scholarly journals When Is a Risky Asset “Urgently Needed”?

2014 ◽  
Vol 6 (2) ◽  
pp. 131-162 ◽  
Author(s):  
Felix Kubler ◽  
Larry Selden ◽  
Xiao Wei
Keyword(s):  
Asset Pricing ◽  
Risky Asset ◽  
Portfolio Problem ◽  
Asset Demand ◽  
Preference Condition

Risk free asset demand in the classic portfolio problem is shown to decrease with income if and only if the consumer's uncertainty preferences over assets satisfy the preference condition that the risk free asset is more readily substituted for the risky asset as the quantity of the latter increases. In this case, the risky asset is said to be “urgently needed” following the terminology of the classic certainty analysis of Johnson (1913). The urgently needed property tends to be more readily satisfied in uncertainty versus certainty settings. Asset pricing implications of this property are provided. (JEL D11, D53, D81, G11, G12)

Asymmetric Information, Heterogeneous Belief and Risky Asset Pricing

2012 ◽  
Vol 430-432 ◽  
pp. 1095-1098
Author(s):  
Xiao Qiang Yu ◽  
Shan Cun Liu
Keyword(s):  
Asset Pricing ◽  
Asymmetric Information ◽  
Empirical Research ◽  
Asset Price ◽  
Risky Asset ◽  
Pricing Model ◽  
Asset Pricing Model

In this paper, we put forward the assumption that investors have asymmetric information and heterogeneous belief and derive an asset pricing model. The model suggests the extent of asymmetric information or heterogeneous belief is positively correlated with the risky asset price, which matches the former empirical research.

scholarly journals Modern Portfolio Theory: Some Main Results

1988 ◽  
Vol 18 (2) ◽  
pp. 127-145 ◽  
Author(s):  
Heinz H. Müller
Keyword(s):  
Asset Pricing ◽  
Utility Theory ◽  
Portfolio Theory ◽  
Capital Asset Pricing ◽  
Risk Allocation ◽  
Pricing Model ◽  
Capital Asset ◽  
Modern Portfolio Theory ◽  
Asset Pricing Model ◽  
Portfolio Problem

AbstractThis article summarizes some main results in modern portfolio theory. First, the Markowitz approach is presented. Then the capital asset pricing model is derived and its empirical testability is discussed. Afterwards Neumann–Morgenstern utility theory is applied to the portfolio problem. Finally, it is shown how optimal risk allocation in an economy may lead to portfolio insurance.

scholarly journals How the Investor’s Risk Preferences Influence the Optimal Allocation in a Credibilistic Portfolio Problem

2019 ◽  
Vol 7 (4) ◽  
pp. 317-329
Author(s):  
Irina Georgescu ◽  
Jani Kinnunen
Keyword(s):  
Utility Function ◽  
Portfolio Choice ◽  
Expected Utility ◽  
Optimal Allocation ◽  
Fuzzy Variable ◽  
Risky Asset ◽  
Credibility Theory ◽  
Fuzzy Variables ◽  
Portfolio Problem ◽  
Approximation Calculation

Abstract A classical portfolio theory deals with finding the optimal proportion in which an agent invests a wealth in a risk-free asset and a probabilistic risky asset. Formulating and solving the problem depend on how the risk is represented and how, combined with the utility function defines a notion of expected utility. In this paper the risk is a fuzzy variable and the notion of expected utility is defined in the setting of Liu’s credibility theory. Thus, the portfolio choice problem is formulated as an optimization problem in which the objective function is a credibilistic expected utility. Different approximation calculation formulas for the optimal allocation of the credibilistic risky asset are proved. These formulas contain two types of parameters: Various credibilistic moments associated with fuzzy variables (expected value, variance, skewness and kurtosis) and the risk aversion, prudence and temperance indicators of the utility function.

Optimization of Capital Distribution and Composition of a Shipping Company Fleet Through Evolutionary Algorithms

2021 ◽  
pp. 227853372110119
Author(s):  
Alkis Thrassou ◽  
Demetris Vrontis ◽  
Georgios Georgopoulos ◽  
Petros Lois ◽  
Spyros Repousis
Keyword(s):  
Asset Pricing ◽  
Evolutionary Algorithms ◽  
Portfolio Management ◽  
Risky Asset ◽  
Fleet Management ◽  
Risk Minimization ◽  
Shipping Company ◽  
Fleet Composition ◽  
Research Findings ◽  
Investor Returns

The research examines the optimization of fleet management of a shipping company through control algorithms, as finding an algorithm that will reduce a marine company’s exposure to risk by diversifying its fleet composition is one way to make it dominant. The study focused on three companies that, in 2014, invested US$$1 billion in a fleet of tankers, using three different techniques to optimize their fleet composition: equal number of ships of all types, the established risk minimization model and the proposed Risky Asset Pricing maximization model. Seven years of data was used for the synthesis and 4 years of data was used for the evaluation. The research findings show that classic portfolio management through risk minimization is ineffective, as it appears to reduce performance below what is a random or evenly distributed fleet. Comparing the three methods, the superiority of the Risky Asset Pricing model is clear. This algorithm looks for solutions where the demand for ships is low but has enormous fluctuation potential and seeks to identify ships that are at high risk with great potential for price increases to maximize investor returns. The value of the research lies in the identification of methods to optimize capital distribution and composition of a shipping company fleet, which presents valuable insights for the benefit of scholars and maritime companies. Moreover, and contrary to extant works that focus on Markowitz’s theory, this article instead describes how evolutionary algorithms can be used to optimize fleet management.

