基于信息更新的动态资产组合选择

本文研究了不完全信息下风险资产收益前两阶矩的参数不确定性对动态资产组合选择的影响。首先,在连续时间下假设资产价格服从随机扩散过程,引入参数不确定性,运用随机控制方法推导出风险资产最优选择的封闭解,给出定性分析。其次,在离散时间下用一阶自回归模型描述风险资产收益动态,基于贝叶斯分析框架,以上证综合指数不同区间段的两个样本做实证研究。结果表明,当投资者的风险规避程度大于(小于)对数效用时,参数不确定性将导致负(正)的投资期效应;当投资者在估计过程中运用较多的历史数据、或者风险规避程度增加时,参数不确定性的影响将减弱;参数不确定性下的资产组合选择可解释风险溢价之迷。研究说明了在动态资产组合选择过程中应考虑参数不确定性问题。     

均值-方差模型具有一般不确定性下的最优资产组合选择

引入以记忆系数和无差异系数表征的随机变量测度均值-方差模型的一般不确定性特征,反映投资者的模型信任程度,研究均值-方差模型具有一般不确定性下的最优资产组合选择问题。基于资本市场线理论,构建最优资产组合选择是模型信任程度和基于均值-方差模型的传统资产组合选择的线性函数;基于记忆系数和无差异系数的不同组合,运用基于事例推理的方法求解二次效用投资者的最优模型信任程度,获得均值-方差模型具有一般不确定性下的最优资产组合,并以上证综指1997年1月-2014年8月的月度收益数据形成两个研究样本予以实证比较研究。结果表明,较大风险规避投资者,在较大记忆系数和较小无差异系数下,其模型信任程度调整较快、资产组合调整幅度大,表现出可获得性和代表性行为偏差,通常采取积极资产组合策略;反之,其模型信任程度调整渐进、资产组合调整幅度小,表现出锚定性和保守性行为偏差,通常采取消极资产组合策略;模型一般不确定性对最优资产组合选择的影响强于股票市场记忆性的影响。研究体现了投资者的有限理性,将传统的资产组合选择问题延伸至行为金融学领域。     

RELATIVE RISK AVERSION IS CONSTANT: EVIDENCE FROM PANEL DATA

Most classical tests of constant relative risk aversion (CRRA) based on individual portfolio composition use cross‐sectional data. Such tests must assume that the distributions of wealth and preferences are independent. We use panel data to analyze how individuals’ portfolio allocation between risky and riskless assets varies in response to changes in total financial wealth. We find the elasticity of the risky asset share to wealth to be small and statistically insignificant, supporting the CRRA assumption; this finding is robust when the sample is restricted to households experiencing large income variations. In addition, we find a small but significant negative correlation between wealth and risk aversion. Various extensions are discussed.     

Ambiguity,Learning, and Asset Returns

We propose a novel generalized recursive smooth ambiguity model which permits a three‐way separation among risk aversion, ambiguity aversion, and intertemporal substitution. We apply this utility model to a consumption‐based asset‐pricing model in which consumption and dividends follow hidden Markov regime‐switching processes. Our calibrated model can match the mean equity premium, the mean risk‐free rate, and the volatility of the equity premium observed in the data. In addition, our model can generate a variety of dynamic asset‐pricing phenomena, including the procyclical variation of price–dividend ratios, the countercyclical variation of equity premia and equity volatility, the leverage effect, and the mean reversion of excess returns. The key intuition is that an ambiguity‐averse agent behaves pessimistically by attaching more weight to the pricing kernel in bad times when his continuation values are low.     

Perceived Ambiguity and Relevant Measures

We axiomatize preferences that can be represented by a monotonic aggregation of subjective expected utilities generated by a utility function and some set of i.i.d. probability measures over a product state space, S^∞. For such preferences, we define relevant measures, show that they are treated as if they were the only marginals possibly governing the state space, and connect them with the measures appearing in the aforementioned representation. These results allow us to interpret relevant measures as reflecting part of perceived ambiguity, meaning subjective uncertainty about probabilities over states. Under mild conditions, we show that increases or decreases in ambiguity aversion cannot affect the relevant measures. This property, necessary for the conclusion that these measures reflect only perceived ambiguity, distinguishes the set of relevant measures from the leading alternative in the literature. We apply our findings to a number of well‐known models of ambiguity‐sensitive preferences. For each model, we identify the set of relevant measures and the implications of comparative ambiguity aversion.     

