Quantitative Developer||Derivative pricing & market microstructure||half a decade experience in the financial markets||github.com/ay007008||
Joined August 2022
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Apr 24
***Options theory
Solid understanding of greeks
***Stochastic calculus
Personal derivation of itô's calculus using Maclaurin
***Market Making Engine
Deployed live on @baysemarkets
Solid understanding of risk mgmt techniques in market making
GitHub projects @ay007008
28 Sep 2025
Linear Algebra✓
Numerical methods✓
Scripting language✓
Version control✓
Python✓
Python DSA (weak)✓
Python data visualization libraries ✓
C software design and Derivative pricing (project going on)
Mathematical finance(can do a lot of derivations)✓
Mql5 language ✓
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Jun 13
For the assumption associated with poisson arrivals where crossings are dependent,we know that volatility clusters and we could get moves in one direction and we're working on how gamma capture handles autocorrelation.
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Jun 13
We all know that BSM doesn't produce useful option price at T->0.
A discrete poisson model with observable crossing rates produces real non zero OTM option prices without parameter inflation.
The discrete approximations is closer to market microstructures reality than GBM
Jun 13
SPY price on a 1 min chart is effectively discrete
The barrier width b(t)=$0.76 is larger than the min tick.
Every 0-DTE practitioner knows that the real question isn't whether price is technically continuous,it is if a continuous gaussian assumption produces useful option price
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Jun 13
SPY price on a 1 min chart is effectively discrete
The barrier width b(t)=$0.76 is larger than the min tick.
Every 0-DTE practitioner knows that the real question isn't whether price is technically continuous,it is if a continuous gaussian assumption produces useful option price
Jun 13
You might be thinking that our terminal distribution is skellam and markets don't close at a discrete integer number of barrier crossings so how are we able to justify a discrete model for continuous price process?
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Jun 13
You might be thinking that our terminal distribution is skellam and markets don't close at a discrete integer number of barrier crossings so how are we able to justify a discrete model for continuous price process?
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Jun 13
We've shown it prices in the correct neighborhood on 220 real trading days without any curve fitting whatsoever.
Where BSM requires rebuilding vol surface every morning.
GCM also use observable parameters directly.
Jun 13
You should know BSM wasn't validated for the last 50yrs ,it is been used despite being wrong at 0-DTE.
Practitioners know it is broken,they inflate implied volatility to compensate
As for GCM, I'm claiming it's a better theoretical model for short dated options with real data
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Jun 13
You should know BSM wasn't validated for the last 50yrs ,it is been used despite being wrong at 0-DTE.
Practitioners know it is broken,they inflate implied volatility to compensate
As for GCM, I'm claiming it's a better theoretical model for short dated options with real data
Jun 13
Black-scholes has been stress-tested for 50yrs across billions of trades and we have validation for gamma capture on one year of instruments and you're wondering why it should be trusted?
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Jun 13
Black-scholes has been stress-tested for 50yrs across billions of trades and we have validation for gamma capture on one year of instruments and you're wondering why it should be trusted?
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Jun 11
Priced SPY 0-DTE options at 9:30 AM using a Poisson barrier-crossing model
(Gamma Capture) instead of Black-Scholes.
Ran 220 trading days,2,420 strike-day observations.
ATM result:
→ Model price: $2.36
→ Actual terminal payout: $1.96
→ Systematic $0.40 bias across ALL strikes
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Ayomide retweeted
Jun 8
Gamma Capture Replaces Black Scholes
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Jun 8
Don't say I didn't tell you about the gamma capture model
Research reference available on request
May 28
BSM assumes a lognormal terminal distribution.
Gamma Capture derives a Skellam distribution the difference of two independent Poisson variables counting up and down crossings.
Skellam has fatter tails than Gaussian at the same variance.
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Jun 8
The only flaw found in @I_Am_The_ICT trading models
Speaking of models,gamma capture model is a model you need to look out for
It is the only model that can replace the black scholes
Been having talking to louis pellathy @carbonreports about the validation and it's implementation
Jun 8
Baffled why a trend sometimes breaks structure but never pulls back to an FVG?
In fast moving trends, letting price pull back deep invites more opposing orders, worsening the MM's deficit. The engine performs a micro-pause, layers limit orders at the high, and resumes.
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Jun 8
Baffled why a trend sometimes breaks structure but never pulls back to an FVG?
In fast moving trends, letting price pull back deep invites more opposing orders, worsening the MM's deficit. The engine performs a micro-pause, layers limit orders at the high, and resumes.
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Jun 8
This forced mechanical buying creates the sharp "spike" past daily highs.
The moment that liquidity pool is exhausted & price ticks down,the dealer's negative delta crashes.
They must instantly UNWIND their hedges by dumping assets,printing the 2nd leg.
This is called gamma flip
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Jun 8
On derivatives desks, the engine shifts to managing options Greeks (Delta & Gamma).
When price approaches a macro high, dealers holding short calls hit severe Short Gamma exposure. To stay Delta-Neutral, their algorithms are forced to aggressively buy the underlying asset.
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