scholarly journals Life-Cycle Portfolio Choice, the Wealth Distribution and Asset Prices

Author(s):  
Felix E. Kubler ◽  
Karl H. Schmedders
2021 ◽  
Vol 55 (Különszám 2) ◽  
pp. 33-46
Author(s):  
Alexandra Posza ◽  
Vivien Csapi

THE AIMS OF THE PAPER The population factor in general influences most of the global megatrends. While it was considered one of the major driving forces for economicgrowth in the 20th century, it has become the greatest risk factor for the socio-economic landscape. Hungary is experiencing one of the fastest demographic transitions in Europe. Due to the continued extension of longevity and the steep decline in fertility rate, the size and percentage of theelderly population (i.e., aged 65 and above) rapidly increased during the last decades. The paper aims to examine whether population ageing has an effect on asset prices in Hungary. METHODOLOGY The life cycle theory for Hungary was applied while exploring the quantitative link between population structures and asset prices, particularly onstock and bonds. In this study, the relationship between Hungary’s demographic characteristics and asset class returns will be examined by reviewing previous academic and policy studies through conducting a regression analysis of bond yields and P/E ratio of BUX Index related to demographic variables. MOST IMPORTANT RESULTS The connection between stock prices and demographic trends is impacted by the life cycle theory of asset accumulation/decumulation and portfolio choice. In Hungary, the younger adults between 36 and 45, and the classic middle-aged individuals are in their peak savings years and invest heavily in stocks, driving up stock prices. The old-aged individuals decumulate assets and sell stocks to finance their retirement, depressing stock prices. In addition, the investors become more risk-averse and prefer fewer holdings of stocks as they grow older. The Middle/Old ratio and the BUX P/E ratio have a strong positive correlation during the period 1995-2020. The bond yields show a similar connection with the Yuppie/Nerd ratio. The results of demographic variables predicting bond-yields are strong and proving the international patterns. RECOMMENDATIONS The paper highlighted that the demographic variables are not only appropriate for socio-demographic analysis since the members of the different age groups have their own consumption, saving and investing characteristics that can have an impact on the asset prices besides other commonly usedparameters. Acknowledgements: This article was supported by EFOP­3.6.1­16­2016­00004 that has been entitled ‘Comprehensive developments at the University of Pécs for smart specialization’. (Project element ‘Decision­making at older ages’, topic no. 11)


2019 ◽  
Author(s):  
Alexander Michaelides ◽  
Yuxin Zhang
Keyword(s):  

2017 ◽  
Vol 72 (2) ◽  
pp. 705-750 ◽  
Author(s):  
ANDREAS FAGERENG ◽  
CHARLES GOTTLIEB ◽  
LUIGI GUISO

The uncertainty in life expectancy plays a critical role in individual financial planning. Its impact is magnified during the retirement years (the wealth distribution stage of the life cycle), as new sources of income typically are not available to retired persons. Utilizing a multi-stage stochastic program, the authors model and solve the optimal asset allocation problem of a retired couple with uncertain life expectancy in the presence of a term life insurance policy. In the base case, they find optimal policies assuming no longevity risk (i.e., lifetime scenarios are uncertain although life expectancy is fixed on the retirement date). Next, they introduce longevity risk in the scenario generation stage through either a shift in the expected lifetimes or an unexpected cut in periodic retirement income. The authors find that the optimal asset allocation policy depends on the presence and the type of these risks, as well as the relative price of insurance and the size of any cut in pension benefits.


Author(s):  
Hans Fehr ◽  
Fabian Kindermann

The optimal savings and investment decisions of households along the life cycle were a central issue in Chapter 5. There, savings decisions were made under various forms of risks.However, we restricted our analysis to three period models owing to the limitations of the numerical all-in-one solution we used. In this chapter we want to take a different approach. Applying the dynamic programming techniques learned so far allows us to separate decision-making at different stages of the life cycle into small sub-problems and therefore increase the number of periods we want to look at enormously. This enables us to take amuchmore detailed look at how life-cycle labour supply, savings, and portfolio choice decisions are made in the presence of earnings, investment, and longevity risk. Unlike in Chapter 9, the models we study here are partial equilibrium models. Hence, all prices as well as government policies are exogenous and do not react to changes in household behaviour. This chapter is split into two parts. The first part focuses on labour supply and savings decisions in the presence of labour-productivity and longevity risk. Insurance markets against these risks are missing, such that households will try to self-insure using the only savings vehicle available, a risk-free asset. This model is a quite standard workhorse model in macroeconomics and a straightforward general equilibrium extension exists, the overlapping generations model, which we study in Chapter 11. In the second part of the chapter, we slightly change our viewpoint and look upon the problem of life-cycle decision-making from a financial economics perspective. We therefore exclude laboursupply decisions, but focus on the optimal portfolio choice of households along the life cycle, when various forms of investment vehicles like bonds, stocks, annuities, and retirement accounts are available. This section is devoted to analysing consumption and savings behaviour when households face uncertainty about future earnings and the length of their life span. We study how households can use precautionary savings in a risk-free asset as a means to selfinsure against the risks they face. While in our baseline model we assume that agents always work full-time, we relax this assumption later on by considering a model with endogenous labour supply as well as a model with a labour-force participation decision of second earners within a family context.


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