Open BB, a Python-based environment for investment research

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:

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?

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:

Let's start by analyzing Tesla.

First, type *stocks* at the command prompt to show the menu.

These are all the sub menus you can explore to analyze stocks.

The menu items in grey are not available until you load stock data.

Let's load TSLA now.

Type *load TSLA*.

This will load TSLA price data (for free) and print out a performance summary.

Now we can start to analyze TSLA.

Type *help* to see that all 17 sub menus are now available.

There's too much here to cover in a thread.

Take some time and explore each of the sub menus to find the functions.

Let's keep going.

We start with a fundamental analysis.

Load the fundamental analysis functions by typing *fa*.

OpenBB presents another list of functions to analyze TLSA's fundamentals.

Let's check out how the market capitalization has changed through time.

Type *mktcap*.

Voila!

OpenBB opens up a chart in a separate window.

Check out some of the other functions now.

To go back, type *q*.

Let's move on to technical analysis by typing *ta*.

Since TSLA is already loaded, all 25 of the menu items are lit up.

Let's check out the exponential moving average

Type *ema*.

OpenBB opens up a new window with the price chart and EMA.

Let's check out all our favorite:

Quantitative analysis.

Type *q* to go back and type *qa* to open the menu.

OpenBB has 23 functions for quantitative analysis.

By default, all analyses are done on returns.

If you want to change the data field, type *pick* then a space.

Let's check out a histogram of returns.

This gives you an idea of the shape of the distribution.

It also lets you view and return outliers.

Type *hist* and OpenBB opens up a histogram of returns.

Rumor has it that hedge funds rely on signal processing to make trade decisions.

Let's decompose the cyclic-trend, season, and residuals of price.

Type *decompose*.

OpenBB has rich options analysis functionality.

Let's check it out.

Type *q* to go back and type *options*.

You can run an analysis on unusual activity or an options screener.

I want to analyze options for TSLA.

We first need to load an expiration.

Type *exp* to display a list of expirations.

Then type *exp {number}* to load data for a specific option.

I'll select the September expiration for TSLA by typing *exp 7*.

Type *help* again.

All the menus are now available.

The put call ratio is the ratio of open interest in put options divided by the open interest in call options.

Values over 1 indicate bearish sentiment.

Type *pcr* to plot this ratio.

If you're interested in options trading, you may like the 46-Page Ultimate Guide to Pricing Options and Implied Volatility With Python.

• Black-Scholes pricing
• Calculate the greeks
• Compute implied volatility

All with Python.

https://pyquantnews.gumroad.com/l/46-page-ultimate-guide-pricing-options-implied-volatility-python-pdf-code-pyquant-news

More with OpenBB:

Screeners
Sentiment
Forex data
Excel models
Co-integration
Autocorrelation
Max drawdown
Volatility surface
Economic indexes
Crypto order books
Time series analysis
Portfolio optimization
Brokerage integration
Mutual fund allocation
Custom reports & dashboards

A license for a Bloomberg Terminal costs $24,000 per year.

OpenBB is free.

Get it here:

https://openbb.co/products/terminal

That's a wrap!

If you enjoyed this thread:

• Follow @pyquantnews for the best resources for using Python for quantitative analysis
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Originally tweeted by PyQuant News (@pyquantnews) on July 21, 2022.

I downloaded the installer but have done nothing more. Link provided because it is interesting. ABN

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