A simplified Capital Asset Pricing Model

私募资产配置的动态模型

A Dynamic Model of Private Asset Allocation

本文构建了一个考虑非流动性、时间滞后、商业周期、收益序列相关性和监管约束的私募资产配置动态模型，利用机器学习方法量化基金生命周期内的最优投资策略，并为监管机构设定风险资本要求提供量化工具。

资产定价模型中的投资者情绪：实证证据综述

Investor Sentiment in Asset Pricing Models: A Review of Empirical Evidence

本文综述了2000至2021年间71篇相关论文，发现更复杂的投资者情绪度量能提高模型拟合度，但并未带来更优的预测能力，且情绪作用因资产与时期而异，BW指数共识或需调整。

Deep Partial Least Squares for Empirical Asset Pricing

We use deep partial least squares (DPLS) to estimate an asset pricing model for individual stock returns that exploits conditioning information in a flexible and dynamic way while attributing excess returns to a small set of statistical risk factors. The novel contribution is to resolve the non-linear factor structure, thus advancing the current paradigm of deep learning in empirical asset pricing which uses linear stochastic discount factors under an assumption of Gaussian asset returns and factors. This non-linear factor structure is extracted by using projected least squares to jointly proj…

Asset Allocation under the Basel Accord Risk Measures

Financial institutions are currently required to meet more stringent capital requirements than they were before the recent financial crisis; in particular, the capital requirement for a large bank's trading book under the Basel 2.5 Accord more than doubles that under the Basel II Accord. The significant increase in capital requirements renders it necessary for banks to take into account the constraint of capital requirement when they make asset allocation decisions. In this paper, we propose a new asset allocation model that incorporates the regulatory capital requirements under both the Basel…

绩效分析与实证资产定价中的随机控制

Randomized Control in Performance Analysis and Empirical Asset Pricing

本文提出用几何随机游走生成满足投资者约束的随机投资组合作为控制组，以分析因子溢价与实际绩效，并指出传统随机投资组合推断在高维几何下面临的挑战。

Multi-Moments Method for Portfolio Management: Generalized Capital Asset Pricing Model in Homogeneous and Heterogeneous markets

We introduce a new set of consistent measures of risks, in terms of the semi-invariants of pdf's, such that the centered moments and the cumulants of the portfolio distribution of returns that put more emphasis on the tail the distributions. We derive generalized efficient frontiers, based on these novel measures of risks and present the generalized CAPM, both in the cases of homogeneous and heterogeneous markets. Then, using a family of modified Weibull distributions, encompassing both sub-exponentials and super-exponentials, to parameterize the marginal distributions of asset returns and the…

Comparing Asset Pricing Models: Distance-based Metrics and Bayesian Interpretations

In light of the power problems of statistical tests and undisciplined use of alpha-based statistics to compare models, this paper proposes a unified set of distance-based performance metrics, derived as the square root of the sum of squared alphas and squared standard errors. The Bayesian investor views model performance as the shortest distance between his dogmatic belief (model-implied distribution) and complete skepticism (data-based distribution) in the model, and favors models that produce low dispersion of alphas with high explanatory power. In this view, the momentum factor is a crucial…

Optimal Investment Strategy for Risky Assets

We design an optimal strategy for investment in a portfolio of assets subject to a multiplicative Brownian motion. The strategy provides the maximal typical long-term growth rate of investor's capital. We determine the optimal fraction of capital that an investor should keep in risky assets as well as weights of different assets in an optimal portfolio. In this approach both average return and volatility of an asset are relevant indicators determining its optimal weight. Our results are particularly relevant for very risky assets when traditional continuous-time Gaussian portfolio theories are…

Calculated Boldness: Optimizing Financial Decisions with Illiquid Assets

We consider games of chance played by someone with external capital that cannot be applied to the game and determine how this affects risk-adjusted optimal betting. Specifically, we focus on Kelly optimization as a metric, optimizing the expected logarithm of total capital including both capital in play and the external capital. For games with multiple rounds, we determine the optimal strategy through dynamic programming and construct a close approximation through the WKB method. The strategy can be described in terms of short-term utility functions, with risk aversion depending on the ratio o…