Robust Contracts in Continuous Time

We study a continuous‐time contracting problem under hidden action, where the principal has ambiguous beliefs about the project cash flows. The principal designs a robust contract that maximizes his utility under the worst‐case scenario subject to the agent's incentive and participation constraints. Robustness generates endogenous belief heterogeneity and induces a tradeoff between incentives and ambiguity sharing so that the incentive constraint does not always bind. We implement the optimal contract by cash reserves, debt, and equity. In addition to receiving ordinary dividends when cash reserves reach a threshold, outside equity holders also receive special dividends or inject cash in the cash reserves to hedge against model uncertainty and smooth dividends. The equity premium and the credit yield spread generated by ambiguity aversion are state dependent and high for distressed firms with low cash reserves.     

模型不确定性条件下的Robust投资组合有效前沿与CAPM

本文提出了Robust投资组合有效前沿的概念,并研究了模型不确定性条件下的资本资产定价模型(CAPM)。研究发现,当市场上不存在无风险资产时,模型不确定性对风险资产投资比例的影响是非平等的,因此会导致投资组合的非分散化;而且此时的两基金分离定理以及零-βCAPM也不成立。但是当市场上存在无风险资产时,模型不确定性对风险资产投资比例的影响则是平等的,并且两基金分离定理仍然成立,因为任何Robust有效前沿组合都可以表示为市场组合与无风险资产的线性组合。而此时的CPAM仍然能够成立,只是在表达形式上增添了一个因子--不确定性因子;并且所有资产或资产组合的超额收益都可以分解为风险溢价与不确定性溢价两部分。     

A Smooth Model of Decision Making under Ambiguity

We propose and characterize a model of preferences over acts such that the decision maker prefers act f to act g if and only if 𝔼_μφ(𝔼_πu○f) 𝔼_μφ(𝔼_πu○g), where 𝔼 is the expectation operator, u is a von Neumann–Morgenstern utility function, φis an increasing transformation, and μis a subjective probability over the set Πof probability measures πthat the decision maker thinks are relevant given his subjective information. A key feature of our model is that it achieves a separation between ambiguity, identified as a characteristic of the decision maker's subjective beliefs, and ambiguity attitude, a characteristic of the decision maker's tastes. We show that attitudes toward pure risk are characterized by the shape of u, as usual, while attitudes toward ambiguity are characterized by the shape of φ. Ambiguity itself is defined behaviorally and is shown to be characterized by properties of the subjective set of measures Π. One advantage of this model is that the well‐developed machinery for dealing with risk attitudes can be applied as well to ambiguity attitudes. The model is also distinct from many in the literature on ambiguity in that it allows smooth, rather than kinked, indifference curves. This leads to different behavior and improved tractability, while still sharing the main features (e.g., Ellsberg's paradox). The maxmin expected utility model (e.g., Gilboa and Schmeidler (1989)) with a given set of measures may be seen as a limiting case of our model with infinite ambiguity aversion. Two illustrative portfolio choice examples are offered.     

Expected Uncertain Utility Theory

We introduce and analyze expected uncertain utility (EUU) theory. A prior and an interval utility characterize an EUU decision maker. The decision maker transforms each uncertain prospect into an interval‐valued prospect that assigns an interval of prizes to each state. She then ranks prospects according to their expected interval utilities. We define uncertainty aversion for EUU, use the EUU model to address the Ellsberg Paradox and other ambiguity evidence, and relate EUU theory to existing models.     

基于动态损失厌恶投资组合模型的最优资产配置与实证研究

从行为金融学的角度考虑投资者损失厌恶的心理特征,建立预期效用最大化的动态损失厌恶投资组合优化模型。以我国股票市场为依托,将市场分为上升、下降和盘整三种状态,研究动态损失厌恶投资组合模型的最优资产配置和绩效表现,并与静态损失厌恶投资组合模型、M-V投资组合模型和CVaR投资组合模型进行比较。最后,在具有交易成本的条件下对动态模型进行稳健性检验。得出结论：不同情况下,动态损失厌恶投资者具有不同的最优资产配置比例,且动态损失厌恶投资组合模型明显优于静态模型、M-V投资组合模型和CVaR投资组合模型。     

