A wavelet approach of investing behaviors and their effects on risk exposures

Exposure to market risk is a core objective of the Capital Asset Pricing Model (CAPM) with a focus on systematic risk. However, traditional OLS Beta model estimations (Ordinary Least Squares) are plagued with several statistical issues. Moreover, the CAPM considers only one source of risk and supposes that investors only engage in similar behaviors. In order to analyze short and long exposures to different sources of risk, we developed a Time–Frequency Multi-Betas Model with ARMA-EGARCH errors (Auto Regressive Moving Average Exponential AutoRegressive Conditional Heteroskedasticity). Our model considers gold, oil, and Fama–French factors as supplementary sources of risk and wavelets decompositions. We used 30 French stocks listed on the CAC40 (Cotations Assistées Continues 40) within a daily period from 2005 to 2015. The conjugation of the wavelet decompositions and the parameters estimates constitutes decision-making support for managers by multiplying the interpretive possibilities. In the short-run, (“Noise Trader” and “High-Frequency Trader”) only a few equities are insensitive to Oil and Gold fluctuations, and the estimated Market Betas parameters are scant different compared to the Model without wavelets. Oppositely, in the long-run, (fundamentalists investors), Oil and Gold affect all stocks but their impact varies according to the Beta (sensitivity to the market). We also observed significant differences between parameters estimated with and without wavelets.

Children’s toy or grown-ups’ gamble? LEGO sets as an alternative investment

Purpose The purpose of this paper is to study LEGO sets as a potential alternative asset class. An exhaustive sample of 10,588 sets is used to generate inferences regarding long-term LEGO performance, its diversification benefits and return determinants. Design/methodology/approach LEGO set performance is studied in terms of equal- and value-weighted portfolios, sorts based on set characteristics and cross-sectional regressions. Findings Over 1966–2018, LEGO value-weighted index accounted for survivorship bias enjoys 1.20% inflation-adjusted return per annum, well below 5.54% for equities. However, the defensive properties of LEGO are considerable, as including 5%–25% of LEGO in a diversified portfolio is beneficial for investors with varying levels of risk aversion. LEGO secondary market is relatively internationalised, with investors from larger economies, countries with higher per capita incomes and less income inequality are shown to trade LEGO more actively. Practical implications LEGO investors derive non-pecuniary utility that is separable from their risk-return profile. LEGO is not exposed to any of the Fama-French factors, however, set-specific size and value effects are also well-pronounced on the LEGO market, with smaller sets and sets with lower price-to-piece ratio exhibiting higher yields. Older sets are also enjoying higher returns, demonstrating a liquidity effect. Originality/value This is the first study to investigate the investment properties of LEGO as an alternative asset class from micro- and macro-financial perspectives that overcomes many survivorship bias limitations prevalent in earlier research. LEGO trading is shown to be an important source of valuable data to enable original robustness checks for prominent theoretical concepts from asset pricing and behavioural finance literature.

High-order moments in stock pricing: evidence from the Chinese and US markets

Purpose The purpose of this paper is to introduce an augmented high-order capital asset pricing model (AH-CAPM) as a new risk-based model to price stocks. Design/methodology/approach The AH-CAPM is defined as a linear model with high-order marginal moments and co-moments from the joint distributions of the sorted stock portfolio returns and the market return. Findings The performance of the AH-CAPM is tested in the Chinese and US stock markets. Empirical results show that the high-order marginal moments and co-moments from the joint distributions in AH-CAPM contain the risk and return information implied by the Fama–French factors, indicating it as a better risk measurement. Moreover, the AH-CAPM performs better than the Fama–French three-factor model and the Carhart four-factor model in both the Chinese and US stock markets. Originality/value Overall, this study introduces a new asset pricing model with better measurements to incorporate risk information in the stock market.

Testing Beta-Pricing Models Using Large Cross-Sections

We propose a methodology for estimating and testing beta-pricing models when a large number of assets is available for investment but the number of time-series observations is fixed. We first consider the case of correctly specified models with constant risk premia, and then extend our framework to deal with time-varying risk premia, potentially misspecified models, firm characteristics, and unbalanced panels. We show that our large cross-sectional framework poses a serious challenge to common empirical findings regarding the validity of beta-pricing models. In the context of pricing models with Fama-French factors, firm characteristics are found to explain a much larger proportion of variation in estimated expected returns than betas. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

Extending Fama–French Factors to Corporate Bond Markets

The explanatory power of size, value, profitability, and investment has been extensively studied for equity markets. Yet, the relevance of these factors in global credit markets is less explored, although equities and bonds should be related according to structural credit risk models. In this article, the authors investigate the impact of the four Fama–French factors in the US and European credit space. Although all factors exhibit economically and statistically significant excess returns in the US high-yield market, the authors find mixed evidence for US and European investment-grade markets. Nevertheless, they show that investable multifactor portfolios outperform the corresponding corporate bond benchmarks on a risk-adjusted basis. Finally, their results highlight the impact of company-level characteristics on the joint return dynamics of equities and corporate bonds.