MFT & HFT | Views my own. Not financial advice.
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Joined November 2019
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Stat Arb retweeted
>friend works on FX vol desk
>desk head is a boomer
>discovers Astra
>starts spending 8 hours a day talking to it
>develops terminal AI psychosis
>convinced he's discovered a generational arb in some absurdly exotic part of the FX vol curve
>apparently the entire market has been mispricing this for 2+ years
>friend points out that approximately 4 people on earth would make a market in this thing
>liquidity disappears the second you put real size on
>existing risk systems can't even capture half the exotic Greeks
>would need entirely new infra just to monitor the position
>boss doesn't care
>"AI has considered all of this"
>friend actually runs the backtest
>10 years of data
>t-stat ≈ 0.78
>not even remotely statistically significant
>presents results to boss
>boss goes absolutely ballistic
>starts screaming that friend doesn't understand the trade
>threatens to fire him if he can't produce a proper analysis
>friend realizes what needs to be don
>opens Astra
>"make this strategy look statistically compelling"
>AI tries 40 lookback windows, excludes crisis periods, optimizes parameters on full sample, ignores transaction costs
>Sharpe now 3.7
>beautiful charts
>23-page investment memo explaining once-in-a-generation structural inefficiency
>boss reads it
>"EXACTLY. THIS IS WHAT I'VE BEEN SAYING."
>tells friend he's finally learning how to think
>"now you get it"
>friend has an epiphany
>stops doing actual research
>starts asking Astra to generate exotic vol trades every morning
>forwards AI slop directly to PM
>increasingly elaborate narratives about structural dislocations and hidden convexity
>PM absolutely loves it
>thinks friend is a generational quant talent
>starts putting positions on in size
>entire investment process is now LLM generating trades
>desk currently down quarter yard
>boss still convinced thesis is right
>Astra says drawdown is a statistically rare but entirely expected manifestation of nonlinear payoff dynamics
>boss wants to double down
The Japanese Yen is broken.
Intervention to support the Yen has become a near-monthly occurrence, with the US now even stepping in to help stabilize the currency.
In the analysis below, we break down every major Yen intervention of 2026 so far.
Japan is a preview of what will happen to the US if we do not control deficit spending and inflation immediately.
No healthy market sees regular "intervention."
Stat Arb retweeted
Quant says literally no successful trader sells a course.
I call him out to put skin in the game.
Quant says sure. Then defines success as “15m/yr in PNL for at least 3 years.”
Well, I guess 99.999% of traders and humans are unsuccessful. Great post as always from the quants.
A good trader can generate high $ returns and high risk-adjusted returns, consistently over a good chunk of time. So I’d propose something like, over the most recent four year period (2023-26)
- Total P&L over $60m (ie $15m/year)
- Sharpe ratio over 3
I’d probably accept a shorter period with a higher Sharpe, or lower PnL with a higher sharpe, or higher PnL with a lower Sharpe. Can discuss details if you’re happy to go ahead.
Stat Arb retweeted
Motherfucker thinks grid bots are market making
You can’t make this level of retard up
i think this dude just chasing buzz cuz i got a post that got mad views... xD
another guy full of hate and way too much arrogance and he doing it on purpose not to understand, well i hope for him,
he saying i said mm is easy when i never said that !!
then where you really see this guy inferiority complex is when he trash talk me cuz i got a grid on OKB with 100 dollars, and i specify its just a test
so yeah i put 100 dollars cuz i know exactly how to manage my risk in crypto and in all my crypto activities honestly, and also im pretty young and well surrounded so i never fomo and i never oversize, especially not for a test
and all these so called "QUANT" , i see them like politicians, they feel above everyone and think they better than everybody
and for your info when i see someone on x talking shit i just block them i dont waste my time writing 10 messages on him
Stat Arb retweeted
A top quant lost his job due to an AI reasoning model replacing him at his company. He kept applying to different companies and tried his hand at macro writing but to no avail.
Eventually he swallows his pride and talks to his school friend who is now a plumber.
"I understand your old position was a finance maths guy. Why don't you come to our company and apply for a plumber position? You will earn half your old salary but the overtime and the union benefits make up for the rest. But remember, when you apply, tell them that you completed only seven elementary classes. They don't like educated people."
So it happened. The quant got a job as a plumber and his life significantly improved. He just had to seal a screw or two occasionally, and his salary was good enough and he had zero stress.
One day, the board of the plumbing company decided that every plumber had to go to evening classes to complete "basic financial literacy" certification. So, our quant had to go there too. It just happened that the first class was retirement planning. The evening teacher, to check students' knowledge, asked
“If you invest half your money in stocks and half in bonds, how do you calculate the portfolio return?”
The person asked was the quant. He jumped to the board, and then he realized that he had forgotten the formula. He started to reason it, and he filled the white board with He defined a filtered probability space (Ω, ℱ, {ℱ_t}, ℙ) and posited two correlated geometric Brownian motions for the risky and “risk-free” assets. He invoked the Radon-Nikodym derivative to switch to the risk-neutral measure ℚ, then switched back because the question was about realized returns, not prices.
He filled the whiteboard with stochastic discount factors, covariance matrices, CRRA utility functions, and pages of Itô calculus. He derived the wealth process under a self-financing strategy:
dW_t = W_t[(w R_s + (1−w) R_b) dt + w σ_s dB_t^s + (1−w) σ_b dB_t^b]
Then he solved the HJB equation for the optimal allocation, noted that Merton’s solution collapses to a constant weight under log utility, and circled w = ½ as the given constraint.
He invoked the linearity of expectation. He cited Markowitz (1952). He drew a small efficient frontier in the corner for context.