Overcoming Learning Aversion in Evaluating and Managing Uncertain Risks

Decision biases can distort cost‐benefit evaluations of uncertain risks, leading to risk management policy decisions with predictably high retrospective regret. We argue that well‐documented decision biases encourage learning aversion, or predictably suboptimal learning and premature decision making in the face of high uncertainty about the costs, risks, and benefits of proposed changes. Biases such as narrow framing, overconfidence, confirmation bias, optimism bias, ambiguity aversion, and hyperbolic discounting of the immediate costs and delayed benefits of learning, contribute to deficient individual and group learning, avoidance of information seeking, underestimation of the value of further information, and hence needlessly inaccurate risk‐cost‐benefit estimates and suboptimal risk management decisions. In practice, such biases can create predictable regret in selection of potential risk‐reducing regulations. Low‐regret learning strategies based on computational reinforcement learning models can potentially overcome some of these suboptimal decision processes by replacing aversion to uncertain probabilities with actions calculated to balance exploration (deliberate experimentation and uncertainty reduction) and exploitation (taking actions to maximize the sum of expected immediate reward, expected discounted future reward, and value of information). We discuss the proposed framework for understanding and overcoming learning aversion and for implementing low‐regret learning strategies using regulation of air pollutants with uncertain health effects as an example.     

奈特不确定性下的资产及其组合的惰性区间

不确定性是证券市场的基本特征之一,是资产定价和投资者交易行为等研究的主要内容。标准期望效用理论认为投资者具有唯一的资产执行价格,当市场价格高于执行价格时,投资者出售资产;反之,则会购进。然而,源于不确定性的存在,资产的均衡价格或交易价格并非某一确定值而是某一区间;在此区间内,投资者无交易行为,我们称之为资产的惰性区间。本文假定投资者是不确定性规避型,基于可行域上的容度,引入测度奈特不确定性程度的等级参数,研究奈特不确定性下的资产及其组合的惰性区间。基于容度期望效用模型,利用容度代替概率测度表征投资者预期效用,提出奈特不确定性下投资者决策行为的偏好表达式;基于对偶测度构建资产交易的惰性区间,分析奈特不确定性程度与惰性区间的关系;最后,基于Black-Scholes期权定价模型,选择存续期为2008年10月-2011年8月的江铜认购权证和长虹认购权证为研究对象,以其单资产及不同比例资产组合的日收益数据为样本予以实证。结果表明：随着奈特不确定性程度的不断增强（减弱）,资产及其组合的惰性区间不断扩大（缩小）,市场流动性随之下降（上升）;随着奈特不确定性程度的增强,高价格、高波动率的资产及其组合的惰性区间变化更为明显;在适度的奈特不确定性程度范围内,高波动率的资产及其组合的交易相对活跃。研究解释了证券市场上的“非市场参与”之谜和“特质波动率”之谜,说明了证券市场上的“有限市场参与”特征,为资产定价与市场流动性关系的研究提供了参考。     

Ambiguity,Risk, and Asset Returns in Continuous Time

Models of utility in stochastic continuous–time settings typically assume that beliefs are represented by a probability measure, hence ruling out a priori any concern with ambiguity. This paper formulates a continuous–time intertemporal version of multiple–priors utility, where aversion to ambiguity is admissible. In a representative agent asset market setting, the model delivers restrictions on excess returns that admit interpretations reflecting a premium for risk and a separate premium for ambiguity.     

Vector Expected Utility and Attitudes Toward Variation

This paper proposes a model of decision under ambiguity deemed vector expected utility, or VEU. In this model, an uncertain prospect, or Savage act, is assessed according to (a) a baseline expected‐utility evaluation, and (b) an adjustment that reflects the individual's perception of ambiguity and her attitudes toward it. The adjustment is itself a function of the act's exposure to distinct sources of ambiguity, as well as its variability. The key elements of the VEU model are a baseline probability and a collection of random variables, or adjustment factors, which represent acts exposed to distinct ambiguity sources and also reflect complementarities among ambiguous events. The adjustment to the baseline expected‐utility evaluation of an act is a function of the covariance of its utility profile with each adjustment factor, which reflects exposure to the corresponding ambiguity source. A behavioral characterization of the VEU model is provided. Furthermore, an updating rule for VEU preferences is proposed and characterized. The suggested updating rule facilitates the analysis of sophisticated dynamic choice with VEU preferences.     

Incorporating Black-Litterman views in portfolio construction when stock returns are a mixture of normals

In this paper, we consider the basic problem of portfolio construction in financial engineering, and analyze how market-based and analytical approaches can be combined to obtain efficient portfolios. As a first step in our analysis, we model the asset returns as a random variable distributed according to a mixture of normal random variables. We then discuss how to construct portfolios that minimize the Conditional Value-at-Risk (CVaR) under this probabilistic model via a convex program. We also construct a second-order cone representable approximation of the CVaR under the mixture model, and demonstrate its theoretical and empirical accuracy. Furthermore, we incorporate the market equilibrium information into this procedure through the well-known Black-Litterman approach via an inverse optimization framework by utilizing the proposed approximation. Our computational experiments on a real dataset show that this approach with an emphasis on the market equilibrium typically yields less risky portfolios than a purely market-based portfolio while producing similar returns on average.     

