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No new signal, learner, tuning grid or output cap.", "absolute_monthly_forecast_warning": 0.2, "cohorts": [ "all common forecast dates, including portfolio warm-up", "all common allocated development dates" ], "forecast_priority": "Per-asset MAE, RMSE and OOS R2 against same-date expanding historical mean; largest absolute forecast; count and frequency above the unchanged 20% inspection threshold; inspect every flagged month and asset.", "portfolio_secondary": "Net return, daily drawdown, turnover, costs, allocation-limit frequency and calendar-year stability using identical continuous dates and allocation rules. Never select preprocessing to recover the original 23.99% return.", "cause_audit": "Reconstruct January 2020 from raw policy sheet values, completed training targets, median imputation, ddof=0 scaling, selected Ridge coefficients and additive contributions. Preserve units and source dates.", "selection": "Explicit corrected primary chosen for numerical safeguards, not highest portfolio return. Its numerical acceptance and matched historical-mean predictive claims are evaluated separately. Report negative results without restoring unstable behavior.", "reserved_test": "No 2023-onward holding month is evaluated. Final candidate, preprocessing and acceptance criteria must be explicitly frozen before any test, and the team must confirm whether that period remains unexamined.", "vintages": "Revised-data limitation remains. ALFRED collection is a separate deferred task." }, "primary_scope": "all common eligible holding months through December 2022", "reserved_test_start": "2023-01-01", "unchanged_signal_candidates": [ "claims", "credit", "curve" ], "benchmarks": [ "expanding historical mean through BL", "BL prior without predictive views", "fixed 45/35/20", "fixed 60/40", "SPY only" ], "robustness_checks": { "robust": "Original inputs; clip training and test features to training-only 1st/99th percentiles in every fold; Ridge grid [1,10,100,1000]. No return-forecast cap.", "no_policy": "Original inputs excluding the five policy-path fields; same dates, training minimum, tuning and allocator as baseline. Quantifies dependence on sparse policy history.", "clip_only": "Training-fold 1st/99th percentile clipping with original Ridge grid [0.01,0.1,1,10,100].", "shrink_only": "No input clipping; stronger Ridge grid [1,10,100,1000].", "supported_policy": "Original Ridge grid and no clipping; a policy feature is disabled in each training/validation fold until it has 12 finite observed training values. The threshold is a fixed sensitivity setting, not a selected production rule." }, "diagnostics": [ "per-asset errors and ranges", "training coverage", "standardized input extremes", "additive feature contributions to each forecast", "monthly forecast/posterior/weight and realized-return attribution", "calendar-year returns", "2020-excluded compounded returns" ], "interpretation": "The corrected primary is explicitly selected for documented numerical safeguards after earlier development results were observed. No significance claim, vintage reconstruction, new horizon search or reserved-test evaluation. Earlier variants remain diagnostic comparisons. No return-based threshold optimization.", "timing_corrections": "Every inner validation target must end by its validation decision date. Policy snapshots dated after the last trading-day cutoff are withheld in all variants.", "inspection_threshold": "Absolute monthly forecasts above 20% are flagged, not clipped.", "previous_specification_sha256": "bc3b3bb658865f3183c2c42dd24b45b1997345a51c858c178520ed9df926fdc0", "inference": { "bootstrap": { "method": "paired circular