We propose a continuous-time model in which investors use expert forecasts to construct a benchmark-outperforming portfolio in two steps. The estimation step takes the form of a Kalman filter. The control step derives the optimal investment policy in closed form and establishes that the value function is the unique classical solution to the Hamilton-Jacobi-Bellman partial differential equation. We show that the optimal investment policy generates a continuum of investment strategies, from passive benchmark replication to fully active bets in the Kelly portfolio. However, our model warns against over-betting on financial markets. Moreover, we find that the Kelly portfolio performs both security selection and factor tilt. A simulation study with market data confirms that factor choice is critical at every stage of the investment process. Finally, debiasing is equally crucial. Portfolios with debiased expert forecasts outperform portfolios with biased forecasts.

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具有专家预测的风险敏感型基准资产管理

我们提出了一个连续时间模型，在该模型中，投资者使用专家预测分两步构建一个跑赢基准的投资组合。估计步骤采用卡尔曼滤波器的形式。控制步骤以封闭形式导出最优投资策略，并确定价值函数是 Hamilton-Jacobi-Bellman 偏微分方程的唯一经典解。我们表明，最佳投资政策会产生一系列投资策略，从被动的基准复制到凯利投资组合中的完全主动下注。然而，我们的模型警告不要在金融市场上过度下注。此外，我们发现凯利投资组合执行证券选择和因子倾斜。对市场数据的模拟研究证实，因子选择在投资过程的每个阶段都至关重要。最后，消除偏见同样重要。具有无偏专家预测的投资组合的表现优于具有有偏预测的投资组合。