Recent literature has identified consumers’ fairness and image concerns as the primary drivers of payments under pay-what-you-want (PWYW) pricing. Consequently, managers have employed a variety of ...design variations to invoke/alleviate these concerns to attract more customers and increase payment magnitudes. We develop a theoretical approach that combines both prosocial and self-interested motives to examine consumers’ four possible responses to design variations in PWYW exchange: (1) opt-out, (2) free-ride, (3) default to recommendation, or (4) other payment. We confirm model predictions using an empirical approach that jointly estimates the multipartite customer response. We report findings pertaining to four managerially controllable variables namely, ‘payment visibility’, ‘information on payment recipients’, ‘timing of payment’, and ‘explicit price recommendations’ using both secondary data and controlled experiments. We show that design variations have a heterogeneous effect on different types of consumer responses leading to countervailing effects on revenues. We derive several actionable managerial recommendations.
Intertwined with the persisting effects of the COVID-19 pandemic on the world economy, the price of WTI crude oil futures became negative on April 20, 2020. This anomalous incident has drawn much ...attention within the literature. This paper attempts to investigate the origins and specific impacts of the negative pricing event on the price discovery of WTI futures by employing a bivariate VECM-DCC-GARCH-SNP model, incorporating Legendre polynomials, where the dynamics of major information share measures at high-frequency time intervals are uncovered. Time-varying patterns of information share are identified across the period surrounding negative WTI prices. In particular, price discovery effects steadily abate after a sharp shock during the eight weeks before the negative pricing event. Peak price discovery differentials then re-occur within the negative-pricing event, before once again abating. Such results verify CFTC concerns surrounding the peculiarity of WTI futures trading conditions, that is, the conditions for the negative pricing event were well-established in the weeks before April 2020. Our results shed light on stylised evidence relating to the information efficiency of the international crude oil market more generally.
•Analyses the origins and specific impacts of the negative pricing of WTI futures•Time varying patterns of information share are identified during negative WTI pricing•The conditions for the shock were well-established eight weeks before it occurred•Results shed light on the informational efficiency of international crude oil markets
•We use the GARCH-MIDAS framework to identify drivers of Cryptocurrency volatility.•In contrast to former studies, we use an out-of-sample setting only.•We find the Global Real Economic Activity to ...be the best explanatory variable for long-term Cryptocurrency volatility.•Especially during bear markets, explanatory variables offer better predictions than the simple GARCH.•Averaging explanatory variables shows promising results.
We apply the GARCH-MIDAS framework to forecast the daily, weekly, and monthly volatility of five highly capitalized Cryptocurrencies (Bitcoin, Etherium, Litecoin, Ripple, and Stellar) as well as the Cryptocurrency index CRIX. Based on the prediction quality, we determine the most important exogenous drivers of volatility in Cryptocurrency markets. We find that the Global Real Economic Activity outperforms all other economic and financial drivers under investigation. We also show that the Global Real Economic Activity provides superior volatility predictions for both, bull and bear markets. In addition, the average forecast combination results in low loss functions. This indicates that the information content of exogenous factors is time-varying and the model averaging approach diversifies the impact of single drivers.
Technological advances are preparing consumers to plan their purchases strategically. Selling to strategic consumers at a fixed price forgoes the profit from salvaging inventory, whereas high-low ...pricing, as a ubiquitous pricing strategy, is costly due to the offered markdown discount. This research explores the overall impact of consumer's strategic buying behaviour on a pricing strategy, and identifies conditions where fixed pricing, strategic high pricing, or high-low pricing is the best approach by analytically comparing the profits of the three pricing strategies. Our results show that high-low pricing is appropriate only if the offered markdown discount is relatively small. If strategic consumers have a small population and the needed markdown discount is relatively large, retailers can ignore strategic buying behaviour and sell products at a fixed price. Our results emphasize that the markdown discount for clearance sales and the market structure of heterogeneous consumers play vital roles in determining the optimal pricing strategy.