moving-block bootstrap of monthly net-return differences versus baseline, conditional on the fitted continuous runs", "replications": 3000, "seed": 20261102, "block_lengths": [ 3, 6, 12 ], "confidence": 0.95, "statistic": "mean monthly net-return difference; unadjusted percentile intervals, exploratory, no multiple-comparison correction and no model refitting" }, "episode_boundary_offsets_months": [ -1, 0, 1 ], "episode_boundary_rule": "Shift starts and ends independently. Evaluate only complete windows within the common development history. Never clip requests into the reserved test or reset holdings.", "leave_out": "Exclude each named episode from the continuous development run without retraining; compound retained months only.", "credit_redundancy": "Report ANFCI and credit-level/change correlations on common development dates, plus expanding past-only prediction of each credit feature from contemporaneous known ANFCI level/change; 24 prior feature rows minimum. Descriptive shared information, not causal or proof of redundancy." }, "deferred": [ "real-time vintage/release timestamp reconstruction", "release-day and 3/6-month targets", "duration-adjusted credit and claims-consensus data", "separately authorized reserved-period evaluation after freeze verification and team nonexposure confirmation" ] }, "specification_sha256": "5ff8d68bb6996dc270b978c1c22ce2746fa1c3b1d212947ec21b0310376cd67a", "code_hashes": { "corrected_primary.py": "8630d700ddb904e85b281db15a8958055872cb9677a39b38af6df98085f38648", "research_backtest.py": "15023f494eff043a8bb1a211fd7eb94535f5c133a76f31016eed1a21975daa8c", "research_stability.py": "9c69973c35165e060512be69f963d3b539f8c7aee89efaf278d7b0e22f0d9ac7", "research_diagnostics.py": "ebb219491f006ec9a953ab079acc791fe2607159e6de5ed68651dce59bebf812", "research_inference.py": "78e32a8b08a9b0b047a6809ed72c75a1ebaa7695438f5ac4db3256535beea9e4", "deterministic_mvp.py": "4df2eadd4645c2d8e2a4ff868b4cfe65347c87be2fd86942407291f65a3436d9" }, "periods": [ { "id": "covid_shock", "name": "COVID shock", "start": "2020-02-29", "end": "2020-04-30", "description": "February\u2013April 2020 holding months. 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No cash series is supplied: views are total returns, not cash-adjusted excess returns.", "warning_threshold": "Absolute forecast above 20% per holding month is flagged for inspection only; never clipped by this diagnostic.", "vintages": "Latest revised histories with assumed lags. These diagnostics do not reconstruct real-time vintages." }, "stability": { "status": "Corrected primary explicitly selected for numerical safeguards; historical variants retained as diagnostic comparisons. No reserved-test evaluation.", "threshold": 0.2, "comparison_order": [ "corrected", "baseline", "supported_policy", "no_policy", "clip_only", "shrink_only", "robust", "historical_mean" ], "threshold_interpretation": "Inspection threshold fixed before this investigation. Zero flags does not establish forecast accuracy or a calibrated prediction interval. 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"constant_training_column": false, "input_clipped": false, "enabled": true, "raw_input": -0.624, "input_imputed": false, "imputation_median": -0.5315000000000001, "training_mean": -0.4957586206896552, "processed_input": -0.624, "coefficient": 0.0013445438078152348, "distinct_observed_values": 53 }, { "feature": "policy_6m_level", "contribution": -0.0007764075184676311, "standardized_input": 2.3325248612411293, "observed_training_rows": 3, "training_scale": 0.04425129313493732, "constant_training_column": false, "input_clipped": false, "enabled": true, "raw_input": 1.3611, "input_imputed": false, "imputation_median": 