finance

Describe your context
Please provide us your environment, so we can easily reproduce the issue.

• replace the result of pip list | grep dash below

dash                      2.0.0
dash-bootstrap-components 1.0.0

• if frontend related, tell us your Browser, Version and OS

  • OS: [e.g. iOS] Windows
  • Browser [e.g. chrome, safari]: Chrome 96.0x, Edge 96.0x, Firefox

🐛 Bug Description

Qlib does not require the installation of packages like CatBoostModel

But the output looks a little misleading.

To Reproduce

Run examples/workflow_by_code.ipynb in jupyter notebook.

Expected Behavior

Successfully run the script without installing CatBoostModel and warning.

Screenshot

![image](https://user-images.githubusercontent.com/465606/1

Expected Behavior

LEAN provides an example of IndicatorVolatilityModel for documentation.

Actual Behavior

There is no example for this feature.

Potential Solution

Adds an example and/or unit tests.

Checklist

• I have completely filled out this template
• I have confirmed that this issue exists on the current master branch
• I have confirmed that t

The preprocessing is very slow in FinRL. The Nmba allow GPU parallelization with C speed for process array data. Some high speed trading framework like vectorbt use it.

Is possible to take experience from vectorbt and use Numba to speed up FinRL?

Reading currencies, alphavantage returns a greeting note ("welcome") and this note raises an error in alphavantage.py line 363.

            elif "Note" in json_response and self.treat_info_as_error:
                raise ValueError(json_response["Note"])

For this reason, alphavantage does not work in home assistant.

Heston model has accurate density approximations for European option prices, which are of interest.

The module implementing this method should live under tf_quant_finance/volatility/heston_approximation.py. It should support both European option puts and calls approximations. Tests should be in heston_approximation_test.py in the same folder.

According to @rspadim, functions in entropy.py could use numpy array instead of strings, as it's better to numba.

Guide on how to implement this is available in the comments in PR #311 .

Ulcer Index

in development version: I am ignoring everget

highest_close = close.rolling(length).max()
downside = scalar * (close - highest_close)
downside /= highest_close
d2 = downside * downside
_ui = d2.rolling(length).sum()
ui = np.sqrt(_ui / length)

In development version, sometime I am getting RuntimeWarning: invalid value encountered in sqrt after searching abo

As an intermediate step towards #1015, and various parts thereof, would it be possible to ignore the syntax for features not currently supported, yet use the parts which are supported in trades?
I'm thinking out loud and wondering what effects this may have.

My end goal here is to be able to read a data file https://gitlab.com/snippets/1856416 without errors. Hledger would be able to parse thi