NuclearPhynance Archive

Posted: **Wed Jun 12, 2019 5:08 pm**

@nikol

THX

Posted: **Wed Jun 12, 2019 5:37 pm**

@PSS. Climate modelling is not the only place to look at. I remember, back in ~2003-2005 biologists/gene analysts were very popular in finance due to their PCA. I saw nice methods in linguistics. Kantorovich back in 1939 advanced in linear programming while solving problems of optimal production in a plywood industry for which he was given Nobel prize in economics. Math is everywhere.

@nikol if math is everywhere then you need to find areas where there are interesting things going on!

Posted: **Wed Jun 12, 2019 6:11 pm**

E-commerce market making

Posted: **Fri Jun 14, 2019 8:57 am**

CUSUM is basically a cliquet on the underlying process?

Surely there are more informative measures of non-Gaussianity. This could trigger because of autocorrelation, but it could also trigger because of kurtosis, vol of vol, jumps, and who knows what else.

Posted: **Fri Jun 14, 2019 2:01 pm**

The subject is Turning Points, not CUSUM. I guess, that TP is model free (upto identification, filtering method). For me it is important to identify where they are. Even cheating with forward information is allowed.

If I have those TPs, then I plan to reverse engineer parameters of large pool of indicators in parametric space when t=TP (signal) versus t=/=TP (noise) and select the most sensitive ones.

Posted: **Fri Jun 14, 2019 5:41 pm**

More or less.

If your time series is Brownian, there are no turning points. They don't exist. You are just fooled by randomness, to borrow a phrase.

Posted: **Fri Jun 14, 2019 9:51 pm**

I have never seen Brownian, but your argument of "fooled by randomness" is still valid.

Posted: **Wed Jun 24, 2020 8:58 pm**

@Magette

I have run after this idea for couple of weeks without good result.

However, seems these guys have extracted some meaning

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3594888

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3489539

If authors read this - Hi !

Posted: **Thu Jun 25, 2020 7:06 am**

Sorry for pushing you in the wrong direction. But at least I had a disclaimer. My applications were outside of finance and on signals with higher signal to noise ratio.

My gut feeling would be that you would have to de-noise financial market data to a point where you are actually loosing quite some information, let's say some EMD filter/decomposition and apply cusum there. And I am still not convinced that you would be able to detect turning points.

Again, sorry for wasting your time.

Posted: **Thu Jun 25, 2020 8:08 am**

@Magette

I did denoising.

Come on, analysis is an exploration. I get wrong answers all the time, while trying to teach others.

Btw, I'm not unhappy in any way, just in contrary.