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Apr 2, 2022 - Python
finance
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🌟 Feature Description
Motivation
Qlib has integrated pylint and flake8 to automatically detect the problem of coding style
But some errors are not fixed due to the limited bandwidth of the maintainers.
It will be very helpful if the commun
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Expected Behavior
backtesting binance cypto
Actual Behavior
Can't place an order
Potential Solution
- Add all crypto exchanges missing stable coins to be added at https://github.com/QuantConnect/Lean/blob/master/Common/Currencies.cs#L116
Reproducing the Problem
def Initialize(self):
self.SetStartDate(2018, 5, 2)
self.SetEndDate(2021, 5, 4)
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Apr 2, 2022 - Python
Hi,
I am currently using your FinRL_PortfolioAllocation_NeurIPS_2020 code and I have some strange behavior at the beginning of training. Sometimes the first episode reward mean value is super high and then drops during the training as shown on the tensorboard plot. This high value is never reached again. Any idea why this is happening ?
Edit: I'm training PPO agent from stablebaselines3 wit
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.
Can we display an asset name in https://pyportfolioopt.readthedocs.io/en/latest/_images/ef_plot.png ?
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Feb 17, 2021
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Apr 1, 2022 - Python
When I ran Center of Gravity: cg over 3 months of Bitcoin prices ("20200801" to "20201101"), I got
| Close | cg | |
|---|---|---|
| count | 132481.000000 | 132472.000000 |
| mean | 11378.306788 | -5.499988 |
| std | 844.355621 | 0.001991 |
| min | 9881.820000 | -5.616297 |
| 25% | 10710.500000 | -5.500833 |
| 50% | 11368.680000 | -5.499987 |
| 75% | 11742.540000 | -5.499146 |
| 1 |
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