1.2579, "training_mean": 1.2578827586206898, "processed_input": 1.3611, "coefficient": -0.0003328614118412899, "distinct_observed_values": 3 } ] } }, "same_decision_repairs": { "corrected": [ 0.01509157836169056, 0.0018476274414089256, 0.0028777358739449912 ], "baseline": [ 5.894544161780397, 0.6583727284491454, 6.7747514451618995 ], "robust": [ 0.012150144098659207, 0.002116602919008865, 0.003913660003719241 ], "clip_only": [ 0.025280562755078596, -2.6686500329766057e-06, 0.004267441021785431 ], "shrink_only": [ 0.8381440640203327, 0.18037477400381347, 0.289190562472002 ], "supported_policy": [ 0.015045407980710232, 0.0018797194915454952, 0.01676484895811063 ], "no_policy": [ 0.015045407980710232, 0.0018797194915454952, 0.01676484895811078 ], "historical_mean": [ 0.009771539741788274, 0.002384876922640984, 0.004002660981074045 ] }, "conclusion": "Reproduced sparse-feature extrapolation: two almost identical observed policy changes, plus median-imputed earlier rows, produce a tiny fitted scale. January's opposite-signed change becomes an enormous standardized input. The coefficient times that input reconstructs the dominant forecast contribution. This confirms the numerical mechanism in the supplied workbook, not the external correctness or historical availability of the workbook values." }, "evaluation_rules": { "scope": "Add the corrected primary to existing baseline, policy-coverage safeguard, no-policy, clipping-only, shrinkage-only, combined robust and expanding historical mean. New policy eligibility rules are fixed in primary_spec.json, not selected from episode returns. No new signal, learner, tuning grid or output cap.", "absolute_monthly_forecast_warning": 0.2, "cohorts": [ "all common forecast dates, including portfolio warm-up", "all common allocated development dates" ], "forecast_priority": "Per-asset MAE, RMSE and OOS R2 against same-date expanding historical mean; largest absolute forecast; count and frequency above the unchanged 20% inspection threshold; inspect every flagged month and asset.", "portfolio_secondary": "Net return, daily drawdown, turnover, costs, allocation-limit frequency and calendar-year stability using identical continuous dates and allocation rules. Never select preprocessing to recover the original 23.99% return.", "cause_audit": "Reconstruct January 2020 from raw policy sheet values, completed training targets, median imputation, ddof=0 scaling, selected Ridge coefficients and additive contributions. Preserve units and source dates.", "selection": "Explicit corrected primary chosen for numerical safeguards, not highest portfolio return. Its numerical acceptance and matched historical-mean predictive claims are evaluated separately. Report negative results without restoring unstable behavior.", "reserved_test": "No 2023-onward holding month is evaluated. Final candidate, preprocessing and acceptance criteria must be explicitly frozen before any test, and the team must confirm whether that period remains unexamined.", "vintages": "Revised-data limitation remains. ALFRED collection is a separate deferred task." } }, "primary": { "key": "corrected", "specification": { "id": "corrected-primary-v1", "selected_on": "2026-11-05", "status": "Primary specification selected after development diagnostics, before running this new rule. Exploratory development result; not independently selected.", "variant": "corrected", "features": [ "growth_surprise", "inflation_surprise", "policy_3m_level", "policy_6m_level", "policy_path_slope", "policy_3m_change", "policy_6m_change", "anfci", "gpr", "growth_x_anfci", "inflation_x_anfci", "growth_x_gpr", "inflation_x_gpr" ], "preprocessing": { "imputation": "Finite training median per feature; zero only if