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.
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
📚 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
📚 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 https://t.co/NCy5CQN3V8
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…
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
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 https://t.co/qfOVDil2zf
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:
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.
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:
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…
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…
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):
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