Utility-Weighted Forecasting and Calibration for Risk-Adjusted Decisions under Trading Frictions
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arXiv
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| Natura: | Preprint |
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2026
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| _version_ | 1866917198240415744 |
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| author | Wright, Craig S |
| author_facet | Wright, Craig S |
| contents | Forecasting accuracy is routinely optimised in financial prediction tasks even though investment and risk-management decisions are executed under transaction costs, market impact, capacity limits, and binding risk constraints. This paper treats forecasting as an econometric input to a constrained decision problem. A predictive distribution induces a decision rule through a utility objective combined with an explicit friction operator consisting of both a cost functional and a feasible-set constraint system. The econometric target becomes minimisation of expected decision loss net of costs rather than minimisation of prediction error. The paper develops a utility-weighted calibration criterion aligned to the decision loss and establishes sufficient conditions under which calibrated predictive distributions weakly dominate uncalibrated alternatives. An empirical study using a pre-committed nested walk-forward protocol on liquid equity index futures confirms the theory: the proposed utility-weighted calibration reduces realised decision loss by over 30\% relative to an uncalibrated baseline ($t$-stat -30.31) for loss differential and improves the Sharpe ratio from -3.62 to -2.29 during a drawdown regime. The mechanism is identified as a structural reduction in the frequency of binding constraints (from 16.0\% to 5.1\%), preventing the "corner solution" failures that characterize overconfident forecasts in high-friction environments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_07852 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Utility-Weighted Forecasting and Calibration for Risk-Adjusted Decisions under Trading Frictions Wright, Craig S Econometrics Computational Finance Portfolio Management Trading and Market Microstructure 62M10, 62P05, 91B05, 90C15, 91G10, 91G70 G.3; G.1.6; J.4; H.4.2 Forecasting accuracy is routinely optimised in financial prediction tasks even though investment and risk-management decisions are executed under transaction costs, market impact, capacity limits, and binding risk constraints. This paper treats forecasting as an econometric input to a constrained decision problem. A predictive distribution induces a decision rule through a utility objective combined with an explicit friction operator consisting of both a cost functional and a feasible-set constraint system. The econometric target becomes minimisation of expected decision loss net of costs rather than minimisation of prediction error. The paper develops a utility-weighted calibration criterion aligned to the decision loss and establishes sufficient conditions under which calibrated predictive distributions weakly dominate uncalibrated alternatives. An empirical study using a pre-committed nested walk-forward protocol on liquid equity index futures confirms the theory: the proposed utility-weighted calibration reduces realised decision loss by over 30\% relative to an uncalibrated baseline ($t$-stat -30.31) for loss differential and improves the Sharpe ratio from -3.62 to -2.29 during a drawdown regime. The mechanism is identified as a structural reduction in the frequency of binding constraints (from 16.0\% to 5.1\%), preventing the "corner solution" failures that characterize overconfident forecasts in high-friction environments. |
| title | Utility-Weighted Forecasting and Calibration for Risk-Adjusted Decisions under Trading Frictions |
| topic | Econometrics Computational Finance Portfolio Management Trading and Market Microstructure 62M10, 62P05, 91B05, 90C15, 91G10, 91G70 G.3; G.1.6; J.4; H.4.2 |
| url | https://arxiv.org/abs/2601.07852 |