It's been a long time since I wrote anything remotely informative on X. I have something minor that sits somewhere in between [finance] signal analysis and statistics, which is also very practical, simple, and with a familiar ending. A loong 🧵 👇.
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$GGAL #PlanillerosArgy#Merval
Los 45 u$, hace meses, una y otra, y otra vez. Estaba caliente la probabilidad ahí, comentamos.
Los deltas derretidos, mientras que el ratio 66/66 hace lo suyo, volviendo a la media, dandole satisfacción a las probabilidades.
Porque al final todo se resume a eso. 3 puertas y un par de cabras jaja
DLR, un poco más volátil, y el MEP con brecha de 23 pesitos nomás, muito barato para mi...
Gracias a quienes participaron, la Capacitación de Sistemas Cuantitativos, la ganó @federodriguezh_ . Escribime por privado y coordinamos. Abrazo a todos!
Hoy, un alumno de la capacitación cuantitativa de opciones, me hizo llegar eso. Es su tesis de maestría, inspirada en la capacitación.
Justo, cuando pensás que el contenido por ahí no se entiende, no sirve, está mal explicado. Aparece algo así.
Eternamente agradecido, jamás pensé que de algo que se grabó con entusiasmo y ganas de ayudar, llegará hasta aquí.
🔉Cómo agradecimiento al estimado, voy a sortear hasta el otro finde una capacitación, pero de Sistemas Cuantitativos. Participan RT y Like.
Todo sobre sistemas, probabilidad, markov, bonos y dólar(es), al mercado argentino, cómo siempre.
No te duermas. Y gracias a todos.
$GGAL #PlanillerosArgy #Merval
We will be doing another giveaway this month for @breakoutprop .
We will be giving away four 25k accounts tryouts. Find out why traders love this opportunity.
For current @breakoutprop users and anyone who likes and retweets this post. Winners announced Friday April 10th.
🚨 BOOK GIVEAWAY 🚨
A couple weeks ago I promised 0xSero I’d do this… and today I’m delivering 🔥
This is my way of giving back to the #AI community that’s taught me so much.
If you see all the AI/ML buzzwords on X and feel:
• Totally lost
• The math behind it just isn’t mathing
this book is it.
“Why Machines Learn: The Elegant Math Behind Modern AI” by Anil Ananthaswamy
It breaks down the real fundamentals of how machines actually learn in a clear, story-driven way that finally makes everything click.
Shipping 3 physical copies FREE. Anywhere in the world 🌍
Super simple to enter:
1. 🚶Follow me
2. ❤️ Like
2. 🔁 Retweet (helps spread it!)
3. 💬 Reply: “I want the book” or tell me one AI/ML concept that’s confusing you the most right now?
I’ll pick the 3 most interesting/thoughtful replies till Monday.
Tag a friend who’s trying to level up in AI/ML 👇
Let’s help more people truly understand this stuff!
#AIGiveaway #MachineLearning #BookGiveaway #AI
Thought a little and wanted to write about optimal execution today!
Most of us work really hard on the alpha part of the investment process. It’s the “sexiest” part and we all love to feel like biggus brainus producing PnL charts that go diagonally from left to right with no bumps. Unfortunately, translating that perfect PnL chart into actual dollars earned is pretty difficult once you account for real life trading frictions. We have fees we need to pay to the exchange, slippage from being front-ran and bid-ask spread if we have no patience.
Large firms often hire large execution trading teams that decide on trading policies. These policies decide whether to make or take, and when quoting, whether to wait and leave the quote as-is, or refresh their quotes and lose time priority.
You’re not a large firm, so you are probably thinking to yourself, should I use limit or market orders? Should I be aggressive or passive? When do I switch between them? This article is meant to address these questions.
As usual happy to give a copy to supporters who retweet and drop a comment :-).
This is another crypto signal that works!
I am, of course, talking about the mighty value signal, but in crypto! It is mightily easy to construct, and is essentially proxied by a single estimator.
As usual, happy to share the article with some comments + reweets on this post!
Neural networks are pretty magical, they can create features that are predictive of price by virtue of some high-dimensional pattern recognition.
BUT, it's not easy to create good neural networks in trading, and I've read a lot of papers on neural networks in trading and boy are they practically impossible to parse. I want to keep my articles on neural networks practical, and you should walk away from this thinking: "Huh, that's all there is to it, doesn't seem too difficult to try."
Here's how to implement a convolutional neural network that can predict short-term price direction from limit order book data with > 80% accuracy.
As usual, happy to share articles with anyone who comments and retweets on THIS post.