Risky asset pricing based on safety first fund management

2009 ◽  
Vol 9 (3) ◽  
pp. 353-361 ◽  
Author(s):  
Yuanyao Ding§ ◽  
Bo Zhang
Keyword(s):  
Asset Pricing ◽  
Risky Asset ◽  
Fund Management ◽  
Safety First

Defining Bad News: Changes in Return Distributions That Decrease Risky Asset Demand

2009 ◽  
Vol 55 (7) ◽  
pp. 1227-1236 ◽  
Author(s):  
Burton Hollifield ◽  
Alan Kraus
Keyword(s):  
Risky Asset ◽  
Bad News ◽  
Return Distributions ◽  
Asset Demand

scholarly journals Optimal stopping time, consumption, labour, and portfolio decision for a pension scheme

2020 ◽  
Author(s):  
Francesco Menoncin ◽  
Sergio Vergalli
Keyword(s):  
Optimal Stopping ◽  
Labour Supply ◽  
Stopping Time ◽  
Risky Asset ◽  
Pension Scheme ◽  
Optimal Stopping Time ◽  
Martingale Approach ◽  
Portfolio Problem ◽  
Portfolio Decision ◽  
Hamilton Jacobi Bellman

Abstract In this work we solve in a closed form the problem of an agent who wants to optimise the inter-temporal recursive utility of both his consumption and leisure by choosing: (1) the optimal inter-temporal consumption, (2) the optimal inter-temporal labour supply, (3) the optimal share of wealth to invest in a risky asset, and (4) the optimal retirement age. The wage of the agent is assumed to be stochastic and correlated with the risky asset on the financial market. The problem is split into two sub-problems: the optimal consumption, labour, and portfolio problem is solved first, and then the optimal stopping time is approached. We compute the solution through both the so-called martingale approach and the solution of the Hamilton–Jacobi–Bellman partial differential equation. In the numerical simulations we compare two cases, with and without the opportunity, for the agent, to work after retirement, at a lower wage rate.

scholarly journals Modern Portfolio Theory: Some Main Results

1989 ◽  
Vol 19 (S1) ◽  
pp. 9-27
Author(s):  
Heinz H. Müller
Keyword(s):  
Asset Pricing ◽  
Utility Theory ◽  
Portfolio Theory ◽  
Capital Asset Pricing ◽  
Risk Allocation ◽  
Pricing Model ◽  
Capital Asset ◽  
Modern Portfolio Theory ◽  
Asset Pricing Model ◽  
Portfolio Problem

AbstractThis article summarizes some main results in modern portfolio theory. First, the Markowitz approach is presented. Then the capital asset pricing model is derived and its empirical testability is discussed. Afterwards Neumann–Morgenstern utility theory is applied to the portfolio problem. Finally, it is shown how optimal risk allocation in an economy may lead to portfolio insurance.

Freedom Indices and Capital Asset Pricing Model: Some Malaysian Evidence

2020 ◽  
Vol 1 (1) ◽  
pp. 1-21
Author(s):  
Ying Tay Lee ◽  
Devinaga Rasiah ◽  
Ming Ming Lai
Keyword(s):  
Human Rights ◽  
Asset Pricing ◽  
Stock Returns ◽  
Firm Size ◽  
Explanatory Power ◽  
Least Square ◽  
Press Freedom ◽  
Capital Asset Pricing ◽  
Capital Asset ◽  
Cross Sectional

Human rights and fundamental freedoms such as economic, political, and press freedoms vary widely from country to country. It creates opportunity and risk in investment decisions. Thus, this study is carried out to examine if the explanatory power of the model for capital asset pricing could be improved when these human rights movement indices are included in the model. The sample for this study comprises of 495 stocks listed in Bursa Malaysia, covering the sampling period from 2003 to 2013. The model applied in this study employed the pooled ordinary least square regression estimation. In addition, the robustness of the model is tested by using firm size as a controlled variable. The findings show that market beta as well as the economic and press freedom indices could explain the cross-sectional stock returns of the Malaysian stock market. By controlling the firm size, it adds marginally to the explanation of the extended CAP model which incorporated economic, political, and press freedom indices.

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