DAVID @binbootdev1

bxcv - risk taker 🦢 Worldwide Joined December 2017

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To queries on Learning Market Profile Starting a course on it with Live market trading Will drop more info in Discord/TG on How to join it. You will make One of the Best decision in 2024 I assure you.

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Crypto𝔸ce @CryptoAceBull

2 years ago

Is there anyone who can write Solidity code for L1 based chain? (like ETH, etc) or someone who can write AI models (or finetune existing ones)? I have few great ideas and want to make them as product in 2024 DM me if you are interested

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BURKOV @burkov

2 years ago

What is a good detailed tutorial on LLM fine-tuning?

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Steve Burns @SJosephBurns

2 years ago

5 Steps To Creating A Price Action Trading System - New Trader U newtraderu.com/2019/09/29/5-s…

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Crypto𝔸ce @CryptoAceBull

2 years ago

📚 𝐌𝐚𝐫𝐤𝐞𝐭 𝐏𝐫𝐨𝐟𝐢𝐥𝐞 𝐁𝐚𝐬𝐢𝐜𝐬 🧵 You heard about MP but what is it? How to trade with values? 1. Analyzing Volume, Price & Time all in one chart is market profile Point of Control: Price where highest volume was traded Values : 70% of the total volumes traded

Crypto𝔸ce @CryptoAceBull

2 years ago

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Crypto𝔸ce @CryptoAceBull

2 years ago

Published the Market Profile indicator with Day type settings Will definitely share a thread over weekend to understand basics of MP and how to find trades tradingview.com/script/Os7l8yk…

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Crypto𝔸ce @CryptoAceBull

2 years ago

Long got triggered and it was quick bounce Took entry bit higher as I was trying get limit order filled while it was going up 😄 Above 41.6k it can go for 42k/42.6k Took 20% off as 41.2k is current VAL and if it rejects from here then 40.4k likely TSL right below 40.8k for rest

Crypto𝔸ce @CryptoAceBull

2 years ago

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PyQuant News 🐍 @pyquantnews

2 years ago

A machine learning framework for speculators and data scientists: AlphaPy Here's what you can do: • Run machine learning models • Generate blended or stacked ensembles • Create models for analyzing the markets with MarketFlow It's on GitHub:

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PyQuant News 🐍 @pyquantnews

2 years ago

A framework for algorithmic trading: 1. Hypothesis formation: Generate ideas, collect data, analyze 2. Experiment setup: Backtest, test the backtest, iterate 3. Measure results: Risk and performance metrics 4. Execution: Paper trade, tandem trade, automate Do it with Python.

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PyQuant News 🐍 @pyquantnews

2 years ago

Algorithmic Trading with Python: Quantitative Methods and Strategy Development Quant trading with: • NumPy • pandas • Scikit-learn Code included below:

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PyQuant News 🐍 @pyquantnews

2 years ago

The most foundational time series analysis tool: Decomposition. Unfortunately, most people forget about it. So instead of spending months and months studying it, just use it. In a few lines of Python:

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QuantPrep🚀 @quant_prep

2 years ago

How to build an efficient Limit Order Book with the following operations: - Add: O(1) - Cancel: O(1) - Execute: O(1) The idea is to build a binary tree of Limit objects sorted by price, each of which is a linked list of Order objects Get it here👇 github.com/Crypto-toolbox…

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Kirk Borne @KirkDBorne

2 years ago

#MachineLearning for Financial Risk Management with #Python — #Algorithms for Modeling Risk: amzn.to/3t7ARbG ——— #AI #DataScience #Finance #Coding #BigData #100DaysOfCode #RiskManagement #DigitalTransformation #Fintech #PredictiveAnalytics

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PyQuant News 🐍 @pyquantnews

2 years ago

Introduction to algo trading (for retail traders). By the legend Kevin Davey. Here's what you'll learn:

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QuantPrep🚀 @quant_prep

2 years ago

A curated list of practical Financial Machine Learning tools and applications Topics include: - Deep Learning & Reinforcement Learning - Data Processing & Transformations - Portfolio Selection and Optimisation - Factor and Risk Analysis Get it here👇 github.com/firmai/financi…

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PyQuant News 🐍 @pyquantnews

2 years ago

Myth: AI bots are taking over the markets. Truth: Most shops still run Excel '97. Some shops using machine learning. 10 ways to use machine learning in trading (with the Python library):