entirely missing. Fit separately inside every inner and outer training fold.", "clip_quantiles": [ 0.01, 0.99 ], "quantile_method": "linear; computed on training rows after training-only imputation", "scaling": "Training mean and population standard deviation (ddof=0), after clipping. Apply training bounds, center and scale to validation/current inputs.", "numerical_constant_std": 1e-12, "disabled_feature": "Zero both training and prediction standardized columns; coefficient/contribution exactly zero.", "policy": { "min_source_observations": 12, "min_distinct_resolution_bins": 3, "resolution_percentage_points": 0.01, "min_observed_std_percentage_points": 0.01, "min_processed_std_percentage_points": 0.01, "counting": "Only finite original source observations whose source date is at or before that row's decision cutoff; each source date counts once per feature. Imputed or carried-forward-only rows do not create observed history.", "variation": "Observed-only std on unique eligible source snapshots; distinct values are numpy rint(value/0.01) bins. Also require processed training std after imputation/clipping. Thresholds are inclusive.", "rationale": "Retain the existing twelve-observation sensitivity as a minimum, strengthen it to distinct source snapshots and three distinct one-basis-point bins, and reject sub-one-basis-point standard deviations. One basis point is an explicit economic-resolution engineering choice, not a validated optimum. Rules will not be tuned against development portfolio returns." } }, "ridge": { "alphas": [ 0.01, 0.1, 1.0, 10.0, 100.0 ], "objective": "Sum squared loss plus alpha times squared coefficient norm; unpenalized training-target-mean intercept, targets in monthly decimal returns.", "tuning": "Same chronological per-asset MSE tuning as clipping-only; inner targets must finish by validation cutoff. Fixed alpha order breaks ties. All preprocessing and policy checks are refit in every fold." }, "training": { "start": "2015-02-28", "min_completed_outer_targets": 36, "inner_first_index_rule": "max(24, n_train // 2); embargo incomplete training intervals before each validation decision" }, "portfolio": { "assets": [ "SPY", "IEF", "LQD" ], "starting_weights": [ 0.45, 0.35, 0.2 ], "bounds": [ [ 0.2, 0.7 ], [ 0.15, 0.6 ], [ 0.1, 0.4 ] ], "risk_aversion": 2.5, "tau": 0.05, "grid_step": 0.01, "turnover_penalty": 5e-05, "covariance_months": 36, "min_covariance_months": 24, "min_prior_errors": 12, "cost_bps_per_dollar_traded": 5, "covariance": "Last 36 known calendar-close monthly returns, at least 24; sample covariance.", "view_uncertainty": "Sample variance (ddof=1) of this corrected model's own prior completed forecast errors, at least 12. Recomputed from the start; no original-model error history reused.", "execution": "Decide at 8pm New York on last trading day; enter next trading-day adjusted close, exit next rebalance adjusted close. Continuous holdings with drift and multiplicative trading costs. Initial mix already funded." }, "evaluation": { "development_last_holding_month": "2022-12-31", "forecast_cohorts": [ "all matched forecasts including allocation warm-up", "common portfolio holding dates" ], "benchmarks": [ "historical_mean", "fixed453520", "sixtyForty", "spyOnly", "prior_only" ], "diagnostic_comparisons": [ "baseline", "clip_only" ], "warning_absolute_monthly_return": 0.2, "numerical_acceptance": "Finite forecasts, exact decomposition within 1e-10, no policy contribution when disabled, prior-only preprocessing/target/error timing, reconciled wealth/costs/bounds, zero 20% warning flags over both development cohorts. Failure is reported; no output cap, silent fallback or automatic retuning.", "forecast_reporting": "Per-asset MAE/RMSE, OOS