贝叶斯方法在养老基金资产负债管理中的应用

把一个静态资产负债管理模型———均值方差模型应用到定额给付养老金计划的资产负债管理中,在允许无风险借贷的条件下研究养老金在无风险资产和风险资产间的分配问题,用定量分析的方法求出了最优投资组合的一般形式;又针对投资收益率特征参数未知的情况,提出了矩估计和贝叶斯估计两种方法求解最优资本配置比例,将两种方法的结果与一般形式对比,分析了影响最优投资组合的因素,得知养老基金在风险资产中的投资比例与基金经理对风险的厌恶程度、风险资产的风险益酬、风险资产收益率的波动性成负相关关系;并且随决策者掌握的历史信息增加,在风险资产上的投资比例也随之增加,投资行为逐渐趋于理性化;对上述结果进行仿真,验证了结论的有效性。     

收益现值法的若干结果

本文对资产评估中常用的方法——收益现值法的现有计算公式进行了拓展，并对资产预期收益的一些具体形式给出了资产评估值的计算公式。     

具有比例摩擦金融市场的一般经济均衡与资产定价(英文)

本文建立具有比例摩擦金融市场的简单两时期模型．经济人具有均值－方差偏好,并且在交易金融资产的过程中支付交易费用．本文证明了两种金融资产的一般经济均衡与资产定价的基本估值公式．     

Student-like models for risky asset with dependence

We present a new construction of the Student and Student-like fractal activity time model for risky asset. The construction uses the diffusion processes and their superpositions and allows for specified exact Student or Student-like marginal distributions of the returns and for flexible and tractable dependence structure. The fractal activity time is asymptotically self-similar, which is a desired feature seen in practice.     

Longevity-linked assets and pre-retirement consumption/portfolio decisions

We solve the consumption/investment problem of an agent facing a stochastic mortality intensity. The investment set includes a longevity-linked asset, as a derivative on the force of mortality. In a complete and frictionless market, we derive a closed form solution when the agent has Hyperbolic Absolute Risk Aversion preferences and a fixed financial horizon. Our calibrated numerical analysis on US data shows that individuals optimally invest a large fraction of their wealth in longevity-linked assets in the pre-retirement phase, because of their need to hedge against stochastic fluctuations in their remaining life-time at retirement.     

Deep learning for finance: deep portfolios

We explore the use of deep learning hierarchical models for problems in financial prediction and classification. Financial prediction problems – such as those presented in designing and pricing securities, constructing portfolios, and risk management – often involve large data sets with complex data interactions that currently are difficult or impossible to specify in a full economic model. Applying deep learning methods to these problems can produce more useful results than standard methods in finance. In particular, deep learning can detect and exploit interactions in the data that are, at least currently, invisible to any existing financial economic theory. Copyright © 2016 John Wiley & Sons, Ltd.     

Confidence band for expectation dependence with applications

Motivated by the applications of the concept of expectation dependence in economics and finance, we propose a method to construct uniform confidence band for expectation dependence. It is derived based on Hoeffding’s inequality. Our proposed confidence band can be explicitly expressed and thus it is very easy to implement. Our method has applications to demand for a risky asset and first-order risk aversion problems. Simulations suggest our proposed confidence interval can control the coverage probabilities very well, and the average lengths are very short. Two empirical applications are presented to illustrate the usefulness of the constructed confidence band of expectation dependence.     

Optimal dynamic asset allocation of pension fund in mortality and salary risks framework

In this paper, we consider the optimal dynamic asset allocation of pension fund with mortality risk and salary risk. The managers of the pension fund try to find the optimal investment policy (optimal asset allocation) to maximize the expected utility of terminal wealth. The market is a combination of financial market and insurance market. The financial market consists of three assets: cashes with stochastic interest rate, stocks and rolling bonds, while the insurance market consists of mortality risk and salary risk. These two non-hedging risks cause incompleteness of the market. By martingale method and dynamic programming principle we first derive the approximate optimal investment policy to overcome the difficulty, then investigate the efficiency of the approximation. Finally, we solve an optimal assets liabilities management(ALM) problem with mortality risk and salary risk under CRRA utility, and reveal the influence of these two risks on the optimal investment policy by numerical illustration.     

Better than optimal mean–variance portfolio policy in multi-period asset–liability management problem

When the wealth is larger than some threshold in multi-period mean–variance asset–liability management, the pre-committed policy is no longer mean–variance efficient policy for the remaining investment horizon. To revise the policy, by relaxing self-financing constraint and allowing to withdraw some wealth, we derive a new dominating policy, which is better than the pre-committed policy. The revised policy can achieve the same mean–variance pairs attained by the pre-committed policy, and yields a nonnegative free cash flow stream over the investment horizon.     

文化创意产业债务融资结构的影响因素研究——基于2012～2016年上市公司的面板数据

文化创意企业具有轻实物资产,无形资产作用强;收益不确定,创意价值高;投入产出效率差异大,衍生品链条长的特点。本文基于沪深股市159家文化创意上市公司2012～2016年度的面板数据,采用固定效应模型和动态面板模型,研究了文化创意产业融资结构的影响因素。与已有研究结果不同的是,无形资产持有率和资产负债率正相关,盈利能力和资产负债率负相关,而股权结构、企业规模、成长性和资产负债率不相关。同时发现资产负债水平存在自我调节机制,滞后两期资产负债率对当期资产负债率产生影响,存在反应时滞。根据研究结论与文化创意企业的特点,提出了改善文化创意企业资本结构的建议。