Stock Price Level Effect

Companies actively manipulate stock price ranges through IPOs, stock splits, and repurchases. Indeed, empirical results suggest that the stock's price range, whether at a high or low price level, affects market performance. Unfortunately, archival data does not allow us to test the effect of stock price levels on investor behavior due to uncontrolled confound effects. We thus conduct a controlled online experiment with 900 US retail investors to test whether a difference in stock price levels affects the investor's risk perception, the price forecast, and the investment. Even though we �nd no differences in risk perception and forecasts, our results show signi�cantly higher investments in high-priced stocks in comparison to low-priced stocks. This effect disappears when we allow fractional share purchases or restrict naive trading strategies

History Matters: How Short-Term Price Charts Hurt Investment Performance

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

A multidisciplinary perspective on COVID-19 exit strategies

Lockdowns and associated measures imposed in response to the COVID-19 crisis inflict severe damage to society. Across the globe, scientists and policymakers study ways to lift measures while maintaining control of virus spread in circumstances that continuously change due to the evolution of new variants and increasing vaccination coverage. In this process, it has become clear that finding and analysing exit strategies, which are a key aspect of pandemic mitigation in all consecutive waves of infection, is not solely a matter of epidemiological modeling but has many different dimensions that need to be balanced and therefore requires input from many different disciplines. Here, we document an attempt to investigate exit strategies from a multidisciplinary perspective through the Science versus Corona project in the Netherlands. In this project, scientists and laypeople were challenged to submit (components of) exit strategies. A selection of these were implemented in a formal model, and we have evaluated the scenarios from a multidisciplinary perspective, utilizing expertise in epidemiology, economics, psychology, law, mathematics, and history. We argue for the integration of multidisciplinary perspectives on COVID-19 and more generally in pandemic mitigation, highlight open challenges, and present an agenda for further research into exit strategies and their assessmen

What makes an investment risky? An analysis of price path characteristics

We examine the influence of financial asset historical price path characteristics on investors’ risk perception, return beliefs and investment propensity. To that end, we run a series of survey experiments in which we present various price patterns to individuals with vested interest in financial matters. Our findings reveal that price paths with identical daily and monthly returns (and consequently identical return standard deviation) can lead to substantially different risk perception by investors, indicating that historical volatility is insufficient to explain risk perception. Salient features such as highs, lows and crashes are the most influential drivers of perceived risk in price paths. Return forecasts are primarily driven by past overall returns and the most recent price developments. Perceived risk and return beliefs strongly predict investment propensity

Smart Distance Lab

The Smart Distance Lab is an initiative and methodological framework to test the effectiveness of behavioural interventions on social distancing. We conducted a first experiment at an art fair (28-30 August 2020). We have made all collected data publicly available and written a paper on the results of different behavioural interventions

The lighting of the BECONs: A behavioral data science approach to tracking interventions in COVID-19 research

The imposition of lockdowns in response to the COVID-19 outbreak has underscored the importance of human behavior in mitigating virus transmission. Scientific study of interventions designed to change behavior (e.g., to promote social distancing) requires measures of effectiveness that are fast, that can be assessed through experiments, and that can be investigated without actual virus transmission. This paper presents a methodological approach designed to deliver such indicators. We show that behavioral data, obtainable through tracing apps currently in development, can be used to assess a central concept in epidemiology known as the contact network: a network representation that encodes which individuals have been in physical proximity long enough to transmit the virus. Because behavioral interventions alter the contact network, a comparison of contact networks before and after the intervention can provide information on the effectiveness of the intervention. We coin indicators based on this idea Behavioral Contact Network (BECON) indicators. We examine the performance of three indicators: the Density BECON (based on differences in network density), the Spectral BECON (based on differences in the eigenvector of the adjacency matrix), and the ASPL BECON (based on differences in average shortest path lengths). Using simulations, we show that all three indicators can effectively track the effect of behavioral interventions. Even in conditions with significant amounts of noise, BECON indicators can reliably identify and order effect sizes of interventions. The present paper invites further study of the method as well as practical implementations to test the validity of BECON indicators in real data

Smart Distance Lab: A new methodology for assessing social distancing interventions

