Estimation of Goal Achieving Probabilities
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Using transition probabilities, it estimates the Expected Wealth paths and the probability of achieving the goals from a specific point in time (t0) to the goal achievement time (T).
- For instance, it can estimate the probability that wealth of around $100 in January 2020 will exceed $250 by December 2022.
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All you need is asset return panel data and weights panel data
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check tutorial.ipynb
- Portfolio: All Weather Portfolio (SPY, TLT, IEF, GLD, DBC)
- Assume an investor wants to know the probability that the wealth, which was 200 in January 2020, will be greater than 220 or 250 in December 2021
- no additional cashflows excluding initial wealth
- you can consider cashflows plans using
model.add_cashflow()
method.
Start Date | End Date | Wealth(start) | Wealth(end) | Probability |
---|---|---|---|---|
2020-01-31 | 2021-12-31 | 200 | 220 | 0.5606 |
2020-01-31 | 2021-12-31 | 200 | 250 | 0.3607 |
- Python >= 3.8
- numpy
- pandas
- scipy