- Purpose: [Describe the purpose of this document. E.g., to define the design of the XYZ system.]
- Scope: [Summarize the system's objectives and what is in/out of scope.]
- Definitions and Acronyms: [List and define important terms.]
- References: [Link to related documents: requirements, API specs, etc.]
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| # compute sharpe ratio using Pandas rolling and std methods, the trading days is set to 252 days | |
| TRADING_DAYS = 252 | |
| returns = np.log(df['Close']/df['Close'].shift(1)) | |
| returns.fillna(0, inplace=True) | |
| volatility = returns.rolling(window=TRADING_DAYS).std()*np.sqrt(TRADING_DAYS) | |
| sharpe_ratio = returns.mean()/volatility | |
| sharpe_ratio.tail() | |
| fig = plt.figure(figsize=(15, 7)) | |
| ax3 = fig.add_subplot(1, 1, 1) |
Many different applications claim to support regular expressions. But what does that even mean?
Well there are lots of different regular expression engines, and they all have different feature sets and different time-space efficiencies.
The information here is just copied from: http://regular-expressions.mobi/refflavors.html
Specifically from Rakuten TV (live.tv.rakuten.co.jp)
FMI: https://cdm-project.com/How-To/ & https://old.reddit.com/r/Piracy/comments/y30ffr/
- Install Tampermonkey: https://www.tampermonkey.net/
- Install yt-dlp: https://github.com/yt-dlp/yt-dlp#installation
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