treynor_ratio() missing 1 required positional argument: 'benchmark' in train_and_evaluate.ipynb Cell 10

[Quentin168]

Please make sure that this is a Bug or a Feature Request and provide all applicable information asked by the template. If your issue is an implementation question, please ask your question on StackOverflow or on the TensorTrade Discord #help-desk channel instead of opening a GitHub issue.

System information

• Have I written custom code (as opposed to using example directory):
• OS Platform and Distribution Windows 10
• TensorTrade version:
• TensorFlow version: AttributeError: module 'tensorflow' has no attribute 'GIT_VERSION'
• Python version: Python 3.9.7

You can obtain the TensorFlow version with:
python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)"

### _d:\tensortrade-master\examples\train_andevaluate.ipynb Cell 10'**** in <cell line: 1>() ----> 1 data = generate_features(data) d:\tensortrade-master\examples\train_and_evaluate.ipynb Cell 9' in generate_all_default_quantstats_features(data) 54 for indicator_name in indicators_list: 55 try: 56 #print(indicator_name) ---> 57 indicator = qs.stats.dictindicator_name 58 if isinstance(indicator, pd.Series): 59 indicator = indicator.to_frame(name=indicator_name)

TypeError: treynor_ratio() missing 1 required positional argument: 'benchmark'

Describe the expected behavior treynor_ratio() is special, missing 1 required positional argument: 'benchmark'

Code to reproduce the issue
Provide a reproducible test case that is the bare minimum necessary to generate the problem.

Other info / logs
Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached.

[segatrade]

Got the same bug

[sanoj2021]

Same here after following @selentium0 advise in issue #443

[lifehsiwu]

Got the same bug

[fsz168]

The same problem, many bugs

[nexon33]

same

[newzapster]

Same here. Any solution?

[newzapster]

Solved by adding treynor_ratio in the excluded_indicators like below:

def generate_all_default_quantstats_features(data): excluded_indicators = [ 'compare', 'greeks', 'information_ratio', 'treynor_ratio', 'omega', 'r2', 'r_squared', 'rolling_greeks', 'warn' ]