The empirical application is to Bitcoin options, with code at github.com/ArturSepp/Stoc… and github.com/QuantLet/HJP/t…
My solutions from a decade ago are public, btw. You can find them on my GitHub github.com/chshersh/unive…
GitHub repo: github.com/karpathy/nanoc… A lot more detailed and technical walkthrough: github.com/karpathy/nanoc… Example conversation with the $100, 4-hour nanochat in the WebUI. It's... entertaining :) Larger models (e.g. a 12-hour depth 26 or a 24-hour depth 30) quickly get more…
I’m turning 41, but I don’t feel like celebrating. Our generation is running out of time to save the free Internet built for us by our fathers. What was once the promise of the free exchange of information is being turned into the ultimate tool of control. Once-free countries…
If you’re getting into PyTorch, give this a read. It discusses the usability, design patterns and implementation ideas behind the framework. A few bits and pieces that can help you build a good foundation.
OpenAI shows how gpt-oss can autonomously beat 2048 using reinforcement learning (RL). Training was done locally with Unsloth on NVIDIA DGX Spark. You can also do it free on Colab. 🦥 OpenAI DevDay notebook: github.com/openai/gpt-oss…
GPT-5 Pro found a counterexample to the NICD-with-erasures majority optimality (Simons list, p.25). simons.berkeley.edu/sites/default/… At p=0.4, n=5, f(x) = sign(x_1-3x_2+x_3-x_4+3x_5) gives E|f(x)|=0.43024 vs best majority 0.42904.
The daily mean reversion strategy was discussed at reddit.com/r/quant/commen…. Someone replicated the algorithm github.com/rwydaegh/overn… and got Sharpes that were positive but lower than in the original post. Running the code gives # Biotech Universe: Results Comparison ## All…
quantreturns.substack.com/p/overnight-me… The negative correlation of close-to-open with following open-to-close returns is exploitable in ETFs according to the author.
A very interesting paper, I can think of several practical uses for some #trading systems.
quantreturns.substack.com/p/overnight-me… The negative correlation of close-to-open with following open-to-close returns is exploitable in ETFs according to the author.
Some more words from us, trying to "demystify" our little corner of the world. Applications for 2026 grads are open and we are interviewing heavily right now, hope to see you personally at the final round.
How is engineering at HRT organized? What can candidates expect from the interview? After 13 years building our infra, scaling teams, and shaping our hiring process, Joe Smith answers questions he hears most from candidates and curious engineers alike. hudsonrivertrading.com/hrtbeat/engine…
How is engineering at HRT organized? What can candidates expect from the interview? After 13 years building our infra, scaling teams, and shaping our hiring process, Joe Smith answers questions he hears most from candidates and curious engineers alike. hudsonrivertrading.com/hrtbeat/engine…
If you want some info on how to do market making in these markets, I have some great articles on the topic which go into detail.
Stablecoin markets are piss easy to MM, if you want some easy market making experience. Go MM stablecoin to stablecoin markets. Super non-toxic, can literally do it manually. I made money doing it manually at one point.
There’s chatter about frontier labs having a secret super-advanced-GRPO. But let me tell you something new about GRPO; the clipping mechanisms induce entropy biases: - clip-low increases entropy - clip-high decreases entropy (1/5)
Very excited about this release!! As a former grad student I struggled to finetune llms. Even when the gpus are enough, it was painful to set up the infra correctly. Tinker allows more researchers to understand and language models, beyond a few well-funded labs.
Introducing Tinker: a flexible API for fine-tuning language models. Write training loops in Python on your laptop; we'll run them on distributed GPUs. Private beta starts today. We can't wait to see what researchers and developers build with cutting-edge open models!…
Today we launched Tinker. Tinker brings frontier tools to researchers, offering clean abstractions for writing experiments and training pipelines while handling distributed training complexity. It enables novel research, custom models, and solid baselines. Excited to see what…
Introducing Tinker: a flexible API for fine-tuning language models. Write training loops in Python on your laptop; we'll run them on distributed GPUs. Private beta starts today. We can't wait to see what researchers and developers build with cutting-edge open models!…
This was really interesting. The goal was to try and predict prices a minute out from an order book of previous bids and asks. Of course, my very simple linear model obviously would not successfully predict the trajectory of mid price in a real market. But the exercise helped…
We invited @dwarkesh_sp to tackle a foundational question in quant trading: What does it take to build a predictive signal from market data? We loved showing him what makes work at HRT so fun — and why, in Marc’s words, “it occupies a lot of very smart people for years.”
Finally had a chance to listen through this pod with Sutton, which was interesting and amusing. As background, Sutton's "The Bitter Lesson" has become a bit of biblical text in frontier LLM circles. Researchers routinely talk about and ask whether this or that approach or idea…
.@RichardSSutton, father of reinforcement learning, doesn’t think LLMs are bitter-lesson-pilled. My steel man of Richard’s position: we need some new architecture to enable continual (on-the-job) learning. And if we have continual learning, we don't need a special training…
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