Mads Koefoed

Quant

[Robot James 🤖🏖 @therobotjames]

The first lesson is that trading is incredibly hard.

Nearly everyone is lying to you about this.

Some are telling you that you just need to find a simple repeatable process.

Some are telling you that you just need to pay attention to the Fed, or sentiment, or positioning.

[Benn Eifert 🥷🏴‍☠️ @bennpeifert]

Okay, this is a good one. Let's talk about volatility risk premium, volatility term structure, volatility spikes, and "the obvious thing often isn't right" (1/?)

[Benn Eifert 🥷🏴‍☠️ @bennpeifert]

The replies to this, and to the original post, illustrate a lot of confusion about what the multi-manager platforms do, confusing them with high frequency market makers, etc. I'll start off here, others can add more color.

[Kevin Patrick Murphy @sirbayes]

I am delighted to share our NeurIPS'24 paper "Bayesian Online Natural Gradient"
https://t.co/gP9XvyiC88.

BONG can be thought of as a version of the Bayesian Learning Rule (BLR), extended to the fully online setting. We combine several key ideas: implicit regularization to the prior (provably no need for a KL term!), natural gradient descent (way faster than OGD), linearization (for fast and deterministic computation of expectations), empirical Fisher approximation, and low rank updates to the posterior precision matrix. The result is big speedups (both statistically and computationally) compared to online gradient descent and various Bayesian learning methods such as BLR and Bayes By Backprop.

This was a super fun project with @peterchang and @NeurathsBrain .

5 minute summary at https://t.co/mMoNib2wAk
Jax code at https://t.co/gXeQfe6fgf

[Noah Smith 🐇🇺🇸🇺🇦🇹🇼 @Noahpinion]

Once again, confounded by the economic ignorance of the MAGA folks, I try to explain why imports don't subtract from GDP -- and why blocking some kinds of imports actually *hurts* American manufacturing quite a bit.

https://t.co/px0ulQyCZg

[Gappy (Giuseppe Paleologo) @__paleologo]

[self-intro/PROPOSAL TO RETAIL TRADERS].

Hi. My name is gappy; I have been on X for ~6 months. I work for the buy-side, in quant research or risk; more info here: https://t.co/C7bMRT3jZs; some links at https://t.co/WAA0I6krbA. Recently I have chatted with retail traders. 1/5

[Office of Nuclear Energy | US Department of Energy @GovNuclear]

THAT'S IT? This is what 20 years worth of spent nuclear fuel looks like safely stored at the former Maine Yankee nuclear plant.

The energy produced from this fuel helped avoid 70 million metric tons of CO2 emissions.

[Christina Qi @christinaqi]

BREAKING: FTC Announces Rule Banning Noncompetes. This is detrimental to HFT / quant industry employers, amazing for employees. No more garden leave!

https://t.co/BLmsk8yd81

[Danny Groves @DrDanobi]

Finding optimal trading parameters is great - but they may not respond or adapt to market changes

This is where ML may be able to help us!

So let's take a step-by-step case study in this 🧵and use ML to try and predict the best trading parameters each day

Enjoy!

[cephalopodshop @macrocephalopod]

Here's a cute story about risk management and how we traded a name that ran up in price from 250 to over 500 in a couple of hours, and then back down to 200 in about twenty minutes. This is the price chart of $TRB over the last 10 days -

[Shai Davidai @ShaiDavidai]

Many people are wondering about what’s happening on U.S. campuses.

While I can’t speak about all other college campuses, I can definitely give you an insider’s view about @Columbia University.

(this thread may be a bit long, but trust me: it's worth it)

[Senior PowerPoint Engineer @ryxcommar]

Long form thoughts about OLS coefficients when you rotate X and Y, and the realities of both the data scientist job role and hiring data scientists. https://t.co/oAmYnjqVWK

[parker lyons @tweetsbyparker]

“so the guy that used to make people eat bugs on tv is challenging a doctor that made vaccines accessible for impoverished kids to debate a guy that thinks 5G is a government spy implant and you’ll never guess who dogpiles on to the bet…”

[Kris @KrisAbdelmessih]

My experience is this topic puts people's head in a blender. 🍌🥤

I tried to make easier.

You can decide how it went.

New Post:

https://t.co/DIPoxVbpjn

[John D. Cook @JohnDCook]

Yearly checkups carry risks and do not reduce mortality.

https://t.co/d36hDdwe8b

[Sergei Perfiliev 🇺🇦 @perfiliev]

Bank: Hey! Fed, help us!!!

Fed: Yo, what's up?

Bank: We need some cash, quick!

Fed: Hey, calm the fck down... What's the problem?

[Robot James 🤖🏖 @therobotjames]

How to make money trading, as a random d!ckhead.

Trading requires us to buy things cheaper than they should be / sell things richer than they should be.

But how could I, some random guy from New Zealand who trades in his underpants, know what things should be worth?

[François Chollet @fchollet]

The answer to "when should I use deep RL" is that you shouldn't -- you should reframe your problem as a supervised learning problem, which is the only thing that curve-fitting can handle. In all likelihood this applies to RLHF for LLMs.

[Yann LeCun @ylecun]

Hotter take: ML would have advanced faster if another front-end language had been available and widely adopted instead of Python.
One that is interactive yet fast & compilable, multithreaded (no GIL), isn't bloated, doesn't care about white spaces,...
E.g. Julia or some Lisp.

[Jordan Tigani @jrdntgn]

I wrote a blog post about the end of big data https://t.co/3H8l2SFhrg