity.wordpress.com/?p=6686#comment-2824This text iѕ invɑluable. Where can I find out morе?
]]>Comment on Why Log Returns by Why Use Log Returns? | Châteaux de Bah
http://quantivity.wordpress.com/2011/02/21/why-log-returns/#comment-2805
Sun, 10 Aug 2014 22:28:37 +0000http://quantivity.wordpress.com/?p=3018#comment-2805[…] Excellent summary on why log natural returns are used in favour of raw returns. Original is found here. […]
]]>Comment on Why Minimize Negative Log Likelihood? by Ian Goodfellow
http://quantivity.wordpress.com/2011/05/23/why-minimize-negative-log-likelihood/#comment-2785
Wed, 06 Aug 2014 00:51:13 +0000http://quantivity.wordpress.com/?p=5505#comment-2785This is kind of overlooking the real point: asymptotic consistency (maximum likelihood will recover the true distribution given enough samples) and asymptotic efficiency (it gets close to the true distribution pretty fast as you add samples).
]]>Comment on Mean Reversion Redux by spx |
http://quantivity.wordpress.com/2011/07/03/mean-reversion-redux/#comment-2509
Mon, 26 May 2014 11:06:43 +0000http://quantivity.wordpress.com/?p=5829#comment-2509[…] regression to mean (mean reversion) 1787.580 (200), 1868.019 (50), 1879.730 (20). SPX set a record high 1902.17 May 13, […]
]]>Comment on Curiosity of LPPL by Deve
http://quantivity.wordpress.com/2011/02/08/curiosity-of-lppl/#comment-2506
Sun, 25 May 2014 15:09:11 +0000http://quantivity.wordpress.com/?p=2806#comment-2506Very helpful information,…………how we set initial values for the parameters to fit with the data????can you explain….i tried so many times…the error is still cannot reduce…..poorly fitted
]]>Comment on Why Log Returns by Why log returns ? |
http://quantivity.wordpress.com/2011/02/21/why-log-returns/#comment-2505
Sun, 25 May 2014 10:51:10 +0000http://quantivity.wordpress.com/?p=3018#comment-2505[…] http://quantivity.wordpress.com/2011/02/21/why-log-returns/ […]
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