Discover and read the best of Twitter Threads about #OptionSellers

Most recents (5)

#Options have same maths as #Insurance.

Insurance Companies win because:
1) #Mathematically Options are priced expensive,
2) With their deep pockets writing large enough number of options the #Probability works for them,
3) Endless Covenants to the Contract protect 'em
1/n
Thus #OptionSellers can hope to win OVER TIME if they have the same wherewithal as #Insurance Sellers, i.e.:
a) Deep Pockets
b) Very large number of trades over time
c) Math / Actuarial Skills
d) Legal Wherewithal.

Thus option sellers will be destroyed at some point.
2/n
#OptionBuyers are hoping beyond hope! They are in a worse position than #OptionSellers because:
#Probability is loaded against them & that makes a pressure to achieve #Extraordinary #Market Timing

3/n
Read 5 tweets
Considering recent volatile movements in #Nifty and #banknifty due to #CoronaVirus ,did data analysis with 20+ years of historical data to find how the index moved after such gap days, how #intraday traders can develop a #TradingStrategy out of it. Here's the details.
Analysed the following scenarios.
List of gap down days, more than -1% on Nifty & Bank Nifty
List of Gap up days, more than +1% on Nifty and Bank Nifty
What is the % movement during gap down days, i.e from Open to close on such days.
What is the % movement during gap up days
There are in total only 82 times #Nifty opened gap down more than -1% in last 20+ years and this is how the Intraday movement were during such days. X axis represents percentage of gap down and Y axis represents percentage of intraday movement.
Read 21 tweets
#GapTrading is interesting for #Intraday traders, however for #optionsellers Gaps are headache, as its hard to manage their trades. Here's the last 12 years historical data analysis of #Nifty and #BankNifty, showing the no of days where gap % is greater 1% or lesser than -1%. ImageImage
#BankNifty has seen more no of gaps during the 2008 market crash period, however #Nifty has seen more no of gaps in year 2011, Nifty haven't seen more gaps during highly volatile period of 2008,so most of the significant movement in Nifty happened during the intraday time frame
If #BankNifty repeats even half of what it has witnessed in 2008, it could be catastrophic for #optionsellers who doesn't have proper #riskmanagement
Read 3 tweets
This is a 10 year data analysis on #BankNifty index,
Y axis represents no of days and X axis represents each year and what is the Bank Nifty #ATR % that has occurred maximum in that year. Image
For instance, year 2008 was highly volatile year every recorded in history where more than 100 days, the ATR % was around 7%, which means if Bank Nifty is at 10000, it can move 7% either direction in just 1 day from its previous close price.
Is your breakout trading strategy did not work in 2017?

Its because 2017 has seen the lowest volatility ever in history, where Bank nifty ATR was just 1.36%, means, consider Bank Nifty at 25000, it did not move more than 350 points in either direction from its previous close,
Read 4 tweets
Traders need to check their ledger not daily MTM PNL statements.

Selling of deep ITM options to hide and carry forward losses is a common practice amongst unscrupulous "sub-brokers" illegally managing others money in #OptionsTrading.
There are no mandates from @SEBI_India on allowing "sub-brokers" or any party to trade and manage client funds in #OptionsTrading.

Certainly no mandate to take leverage of the sorts usually taken.
@SEBI_India Even AIF Category 3 norms don't allow leverage upwards of 2.

Beyond that, even an AIF cannot solicit funds from the public openly.

More on these norms here:
sebi.gov.in/sebi_data/atta…
Read 4 tweets

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