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Where finance practitioners get started with Python for quant finance, algorithmic trading, and data analysis | Tweets & threads with free Python code & tools.
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A Bloomberg Terminal costs $24,000 per year.
It's the portal to all the world's financial data.
Unaffordable for 99% of us.
Reserved for the Wall Street elite to outfox the normal investor.
Until now:
730
6K
31K
My PhD professors taught me MATLAB during my master's degree.
So I watched 200 YouTube videos to learn Python
96% of them were a complete waste of time.
But these 8 taught me more than all my PhD professors combined:
510
5K
21K
My master's degree completely failed to teach me Python for quant finance (they taught me MATLAB).
So I watched 200 YouTube videos.
And the truth is, 96% of them were a complete waste of time.
But these 8 taught me more than all my PhD professors combined:
275
3K
12K
Myth:
You need a computer science degree to get started with Python.
Reality:
You need YouTube.
Get started with these 7 channels:
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12K
College completely failed to teach me data analysis.
So I spent over 10,000 hours learning Python.
Then, I picked the 13 best libraries for machine learning and data analysis.
But unlike college, these won't cost you $120,000.
Here they are for free:
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A Bloomberg Terminal costs $27,660 per year (raising to $30,000 in 2023).
It's the portal to all the world's financial data.
Reserved for the Wall Street elite to outfox the normal investor.
Unaffordable for 99.9% of us.
Until now:
277
2K
10K
Over the past 10 years, I've watched over 250 YouTube videos on quantitative finance.
And the truth is, 99% of them were a complete waste of time.
But these 8 are worth more than a 4-year degree:
186
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8K
Skip the quant finance degree.
Dive into 17 code repos that will teach you more than all your professors at school.
All without costing you $90,000:
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2K
8K
Python and Excel:
Use them together and you have a potent combination for working with data.
Here are the 17 Python libraries to help you unlock the power.
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College completely failed to teach me data analysis outside Excel.
So I spent over 5,000 hours learning Python.
Then, I picked the 16 best libraries for machine learning and data analysis.
But unlike college, these won't cost you $60,000.
Here they are for free:
107
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6K
College completely failed to teach me data analysis beyond Excel.
So I learned Python and never looked back.
Along the way, I picked the best libraries for machine learning and data analysis.
But unlike college, these won't cost you $60,000.
Here are the 16 best for free:
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The most-used analytics software of the last 37 years:
Excel
But Excel on your resume is no longer enough to get a quant job.
Because Python is the new Excel.
But with 473,000,000 results for "python tutorial", most people struggle to start.
The 6 steps get started in 1 day:
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5K
12 Python libraries for free market data everyone should know:
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Algorithmic trading is the domain of secretive hedge funds.
Python has unlocked these secrets for everyone (even Goldman Sachs has an open source tool).
Use the same tools the professionals use.
Here's 5 tools to start automating your trading:
171
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4K
Python and Excel:
A potent combination for working with data.
Here are the 17 Python libraries to help you unlock the power.
80
935
4K
My Ph.D. professors taught me MATLAB during my master's degree.
So I watched 200 YouTube videos to learn Python
96% of them were a complete waste of time.
But these 8 taught me more than all my Ph.D. professors combined.
113
1K
4K
Skip the $90,000 computer science degree.
Get started with Python with these 8 YouTube channels instead:
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20 Python libraries for market data everyone should know:
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With OpenBB.
The OpenBB Terminal is a Python-based environment for investment research.
There are over 500 functions covering:
• ETFs
• Forex
• Stocks
• Crypto
• Options
• Portfolio
• Economy
• Mutual funds
• Econometrics
Strap on your seat belt.
Let's dive in:
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A license for a Bloomberg Terminal costs $24,000 per year.
OpenBB is free.
Get it here:
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Jupyter Notebook is the most powerful tool Python developers have.
But most people don’t know the hidden features.
Need a quick web app?
Or to create REST APIs?
Here's the 6 ways to use Jupyter notebook you never knew existed:
63
554
3K
My professors taught me MATLAB during my master's degree.
So I studied 76,948 Python code repositories to teach myself Python.
99.9% of them were a complete waste of time.
But these 9 are worth more than a $90,000 master's degree:
77
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3K
9 trading strategies everyone should know (with Python code):
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Python training from JPMorgan
Published by JPMorgan for business analysts and traders—by the best in the business.