R2 against matched expanding historical mean, largest absolute forecast and warning counts; calendar years and policy activation reasons.", "predictive_claim_rule": "Claim per-asset development improvement only if OOS R2 > 0 and MAE <= expanding historical mean in both cohorts. Report failures explicitly; this is descriptive, not a significance claim.", "portfolio_reporting": "Net cumulative return, daily maximum drawdown, turnover, costs, allocation-limit frequency and calendar-year returns on identical continuous dates. No minimum return target and no selection to restore 23.99%." }, "reserved_test": { "start": "2023-01-01", "run_authorized": false, "team_nonexposure_confirmed": false, "rule": "Never evaluate in these development commands. Freeze hashes before a separately authorized evaluation; first confirm whether the team has examined this period. Do not retune after seeing reserved results." }, "data_limitations": "Latest revised macro histories and assumed release lags remain; no ALFRED real-time vintage reconstruction. A numerical correction does not cure revised-data bias." }, "specification_sha256": "e3d6ff9b3a8c5aeb44a3969b62b39546259724b6879608ab51f2b3f157b5cf8a", "selection_basis": "Clipping-only candidate plus source-history/variation safeguards fixed before this correction's development run. No threshold search to recover portfolio returns.", "numerical_acceptance": { "passed": true, "checks": { "finite_forecasts": true, "decomposition_reconciles": true, "disabled_contributions_zero": true, "completed_training_targets": true, "own_completed_bl_error_history": true, "portfolio_bounds": true, "costs_reconcile": true, "no_reserved_holding_month": true, "zero_extreme_flags_both_cohorts": true } }, "predictive_claims": { "equity": false, "treasury": false, "ig_credit": false }, "forecast_conclusion": "Per-asset improvement is descriptive and requires positive OOS R2 and no worse MAE in both cohorts. Numerical stability alone is insufficient.", "comparisons": [ "corrected", "historical_mean", "fixed453520", "sixtyForty", "spyOnly", "prior_only", "clip_only", "baseline" ], "portfolio_results": { "corrected": { "months": 44, "cumulative_return": 0.1263308958735545, "annualized_return": 0.03297717785201426, "annualized_volatility": 0.118963948009501, "sharpe_zero_rf": 0.3314444354773638, "maximum_drawdown": -0.24210384349380942, "average_turnover": 0.19725062459116546, "cost_bps_sum": 43.395137410056414, "end_value": 112.63308958735546, "entry": "2019-05-01", "exit": "2023-01-03", "recovery_date": null, "drawdown_trough": "2022-10-14", "difference_vs_baseline": -0.11354251833085738 }, "historical_mean": { "months": 44, "cumulative_return": 0.1459269500145861, "annualized_return": 0.03784789566837232, "annualized_volatility": 0.11591851571460501, "sharpe_zero_rf": 0.3780514158161797, "maximum_drawdown": -0.22123479334255813, "average_turnover": 0.021513385368840985, "cost_bps_sum": 4.732944781145016, "end_value": 114.59269500145861, "entry": "2019-05-01", "exit": "2023-01-03", "recovery_date": null, "drawdown_trough": "2022-10-14", "difference_vs_baseline": -0.09394646418982577 }, "fixed453520": { "months": 44, "cumulative_return": 0.16594552459310874, "annualized_return": 0.04276148033853677, "annualized_volatility": 0.11412927869278004, "sharpe_zero_rf": 0.4237195511124054, "maximum_drawdown": -0.21302906371996233, "average_turnover": 0.023390601774975983, "cost_bps_sum": 5.145932390494718, "end_value": 116.59455245931088, "entry": "2019-05-01", "exit": "2023-01-03", "recovery_date": null, "drawdown_trough": "2022-10-14", "difference_vs_baseline": -0.07392788961130314 }, "sixtyForty": { "months": 44, "cumulative_return": 0.22815881931602977, "annualized_return": 