分形布朗运动下最优投保和消费策略

基于Merton的最优消费和投资组合模型,通过假设风险资产的价格变化服从几何分形布朗运动,探讨了一类具有人寿保险的最优投资消费问题.首先根据投资者在整个生命周期的消费和投保效用期望值最大的原则,利用贝尔曼动态规划原理,建立了最优投保和消费策略模型.然后在给定消费和遗赠评价效用函数的情况下,给出了最优投保和消费的闭式解,并获得了最优投资组合受模型参数变化影响的一些重要性质.最后,通过数值例子讨论了时间间隔、赫斯特指数变化时最优投保和最大期望效用的变化趋势.     

Risk‐Based Sampling: I Don't Want to Weight in Vain

Recently, there has been considerable interest in developing risk‐based sampling for food safety and animal and plant health for efficient allocation of inspection and surveillance resources. The problem of risk‐based sampling allocation presents a challenge similar to financial portfolio analysis. Markowitz (1952) laid the foundation for modern portfolio theory based on mean‐variance optimization. However, a persistent challenge in implementing portfolio optimization is the problem of estimation error, leading to false “optimal” portfolios and unstable asset weights. In some cases, portfolio diversification based on simple heuristics (e.g., equal allocation) has better out‐of‐sample performance than complex portfolio optimization methods due to estimation uncertainty. Even for portfolios with a modest number of assets, the estimation window required for true optimization may imply an implausibly long stationary period. The implications for risk‐based sampling are illustrated by a simple simulation model of lot inspection for a small, heterogeneous group of producers.     

参数暧昧环境下投资者决策与管制措施研究—基于随机禀赋与风险资产之间相关系数暧昧性的视角

假定全融市场中简单投资者具有暧昧厌恶偏好,在期末获得 1个单位随机禀赋（非全融资产收益）,而当前时刻他们对随机禀赋与风险资产未来收益之间的相关系数存在暧昧性,考察这种暧昧性对资产定价和社会福利的影响．研究表明相关系数暧昧性将导致投资者有限参与和资产定价扭曲．如果随机禀赋与凤险资产负相关,且凤险资产权益溢价为正,则简单投资者的超额收益为正,如果不相关,或者凤险资产权益溢价为零,则简单投资者无法获得超额收益,其它情况下简单投资者的超额收益为负．为缓解参数暧昧性,提高投资者参与市场的积极性,市场管理者可能实施提高复杂投资者的准入门槛、增强信息披露等管制措施．进一步研究发现,提高复杂投资者的准入门槛将减少其投资者占比,降低社会福利水平,而加强信息披露,提高市场透明度的措施可以提高社会福利水平．     

待遇预定制养老基金资产组合与缴费计划最优决策——基于随机波动率Heston模型及Legendre对偶变换法

待遇预定制养老金制度在中国应用非常广泛,缴费制定和资产配置是此类养老金管理的两大核心问题。由此,面对随机波动的现实市场,文章针对待遇预定制养老基金的资产组合管理问题,应用最优控制理论,选用对数效用函数,建立Heston随机波动率模型;在难以求解随机微分Bellman方程的情况下,应用Legendre变换,将原来问题转化为对偶问题,从而求得原问题的解析解。在理论上,进一步丰富了资产组合问题的随机最优控制模型的构建和随机微分方程的求解理论。在实践上,确定了养老金管理风险资产配置比例和缴费水平,给出了最优决策与总资产、发放待遇、净资产与风险溢价之间的数量关系,从而实现养老基金管理的最优资产配置和最低缴费水平的效用目标。     

EXPECTATIONS‐BASED REFERENCE‐DEPENDENT PREFERENCES AND ASSET PRICING

This paper explores the quantitative asset‐pricing implications of expectations‐based reference‐dependent preferences, as introduced by Koszegi and Rabin (2009, American Economic Review, 99(3), 909–936), in an otherwise traditional Lucas‐tree model. I find that the model easily succeeds in matching the historical equity premium and its variability when the preference parameters are calibrated in line with micro evidence. The equity premium is high because expectations‐based loss aversion makes uncertain fluctuations in consumption more painful. Additionally, loss aversion introduces variation in returns because unexpected cuts in consumption are particularly painful, and the agent wants to postpone such cuts to let his reference point decrease. This variation generates strong predictability. However, it also causes counterfactually high volatility in the risk‐free rate, which I address by allowing for variation in expected consumption growth, heteroskedasticity in consumption growth, time‐variant disaster risk, and sluggish belief updating.