Precious Metal Prediction by Using XAI in the Perspective of Digital Transformation

Recent advances in deep learning methodology led to artificial intelligence (AI) performance achieving and even surpassing human levels in an increasing number of complex tasks. There are many impressive examples of this development such as image classification, sensitivity analysis, speech understanding, or strategic gaming. The estimations based on the AI methods do not give any certain information due to the lack of transparency for the visualization, explanation, and interpretation of deep learning models which can be a major disadvantage in many applications. This chapter discusses studies on the prediction of precious metals in the financial field that need an explanatory model. Traditional AI and machine learning methods are insufficient to realize these predictions. There are many advantages to using explainable artificial intelligence (XAI), which enables us to make reasonable decisions based on inferences. In this chapter, the authors examine the precious metal prediction by XAI by presenting a comprehensive literature review on the related studies.

Approaches to Climate Change: Something Is Missing

The Paris agreement from 2015 is not what the masses had hoped for. The IPCC has made a great effort to gather information for global policy making, but the Anthropocene fear of global warming has not been appeased. Why is this? Climate change theory does not consider how states and their governments engage in strategic gaming.

The Disruption of the Prudential Regulatory Framework

ABSTRACT This article first explores how the prudential regulatory framework may be drastically changed as a result of the adoption of regtech and suptech innovations. The adoption of a shared data architecture, whereby the regulator is provided with seamless access to the accounts of regulated firms, may result in the development of a centralized approach to regulatory modelling, thus bypassing the existing partition between internal models and standardized approaches. Secondly, this article discusses how, thanks to the adoption of advanced predictive analytics, non-bank fintech lenders can gain insights into borrowers’ creditworthiness irrespective of banks’ control over traditional sources of information for credit scoring. This, though, may give rise to a new type of strategic gaming, this time by borrowers keen to maximize their chances of being granted a loan. In any case, preventing banks from adopting these new methods for the purpose of regulatory modelling might weaken their competitiveness. Thirdly, this article explores whether the transition to a centralized approach for credit risk management would conflate the distinction between microprudential and macroprudential interventions, in particular with respect to the countercyclical macroprudential policy. Finally, the article argues that non-bank (fintech) firms could be persuaded to coalesce behind endorsement of the new regulatory shared data platform in return for the support from the central bank. In this way, the regulatory perimeter could be extended in order to steer the adoption of financial innovations in a manner that benefits society overall.

Incentives and Competition in the Airline Industry

We examine how performance changes at airlines in response to a change in executive incentives. Airlines with executive bonuses contingent on on-time arrival do improve on-time performance. We find evidence of strategic gaming of the incentive as some carriers increase scheduled flight times, making it easier for flights to arrive on time. This effect is more pronounced for competitive routes. Carriers also do not decrease the frequency of flights or the number of passengers to make it easier to be on time, but they do slightly decrease fares. Competitors on the same routes also improve their on-time performance, even when their executive bonuses are not contingent on on-time performance, consistent with competition in strategic complements. (JEL G30, G34, G32) Received February 5, 2018; editorial decision April 3, 2019 by Editor Andrew Ellul.

Novel optimization using hierarchical Path finding A* (HPA*) algorithm for strategic gaming setup

In game Industry, the most trending research area is shortest path finding. There are many video games are present who are facing the problem of path finding and there is various algorithms are present to solve this problem. In this paper brief introduction is given in the most using algorithm for path finding and A* algorithm has been proved the best algorithm for resolving the problem of shortest path finding in games. It provides the optimal solution for path finding as compare to other search algorithm. At the start of the paper, brief introduction about the path finding is given. Then the reviews of different search algorithm are presented on the basis of path finding. After that information of A* algorithm and optimization techniques are described. In the last, application and examples how the path finding techniques are used in the game is addressed and future work and conclusion are drawn.