Household Portfolio Research Articles

Household portfolio allocation, uncertainty, and risk

Analysing the Panel Study of Income Dynamics and the Health and Retirement Study, we investigate the extent to which US households reduce their financial risk exposure when confronted with background risk. Our novel modelling approach – termed a deflated ordered fractional model – quantifies how the overall composition of a household portfolio with three asset classes adjusts with background risk, and is unique in recovering for any given risky asset class the shares that are reallocated to each safer asset category. Background risk exerts a significant impact on household portfolios, inducing a ‘flight from risk’ from riskier to safer assets.

Assessing the relationship between health and household portfolio allocation

AbstractThis paper surveys the literature on the relationship between health and household portfolio allocation and provides updated empirical analysis based on recent data. Prior research finds robust evidence for cross‐sectional correlations between measures of health status and portfolio decisions, but establishing the causal pathways and underlying mechanisms has proven more difficult and complex. Analysis from the most recently available 2016 and 2018 waves of the Health and Retirement Study yields results that are consistent with existing literature. Households with worse self‐reported health have a lower probability of holding various types of financial assets and invest a higher share of their portfolios in safe assets, relative to other asset categories. However, there is only weak evidence that new health shocks to a household change portfolio holdings. The paper concludes with a discussion of the implications of this research and directions for future work.

Incentive-Based Demand Response Framework for Residential Applications: Design and Real-Life Demonstration

In 2020, residential sector loads reached 25% of the overall electrical consumption in Europe and it is foreseen to stabilise at 29% by 2050. However, this relatively small increase demands, among others, changes in the energy consuming behaviour of households. To achieve this, Demand Response (DR) has been identified as a promising tool for unlocking the hidden flexibility potential of residential consumption. In this work, a holistic incentive-based DR framework aiming towards load shifting is proposed for residential applications. The proposed framework is characterised by several innovative features, mainly the formulation of the optimisation problem, which models user satisfaction and the economic operation of a distributed household portfolio, the customised load forecasting algorithm, which employs an adjusted Gradient Boosting Tree methodology with enhanced feature extraction and, finally, a disaggregation tool, which considers electrical features and time of use information. The DR framework is first validated through simulation to assess the business potential and is then deployed experimentally in real houses in Northern Greece. Results demonstrate that a mean 1.48% relative profit can be achieved via only load shifting of a maximum of three residential appliances, while the experimental application proves the effectiveness of the proposed algorithms in successfully managing the load curves of real houses with several residents. Correlations between market prices and the success of incentive-based load shifting DR programs show how wholesale pricing should be adjusted to ensure the viability of such DR schemes.

Which economic uncertainty measure matters for households' portfolio decision?

AbstractIn this study, we address two research questions: Do recently developed economic uncertainty measures matter for household portfolio choices? If so, which measure is most important? Using household data, we compare 16 uncertainty measures in our unified framework. We find that the economic policy uncertainty (EPU) measure is the most important for household portfolios. We further find that married, more educated, older, and wealthier households are more sensitive to EPU. Finally, our findings highlight the importance of labor income in the sensitivity of households' portfolio decisions to uncertainty.

Household Wealth: Low-Yielding and Poorly Structured?

In this paper, we present a newly generated data set on real returns of households’ aggregated asset holdings, which adds additional and more sophisticated information to existing relevant datasets in the literature. To do this, we draw on various datasets from public and private sources and then transform and combine them in a consistent manner that allows for international comparative and intertemporal analyses. Based on this, we address two current debates on the development of household wealth in the euro area that have been triggered by the low-interest environment. The first debate refers to the development of real yields on household wealth from 2000 to 2018, whereas the second debate deals with the mean-variance efficiency of household portfolios. Contrary to widespread belief, we find that yields on total wealth, which were largely dominated by non-financial assets’ yields, were mostly positive, although they exhibit a declining trend. Moreover, on average, overall real yields were significantly lower after 2008. Referring to portfolio efficiency, we find that current portfolios seem to be comparatively close to mean-variance efficiency. If households were to optimize their portfolios despite limited room for improvement, holdings of equity and investment fund shares should be reduced, contradicting common recommendations of financial advisors.

Monetary Policy and Reaching for Income

ABSTRACTUsing data on individual portfolio holdings and on mutual fund flows, we find that low interest rates lead to significantly higher demand for income‐generating assets such as high‐dividend stocks and high‐yield bonds. We argue that this “reaching‐for‐income” phenomenon is driven by investors who follow the “living off income” rule‐of‐thumb. Our empirical analysis shows that this preference for current income affects both household portfolio choices and the prices of income‐generating assets. In addition, we explore the implications of reaching for income for capital allocation and the effectiveness of monetary policy.

How does entrepreneurship influence the efficiency of household portfolios?