Get it all here (for free):
51
517
3K
My rocket scientist professor told me to learn Octave during my master's degree ("it's free MATLAB").
So I watched 197 YouTube videos to learn Python instead.
94.4% of them were a complete waste of time.
But these 11 taught me more than all my PhD professors combined:
85
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3K
JPMorgan's Python training.
Published for business analysts and traders—by the best in the business.
Get it all here (for free):
44
463
3K
I love Python.
But I wanted something faster.
So I built an options pricing library in C and call it from Python.
Now I have the same speed as the pros (and you can too).
Here's a dead-simple way you can 45x the performance of your Python code with C (code included):
63
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Skip the quant finance degree.
Dive into 17 code repos that will teach you more than all your professors at school.
All without costing you $90,000:
73
544
2K
I spent a good portion of my $90,000 master's degree learning 1 thing:
Simulating stock prices.
The good news?
You don't need a master's degree to build your own stock price simulator in Python.
I'm going to show you how step-by-step:
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In 2012, my first options trade lost $9,000.
12 months later I was making $1,100 per week trading in my free time.
What changed?
I read 20 books on options and finished a master’s degree.
But what took my game to the next level was Python.
Here’s the code I still use today:
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I love Python.
But it's slow.
So I built an options pricing library in C and call it from Python.
Now I can trade like a professional (and you can too).
Here's a dead-simple way you can 45x the performance of your Python code with C (code included):
53
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2K
Algorithmic trading is the domain of secretive hedge funds and banks.
Python unlocked these secrets for everyone (even Goldman Sachs has an open-source tool).
Use the same tools the professionals use.
Here are 17 Python libraries that open the black box:
65
561
2K
Jupyter Notebook is the most powerful tool Python developers have.
But most people don’t know the hidden features.
Need a quick web app?
Or to create REST APIs?
Here's the 6 ways to use Jupyter notebook you never knew existed:
68
467
2K
Paid courses completely failed to teach me how machine learning works.
I used to just import scikit-learn and call model. fit.
So I spent 6 months studying the most popular models.
Here are the 7 resources I used to get ahead:
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Python beginners all face the same 9 problems:
Boredom
Getting help
No clear goal
Overwhelmed
Uncertain payoff
Can't apply tutorials
No idea where to start
Get the job done with Excel
"Not a programmer" mindset
If you struggle with any of these, read this thread:
40
454
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Jupyter Notebook is the most powerful tool Python developers have.
But most people don’t know the hidden features.
Need a quick web app?
Or to create REST APIs?
Here are the 6 ways to use Jupyter notebook you never knew existed:
52
409
2K
I've been using pandas since 2011.
It's the most important tool for analysts working in Python today.
If you're using Python, you need pandas.
Here's the 7 tutorials I wish I had when I started:
52
368
2K
Jupyter Notebook is the most powerful tool Python developers have.
But most people don’t know the hidden features.
Need a quick web app?
Or to create REST APIs?
Here's the 6 ways to use Jupyter notebook you never knew existed:
69
363
2K
Python beginners all face the same 9 problems:
Boredom
Getting help
No clear goal
Overwhelmed
Uncertain payoff
Can't apply tutorials
No idea where to start
Get the job done with Excel
"Not a programmer" mindset
If you struggle with any of these, read this thread:
31
466
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Python has unlocked algorithmic trading for all traders and investors.
But getting started can feel impossible.
PyQuant News has been curating the best quant resources on the internet since 2015 for professionals and beginners alike.
Here's 5 you need to read today:
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9 trading strategies everyone should know (with Python code):
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My Ph.D. professors taught me MATLAB but I couldn't afford the $2,000 license.
So I watched 200 YouTube videos to master Python.
96% of them were a complete waste of time.
But these 8 helped me save $2,000 (that I lost it in the market instead):
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The net worth of Ray Dalio, founder of Bridgewater Associates:
$22,000,000,000
Bridgewater is one of the biggest hedge funds on Earth.
How did it get so big?
A portfolio strategy 100s of PhDs developed over 10+ years.
And now you can use it too.
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Algorithmic Trading Using Python (4.5 hours)
Learn how to perform algorithmic trading using Python in this complete course. Algorithmic trading means using computers to make investment decisions.