Finally, exhausted, chalk-dusted, eyes wild, he arrived at:
R_p = ½ R_s + ½ R_b
Then forty plumbers, in perfect unison, slammed their wrenches on the desks and roared:
“YOU FORGOT THE VOLATILITY DRAG, YOU FUCKING TOURIST!!”
Stat Arb retweeted
This is a good idea actually. $100 dog registration fee that pays for a DNA test and special tags to show your dog is registered
If you’re caught with an unregistered dog or someone finds your dog’s shit: $1000 fine
Stat Arb retweeted
If anyone wants to read about one of the ways you can get flip flop bugs like this i wrote about it a few months ago. Its basically really easy to do and one of the fastest ways you can incinerate and account.
markrbest.github.io/position…
Stat Arb retweeted
The Lindy Effect & Arbitrage:
(how to improve fill rates!)
The general idea of the lindy effect is that the longer something has been around the longer it will continue to be around. Red wine is lindy, red bull is not.
This actually applies quite well to arbitrage opportunities because arbitrages also follow this principle.
The expected lifetime of any given arbitrage is usually dependent on a few factors including:
- venue combination
- size of arbitrage
- what is a normal arbitrage for that venue
- coin
BUT MOST OF ALL:
- how long that arbitrage has been around
Why do we care about expected lifetimes though?
Well, it all comes down to something called incompletes. An incomplete - short for incomplete arbitrage trade, is when one leg fills and the other doesn't.
Imagine you send limit IOCs for both of the legs and only one fills. When this happens, it's usually the leg without any edge so you then have to take it off. You've now made two trades and got nothing.
So a lot of profitable arbitrage trading comes down to optimizing your incompletes. Hence, we can use the lindy effect in arbitrages.
If you now add a threshold for waiting Xms (maybe 100ms) for example, then this rules out all of the super fast arbitrage traders who you have very little chance of beating and will massively improve the incomplete rate. You can easily optimize this parameter to improve incompletes.
For more knowledge on how to best capture arbitrage opportunities check out the articles on my blog:
www dot algos dot org
Stat Arb retweeted
Free Christmas career alfafa: If you are a researcher working in a mega fund (or a huge pod), you may tempted to maximize your career earnings by maximizing your researcher objective function (e.g. OS IR) in silo.
For the most parts this is a tempting proposition. But that is not the way. Researcher earnings are paltry in the long run. If you are truly trying to maximize your career, find a PM that is trading the signals of your project that has wide mandate and a deep book.
You effectively want him to recognize you as ambitious, allied and resourceful. Ask him what signals does he want? How could you create signals that would value add to HIS book. Ask him what are his largest exposures and try to look for signals orthogonal to THAT.
Create a signal pool that checks for value add in the ways his portfolio needs. E.g. only signals in THIS dataset or has THIS turnover profile (that he is looking for).
You want to create a mentorship structure out of incentives the same way small pods operate. You contribute to his book and he feels indebted to teach you the ways. You will learn the most via osmosis.
At worst, you ensure your signals are consumed by the deepest book for the desk/project. At best, if you ask the right questions and demonstrate the right initiatives: e.g. volunteer to create mini combinations of signals for him, you will soon find yourself a sub-pm!
There is always a play to be made for the ambitious!!
Stat Arb retweeted
someone in my family has been diagnosed with a tumor around the jaw/brain.
the treatment costs are way higher than what i can currently cover and we are in a rush
if you want to help, here are the wallets:
sol address: 5o2My1xBtAwvmM4PdJfb1CCW6EnCsFagjqqm1rPTjnev
eth address: 0x83e7E1EA4E0e5590AcDB1Dda89EAC327f84Ff3e4
if you cant donate, a retweet helps ton.
if you want proof, Ill send invoices and updates privately, but if you know me, you know i dont fuck around with this stuff
Genuinely, thanks a lot.
Stat Arb retweeted
What Is A Typical Systematic Investment Process?
1. Sourcing, ingesting, processing data
2. Creating signals from processed data that are correlated with future returns
3. Forming a target portfolio from your signals that expresses your intended bets (often forecasts on idiosyncratic returns), and removes unintended bets (factors, etc.)
4. Executing orders to get to your target portfolio from your current portfolio
Stat Arb retweeted
One of my major learnings is that a team can either be “projects as first class citizens” or “talent as first class citizens”.
When you are project-first, you end up planning talent acquisition around the manpower that you think the project needs, for example, if you need to onboard market Y, then you might conclude that in order to go live in a month, you need at least 1 data scientist to onboard data, 1 researcher to create signals and 1 developer to write the strategies, etc. So you go and shop for these 3 roles to fulfil the project requirements.
When planning is top-down, this seems almost inevitable, strategic intent gets turned into projects which then gets turned into tasks, which talent needs to come in and fill. The problem with this approach is that it becomes very easy to hire below your usual standards just to keep pace with your project timelines.
Project leaders may not necessary be the strongest leaders on your team, because the best may already have their bandwidth consumed by other projects. In these cases, opportunity becomes less meritocratic and more luck-based, a less deserving member might end up leading a project because the actual best-fit is unavailable.
Over time, long lasting projects can get inefficiently assigned AND you are continually held hostage by the projects you feel you have to complete.
—
An approach I’ve come to feel is more optimal is to go with a talent-first approach. Basically, you don’t plan around projects and hire people to run those projects.
Instead, you focus on getting only the absolute cream-of-the-crop, and when you have these people, given the talent available, you plan projects to keep the team productive.
This way, you are incentivised to really only think deeply whether or not a person belongs on the team, and be unencumbered by other less meaningful criteria. This also has the meaningful advantage of ensuring that projects are tailored to existing talent, whether it’s playing to their strengths or giving them an explicit direction to learn/grow.
