Knowledge that Transforms

This paper finds evidence that daylight saving time changes influence the decision-making of investors when trading in firms targeted for mergers. We find that investors who face imbalances in their circadian cycle generate more positive abnormal stock returns upon the announcement of target firms. This result holds within a large number of robustness tests. Target firms also experience more pronounced stock return volatility in response to their merger announcements the first trading day after clock changes. Overall, these results seem to indicate that investors may overreact to available information when experiencing imbalances in their circadian cycle.

This paper studies the co-movement of global yield curve dynamics using a Bayesian hierarchical factor model augmented with macroeconomic fundamentals. Our data-driven approach is able to pin down the drivers of yield curve dynamics and produce plausible term premium estimates. We reveal the relative importance of global shocks through two transmission channels: policy and risk channels. Global inflation is the most important core macro fundamental affecting international yields, operating through a policy channel. Two identified global yield factors significantly influence global yield co-movements through a risk channel.

We propose a non-structural method to retrieve the risk-neutral density (RND) implied by options on the CBOE Volatility Index (VIX). The methodology is based on orthogonal polynomial expansions around a kernel density and yields the RND of the underlying asset without the need for a parametric specification. The classic family of Laguerre expansions is extended to include the GIG and the generalized Weibull kernels. We show that orthogonal polynomial expansions yield accurate approximations of the RND of VIX and they generally outperform commonly used non-parametric methods when controlling for accuracy. Based on a panel of observed VIX options, we retrieve the variance swap term structure, the time series of VVIX, the VIX risk-neutral moments and the Volatility-at-Risk, which reveal a number of stylized facts on the RND of VIX.

We investigate the role of prudential supervisors’ independence in affecting income smoothing behavior in European banks. Powerful national supervisors are predicted to influence the accounting practices of their supervised entities, shaping the properties of the accounting numbers they prepare. In particular, we study whether greater independence of powerful supervisors from the government and from the industry is associated with lower income smoothing. We use the mandatory adoption of a single set of accounting standards in Europe as a shock to the influence of prudential supervisors over national banks’ accounting practice. Our results confirm that political and industry independence of the supervisor are important determinants of income smoothing. This suggests that independence of prudential supervisors is a desirable governance characteristic, with positive impacts on financial transparency.

We analyze revealed and stated household preferences for socially responsible investments (SRI). Using a questionnaire specifically designed for this purpose and administered to a Dutch representative household panel, we investigate the actual and latent demand for SRI products. Respondents reported whether they owned SRI products, the reason behind this decision, but also answered stated choice questions on traditional investments and hypothetical SR products with an explicit return penalty and/or an in-kind compensation. Our results show that social investors are willing to pay a price to be socially responsible rather than needing a little nudge, such as a gift (a book or a voucher). Highly educated individuals have a substantial latent demand that is currently unexploited. Keeping education constant, individuals who consider themselves financially literate are less interested in SR products than others. Particularly at the intensive margin, the stated demand for SRI funds is sensitive to the return penalty.

This paper studies the relationship between collective bargaining and mergers and acquisitions activity in 46 countries from the early 1990s. We find that the frequency and volume of mergers and acquisitions within industries increase in countries with powerful labor unions and high coverage of bargaining coordination. Economically, collective bargaining mitigates the negative effect of tighter employment protection legislations on mergers and acquisitions documented in prior works. Further analyses suggest that collective bargaining encourages mergers and acquisitions by reducing employment uncertainty among target firm employees. Our results provide new insights into the real effects of collective bargaining in the context of mergers and acquisitions around the world.

We propose a simple model of how investors evaluate a trading rule, and show that the market timing of technical trading rules induces lottery-like trading profits. Therefore, investors’ preference for positive skewness caters to the popularity of technical analysis. Since prospect theory implies strong skewness preference, it can explain why investors trade extensively on chart patterns that are meaningless in light of the efficient market hypothesis. Technicians often invoke behavioral finance as its theoretical foundation. Contrary to this view, we show that ideas from behavioral finance explain why technical analysis is popular despite the lack of theoretical foundation and empirical success.

We provide the first investigation of herding among closed-end fund investors, drawing on the US closed-end fund market for the 1992–2016 period. Results suggest closed-end fund investors herd significantly, with their herding being mainly driven by non-fundamentals. Closed-end fund herding rises in economic/market uncertainty, with its significance being mainly concentrated in the post-2007 period. Herding among closed-end funds is strongly motivated by discounts, is more pronounced than that among their net asset values and tends to grow inversely with fund-size. The fact that closed-end fund herding is noise-driven and linked to their discounts raises the possibility that it is related to the noise trader risk attributed to closed-end funds by investor sentiment theory.

We estimate the term structures of risk-neutral forward variance and skewness, and examine their predictive power for equity market excess returns and variance. We use Partial Least Squares to extract a single predictive factor from each term structure that is motivated by the theoretical implications of affine no-arbitrage models. The empirical analysis shows that an increased forward variance factor, FVF (forward skewness factor, FSF) corresponds to a more negatively sloped forward variance (more U-shaped forward skewness) term structure, and significantly forecasts higher future market excess returns and variance. More importantly, FSF exhibits predictive power for market returns that is stronger than, and incremental to, that provided by FVF. However, it does not outperform FVF in terms of excess variance predictability.

When constructing a portfolio of stocks, do you turn a blind eye to the firms’ future outlooks based on careful consideration of companies’ fundamentals, or do you ignore the stocks’ correlation structures which ensure the best diversification? The Fundamental Indexing (FI) and Markowitz mean-variance optimization (MVO) approaches are complementary but, until now, have been considered separately in the portfolio choice literature. Using data on S&P 500 constituents, we evaluate a novel portfolio construction technique that utilizes the benefits of both approaches. Relying on the idea of forecast averaging, we propose to blend the two previously mentioned techniques to provide investors with a clear binocular vision. The out-of-sample results of the blended portfolios attest to their superior performance when compared to common market benchmarks, and to portfolios constructed solely based on the FI or MVO methods. In pursuit of the optimal blend between the two distinct portfolio construction techniques, MVO and FI, we find that the ratio of market capitalization to GDP, being a leading indicator for an overpriced market, demonstrates remarkably advantageous properties. Our superior results cannot be explained by classic asset pricing models.