Election predictions as martingales: an arbitrage approach

The more volatile the prediction the closer to an even call     

Estimating emissions based on the integration of microscopic traffic simulation and vehicle dynamics model

This study proposes an integrated simulation approach, which consists of a microscopic traffic simulation model, a vehicle dynamics model, and an emission estimation model, in order to estimate emissions based on more reliable vehicle performance measures. The vehicle performance measures such as engine power and engine speed significantly relate to the amount of emissions, and road curvatures and inclinations are the core inputs affecting these vehicle performance measures. Therefore, providing reliable vehicle performance measures reflecting the road geometric attributes is critical for a reliable emission estimation. This study proposes to use the microscopic traffic simulation model for generating vehicle trajectories, which is advantageous in modeling various traffic situations, and the vehicle dynamics model for producing the vehicle performance measures based on the vehicle trajectories. Finally, the outputs from the vehicle dynamics model are fed into the emission estimation model to compute emission measures. This study conducted a case-study using two road sections, one is a hypothesized road section, including various curvatures and inclinations with regular variations, and the other is a Kesselberg road section, which is an actual geometry in Bayern, Germany. The emission measures are estimated in these case-study road sections using both an existing simulation approach and the proposed integrated simulation approach. The difference between these two emission estimation approaches is discussed in terms of the emission measures, including fuel consumption, nitrogen oxides, and particulate matters.     

Live streaming commerce from the sellers’ perspective: implications for online relationship marketing

ABSTRACT

Live streaming has recently become a popular direct selling channel which offers small, self-employed sellers unseen levels of consumer interaction and engagement. While the extant research focused on consumer motivation and intention to shop via live streaming, little is known from the seller’s perspective. Indeed, the potential advantages of live streaming commerce are accessible to everyone, but sellers experience different levels of success with this medium. Using a mixed quantitative and qualitative approach, this study analyses Facebook data of live streaming sellers to assess the nature and extent of engagement metrics, and delineate the dynamic, interactive live streaming sales process. We identify four sales approaches and twelve strategies adopted in acquiring and retaining customers. This typology of sales approach representing seller-focused antecedents is mapped against the relationship process and outcomes to provide a framework for understanding relationship mechanisms in live streaming commerce.     

The Impact of Industrial Market Access Negotiations on African Economies

This paper proposes an extensive data simulation exercise on the likely impact of non-agricultural market access liberalization. The paper analyses real options for tariff cut reduction, special and differential treatment and the treatment of unbound tariffs. This paper also gives indications concerning the likely economic impact of this trade round of industrial market access negotiations on African economies. It shows that an ambitious tariff cut reduction formula would provide greater access to developed country markets for African producers. However, this kind of formula has a major drawback for African countries in the sense that it could accelerate the de-industrialization of African countries and limit incentives to diversify their economies.     

风险管理，你犯错了吗？

我们无法预测“黑天鹅事件”的发生，与其一味幻想可以执掌未来，防堵风险，不如设法降低此类威胁带来的不良影响。     

Expected shortfall estimation for apparently infinite-mean models of operational risk

Statistical analyses on actual data depict operational risk as an extremely heavy-tailed phenomenon, able to generate losses so extreme as to suggest the use of infinite-mean models. But no loss can actually destroy more than the entire value of a bank or of a company, and this upper bound should be considered when dealing with tail-risk assessment. Introducing what we call the dual distribution, we show how to deal with heavy-tailed phenomena with a remote yet finite upper bound. We provide methods to compute relevant tail quantities such as the Expected Shortfall, which is not available under infinite-mean models, allowing adequate provisioning and capital allocation. This also permits a measurement of fragility. The main difference between our approach and a simple truncation is in the smoothness of the transformation between the original and the dual distribution. Our methodology is useful with apparently infinite-mean phenomena, as in the case of operational risk, but it can be applied in all those situations involving extreme fat tails and bounded support.     

Errors, robustness, and the fourth quadrant

The paper presents evidence that econometric techniques based on variance–L² norm–are flawed and do not replicate. The result is un-computability of the role of tail events. The paper proposes a methodology to calibrate decisions to the degree (and computability) of forecast error. It classifies decision payoffs in two types: simple (true/false or binary) and complex (higher moments); and randomness into type-1 (thin tails) and type-2 (true fat tails), and shows the errors for the estimation of small probability payoffs for type 2 randomness. The fourth quadrant is where payoffs are complex with type-2 randomness. We propose solutions to mitigate the effect of the fourth quadrant, based on the nature of complex systems.