0.05765041679085936, "annualized_volatility": 0.12866963909292348, "sharpe_zero_rf": 0.4999820933877941, "maximum_drawdown": -0.211936207274246, "average_turnover": 0.024706210773111817, "cost_bps_sum": 5.4353663700846, "end_value": 122.81588193160299, "entry": "2019-05-01", "exit": "2023-01-03", "recovery_date": null, "drawdown_trough": "2022-10-14", "difference_vs_baseline": -0.011714594888382113 }, "spyOnly": { "months": 44, "cumulative_return": 0.3887796043892038, "annualized_return": 0.09370450010351727, "annualized_volatility": 0.21317064536082223, "sharpe_zero_rf": 0.5285715917426704, "maximum_drawdown": -0.3371727693638181, "average_turnover": 0.0, "cost_bps_sum": 0.0, "end_value": 138.87796043892038, "entry": "2019-05-01", "exit": "2023-01-03", "recovery_date": "2020-08-10", "drawdown_trough": "2020-03-23", "difference_vs_baseline": 0.1489061901847919 }, "prior_only": { "months": 44, "cumulative_return": 0.16285781332748872, "annualized_return": 0.04200762045318118, "annualized_volatility": 0.11421165813842805, "sharpe_zero_rf": 0.41716826469786833, "maximum_drawdown": -0.21551685427261347, "average_turnover": 0.013675105190230817, "cost_bps_sum": 3.0085231418507803, "end_value": 116.28578133274887, "entry": "2019-05-01", "exit": "2023-01-03", "recovery_date": null, "drawdown_trough": "2022-10-14", "difference_vs_baseline": -0.07701560087692316 }, "clip_only": { "months": 44, "cumulative_return": 0.13324778491334377, "annualized_return": 0.034703399719228534, "annualized_volatility": 0.10955758954284263, "sharpe_zero_rf": 0.36574441713461014, "maximum_drawdown": -0.21840540914632334, "average_turnover": 0.1730219763764399, "cost_bps_sum": 38.064834802816776, "end_value": 113.32477849133438, "entry": "2019-05-01", "exit": "2023-01-03", "recovery_date": null, "drawdown_trough": "2022-10-14", "difference_vs_baseline": -0.10662562929106811 }, "baseline": { "months": 44, "cumulative_return": 0.23987341420441188, "annualized_return": 0.06039226079529203, "annualized_volatility": 0.10423325396875392, "sharpe_zero_rf": 0.6147703559176854, "maximum_drawdown": -0.21416432845537647, "average_turnover": 0.10744165591572524, "cost_bps_sum": 23.637164301459567, "end_value": 123.9873414204412, "entry": "2019-05-01", "exit": "2023-01-03", "recovery_date": null, "drawdown_trough": "2022-10-14", "difference_vs_baseline": 0.0 } }, "calendar_years": [ { "year": 2019, "partial_year": true, "results": { "corrected": { "months": 8, "cumulative_return": 0.09491741552716015, "annualized_return": null, "annualized_volatility": 0.05904974042312602, "sharpe_zero_rf": null, "maximum_drawdown": -0.016383001481400705, "average_turnover": 0.18670091159759578, "cost_bps_sum": 7.4680364639038315, "end_value": 109.49174155271601, "entry": "2019-05-01", "exit": "2020-01-02", "recovery_date": "2019-06-06", "drawdown_trough": "2019-05-13" }, "historical_mean": { "months": 8, "cumulative_return": 0.10054482957222532, "annualized_return": null, "annualized_volatility": 0.057300665388508455, "sharpe_zero_rf": null, "maximum_drawdown": -0.016383001481400705, "average_turnover": 0.010486258591216192, "cost_bps_sum": 0.4194503436486477, "end_value": 110.05448295722253, "entry": "2019-05-01", "exit": "2020-01-02", "recovery_date": "2019-06-06", "drawdown_trough": "2019-05-13" }, "fixed453520": { "months": 8, "cumulative_return": 0.10274061096597653, "annualized_return": null, "annualized_volatility": 0.05859907061542379, "sharpe_zero_rf": null, "maximum_drawdown": -0.016752346457281853, "average_turnover": 0.01861432335123117, "cost_bps_sum": 0.7445729340492467, "end_value": 110.27406109659766, "entry": "2019-05-01", "exit": "2020-01-02", "recovery_date": "2019-08-08", "drawdown_trough": "2019-08-05" }, "sixtyForty": { "months": 