10
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My master's degree completely failed to teach me how to test trading strategies.
So I spent 40 hours looking for Python backtesting libraries.
Then I started using the best ones.
But unlike my quant finance degree, these won't cost you $90,000.
Here they are for free.
41
340
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JPMorgan's Python training.
Published for business analysts and traders—by the best in the business.
Get the code here (for free):
19
227
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The harsh truth about being a quant:
You have to read a lot.
The 4 books every aspiring quant needs on their bookshelf:
15
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Skip the quant finance degree.
Dive into 17 code repos that will teach you more than all your professors at school.
All without costing you $90,000:
67
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The net worth of Jim Simons founder of Renaissance Technologies:
$30.7 billion.
His quant trading firm generated $100 BILLION in profits for investors.
He's returned 66%, per year, for 30 years.
The story of the CIA math genius who won the market:
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How a book written in 1910 can teach you calculus in 30 seconds:
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We’re entering a new era of quantitative analysis.
Where anyone can get big results with little effort.
Want to build an analytics app?
Here's 13 Python libraries to get you started now:
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8 courses to learn Python for FREE everyone should see:
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I read 65 books on quant finance during my master's degree.
Most of them were useless.
But these 4 are still on my shelf 11 years later:
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13 Python libraries for free market data everyone should know:
44
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Free code from book: Algorithmic Trading with Python
Algorithmic Trading with Python discusses modern quant trading methods in Python with a heavy focus on pandas, numpy, and scikit-learn.
Get the code here:
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The 7 must-have books everyone using Python for algorithmic trading needs to know:
39
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Things you don’t need to start quant trading:
• Complex algorithms
• PhD in math
• $10,000,000
Things you do need to start quant trading:
• A laptop
• A broker
• Python
Keep it simple.
18
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During my master's degree, I read 65 books on quant finance.
Most of them were useless.
But these 4 are still on my shelf 10 years later.
And they should be on yours too:
30
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1K
My first options trade lost $9,000.
12 months later I was making $1,100 per week trading in my free time.
What changed?
I read dozens of books and finished a master's degree.
Here's the 10 best books on options you can buy (and a surprise at the end):
39
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All these ChatGPT-4 threads are a joke.
The best prompts for generating trading ideas and writing Python aren't 1 sentence.
That's like having a Ferrari and driving it at 5 MPH.
Here's a 60-second masterclass on how to create prompts like a wizard.
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Quants use principal component analysis to find alpha.
Blackrock uses it to manage $100s of billions in factor funds.
Northfield uses it to earn $10s of millions selling factors to investors.
Here’s how it’s done.
In a few lines of Python:
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You don’t need a PhD to build a risk parity portfolio.
You need Python.
Here’s how to do it:
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Google "python tutorial" and you get 473,000,000 results.
Useless.
Most people are paralyzed by inaction because they don't know which tutorial to pick.
This one is a good start.
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When learning Python, have a clear goal in mind:
• Replace Excel
• Get a new job
• Become a quant
• Make more money
• Automate daily tasks
• Level up your knowledge
• Trade stocks and options
Knowing where you want to end up, helps to know where to start.
12
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In case you're unfamiliar:
• Over 325,000 people use Bloomberg daily
• Used for market data, trading and research
• Launched in 1981 by billionaire Michael Bloomberg
It's a modern icon of financial markets.
So, how can you compete?
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How a book written in 1910 can teach you calculus in 30 seconds:
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Data tables are great.
But nothing beats a pretty picture.
The only 12 Python visualization libraries you'll ever need:
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Professional options traders hedge with delta.
You don't need a PhD to do it.
Or fancy mathematics.
But you do need to know the fundamentals of delta.
Here's what you need to get started:
33
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1K
My PhD professors taught me MATLAB during my master's degree.
So I watched 200 YouTube videos to learn Python
96% of them were a complete waste of time.
But these 8 taught me more than all my PhD professors combined:
13
232
1K
8 great blogs to help you get started using Python for quant finance now.
(All with free code.)
34
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Professional options traders don’t bet that stocks will go up or down.
Rookies do that.
They look for mispricings in the market.
