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Ok here is the explanation. Grab a cup of coffee and read on. If you have not read/noticed this, you will see intraday options movement in a new light.
Say we have two options, one 50 delta ATM options and another 30 delta OTM option. Normally for a 100 point move, the ATM option will move 50 points and the OTM option will move 30 points. But in a high volatile environment, the OTM option will also move nearly 50 points
To understand why this happens, first understand why an ATM option is 50 delta. An ATM option has the probability of 50% of expiring as ITM. The price just has to close a rupee above the strike for the CE to be ITM and vice versa for PEs
Now think of a highly volatile day like today. If someone is asked where the BNF will close for the day or expiry, no one can answer. BNF can close freakin anywhere, That makes every option of an equal probability of being ITM. So all options have a 50% probability of being ITM
Hence, when a huge volatile move starts, all OTM options behave like ATM options. This phenomenon was first observed in the Black Monday crash of 1987 at Wall Street, which also gave rise to the volatility skew/smirk
In a high IV environment or when the market is very volatile
— Subhadip Nandy (@SubhadipNandy16) January 21, 2022
" OTM options will behave like ATM options", one will get almost the same delta movement
Say we have two options, one 50 delta ATM options and another 30 delta OTM option. Normally for a 100 point move, the ATM option will move 50 points and the OTM option will move 30 points. But in a high volatile environment, the OTM option will also move nearly 50 points
To understand why this happens, first understand why an ATM option is 50 delta. An ATM option has the probability of 50% of expiring as ITM. The price just has to close a rupee above the strike for the CE to be ITM and vice versa for PEs
Now think of a highly volatile day like today. If someone is asked where the BNF will close for the day or expiry, no one can answer. BNF can close freakin anywhere, That makes every option of an equal probability of being ITM. So all options have a 50% probability of being ITM
Hence, when a huge volatile move starts, all OTM options behave like ATM options. This phenomenon was first observed in the Black Monday crash of 1987 at Wall Street, which also gave rise to the volatility skew/smirk
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1/OK, data mystery time.
This New York Times feature shows China with a Gini Index of less than 30, which would make it more equal than Canada, France, or the Netherlands. https://t.co/g3Sv6DZTDE
That's weird. Income inequality in China is legendary.
Let's check this number.
2/The New York Times cites the World Bank's recent report, "Fair Progress? Economic Mobility across Generations Around the World".
The report is available here:
3/The World Bank report has a graph in which it appears to show the same value for China's Gini - under 0.3.
The graph cites the World Development Indicators as its source for the income inequality data.
4/The World Development Indicators are available at the World Bank's website.
Here's the Gini index: https://t.co/MvylQzpX6A
It looks as if the latest estimate for China's Gini is 42.2.
That estimate is from 2012.
5/A Gini of 42.2 would put China in the same neighborhood as the U.S., whose Gini was estimated at 41 in 2013.
I can't find the <30 number anywhere. The only other estimate in the tables for China is from 2008, when it was estimated at 42.8.
This New York Times feature shows China with a Gini Index of less than 30, which would make it more equal than Canada, France, or the Netherlands. https://t.co/g3Sv6DZTDE
That's weird. Income inequality in China is legendary.
Let's check this number.
2/The New York Times cites the World Bank's recent report, "Fair Progress? Economic Mobility across Generations Around the World".
The report is available here:
3/The World Bank report has a graph in which it appears to show the same value for China's Gini - under 0.3.
The graph cites the World Development Indicators as its source for the income inequality data.
4/The World Development Indicators are available at the World Bank's website.
Here's the Gini index: https://t.co/MvylQzpX6A
It looks as if the latest estimate for China's Gini is 42.2.
That estimate is from 2012.
5/A Gini of 42.2 would put China in the same neighborhood as the U.S., whose Gini was estimated at 41 in 2013.
I can't find the <30 number anywhere. The only other estimate in the tables for China is from 2008, when it was estimated at 42.8.