8, "cumulative_return": 0.10477915622319434, "annualized_return": null, "annualized_volatility": 0.07557676505912315, "sharpe_zero_rf": null, "maximum_drawdown": -0.026325043100827283, "average_turnover": 0.019517672272715447, "cost_bps_sum": 0.7807068909086179, "end_value": 110.47791562231944, "entry": "2019-05-01", "exit": "2020-01-02", "recovery_date": "2019-09-04", "drawdown_trough": "2019-08-05" }, "spyOnly": { "months": 8, "cumulative_return": 0.1293996669697648, "annualized_return": null, "annualized_volatility": 0.14950208180052463, "sharpe_zero_rf": null, "maximum_drawdown": -0.06618341091341384, "average_turnover": 0.0, "cost_bps_sum": 0.0, "end_value": 112.93996669697647, "entry": "2019-05-01", "exit": "2020-01-02", "recovery_date": "2019-06-20", "drawdown_trough": "2019-06-03" }, "prior_only": { "months": 8, "cumulative_return": 0.10230424160056395, "annualized_return": null, "annualized_volatility": 0.05762292018307141, "sharpe_zero_rf": null, "maximum_drawdown": -0.016911589277390005, "average_turnover": 0.008856509891472495, "cost_bps_sum": 0.35426039565889983, "end_value": 110.23042416005639, "entry": "2019-05-01", "exit": "2020-01-02", "recovery_date": "2019-08-08", "drawdown_trough": "2019-08-05" }, "clip_only": { "months": 8, "cumulative_return": 0.09491741552716015, "annualized_return": null, "annualized_volatility": 0.05904974042312602, "sharpe_zero_rf": null, "maximum_drawdown": -0.016383001481400705, "average_turnover": 0.18670091159759578, "cost_bps_sum": 7.4680364639038315, "end_value": 109.49174155271601, "entry": "2019-05-01", "exit": "2020-01-02", "recovery_date": "2019-06-06", "drawdown_trough": "2019-05-13" }, "baseline": { "months": 8, "cumulative_return": 0.09996798691989972, "annualized_return": null, "annualized_volatility": 0.059250060705770664, "sharpe_zero_rf": null, "maximum_drawdown": -0.016383001481400705, "average_turnover": 0.14949140746149348, "cost_bps_sum": 5.979656298459738, "end_value": 109.99679869198998, "entry": "2019-05-01", "exit": "2020-01-02", "recovery_date": "2019-06-06", "drawdown_trough": "2019-05-13" } } }, { "year": 2020, "partial_year": false, "results": { "corrected": { "months": 12, "cumulative_return": 0.1559682050350284, "annualized_return": 0.1559682050350284, "annualized_volatility": 0.15944201814300107, "sharpe_zero_rf": 0.9880878887015876, "maximum_drawdown": -0.1902806366830151, "average_turnover": 0.11572150505794661, "cost_bps_sum": 6.943290303476797, "end_value": 115.59682050350284, "entry": "2020-01-02", "exit": "2021-01-04", "recovery_date": "2020-05-29", "drawdown_trough": "2020-03-20" }, "historical_mean": { "months": 12, "cumulative_return": 0.13677463419461078, "annualized_return": 0.13677463419461078, "annualized_volatility": 0.15057378910651598, "sharpe_zero_rf": 0.9257924071475632, "maximum_drawdown": -0.17429906482160906, "average_turnover": 0.04719273530717183, "cost_bps_sum": 2.831564118430309, "end_value": 113.67746341946108, "entry": "2020-01-02", "exit": "2021-01-04", "recovery_date": "2020-06-02", "drawdown_trough": "2020-03-20" }, "fixed453520": { "months": 12, "cumulative_return": 0.137702106948133, "annualized_return": 0.137702106948133, "annualized_volatility": 0.14937527324434258, "sharpe_zero_rf": 0.9376860500257932, "maximum_drawdown": -0.16971435923834177, "average_turnover": 0.03415470854172812, "cost_bps_sum": 2.0492825125036873, "end_value": 113.7702106948133, "entry": "2020-01-02", "exit": "2021-01-04", "recovery_date": "2020-06-03", "drawdown_trough": "2020-03-20" }, "sixtyForty": { "months": 12, "cumulative_return": 0.1481890324993662, "annualized_return": 0.1481890324993662, "annualized_volatility": 