Exchange rate dynamics and US dollar-denominated sovereign bond prices in emerging markets

Using data on Brazil, Colombia, Mexico, the Philippines, Russia and Turkey, our empirical results show that the exchange rates of their currencies have adequate explanatory power in explaining their US dollar-denominated sovereign bonds, particularly in the post-global financial crisis period. We develop a two-factor pricing model with closed-form solutions for the sovereign bonds in which the correlated factors are foreign exchange rates and US risk-free interest rates that follow a double square-root process relevant in the low interest rate environment. The numerical results and associated error analysis show that the model credit spreads can broadly track the market credit spreads.     

Option pricing based on hybrid GARCH-type models with improved ensemble empirical mode decomposition

The exploration of option pricing is of great significance to risk management and investments. One important challenge to existing research is how to describe the underlying asset price process and fluctuation features accurately. Considering the benefits of ensemble empirical mode decomposition (EEMD) in depicting the fluctuation features of financial time series, we construct an option pricing model based on the new hybrid generalized autoregressive conditional heteroskedastic (hybrid GARCH)-type functions with improved EEMD by decomposing the original return series into the high frequency, low frequency and trend terms. Using the locally risk-neutral valuation relationship (LRNVR), we obtain an equivalent martingale measure and option prices with different maturities based on Monte Carlo simulations. The empirical results indicate that this novel model can substantially capture volatility features and it performs much better than the M-GARCH and Black–Scholes models. In particular, the decomposition is consistently helpful in reducing option pricing errors, thereby proving the innovativeness and effectiveness of the hybrid GARCH option pricing model.     

Hedonic pricing and the spatial structure of housing data – an application to Berlin

Housing prices are largely determined by physical location. By applying the outsample prediction accuracy of rental prices as evaluation criteria, we examine whether the choice of the hedonic model additionally depends on the spatial structure of housing data, i.e. accounting for locational effects by either district fixed effects or spatial econometric modelling. Our results show that a generalised spatio-temporal model outperforms a district fixed effects model only if the spatial density – the weighted mean distance to nearest neighbours – is relatively small. Moreover, we use the required density thresholds to deduce a pseudo indifference curve, thereby showing that the ratio of the weighted spatial distance-to-the mean district diameter increases with the mean sample size per district. This emphasises the role of data structure and district choices for model selection. Differences in data can thereby serve as an explanation for contradictory findings in literature, whether spatial econometric methods or simple district fixed effects are used.     

Past price ‘memory’ in the housing market: testing the performance of different spatio-temporal specifications

Recent methodological developments provide a way to incorporate the temporal dimension when accounting for spatial effects in hedonic pricing. Weight matrices should decompose the spatial effects into two distinct components: bidirectional contemporaneous spatial connections; and unidirectional spatio-temporal effects from past transactions. Our iterative estimation approach explicitly analyses the role of time in price determination. The results show that both spatio-temporal components should be included in model specification; past transaction information stops contributing to price determination after eight months; and limited temporal friction is exhibited within this period. These findings highlight the decidedly non-linear temporal patterns of such information effects.     

The fair value of a token: How do markets price cryptocurrencies?

With the rise of cryptocurrency tokens as a new asset class, the question of the fair evaluation of a cryptocurrency token has become a question of increasing importance. We estimate the pricing kernel with which users price factors affecting their token holdings. We investigate how traditional risk factors such as market risk are evaluated, as well as how blockchain specific risk factors are priced in. In order to do so, we introduce an asset pricing model and modify its properties to make it applicable to cryptocurrency markets. We group the risk factors into market related and Bitcoin- and Ethereum blockchain specific risk factors. We find that blockchain specific risk factors are priced in. There is evidence that risk factors have moved from Bitcoin to Ethereum specific risk factors with an increasing importance of market factors, providing evidence for a decoupling of on-chain and off-chain trading activity.     

Asset pricing and energy consumption risk

This paper proposes energy consumption in the US as a new measure for the consumption capital asset pricing model. We find that (i) industrial energy growth produces reasonable values for the relative risk aversion coefficient and the implied risk-free rate; (ii) compared to alternative consumption measures, industrial energy performs well in explaining the cross-sectional variation in stock returns with the lowest implied risk aversion and pricing errors; (iii) the industrial energy consumption risk model performs equally well as the Fama–French three-factor model in the cross-sectional asset pricing tests; and (iv) total energy consumption risk is priced in the presence of the Fama–French factor risks.     

The long-run reversal in the long run: Insights from two centuries of international equity returns

We perform the most comprehensive test of long-term reversal in national equity indices ever done. Having examined data from 71 countries for the years 1830 through 2019, we demonstrate a strong reversal pattern: the past long-term return negatively predicts future performance. The phenomenon is not subsumed by other established cross-sectional return patterns, including the value effect. The long-term reversal is robust to many considerations but highly unstable through time. Finally, our findings support the overreaction explanation of this anomaly.     

Profit shifting and tax-rate uncertainty

Using firm-level data for 1,084 parent firms in 24 countries and for 9,497 subsidiaries in 54 countries, we show that tax-motivated profit shifting is larger among subsidiaries in countries that have stable corporate tax rates over time. Our findings further suggest that firms move away from transfer pricing and toward intragroup debt shifting that has lower adjustment costs. Our results are robust to several identification methods and respecifications, and they highlight the important role of tax-rate uncertainty in the profit-shifting decision while pointing to an adjustment away from more costly transfer pricing and toward debt shifting.     

Time-varying pricing may increase total electricity consumption: Evidence from Costa Rica

We study the implementation of a time-varying pricing (TVP) program by a major electricity utility in Costa Rica. Because of particular features of the data, we use recently developed understanding of the two-way fixed effects differences-in-differences estimator along with event-study specifications to interpret our results. Similar to previous research, we find that the program reduces consumption during peak-hours. However, in contrast with previous research, we find that the program increases total consumption. With a stylized economic model, we show how these seemingly conflicted results may not be at odds. The key element of the model is that previous research used data from rich countries, in which the use of heating and cooling devices drives electricity consumption, but we use data from a tropical middle-income country, where very few households have heating or cooling devices. Since there is not much room for technological changes (which might reduce consumption at all times), behavioral changes to reduce consumption during peak hours are not enough to offset the increased consumption during off-peak hours (when electricity is cheaper). Our results serve as a cautionary piece of evidence for policy makers interested in reducing consumption during peak hours—the goal can potentially be achieved with TVP, but the cost is increased total consumption