I develop a new spectrum of moment bounds on the pricing kernel. They stem from the solution of an optimization problem that is complementary to Hansen and Jagannathan (1991) approach. Economically, ...they measure the discrepancy between what an optimizing agent could achieve if all assets (that are priced by the pricing kernel) were tradable and what she can actually achieve in the real-world market. Through the lens of these bounds, I examine leading macro-finance models using index option returns. I show, in a model-free fashion, the difficulty of several classes of models in meeting option-implied bounds. I highlight the unique information that my bounds provide compared with existing approaches.
We propose a novel generalized recursive smooth ambiguity model which permits a three-way separation among risk aversion, ambiguity aversion, and intertemporal substitution. We apply this utility ...model to a consumption-based asset-pricing model in which consumption and dividends follow hidden Markov regime-switching processes. Our calibrated model can match the mean equity premium, the mean risk-free rate, and the volatility of the equity premium observed in the data. In addition, our model can generate a variety of dynamic asset-pricing phenomena, including the procyclical variation of price-dividend ratios, the countercyclical variation of equity premia and equity volatility, the leverage effect, and the mean reversion of excess returns. The key intuition is that an ambiguity-averse agent behaves pessimistically by attaching more weight to the pricing kernel in bad times when his continuation values are low.
We examine the risk transmission from the COVID-19 to metal (precious and industrial) and energy markets using the BEKK-MGARCH model. The findings reveal the significant and negative volatility ...transmission from the COVID-19 to gold, palladium, and brent oil markets, suggesting the safe-haven properties of these markets. The COVID-19 risk is not transmitted to the industrial metal market, whereas the rise in COVID-19 volatility leads to an increase in WTI oil market volatility. These results provide useful insights to investors and policymakers regarding risk management, asset pricing, and financial market stability during the COVID-19 pandemic.
•Investigating the risk transmission from the COVID-19 to metals and energy markets.•Negative volatility transmission from the COVID-19 to gold, palladium, and brent oil markets.•The COVID-19 risk is not transmitted to the industrial metal market.•Rise in COVID-19 volatility leads to an increase in WTI oil market volatility.
We develop a structural model of the global market for crude oil that for the first time explicitly allows for shocks to the speculative demand for oil as well as shocks to flow demand and flow ...supply. The speculative component of the real price of oil is identified with the help of data on oil inventories. Our estimates rule out explanations of the 2003–2008 oil price surge based on unexpectedly diminishing oil supplies and based on speculative trading. Instead, this surge was caused by unexpected increases in world oil consumption driven by the global business cycle. There is evidence, however, that speculative demand shifts played an important role during earlier oil price shock episodes including 1979, 1986 and 1990. Our analysis implies that additional regulation of oil markets would not have prevented the 2003–2008 oil price surge. We also show that, even after accounting for the role of inventories in smoothing oil consumption, our estimate of the short-run price elasticity of oil demand is much higher than traditional estimates from dynamic models that do not account for for the endogeneity of the price of oil.
This book shows how current and recent market prices convey information about the probability distributions that govern future prices. Moving beyond purely theoretical models, Stephen Taylor applies ...methods supported by empirical research of equity and foreign exchange markets to show how daily and more frequent asset prices, and the prices of option contracts, can be used to construct and assess predictions about future prices, their volatility, and their probability distributions.
This paper identifies three common risk factors in the returns on cryptocurrencies, which are related to cryptocurrency market return, market capitalization (size) and momentum of cryptocurrencies. ...Investigating a collection of 78 cryptocurrencies, we find that there are anomalous returns that decrease with size and increase with return momentum, and the momentum effect is more significant in small cryptocurrencies. Moreover, Fama-Macbeth regressions show the size and momentum combine to capture the cross-sectional variation in average cryptocurrency returns. In the tests of the three-factor model, we find most cryptocurrencies and their portfolios have significant exposures to the proposed three factors with insignificant intercepts, demonstrating that the three factors explain average cryptocurrency returns very well.
•We construct three common risk factors which are specific to cryptocurrency market.•Size and momentum are strong in sorts, and small cryptocurrencies have more significant momentum effect.•The combined effect of size and momentum can largely explain the cross-sectional variation in cryptocurrency returns.•Most cryptocurrencies and their portfolios have significant exposures to the three factors with insignificant intercepts.
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