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Modeling Volatility and Correlation and what it means for the VIX Index

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 Jonathan Kinlay, Quantitative Research and Trading | Hedge Fund Partner & Leading Expert in Quantitative Algorithmic Trading Strategies

 Monday, August 21, 2017

http://jonathankinlay.com/2017/08/modeling-volatility-correlation/


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6 comments on article "Modeling Volatility and Correlation and what it means for the VIX Index"

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 David Escuderos López, CFA, Director at MassMutual

 Tuesday, August 22, 2017



Is low stock correlation driving low index volatility, our is it the other way around? Maybe the low index volatility is leading investors to reduce index exposure and going more short/long stocks.


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 David Escuderos López, CFA, Director at MassMutual

 Tuesday, August 22, 2017



Interesting work BTW.


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 Alberto Cejudo, Senior Vicepresident BBVA Suiza

 Wednesday, August 23, 2017



Good job !!!

What's about cointegration?


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 Andreas A. Dr Aigner, Founder of TradeFlags. Alerts. Signals. Flags. Technical Indicators. Free for Everyone. Robo-Algo-Automat

 Thursday, August 24, 2017



One can imply correlations from quotes for Basket Index Options.


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 Zak Maymin, Writer of the Truth - Ethics Morals Laws - series books for kids

 Wednesday, August 30, 2017



This is a good article. It could be that both of those factors describe the same thing: anticipation of the bearish market. When market goes done, both the volatility and the correlation between the stocks tend to increase. It's not clear whether those two factors have any predictive ability of bearish market. That would be an interesting research.


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 John Burchfield, Financial Engineer

 Tuesday, September 5, 2017



One way to view this is through net order flow. When more participants are in agreement, the boat is heavy on a side. Eventually, the supply side will run out, and price reaches a critical point.

Another way to address this concept is through graph theory. Duncan Watts and Stephen Strogatz have interesting ideas regarding graph theory.

Now, putting this in words the rest of us can understand. The more people in disagreement, the lower the volatility. The more people in agreement, the higher the volatility. Think agreement and correlations. When the people's agreements are uniformly distributed, volatility is low and vice versa. When more people are in agreement, fewer people are on the other side of the trade, hence, volatility, high correlations.

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