FORECASTING CROWDFUNDING PLATFORM REVENUES USING ARIMA MODEL

Purpose – In recent years, crowdfunding platforms have become very popular as intermediaries between fundraisers and funders. However, various campaigns published on the platform might be of bad quality or fraudulent, so the crowdfunding platform must be very careful when choosing the right ones. Also, the proper selection depends on the profits of a crowdfunding platform. In most cases, crowdfunding platforms mainly earn money from transaction and administration fees from successful campaigns on their platforms. While it is very hard to select successful cam-paigns, it is possible to analyse already published campaigns and forecast future revenues of crowdfunding platforms. And based on this, to select new projects which might be successful too. The aim of this work is to develop a model to forecast the revenues of crowdfunding platforms. Research methodology – In this research, comparative and statistical analysis will be used, data structuring, modelling and forecasting, performed with the ARIMA model. Findings – Main findings of this research present the three most successful campaign categories from the Kickstarter platform that receives the highest funding. Fees were calculated from those three campaign categories, and revenues for the platform were forecasted using the ARIMA model. Research limitations – Main limitations are that there were used data from a very short period of time. For better results accuracy, a longer period is needed. Practical implications – this research might be of practical use since the forecasts show that the revenues will continue to grow from the successful campaign categories. Consequently, investors should continue to support technology, games and design categories the most. At the same time, crowdfunding platforms should give more attention to these categories when choosing new projects to launch on the platform.

THE MODERATING IMPACT OF ECONOMIC POLICY UNCERTAINTY ON THE RELATIONSHIP BETWEEN INVESTMENT IN WORKING CAPITAL AND PROFITABILITY

Purpose – Investment in working capital and firm profitability with economic policy uncertainty moderating effects has paid less attention in the existing literature. Therefore, this study examines the moderating impact of eco-nomic policy uncertainty on the relationship between Investment in working capital and firm profitability. Research methodology – This study uses secondary data of 38 Pakistani chemical companies over the period of 2014-2019 using dynamic panel data methodology. Findings – The dynamic panel analysis indicates that economic policy uncertainty moderates the relationship of in-vestment in working capital and firm profitability significantly and positively. Overall, the study findings indicate that working capital management investment significantly affect accounting base performance of Pakistani chemical and pharmaceutical companies. Research limitations – In this research, the researcher has collected data only from the non-financial sector. The financial industry can be used to carry the same study to get different results. Practical implications – This study will help practitioners while making an investment decision in working capital management for firms because the results of this study contribute significantly to the firm’s profitability. Originality/Value – This research contributes favourable to a country’s prospective investors at large and in the busi-ness’s internal environment to manage the short-term liquidity issues during economic policy fluctuations.

IS DIGITAL 'NEW NORMAL' OR 'CHALLENGE' FOR BANKS UNDER COVID-19?

Purpose – to reveal prerequisites of technology-enabled banking development in Lithuania, Poland, and Ukraine; to identify if digitalization was a beneficial factor in households deposits-raising during the COVID-19. Research methodology is twofold: analysis of digitalization index based on World Bank data as a premise of tech-nology-enabled banks development; beta-coefficient analysis and descriptive statistics – for digitalization influence assessment. Findings – digitalization index analysis showed that Lithuania has a more generous benefit in terms of digitalization. Poland and Ukraine follow with a slight gap. Traditional banks of analyzed countries are acting towards digitalization but at different paces. There are both digital and neobanks in Lithuania and Poland, while in Ukraine only digital banks. Analysis of Ukrainian banks deposits highlighted the fact that digital banks were in some cases more preferable for households, especially during a pandemic. Research limitations – lack of data: common digitalization indexes could not be calculated for Ukraine; differences in countries’ banking data: content and structuring criteria. Practical implications – the results could be important for policy recommendations to tackle the blind spots of banking digitalization. Originality/Value – suggested digitalization index could be utilized as a universal. Due to DESI limitations, common for EU countries, we were to create our own index and compare results with calculated by European Commission DESI values. While DESI is calculated using some specific survey data, the proposed index is using standardized data of World Bank; the results of digital and traditional banks deposits comparison could be useful for further study.

