Food’s Conservation into 03 Dimension’s Models of Cold Stores Operated by 03 Refrigeration Systems in Biskra Region (Classic, Absorption, Adsorption)

As renewable energy elucidation, the solar refrigeration of fruits such as date palm is a storage alternate to preserve food in healthy parameters of conditioning. This statistical and numeric study investigates the energy gain cost case around the diverse dimensions’ models of positive cold stores (02, 04, and 06 cold rooms), concerning energetic disparity and numerous financial fluctuations of the applied systems. The results of computation and analysis regarding panels of construction, equipment, consumption, and maintenance for classic, absorption, and adsorption refrigeration systems that conserve dates palm into these three cold stores. In the end, the comparison of technical and economic elements in tables and figures by enumerating their advantages and inconveniences. Classic Bitzer, Absorption WFC SC 5, and Adsorption AG ACS 15 and 08 are models in which their evaluation is relating to their costs. In Biskra, these results mean that adsorption chiller termed AG ACS (15 plus 08) is illustrious by its parameters of simplicity, lifespan, safety, and security, valued to 1147.5 €/m² and median cost up ten years of using is 92972 €.

VaR and market value of Fintech companies: an analysis and evidence from global data

PurposeThis study aims at determining the portfolio value at risk (VAR) and market value of Fintech firms and compare it with their counterparts.Design/methodology/approachBy using on a dataset from 46 countries between 2009 and 2018, the authors use five measures of VaR to investigate their empirical dynamics in relation with the market value of Fintech and non-Fintech companies.FindingsThe empirical results indicate that Fintech firms' portfolios have a higher financial risk and a higher market value in comparison to non-fintech firms' portfolios. Furthermore, the authors also report that the Fintech firm portfolios experience more financial risk regardless of the holding period as long-term (one year) or short-term (quarter).Research limitations/implicationsThere are some limitations in this research. This research does not segregate Fintech firms into their different types of services, such as direct financial investment services, loan provision services, insurance services (InsurTech), etc. The authors only aggregate the Fintech firms by country and region. Future research may consider analysing Fintech firms by differentiating the kind of financial services they offerPractical implicationsGiven the importance of their market value, the results imply that Fintech companies might contribute significantly to financial fluctuations in case of large variations of the market. In terms of policy recommendation, this observation requires a particular attention from the regulatory bodies who need to find the best economic balance between promoting innovation/financial technology and regulating the Fintech companies.Originality/valueThis paper is the first study clarifying the relation of financial risk and market value for the Fintech firms, using the large enough database to obtain significant results. This article implies that Fintech companies require a robust risk management framework

A strategy to overcome the effect of economic recession on construction industry in Oman

Construction industry firms are affected by the financial fluctuations in the local and international markets. World countries have been exposed to many financial recessions such as the 2008 recession and the sharp decline in oil prices since 2014, which caused a major financial recession in countries that depend heavily on oil income in their economy like the Sultanate of Oman, where they constitute 70% of the national income. The research objective is to review previous literature review of some countries that have been exposed to economic recessions and how did these countries acclimatization to the recession. It will also focus on the strategies that followed by these countries to get out from the recession. Then, the research will identify the effects of the recession in the construction industry and the impact of it to the contractor in the Sultanate of Oman. Finally, a strategy will be suggested for the construction industry firm to use it through the economic recession to survive. The research methodology relies mainly on information provided by the Government of Oman through the National Center for Statistics and Information and through interviews with various construction specialists. The results show that most of the construction industry firms have been subjected to a great pressure due to the economic recession. The suggested strategy includes a procedure that assists construction firms to reduce expenses, how to bid and get new projects and create a new management style for the firm to cope with the developments and the volatility of the financial market.

Cryptoassets as an emerging class of digital assets in the financial accounting

Introduction. Currently, there is no single, unified framework for the classification of cryptoassets. Consequently, there is no generally applied definition of neither cryptoassets, nor digital tokens, due to the variety of features and bespoke nature of the transactions in practice. The objective of this paper is to define the essence of cryptoassets in the financial accounting, identify attributes for its taxonomy and provide a multipurpose overview of cryptoassets market environment. Methods. In a comprehensive overview of cryptoassets market environment, the authors have used statistical monitoring, as well as dynamic, comparative and structural analysis. The selected sample includes daily data of cryptoassets market capitalization. Data were gathered from multiple sources at various time points during February 2016 - July 2020. Results. According to the conducted research, the countries with the largest number of registered cryptoassets exchanges are: the UK, Hong Kong, Singapore and the US, however, about 17% of exchanges still stay with unknown countries of registration. It is expected that the number of such exchanges will reduce soon, due to the adoption of certain legislative frameworks regarding cryptoassets. The authors define the essence of such terms as: cryptoassets, cryptocurrency, digital tokens and propose a cryptoassets taxonomy, based on the token’s functionality and characteristics. Four main types of cryptoassets have been identified and defined, namely: cryptocurrency (payment tokens), security tokens, utility tokens, asset-backed tokens and hybrid (or mixed) tokens. The authors suggest possible financial accounting treatment for each type of the cryptoassets. Conclusions. The cryptoassets market capitalization reacted to the factors such as global financial fluctuations due to macroeconomic factors and the COVID-19 pandemic as well as increasing digital asset regulations in early 2020. Cryptoassets remain largely a self-regulated industry and they still have no legal definition. The authors define cryptoassets as transferable digital assets recorded with a distributed ledger technology, which prohibits their copying or duplication. Due to the plethora amount of types of cryptoassets, a case-specific review should be required to determine the corresponding financial accounting treatment. The methodology of cryptoassets accounting treatment require further research.

On the Advent of Fractional Calculus in Econophysics via Continuous-Time Random Walk

In this survey article, at first, the author describes how he was involved in the late 1990s on Econophysics, considered in those times an emerging science. Inside a group of colleagues the methods of the Fractional Calculus were developed to deal with the continuous-time random walks adopted to model the tick-by-tick dynamics of financial markets Then, the analytical results of this approach are presented pointing out the relevance of the Mittag-Leffler function. The consistence of the theoretical analysis is validated with fitting the survival probability for certain futures (BUND and BTP) traded in 1997 at LIFFE, London. Most of the theoretical and numerical results (including figures) reported in this paper were presented by the author at the first Nikkei symposium on Econophysics, held in Tokyo on November 2000 under the title “Empirical Science of Financial Fluctuations” on behalf of his colleagues and published by Springer. The author acknowledges Springer for the license permission of re-using this material.

A Modified Deep Learning Enthused Adversarial Network Model to Predict Financial Fluctuations in Stock Market

Predicting financial fluctuations in the real-time stock market is considered to be a major problem due to dynamic changes in financial data. With the advent of using artificial intelligent techniques in the context of predicting the patterns, artificial neural networks have drawn the attention of various researchers to implement the same in several computational applications. Addressing this problem, a modified adversarial network based framework is proposed with the integration of gated recurrent unit and convolution neural network. The main objective of this model is to acquire data from online financial sites and to process the obtained information using adversarial network to generate predictions.