In the wake of the COVID-19 pandemic, the central importance of human behaviour in mitigating the spread of the virus has become universally recognized. We present a methodology to systematically assess the effectiveness of behavioural interventions to stimulate social distancing. In addition, we demonstrate the feasibility of this framework in a large-scale natural experiment. In an experimental design, we varied behavioural interventions to evaluate the effect of face masks, walking directions, and immediate feedback on visitors’ contacts. We represent visitors as nodes, and their contacts as links in a contact network. Subsequently, we used network modelling to test for differences in these contact networks. We find no evidence that face masks influence social distancing, while unidirectional walking directions and buzzer feedback do positively impact social distancing. The presented methodology represents a practically feasible way to optimize social distancing interventions through scientific research and may directly inform policy

Acute and chronic tirasemtiv treatment improves in vivo and in vitro muscle performance in actin-based nemaline myopathy mice

International audienceNemaline myopathy, a disease of the actin-based thin filament, is one of the most frequent congenital myopathies. To date, no specific therapy is available to treat muscle weakness in nemaline myopathy. We tested the ability of tirasemtiv, a fast skeletal troponin activator that targets the thin filament, to augment muscle force—both in vivo and in vitro—in a nemaline myopathy mouse model with a mutation (H40Y) in Acta1. In Acta1H40Y mice, treatment with tirasemtiv increased the force response of muscles to submaximal stimulation frequencies. This resulted in a reduced energetic cost of force generation, which increases the force production during a fatigue protocol. The inotropic effects of tirasemtiv were present in locomotor muscles and, albeit to a lesser extent, in respiratory muscles, and they persisted during chronic treatment, an important finding as respiratory failure is the main cause of death in patients with congenital myopathy. Finally, translational studies on permeabilized muscle fibers isolated from a biopsy of a patient with the ACTA1H40Y mutation revealed that at physiological Ca2+ concentrations, tirasemtiv increased force generation to values that were close to those generated in muscle fibers of healthy subjects. These findings indicate the therapeutic potential of fast skeletal muscle troponin activators to improve muscle function in nemaline myopathy due to the ACTA1H40Y mutation, and future studies should assess their merit for other forms of nemaline myopathy and for other congenital myopathies

Smart Distance Lab's art fair, experimental data on social distancing during the COVID-19 pandemic

In the absence of a vaccine, social distancing behaviour is pivotal to mitigate COVID-19 virus spread. In this large-scale behavioural experiment, we gathered data during Smart Distance Lab: The Art Fair (n = 787) between August 28 and 30, 2020 in Amsterdam, the Netherlands. We varied walking directions (bidirectional, unidirectional, and no directions) and supplementary interventions (face mask and buzzer to alert visitors of 1.5 metres distance). We captured visitors' movements using cameras, registered their contacts (defined as within 1.5 metres) using wearable sensors, and assessed their attitudes toward COVID-19 as well as their experience during the event using questionnaires. We also registered environmental measures (e.g., humidity). In this paper, we describe this unprecedented, multi-modal experimental data set on social distancing, including psychological, behavioural, and environmental measures. The data set is available on Figshare and in a MySQL database. It can be used to gain insight into (attitudes toward) behavioural interventions promoting social distancing, to calibrate pedestrian models, and to inform new studies on behavioural interventions

Promoting physical distancing during COVID-19: a systematic approach to compare behavioral interventions.

In the wake of the COVID-19 pandemic, physical distancing behavior turned out to be key to mitigating the virus spread. Therefore, it is crucial that we understand how we can successfully alter our behavior and promote physical distancing. We present a framework to systematically assess the effectiveness of behavioral interventions to stimulate physical distancing. In addition, we demonstrate the feasibility of this framework in a large-scale natural experiment (N = 639) conducted during an art fair. In an experimental design, we varied interventions to evaluate the effect of face masks, walking directions, and immediate feedback on visitors’ contacts. We represent visitors as nodes, and their contacts as links in a contact network. Subsequently, we used network modelling to test for differences in these contact networks. We find no evidence that face masks influence physical distancing, while unidirectional walking directions and buzzer feedback do positively impact physical distancing. This study offers a feasible way to optimize physical distancing interventions through scientific research. As such, the presented framework provides society with the means to directly evaluate interventions, so that policy can be based on evidence rather than conjecture