ASSESSMENT OF THE IMPACT OF EXTERNAL ENVIRONMENT ON FINTECH DEVELOPMENT

Purpose – to propose an assessment tool of the environment of FinTech sector. Research methodology – systematic analysis of scientific literature has been carried out to form a methodology for FinTech sector environment assessment, which consists of quantitative methods used for the empirical research of the study as follows: PEST analysis, expert evaluation, determination of indicators’ values, normalization of data, multi-criteria assessment (the Simple Additive Weighting (SAW) method). Findings – the practical application of the developed assessment tool is verified by completing an empirical study on the example of the leading FinTech countries as well as the Baltic States. Recommendations for further Lithuanian FinTech sector development are provided. Research limitations – research is based on an assessment of the significance of external environmental indicators of FinTech sector development on a country level. Due to the large number of indicators and countries, only a fraction of factors and countries were selected for research. Therefore, the object of the research requires a more detailed study in the future. Practical implications – the development of FinTech sector has been growing dramatically in the recent years on a global scale, with some countries leading the way due to a more favourable environment. The results show that the proposed assessment tool for the development of the FinTech sector can be used by policymakers in different countries to identify the external environmental factors to improve in order to create better conditions for the development of the FinTech sector. Originality/Value – a new methodology and tool for FinTech environment assessment is developed by the authors as a contribution to the formation of better environment for FinTech sector development. The developed tool provides an opportunity to study the strong and weak sides of the environment development of the FinTech sector, to compare the good practices of other countries and to get ideas for changes in order to create a more favourable environment for the FinTech development on a country level.

YIELDCO AS A PERSPECTIVE INVESTMENT VEHICLE

Purpose – the purpose of the article is to assess the investment potential of YieldСos as an innovative pension vehicle and determine the risks that may arise in connection with them. Methods used: empirical analyses, comparisons, statistical analyses. Research methodology – empirical research, comparative analysis, statistical analyses. Findings – in the paper we compared the new investment vehicle YieldCos (green) and a traditional investment vehicle – energy companies (non-green). It was found that the correlation of YieldCos with the market indices is similar to nongreen companies. But YieldCos are more exposed to risks than energy companies. That may offset their attractiveness as long term investment vehicle. It is necessary to continue research for this investment vehicle during the period of global financial volatility and crash of crude oil price. Research limitations – the authors study the raise of the new investment vehicle – YieldCos, during the period from 2013 to 2018 (pre Covid-19 Era). Practical implications – YieldCos focus on investors interests, raising money in an environmental projects (namely renewable energy), and provide combination of high yield and high income growth. Aforesaid characteristics are attractive for institutional investors that are currently experiencing a lack of resources to meet their obligations. Originality/Value – new investment vehicle is becoming a part of the overall socially responsible investment universe. We have taken the first step in the comparative evaluation of traditional and innovative types of investment instruments. Showed the prospects of a new environmentally oriented tool. It is necessary to continue research of this investment vehicle during the period of global financial volatility, changing landscape of energy resources and stakeholders rising influence.

TRENDS OF MUNICIPAL WASTE FLOWS, COMPOSITION, TREATMENT IN LITHUANIA AND ITS REGIONS

Purpose – to propose conceptual model for forecasting of waste trends and empirically implement the model based on the case of Lithuania and its regions. Research methodology – 1) scientific literature analysis on circular economy, zero waste and waste management, 2) gathering of statistical data on waste flows, composition and treatment 3) creation of conceptual model of forecasting with Exponential Smoothing for prediction of waste-related trends based on literature review. Findings – proposed conceptual model for prediction of waste-related trends is adequate for prognosis of waste flows, composition and treatment ways. The main forecasting results are that the total waste flows will increase in Lithuania, on a regional level, Alytus, Kaunas, Klaipėda, Telšiai, have a tendency of the increase in municipal waste flows. The results imply that in order to contribute to the reduction of waste, the active involvement on a regional level is necessary. Research limitations – the research can be extended with statistical data on waste of other countries to check adequacy of the conceptual model for waste-related trends prognosis. Practical implications – the findings of the research can be applied in planning and decision-making process of gov-ernment bodies on national or local level. The results are also useful for the general public in educational purposes. Originality/Value – the study provides original conceptual model for the forecasting of waste-related trends which provides robust results of predictions and can be replicated by different countries.

COMPANY FINANCIAL FLOW MODELLING BY SYSTEM DYNAMICS METHODOLOGY

Purpose – the purpose of the article is to develop a conceptual model of the company’s financial logistics based on the system dynamics principles. Research methodology – the article is based on the system analysis and system dynamics methods to define, classify and simulate a company financial flow. Findings – the definition of financial logistics for a business system has been defined. The authors make a classification of the company’s financial flow by the main economic activities and time series factors. Research limitations – commercial data, used for the practical implementation of the model, are confidential and cannot be disclosed. Practical implications – the model is implemented by transformation of a system dynamic flow graph into VENSIM programs. It may estimate the stationary trajectory financial flow and short-term and long-term gaps. Originality/Value – the conceptual model of the company’s financial logistics is determined based on the system dynam-ics principles. The model includes the advantages of the financial management methods and contemporary econometric analysis instruments based on a system dynamics.

