ENH Replace linear cone with bootstrapped non-parametric cone #233
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@twiecki I think this might be good to go. |
| create_future_cone=True): | ||
| """Computes a rolling cone to place in the cumulative returns | ||
| plot. See plotting.plot_rolling_returns. | ||
| def forecast_cone_bounds(is_returns, num_days, cone_std, |
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we might want to add more, so maybe forecast_cone_bootstrap?
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Also could provide default cone_std values of 1, 1.5, and 2.
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| perf_ts_r = perf_ts_r.append(future_cone) | ||
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| return perf_ts_r |
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So great to see all that complexity go.
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Looks great overall but see minor comments. |
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Merged with 9cc98eb 👍 |
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The old linear cone had several troubling assumptions (normal returns, use of arithmetic-like return averaging in the backtest, linearity of future returns, starting capital of oos == fixed starting value of the cone).
This new bootstrapped cone makes fewer assumptions by building its forward projection from samples drawn directly from the in-sample daily returns. This direct sampling makes the bootstrapped cone non-parametric, it does not assume backtest returns fit into any particular distribution.
Discussion here: #178