Non-Fungible Tokens (NFTs) is a new virtual asset phenomenon the trade of which has spread quickly without any regulationas no legislation has been adopted in the EU, USA or the UK where the majority of NFT trading takes place. Concerns have been raised about NFTs and their relation to fraud and money launderingasanonymity and price volatility of NFTs create a unique and profitable asset for criminals. This paper addressestwomain issues: (1) trading statistics on NFTs,their analysis,and if and to what extent NFTs are used for financial crimes purposes; and (2) the legal challenges posed by the misuse of NFTs for fraud and other economic crimes. The final section of this paper provides feasible regulatory and business solutions that can help businesses to mitigate risks emanating from NFTs. It is argued that legal scholars, businesses and/or regulators cannot solve the challenges and risks posed by NFTs on their own, requiringmultidisciplinary research from academia and knowledge exchange between private and public stakeholders to close this gap.

In these days, many different techniques are implemented for generating distributions. The core aim in generating distribution, is better modeling capability. With generating new distribution more reliable and appropriate models are available for data sets. In this paper, a new distribution is gained by evaluating the conditional diagonal section of the bivariate Farlie-Gumbel-Morgenstern distribution with exponential marginals. Specifications and characteristics of this new distribution are studied. The statistical assessment and some reliability analyzes are carried out. The success of the new distribution on statistical modeling is detected by using data sets in literature. It is concluded that this new distribution suggests a model that can be used effectively in many different lifetime data sets.

In this study, a new bivariate distribution family is introduced by adding an appropriate term to independent class. By choosing a base distribution which is negatively dependent from the same marginals we derive a new distribution around the product of marginals, i.e. independent class of distribution. We note that the new distribution has additional parameter which would provide additional flexibility in applications. The joint probability density, joint reliability and reversed hazard rate functions of the new bivariate distribution are obtained. Furthermore, we obtain lower and upper bounds of Spearman’s correlation coefficient. Two example are given to illustrate this family. This new bivariate continuous distribution can make more appropriate modeling of some data sets in terms of the Spearman rank coefficient.

In this study, a new approach to transmutation theory is developed by using negative dependency basement. Once choosing a distribution that has negative dependency with the same marginal, a new bivariate distribution is derived. In this study, we examined a new transmutation technique in which a negative dependency offers a big success in modeling rather than most known and used statistical distributions. This approach clash with classical transmutation methods. In this study at the beginning, the classical transmutation is defined. Later, we introduce the new technique and obtain lower and upper bounds of distribution to show that this approach gives us a distribution. Gaining new bivariate continuous distributions with this technique may be more appropriate in theory, and modeling of some data sets in terms of this approach may be more efficient.

This paper introduces a stochastic approach to case numbers of a pandemic disease. By defining the stochastic process random walk process is used. Some stochastic aspects for this disease are argued before stochastic study is started. During random walk process modeling new patients, recovering patients and dead conclusions are modelled and probabilities changes in some stages. Let the structure of this study includes vanishing process as a walk step, some wave happenings like big differences about spread speed as a big step in treatment- an effective vaccine or an influential chemical usage- a second corona virus pumping with virus mutation, a second global happening which bumping virus spread are defined as stages. This study only simulates a stochastic process of corona virus effects.