Quantitative trading is simply the act of trading on data, fast or slowly, but I'll grant you for the more sophisticated audience there is a nuance between "HFT" and "Quant" trading.
To be "super right" you just have to make money over a timeline, you set, according to your own models. If I choose a 5 year timeline for a portfolio, I just have to show my portfolio outperforming "your preferred index here" over that timeline - simple (kind of, I ignore other metrics than "make me money" here).
Depending on what your trading will depend on which algo's you will use, the way to calculate the price of an Option/Derivative hasn't changed in my understanding for 20/30 years - how fast you can calculate, forecast, and trade on that information has.
My statement wont hold true in a conversation with an "investing legend", but to the audiance who asks "do you use llama3" its clearly an appropriate response.
I don't really understand your viewpoint - I assume you don't actually work in trading?
Aside from the "theoretical" developments the other comment mentioned, your implication that there is some fixed truth is not reflected in my career.
Anybody who has even a passing familiarity with doing quant research would understand that black scholes and it's descendants are very basic results about basic assumptions. It says if the price is certain types of random walk and also crucially a martingale and Markov - then there is a closed form answer.
First and foremost black scholes is inconsistent with the market it tries to describe (vol smiles anyone??), so anybody claiming it's how you should price options has never been anywhere near trading options in a way that doesn't shit money away.
In reality the assumptions don't hold - log returns aren't gaussian, the process is almost certainly neither Markov or martingale.
The guys doing the very best option pricing are building empirical (so not theoretical) models that adjust for all sorts stuff like temporary correlations that appear between assets, dynamics of how different instruments move together, autocorrelation in market behaviour spikes and patterns of irregular events and hundreds of other things .
I don't know of any firm anywhere that is trading profitably at scale and is using 20 year old or even purely theoretical models.
The entire industry moved away from the theory driven approach about 20 years ago for the simple reason that is inferior in every way to the data driven approach that now dominates
Very few of the fancy models are actually used. Dupire's non parametric model has been the industrial work horse for a long time. Heston like SV's and Jump diffusions promised a lot and did not work in practice (calibration, stability issues). Some form of local stochastic models get used for certain products.
In general, it is safe to say that Black-Scholes and its deterministic extension local vol have held up well.
Not only that, but Dupire’s local vol, stochastic vol (Heston in rates, or on the equity side models that combine local vol with a stoch vol component to calibrate to implied vols perfectly) and jump diffusion were basically in production 15 years ago.
Since the GFC it’s not about crazy new products (on derivatives desks), but it’s about getting discounting/funding rates precisely right (depending on counterparty, collateral and netting agreements, onshore/offshore, etc), and about compliance and reporting.
> the way to calculate the price of an Option/Derivative hasn't changed in my understanding for 20/30 years
Not true. Most of the magic happens in estimating the volatility surface, BSM's magic variable. But I've also seen interesting work in expanding the rates components. All this before we get into the drift functions.
> all foundational derivatives models were basically in place back then
In vanilla equity options, sure. But that’s like saying we solved rockets in WWII. The foundational models were derived by then; everything that followed was refinement, extension and application.
To be "super right" you just have to make money over a timeline, you set, according to your own models. If I choose a 5 year timeline for a portfolio, I just have to show my portfolio outperforming "your preferred index here" over that timeline - simple (kind of, I ignore other metrics than "make me money" here).
Depending on what your trading will depend on which algo's you will use, the way to calculate the price of an Option/Derivative hasn't changed in my understanding for 20/30 years - how fast you can calculate, forecast, and trade on that information has.
My statement wont hold true in a conversation with an "investing legend", but to the audiance who asks "do you use llama3" its clearly an appropriate response.