RISK MANAGEMENT IN PUBLIC FINANCE SYSTEM OF UKRAINE UNDER GLOBAL CHALLENGES

Purpose – to analyze the current state of risk management in Public Finance System of Ukraine and prefer recommendations for its improvement. Research methodology – the structural-functional method (for revealing the influence mechanism of public finance risks on main indicators of Public Finance System), the comparison method (for comparing the main indicators of Public Finance System between Ukraine and other countries). Findings – recommendations for reducing of public finance risks will provide the budget with reliable sources of in-comes, optimize the structure of government spending, and improve the budget process in order to create conditions for enhancing the quality and efficiency of budget decisions. Research limitations – some risks are only of a qualitative nature and cannot be measured to analyze the impact of risks on the main indicators of Public Finance System. Practical implications – improvement of a risk-oriented method in Public Finance System under global challenges is an effective method of developing the existing Public Finance Management in Ukraine. Originality/Value – risk management in Public Finance system under global challenges is a new stage of comprehen-sive relations which opens the way for further progressive reforms. A great importance is to use the experience of risk management measures gained by EU states, but also taking into account the peculiarities of socio-economic situation in Ukraine.

INVESTIGATION OF THE HERDING AND CONTRARIAN BEHAVIOUR OF INVESTORS

Purpose – The paper analyses two different paradigms of investor behaviour that exist in the financial mar-ket – the herding and contrarian behaviour. The main objective of the paper is to determine which pattern of investor behaviour better reflects the real changes in the prices of financial instruments in the financial markets. Research methodology – Algorithms of technical analysis, deep learning and classification of sentiments were used for the research; data of positions held by investors were analysed. Data mining was performed using “Tweet Sentiment Visualization” tool. Findings – The performed analysis of investor behaviour has revealed that it is more useful to ground financial decisions on the opinion of the investors contradicting the majority. The analysis of the data on the positions held by investors helped to make sure that the herding behaviour could have a negative impact on investment results, as the opinion of the majority of investors is less in line with changes in the prices of financial instruments in the market. Research limitations – The study was conducted using a limited number of investment instruments. In the future, more investment instruments can be analysed and additional forecasting methods, as well as more records in social networks can be used. Practical implications – Identifying which paradigm of investor behaviour is more beneficial to rely on can offer ap-propriate practical guidance for investors in order to invest more effectively in financial markets. Investors could use investor sentiment data to make practical investment decisions. All the methods used complement each other and can be combined into one investment decision strategy. Originality/Value – The study compared the ratio of open positions not only with real price changes but also with data obtained from the known technical analysis, deep learning and sentiment classification algorithms, which has not been done in previous studies. The applied methods allowed to achieve reliable and original results.

FORECASTING COSTS OF CYBER ATTACKS USING ESTIMATION THE GLOBAL COST OF CYBER RISK CALCULATOR V 1.2

Purpose – due to the constant increase of cyber-attacks not only the measures of identifying and controlling cyber risks are created, but also the methods of estimating possible cyber-attacks financial costs should be developed to increase business preparedness. The purpose of this research is to forecast potential costs of cyber-attacks in Baltic countries. Research methodology – to achieve the aim of the article and prepare a prognosis of possible cyber-attacks costs the Estimation the Global Costs of Cyber Risk Calculator V 1.2 tool was used. Findings – estimated costs of cyber-attacks in Lithuania, Latvia and Estonia are highest in the public business and ser-vices sector and also in the defense sector. According to conducted calculations the costs of cyber-attacks in Lithuania will reach 1% of GDP of Lithuania by 2026. Research limitations – in this research the costs of cyber-attacks are estimated regarding industries of business but not excluding specific cyber threats. Therefore, for the future research possibilities could be the analyses of specific cyber risks and their impact to various business sectors. Practical implications – the results of the research may be useful in practical approach for preparing the risk manage-ment tools, evaluating possible damage and effect of cyber-attacks to business, also increasing preparedness level and business resilience. Originality/Value – this estimation model has been not used to evaluate and discuss cyber-risks costs in Lithuania among previous researches, therefore the topic and conducted results are original and significantly relevant for further analyses of cyber security issues in Lithuania.