Knowledge that Transforms

We investigate the effect of agency conflicts between shareholders and debtholders on aggressive tax avoidance using a unique setting of dual holders who simultaneously hold equity and debt of the same firms. We find robust evidence that firms with dual holders exhibit more aggressive tax behavior even after controlling for endogeneity, suggesting that shareholder-debtholder conflicts induce firms to underinvest in tax aggressiveness. In addition, there exists a concave relation between tax aggressiveness and dual owners’ debt exposure relative to their overall debt and equity exposures to the investee firms. Further tests show that the effect of dual ownership on tax aggressiveness is more pronounced among firms with higher risk-shifting tendencies and higher managerial risk-taking incentives. Finally, our bond borrowing cost test shows that dual holdings mitigate the increased cost of borrowing due to aggressive tax avoidance.

In this paper, we identify the most suitable low-frequency proxies for analyzing commodity market quality. We use an 11-year sample of millisecond time-stamped order book data and examine the correlation of high-frequency liquidity and price efficiency measures with their low-frequency proxies measured with daily or 5-min Time-and-Sales (TAS) data. We find that for liquidity, the volatility-over-volume measures are the best proxies for bid–ask spread and price impact. The correlation of price efficiency measures with their daily-frequency counterparts is low. Moderately correlated proxies can be achieved by using 5-min data.

When making investment decisions, people rely heavily on price charts displaying the past performance of an asset. Price charts can come with any time frame, which the provider might strategically choose. We analyze the impact of the time frame on retail investors’ behavior, particularly trading activity and risk-taking, in a controlled experiment with 1041 retail investors. We find that shorter time frames are associated with more trading activity, resulting in higher transaction fees and investor welfare losses. However, the time frame does not affect average risk-taking.

This paper shows that the stock return predictability of analysts’ earnings forecast dispersion is driven by the information content of dispersion about future firm profitability. Greater dispersion predicts lower future profitability, and the return predictability of dispersion disappears after controlling for future profitability. We propose disclosure manipulation as an explanation for the relation between dispersion and future profitability. Disclosure quality is inversely related to forecast dispersion. Moreover, the return predictability of dispersion decreases in disclosure quality. Our results are robust to the consideration of previously suggested explanations for the dispersion anomaly.

This study extends the theoretical model of dynamic investment, dividend payout, costly external financing, and liquidation for financially constrained firms by incorporating ambiguity. We demonstrate that ambiguity aversion induces a trade-off between the “bird-in-hand” effect and an amplified precautionary motive in determining firms’ cash management, which consequently affects firms’ investment, dividend payout, costly external financing, and liquidation decisions. Unlike the models considering risk only, we identify a non-monotonic relationship between the endogenous payout boundary and ambiguity aversion. Our model generates several new implications, including providing an explanation for the high cash holdings and speed-up of asset sales during the recent COVID-19 crisis.

Stochastic optimization models have been extensively applied to financial portfolios and have proven their effectiveness in asset and asset-liability management. Occasionally, however, they have been applied to dynamic portfolio problems including not only assets traded in secondary markets but also derivative contracts such as options or futures with their dedicated payoff functions. Such extension allows the construction of asymmetric payoffs for hedging or speculative purposes but also leads to several mathematical issues. Derivatives-based nonlinear portfolios in a discrete multistage stochastic programming (MSP) framework can be potentially very beneficial to shape dynamically a portfolio return distribution and attain superior performance. In this article we present a portfolio model with equity options, which extends significantly previous efforts in this area, and analyse the potential of such extension from a modeling and methodological viewpoints. We consider an asset universe and model portfolio set-up including equity, bonds, money market, a volatility-based exchange-traded-fund (ETF) and over-the-counter (OTC) option contracts on the equity. Relying on this market structure we formulate and analyse, to the best of our knowledge, for the first time, a comprehensive set of optimal option strategies in a discrete framework, including canonical protective puts, covered calls and straddles, as well as more advanced combined strategies based on equity options and the volatility index. The problem formulation relies on a data-driven scenario generation method for asset returns and option prices consistent with arbitrage-free conditions and incomplete market assumptions. The joint inclusion of option contracts and the VIX as asset class in a dynamic portfolio problem extends previous efforts in the domain of volatility-driven optimal policies. By introducing an optimal trade-off problem based on expected wealth and Conditional Value-at-Risk (CVaR), we formulate the problem as a stochastic linear program and present an extended set of numerical results across different market phases, to discuss the interplay among asset classes and options, relevant to financial engineers and fund managers. We find that options’ portfolios and trading in options strengthen an effective tail risk control, and help shaping portfolios returns’ distributions, consistently with an investor’s risk attitude. Furthermore the introduction of a volatility index in the asset universe, jointly with equity options, leads to superior risk-adjusted returns, both in- and out-of-sample, as shown in the final case-study.

We examine how institutional investors trade stocks with high research and development (R&D) expenses and investigate whether they can detect value-relevant R&D. We document significant differences between hedge funds and other institutional investors in their trading in high R&D stocks. We find that hedge funds (other institutional investors) invest more (less) in high R&D stocks compared to all other stocks. Moreover, hedge funds exhibit strong stock-picking ability in high R&D stocks, and hedge funds with larger allocations to high R&D stocks generate higher future fund returns. Our findings suggest that hedge funds have superior skill in identifying value-relevant R&D.

Do people behave consistently when it comes to sustainability? With few exceptions, most previous studies of sustainable investment behavior rely on survey responses. Numerous studies have noted, however, that peoples’ talk is often cheap when it comes to sustainable choices. We use a financially incentivized choice to study the non-investment-related sustainable behavior of the clients of three German robo advisors and relate it to their investment decisions. We find that sustainable consumption translates into a higher likelihood of choosing a portfolio following a sustainable investment strategy among the clients of a digital wealth manager that offers both conventional and sustainable investments. Sustainable consumption also translates into a particularly strong interest in the launch of sustainable investment strategies among the clients of a conventional robo advisor. The provision of sustainable investment strategies can, next to performance and costs, be a selling point for a digital wealth manager. However, our results show that self-reported sustainable consumer behavior that is not backed up by the pertinent actions is not significantly related to sustainable investment choices. Our results lend further support to the notion that studying sustainability in terms of actual choices is crucial. We provide guidance to practitioners in the financial industry on identifying investors with a potential interest in sustainable investments.

The relationship between corruption and acquisition performance is examined in this study, with a focus on stakeholder support. The findings indicate that total acquisition-related gains are reduced when firms with lower corruption pressures acquire targets with higher corruption pressures. Moreover, a negative relationship is highlighted between the corruption differential and the level of support provided by stakeholders. In addition, merger and acquisition deals with higher corruption differences receive lower average support from suppliers, customers, and employees. The evidence suggests that stakeholder commitment is a possible channel through which corruption affects corporate performance. Implementing anticorruption efforts and operating as a multinational corporation are two important factors that may reduce the impact of corruption on acquisition performance.