0.173607212581132, "sharpe_zero_rf": 0.8812275542468392, "maximum_drawdown": -0.186633629586342, "average_turnover": 0.03740913973564381, "cost_bps_sum": 2.244548384138628, "end_value": 114.81890324993661, "entry": "2020-01-02", "exit": "2021-01-04", "recovery_date": "2020-06-05", "drawdown_trough": "2020-03-23" }, "spyOnly": { "months": 12, "cumulative_return": 0.15639194127651912, "annualized_return": 0.15639194127651912, "annualized_volatility": 0.31391842982651, "sharpe_zero_rf": 0.6162285569649381, "maximum_drawdown": -0.3371727693638181, "average_turnover": 0.0, "cost_bps_sum": 0.0, "end_value": 115.6391941276519, "entry": "2020-01-02", "exit": "2021-01-04", "recovery_date": "2020-08-10", "drawdown_trough": "2020-03-23" }, "prior_only": { "months": 12, "cumulative_return": 0.13713056066172724, "annualized_return": 0.13713056066172724, "annualized_volatility": 0.1491751755220814, "sharpe_zero_rf": 0.9353919013035498, "maximum_drawdown": -0.17230649606338866, "average_turnover": 0.020917209589665975, "cost_bps_sum": 1.2550325753799585, "end_value": 113.71305606617273, "entry": "2020-01-02", "exit": "2021-01-04", "recovery_date": "2020-06-03", "drawdown_trough": "2020-03-20" }, "clip_only": { "months": 12, "cumulative_return": 0.1173790135398256, "annualized_return": 0.1173790135398256, "annualized_volatility": 0.13845269217180967, "sharpe_zero_rf": 0.8694898260548529, "maximum_drawdown": -0.18877239381434752, "average_turnover": 0.25876568694083996, "cost_bps_sum": 15.525941216450393, "end_value": 111.73790135398255, "entry": "2020-01-02", "exit": "2021-01-04", "recovery_date": "2020-07-22", "drawdown_trough": "2020-03-19" }, "baseline": { "months": 12, "cumulative_return": 0.21160572254277987, "annualized_return": 0.21160572254277987, "annualized_volatility": 0.11196362653895586, "sharpe_zero_rf": 1.7784574629262007, "maximum_drawdown": -0.11878268633966127, "average_turnover": 0.26922964452654563, "cost_bps_sum": 16.153778671592736, "end_value": 121.160572254278, "entry": "2020-01-02", "exit": "2021-01-04", "recovery_date": "2020-04-09", "drawdown_trough": "2020-03-19" } } }, { "year": 2021, "partial_year": false, "results": { "corrected": { "months": 12, "cumulative_return": 0.1021170525748587, "annualized_return": 0.1021170525748587, "annualized_volatility": 0.04985264549292579, "sharpe_zero_rf": 1.9811344445331838, "maximum_drawdown": -0.0344088338040327, "average_turnover": 0.1777508819809487, "cost_bps_sum": 10.665052918856924, "end_value": 110.21170525748586, "entry": "2021-01-04", "exit": "2022-01-03", "recovery_date": "2021-04-08", "drawdown_trough": "2021-03-08" }, "historical_mean": { "months": 12, "cumulative_return": 0.10219827524584058, "annualized_return": 0.10219827524584058, "annualized_volatility": 0.04763346364969448, "sharpe_zero_rf": 2.072911865530719, "maximum_drawdown": -0.035156822816508004, "average_turnover": 0.009957350396108067, "cost_bps_sum": 0.5974410237664841, "end_value": 110.21982752458406, "entry": "2021-01-04", "exit": "2022-01-03", "recovery_date": "2021-04-08", "drawdown_trough": "2021-03-04" }, "fixed453520": { "months": 12, "cumulative_return": 0.11065132495107788, "annualized_return": 0.11065132495107788, "annualized_volatility": 0.04782203749515561, "sharpe_zero_rf": 2.226034409637318, "maximum_drawdown": -0.034098187535436475, "average_turnover": 0.015058858214547536, "cost_bps_sum": 0.9035314928728521, "end_value": 111.06513249510779, "entry": "2021-01-04", "exit": "2022-01-03", "recovery_date": "2021-04-08", "drawdown_trough": "2021-03-04" }, "sixtyForty": { "months": 12, "cumulative_return": 0.16004448604431598, "annualized_return": 0.16004448604431598, "annualized_volatility": 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