This paper examines the impact of entrepreneurship on the efficiency of household financial portfolios by constructing Sharpe ratios and Sortino ratios of seven kinds of financial assets, based on data from the 2013, 2015 and 2017 China Household Finance Survey (CHFS), in conjunction with the returns of the financial asset index of China from 2010 to 2018. Employing CRE regressions, Heckman two-stage models and PSM methods, we find that undertaking entrepreneurship helps to increase the efficiency of household portfolios significantly. This study also verifies that entrepreneurial households improve their portfolio efficiency through financial information by testing the moderating effects of social network, business experience and financial literacy. In addition, this study shows that entrepreneurial households generally adopt a less diversified strategy in asset allocation than do non-entrepreneurial households.

Political Background and Household Financial Asset Allocation in China

ABSTRACT Political background is an important factor in determining the household economic behavior. Using 2014–2018 households panel data from the China Family Panel Studies (CFPS), we investigate the effects of political background on China’s household asset allocation behavior. We find that political background has a significant positive impact on the financial market participation. Mediation analysis indicates that political background leads to higher household wealth, better social capital, and fewer credit constraints, thus promotes households investments. Further analysis shows that the marginal impact of political background on household investment behavior is more significant in Eastern and urban areas. Our results contribute to the existing literature on the relationship between the political background and the household investment behavior, also enhancing the understanding of the household portfolio heterogeneity.

Influence Path Analysis of Rural Household Portfolio Selection: A Empirical Study Using Structural Equation Modelling Method

The frequency of incomplete portfolios consisting of a few risk-free assets is an important issue in household portfolio selection, and its cause has not yet been satisfactorily identified. Using data from the Shaanxi Province survey of rural residents’ financial assets in China, this paper validates the influence path model of household portfolios to understand the determinants of rural household’s ownership of risky financial assets. The structural equation modelling method is used to illustrate the complex relationship between household portfolio allocation and influencing factors. The results show that holding risky financial assets is directly determined by total financial assets, risky investment intentions and financial market knowledge. Ability, desire and awareness are all indispensable for holding risky financial assets, which can explain most of the incomplete participant problem. Household wealth, financial literacy, age and education have indirect influences along different paths through these three mediation variables. In addition, a second house is separated from real estate that only includes the residential house and defined investments. A path analysis also shows that real estate (residential house, home appliances and vehicles) does not have a significant effect on holding risky financial assets, while an investment house will crowd out and substitute financial assets and have a negative influence on holding risky financial assets. The findings could help explain the fairly simple and safe structure of the typical household portfolio in rural China and other undeveloped regions and may also have important policy implications for developing risky financial markets in similar regions.

The Heterogeneous Relationship of Owner-Occupied and Investment Property with Household Portfolio Choice

The special, dual nature of property as both a consumption and an investment goodmakes it salient for portfolio choice. In fact, the theoretical literature predicts a con-straint imposed by property on investment and the empirical literature has broughtevidence that this constraint, in some form, exists, but neglecting to investigate its het-erogeneity and to differentiate between owner-occupied and investment property. Withreference to the predictions of a stochastic control model, we turn to the Wealth and As-sets Survey panel for the UK, which allows to break down in detail households’ port-folios, to show empirically how the relationship between property and stockholdingsdepends on the value of property relative to the size of the entire portfolio. While onaverage, an increase in the share of property in the total portfolio is estimated to cor-respond to a slight decrease or to no change in the share of stocks in liquid assets, thisnexus potentially goes from positive to negative depending on the weight of propertyin the portfolio. Consistent with the prediction that only consumption-relevant prop-erty places a constraint on portfolio choice, the relationship can be identified robustlyfor owner-occupied property only.

Household Portfolios, Monetary Policy and Asset Prices

Household Portfolios, Monetary Policy and Asset Prices

FinTech, Financial Inclusion, and Household Portfolio Choice: Evidence from China Household Finance Survey

Based on the China Household Finance Survey in 2017, using different measurements of FinTech, this paper finds that FinTech can promote the ratio of household risky asset holdings significantly. However, this positive effect is not financially inclusive, since it is more obvious among urban households, high-income households and households headed by younger. In terms of mechanism analysis, this paper finds that FinTech increases the ratio of household risky asset holdings through three ways: improving financial literacy, lowering the investment threshold, and promoting social interaction. Further, this paper finds that the reason why FinTech is not financial inclusive is that rural households, low-income households, and households headed by older are not good at using FinTech to improve financial literacy and lower their investment threshold. Our conclusion is still robust after using the average residential electricity consumption as the instrumental variable. This paper enriches the research on household portfolio choice and provides policy suggestions for the future promotion of financial inclusion with FinTech.

Understanding Japanese Household Portfolios

Why do Japanese households hold so few stocks? We use a quantitative life-cycle portfolio choice model to argue in favour of two main explanations. First, households have a very low level of trust in the stock market due to Japan's history of poor corporate governance. Second, stock returns to individual stockholders have been low. Before 1990, this was due to excessive fees and commissions. Since the 1990 financial crisis, the Japanese market itself has delivered low and volatile returns. Counterfactual analysis suggests that, if sustained, recent improvements in corporate governance and economic performance should lead to higher stock market participation.

