Rebalance and user friendliness updates #7
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These changes in simulator.py and portfolio_maker.py help with real life rebalance use cases by accounting for shares owned before the simulation period. Made corresponding updates and corrected typo in HistoricalSimulator.portfolio_value().
HistoricalSimulator() now has a 'target_rb_date' argument for users to select the index of their preferred rebalance day in relevant months. HistoricalSimulator._calc_rebalance_info() and its associated methods have been changed accordingly (and are now more correct than before). Updated example.ipynb as well.
Again focused on helping real life rebalances, HistoricalSimulator.append_a_date() allows users to pass a new date and a dictionary of ticker symbols and new prices that will then be included in the simulation. Made a notebook to demonstrate the process.
Equipped some new pandas magic now that I'm more familiar with the package. Crucially, indexing asset dataFrames by date instead of integer index should make slicing much more intuitive, which should also simplify the Strategy creation process. Making this switch required many small/medium changes throughout HistoricalSimulator and the existing Strategy classes, hence this commit's size. Highlights include: - Shifted from using datetime to pandas' Timestamp for date-related attributes due to its flexibility and speed. - Made asset and rebalance-related dataFrames timezone-naive to improve ease of indexing. - Combined HistoricalSimulator's rb_indices and sat_only into one date-indexed dataFrame of rebalance information, rb_info. - Added another abstract method to HistoricalSimulator for refreshing Strategy-specific class attributes after running append_date().
Added a simpler class to strategies.py and made an example notebook for it, rebalance.ipynb. Also updated example.ipynb to incorporate the previous commit's changes.
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I originally just wanted to provide a way to start certain assets off with a nonzero number of shares, but a combination of learning more about
pandasand getting some distance from the last set of commits led me to make the following changes:PortfolioMakerinstead of being forced to start at 0.append_date, aHistoricalSimulatormethod that allows users to append a day's worth of prices. Since you can't get same-day prices from Tiingo during market hours, this helps with executing real-life rebalances.pandas.Timestamp-based indexingHistoricalSimulatorand allStrategyclasses, which should be more intuitive than needing to match indices to dates.Strategyclass,BuyAndHoldStrategy, for simpler, core-only portfolios.verboseargument toHistoricalSimulatorsoStrategyclass instances can be quieter when needed.