The objective of this paper is to emphasize the differences between a call and a warrant as well as the different valuation methods of warrants which have been introduced in the financial literature. For the sake of simplicity and applicability, we only consider a debt-free equity-financed firm. More recently a formal distinction between structural and reduced form pricing models has been introduced. This distinction is important whether one wishes to price a new warrant issue or outstanding warrants. If we are interested in pricing a new issue of warrants, e.g. in the context of a management incentive package, one has to rely on a structural model. However most of practitioners use the simple Black-Scholes formula. In this context, we analyze the accuracy of the approximation of the “true” price of a warrant by the Black-Scholes formula. We show that in the current low interest rate environment, the quality of the approximation deteriorates and the sensitivity of this approximation to the volatility estimate increases.
Although the Covid-19 crisis has shown how high-frequency data can help track the economy in real time, we investigate whether it can improve the nowcasting accuracy of world GDP growth. To this end, we build a large dataset of 718 monthly and 255 weekly series. Our approach builds on a Factor-Augmented MIxed DAta Sampling (FA-MIDAS), which we extend with a preselection of variables. We find that this preselection markedly enhances performances. This approach also outperforms a LASSO-MIDAS—another technique for dimension reduction in a mixed-frequency setting. Though we find that a FA-MIDAS with weekly data outperform other models relying on monthly or quarterly data, we also point to asymmetries. Models with weekly data have indeed performances similar to other models during “normal” times but can strongly outperform them during “crisis” episodes, above all the Covid-19 period. Finally, we build a nowcasting model for world GDP annual growth incorporating weekly data that give timely (one per week) and accurate forecasts (close to IMF and OECD projections but with 1- to 3-month lead). Policy-wise, this can provide an alternative benchmark for world GDP growth during crisis episodes when sudden swings in the economy make usual benchmark projections (IMF's or OECD's) quickly outdated.
We test the effectiveness of a social comparison nudge to enhance lockdown compliance during the Covid-19 pandemic, using a French representative sample (N=1154). Respondents were randomly assigned to a favourable/unfavourable informational feedback (daily road traffic mobility patterns, in Normandy - a region of France) on peer lockdown compliance. Our dependent variable was the intention to comply with a possible future lockdown. We controlled for risk, time, and social preferences and tested the effectiveness of the nudge. We found no evidence of the effectiveness of the social comparison nudge among the whole French population, but the nudge was effective when its recipient and the reference population shared the same geographical location (Normandy). Exploratory results on this subsample (N=52) suggest that this effectiveness could be driven by noncooperative individuals.
Canada exhibits no correlation between income and victimization, rich neighborhoods are less exposed to property crime, rich households are more victimized than their neighbors, and rich households and neighborhoods invest more in protection. We provide a theory consistent with these facts. Criminals within city choose a neighborhood and pay a search cost to compare potential victims, whereas households invest in self-protection. As criminals' return to search increases with neighborhood income, households in rich neighborhoods are likelier to enter a race to greater protection driving criminals toward poorer areas. A calibration reproduces the Canadian victimization and protection pattern by household/neighborhood income.
Revealed and stated preference techniques are widely used to assess willingness to pay (WTP) for non-market goods as input to public and private decision-making. However, individuals first have to satisfy subsistence needs through market good consumption, which affects their ability to pay. We provide a methodological framework and derive a simple ex post adjustment factor to account for this effect. We quantify its impacts on the WTP for non-market goods and the ranking of projects theoretically, numerically and empirically. This confirms that non-adjusted WTP tends to be plutocratic: the views of the richest – whatever they are – are more likely to impact decision-making, potentially leading to ranking reversal between projects. We also suggest that the subsistence needs-based adjustment factor we propose has a role to play in value transfer procedures. The overall goal is a better representation of the entire population’s preferences with regard to non-market goods.
This paper investigates how affective forecasting errors (A.F.E.s), the difference between anticipated emotion and the emotion actually experienced, may induce changes in preferences on time, risk and occupation after combat. Building on psychological theories incorporating the role of emotion in decision-making, we designed a before-and-after-mission survey for Danish soldiers deployed to Afghanistan in 2011. Our hypothesis of an effect from A.F.E.s is tested by controlling for other mechanisms that may also change preferences: immediate emotion, trauma effect – proxied by post-traumatic stress disorder (P.T.S.D.) – and changes in wealth and risk perception. At the aggregate level, results show stable preferences before and after mission. We find positive A.F.E.s for all three emotions studied (fear, anxiety and excitement), with anticipated emotions stronger than those actually experienced. We provide evidence that positive A.F.E.s regarding fear significantly increase risk tolerance and impatience, while positive A.F.E.s regarding excitement strengthen the will to stay in the military. Trauma has no impact on these preferences.
This paper examines the distributional implications of inflation on top income shares in 14 advanced economies using data over the period 1920–2016. We use local projections to analyze how top income shares respond to an inflation shock, and panel regressions in which all variables are defined as 5-year averages to examine the impact of inflation on the position of the top-one-percent in the long run. Our findings suggest that inflation reduces the share of national income held by the top 1 percent. Furthermore, we find that inflation shocks and long-run inflation have similar effects on top income shares.
Under income-differentiated mortality, poverty measures suffer from a selection bias: they do not count the missing poor (i.e., persons who would have been counted as poor provided they did not die prematurely). The Pre-Industrial period being characterized by an evolutionary advantage (i.e., a higher number of surviving children per household) of the non-poor over the poor, one may expect that the missing poor bias is substantial during that period. This paper quantifies the missing poor bias in Pre-Industrial societies, by computing the hypothetical headcount poverty rates that would have prevailed provided the non-poor did not benefit from an evolutionary advantage over the poor. Using data on Pre-Industrial England and France, we show that the sign and size of the missing poor bias are sensitive to the degree of downward social mobility.
We investigate whether and how an individual giving decision is affected in risky environments in which the recipient’s wealth is random. We demonstrate that, under risk neutrality, the donation of dictators with a purely ex post view of fairness should, in general, be affected by the riskiness of the recipient’s payoff, while dictators with a purely ex ante view should not be. Furthermore, we observe that some influential inequality aversion preferences functions yield opposite predictions when we consider ex post view of fairness. Hence, we report on dictator games laboratory experiments in which the recipient’s wealth is exposed to an actuarially neutral and additive background risk. Our experimental data show no statistically significant impact of the recipient’s risk exposure on dictators’ giving decisions. This result appears robust to both the experimental design (within subjects or between subjects) and the origin of the recipient’s risk exposure (chosen by the recipient or imposed on the recipient). Although we cannot sharply validate or invalidate alternative fairness theories, the whole pattern of our experimental data can be simply explained by assuming ex ante view of fairness and risk neutrality.
Evolutionary finance focuses on questions of “survival and extinction” of investment strategies (portfolio rules) in the market selection process. It analyzes stochastic dynamics of financial markets in which asset prices are determined endogenously by a short-run equilibrium between supply and demand. Equilibrium is formed in each time period in the course of interaction of portfolio rules of competing market participants. A comprehensive theory of evolutionary dynamics of this kind has been developed for models in which short selling is not allowed and asset supply is exogenous. The present paper extends the theory to a class of models with short selling and endogenous asset supply.