How Do Climate Factors Affect Household Portfolio Choices? Empirical Evidence from China's Household Survey

How Do Climate Factors Affect Household Portfolio Choices? Empirical Evidence from China's Household Survey

A bivariate finite mixture growth model with selection

A model is proposed to analyze longitudinal data where two response variables are available, one of which is a binary indicator of selection and the other is continuous and observed only if the first is equal to 1. The model also accounts for individual covariates and may be considered as a bivariate finite mixture growth model as it is based on three submodels: (i) a probit model for the selection variable; (ii) a linear model for the continuous variable; and (iii) a multinomial logit model for the class membership. To suitably address endogeneity, the first two components rely on correlated errors as in a standard selection model. The proposed approach is applied to the analysis of the dynamics of household portfolio choices based on an unbalanced panel dataset of Italian households over the 1998–2014 period. For this dataset, we identify three latent classes of households with specific investment behaviors and we assess the effect of individual characteristics on households’ portfolio choices. Our empirical findings also confirm the need to jointly model risky asset market participation and the conditional portfolio share to properly analyze investment behaviors over the life-cycle.

Household Portfolio Underdiversification and Probability Weighting: Evidence from the Field

AbstractWe test whether probability weighting affects household portfolio choice in a representative survey. On average, people display inverse-S-shaped probability weighting, overweighting low probability events. As theory predicts, probability weighting is positively associated with portfolio underdiversification and significant Sharpe ratio losses. Analyzing respondents’ individual stock holdings, we find higher probability weighting is associated with owning lottery-type stocks and positively skewed equity portfolios. People with higher probability weighting are less likely to own mutual funds and more likely to either avoid equities or hold individual stocks. We are the first to empirically link individuals’ elicited probability weighting and real-world decisions under risk.

Entrepreneurship and household portfolio choice: Evidence from the China Household Finance Survey

The efficient allocation of household assets is important for household wealth and entrepreneurial activities. However, there is scarce evidence on how entrepreneurial activities influence household financial decisions. We use a simple model to characterize the impact of entrepreneurship on household portfolio choice and the two underlying channels—the diversification effect and the risk substitution effect. We also empirically examine the impact of entrepreneurship using data from the 2013, 2015, and 2017 waves of the China Household Finance Survey (CHFS). The empirical results show that entrepreneurship significantly decreases both household risky market participation and risky asset holding. These findings are robust to alternative measurements of key variables, different model specifications, and Lewbel’s two-stage estimators. This study also verifies the co-existence of both the diversification and risk substitution effects. In particular, the net effect of entrepreneurship on household portfolio choice varies between urban and rural areas due to the different offsetting results between the two effects.

Automated portfolio rebalancing: Automatic erosion of investment performance?

Robo-advisers enable investors to establish an automated rebalancing strategy for a portfolio usually consisting of stocks and bonds. Since households’ portfolios additionally include further frequently tradable assets like real estate funds, articles of great value and cash(-equivalents), we analyze whether households would benefit from a service that automatically rebalances a portfolio which additionally includes the latter assets. In contrast to previous studies, this paper relies on real-world household portfolios, which are derived from the German central bank’s (Deutsche Bundesbank) Panel on Household Finances (PHF)-Survey. We compute the portfolio performance increase/decrease that households would have achieved by employing rebalancing strategies instead of a buy-and-hold strategy in the period from September 2010 to July 2015 and analyze whether subsamples of households with certain sociodemographic and socioeconomic characteristics would have benefited more from portfolio rebalancing than other household subsamples. The empirical analysis shows that the analyzed German households would not have benefited from an automated rebalancing service and that no subgroup of households would have significantly outperformed another subgroup in the presence of rebalancing strategies.

Reconsideration of the IS–LM model and limitations of monetary policy: a Tobin–Minsky model

The standard IS–LM model considers all types of financial assets, excluding money, as bonds. We construct a modified IS–LM model to better represent the characteristics of financial markets and investigate the stability of the economy. We present bank behavior explicitly and consider household portfolio preferences through the rate of return on financial assets. We build both static and dynamic models that incorporate the dynamic equation of monetary policy. In our model, an increase in the debt–capital ratio may have a negative impact on the profit rate and bring about the so-called “paradox of debt.” We indicate that factors such as the sensitivity of bank lending to the profit rate and the degree of substitutability between the household’s equity and money have a significant effect on the volatility of the profit rate and equity price. Particularly, the latter may lead to an unstable economy in the long run. We show that it is always possible for the economy to become unstable endogenously. The government and central bank must formulate loan regulations and adopt the appropriate monetary policy to stabilize the economy.

Investor Sophistication and Portfolio Dynamics

We develop a simple dynamic general-equilibrium framework that can jointly rationalize many empirically observed features of household portfolios, investment returns, and wealth dynamics. The model differs from traditional models only along a single, natural dimension: households differ in their confidence about the return processes for risky assets. Less-confident households (but with unbiased beliefs) overinvest in safe assets, hold underdiversified portfolios concentrated in familiar assets, are trend chasers, and earn lower absolute and risk-adjusted investment returns. More confident households hold riskier positions and exhibit superior market-timing abilities. Despite Bayesian learning, this investment behavior persists for long periods, thereby exacerbating wealth inequality.