Here’s how to start trading like a pro with GARCH (and avoid the rookie mistakes):
39
205
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When learning Python, have a clear goal in mind:
• Replace Excel
• Get a new job
• Become a quant
• Make more money
• Automate daily tasks
• Level up your knowledge
• Trade stocks and options
Knowing where you want to end up, helps to know where to start.
10
161
1K
I read 69 books about quant finance during my master's degree.
Most of them were 100% useless.
But these 4 are still on my bookshelf 12 years later:
24
154
1K
Turn $1 into $14,000,000.
(You could have if you invested with Jim Simmons in 1988.)
The most successful hedge fund ever, trading bots, and the 9 steps to build an automated trading system.
The 6 blog posts to read now:
30
230
1K
A Bloomberg Terminal costs $2,500 per month (that's $30,000 per year—the cost of a car)
It's the portal to all the world's financial data.
Reserved for the Wall Street elite to outfox the normal investor.
Unaffordable for 99.9% of us.
Until now:
30
211
1K
9 must-have Python time series libraries everyone working with data should know:
14
168
1K
Beautiful trading strategy tear sheets in 5 lines of Python.
Build your own in 83 seconds:
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Blogs are ok.
But nothing beats a good book.
The 7 must-have books everyone using Python for algorithmic trading needs to know:
27
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Nobody taught me how to backtest a trading strategy.
So I read all the books, documentation, and blogs.
Then, I distilled what I learned into a simple step-by-step guide.
But unlike a 300-page book, this won't take you a month to read.
Here it is in 2 minutes:
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One way to get started with algorithmic trading is buying a $90,000 master's degree.
Another way is YouTube.
The 7 YouTube videos that will get you up and running today:
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998
ChatGPT is overhyped.
That's what I told myself after 2 weeks of failing to use it well.
Turns out, I was just a poor prompt writer.
But after spending 100 hours with it, I've cracked it.
And now, it's my personal research assistant and Python developer.
Here's how:
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ChatGPT will never work for trading.
That's what I thought 3 weeks ago.
Then I spent 35 hours in the GPT-4 rabbit hole.
These 6 blogs show you what you can do.
And it doesn't take a Ph.D. in prompt engineering:
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10 ways to use machine learning in trading (with the Python library):
11
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974
Algorithmic Trading Using Python (4.5 hours)
Learn how to perform algorithmic trading using Python in this complete course. Algorithmic trading means using computers to make investment decisions.
5
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958
BloombergGPT
A large language model for finance.
• Closed source
• $5 million to train
• Uses 1.3 million GPU hours
Enter FinGPT:
An open source large language model for finance.
• Open source
• $300 to train
• Uses 80 GPU hours
Get the code on GitHub:
16
147
969
With the OpenBB Terminal (previously GameStonk Terminal):
A Python-based environment for investment research.
There are over 500 functions covering:
• ETFs
• Forex
• Stocks
• Crypto
• Options
• Portfolio
• Economy
• Mutual funds
• Econometrics
Let's dive in:
13
110
951
My master's degree completely failed to teach me Python for quant finance (they taught me MATLAB).
And Octave (WTF?)
So I watched 200 YouTube videos.
And the truth is, 96% of them were a complete waste of time.
But these 8 taught me more than all my PhD professors combined:
23
207
947
Free code from book: Machine Learning in Finance: From Theory to Practice
This book integrates machine learning with quantitative finance, focusing on how theoretical frameworks inform data modeling and financial decision-making processes.
Get the code here:
7
185
945
I spent $90,000 on a master's degree.
I should have spent my time on YouTube instead.
Here's 32 YouTube videos covering the fundamentals of quant finance.
All free:
12
193
946
Myth:
You need a computer science degree to get started with Python, NumPy, and pandas.
Reality:
You need these 9 YouTube videos:
9
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935
Python for Data Analysis.
By the guy who invented pandas.
Free online:
9
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900
The 6 classic options trading books everyone needs on their bookshelf:
18
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903
Myth:
You need a computer science degree to get started with Python, NumPy, and pandas.
Reality:
You need these 9 YouTube videos:
20
261
892
8 trading and backtesting libraries in Python that will help you find your edge:
28
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The quant finance starter pack:
Markets:
• Participants
• Interest rates
• Microstructure
Stats:
• Probability
• Regression
• Time series analysis
Math:
• Calculus
• Matrix math
• Linear algebra
Programming:
• SQL
• Excel
• Python
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