Decentralized Finance (DeFi) Projects: A Study of Key Performance Indicators in Terms of DeFi Protocols’ Valuations

Decentralized finance (DeFi) protocols use blockchain-based tools to mimic banking, investment and trading solutions and provide a viable framework that creates incentives and conditions for the development of an alternative financial services market. In this respect, they can be seen as alternative financial vehicles that mitigate portfolio risk, which is particularly important at a time of increasing uncertainty in financial markets. In particular, some DeFi protocols offer an automated, low-risk way to generate returns through a “delta-neutral” trading strategy that reduces volatility. The main financial operations of DeFi protocols are implemented using appropriate algorithms, but unlike traditional finance, where issues of value and valuation are commonplace, DeFis lack a similar value-based analysis. The aim of this study is to evaluate relevant DeFi performance metrics related to the valuations of these protocols through a thorough analysis based on various scientific methods and to show what influences the valuations of these protocols. More specifically, the study identifies how DeFi protocol valuations depend on the total value locked and other performance variables, such as protocol revenue, total revenue, gross merchandise volume and inflation factor, and assesses these relationships. The study analyzes the valuations of 30 selected protocols representing three different classes of DeFi (i.e., decentralized exchanges, lending protocols and asset management) in relation to their respective performance measures. The analysis presented in the article is quantitative in nature and relies on Granger causality tests as well as the results of a fixed effects panel regression model. The results show that the valuations of DeFi protocols depend to some extent on the performance measures of these protocols under study, although the magnitude of the relationships and their directions differ for the different variables. The Granger causality test could not confirm that future DeFi protocol valuations can be effectively predicted by the TVLs of these protocols, while other directions of causality (one-way and two-way) were confirmed, e.g., a two-way causal relationship between DeFi protocol valuations and gross merchandise volume, which turned out to be the only variable that Granger-causes future DeFi protocol valuations

Private Renting vs. Mortgage Home Buying: Case of British Housing Market—A Bayesian Network and Directed Acyclic Graphs Approach

The worsening of housing problems in many countries has become a topic of global interest. Researchers point to a variety of factors that influence individual housing tenure decisions. Our study is based on longitudinal English Housing Survey (EHS) data (2008–2009 to 2019–2020, with survey years matching financial years, i.e., running April–March) and identifies flows between different forms of housing tenure in the U.K. and analyses conditional dependencies of a range of EHS variables using a directed acyclic graph (DAG). More specifically, we take into account variables such as first-time buyers (FTB), mortgage payments, rent payments, share of mortgage/rent in household income, and receipt of housing benefit (HB), with some variables also reflecting a regional breakdown (captured separately for London and England excluding London) to illustrate the complex nature of regional differences in explaining changes in housing tenure. We address some of the problems and challenges of the housing market in the U.K. today, and, in particular, examine what influences private renters and those buying with a mortgage. A key conclusion from this study is that housing benefit does not necessarily ease the way for private renters into their own housing. The study is quantitative in nature and uses the English Housing Survey and Bayesian network (BN) analysis. Unlike traditional methods, such as multiple regression or panel regression, where the researcher somehow suggests the type of a relationship between certain variables, BN’s learning algorithm analyses different iterations between variables and finds the most appropriate relationships between them

A Comparison of Different Machine Learning Algorithms in the Classification of Impervious Surfaces: Case Study of the Housing Estate Fort Bema in Warsaw (Poland)

The aim of this study is to extract impervious surfaces and show their spatial distribution, using different machine learning algorithms. For this purpose, geoprocessing and remote sensing techniques were used and three classification methods for digital images were compared, namely Support Vector Machines (SVM), Maximum Likelihood (ML) and Random Trees (RT) classifiers. The study area is one of the most prestigious and the largest housing estates in Warsaw (Poland), the Fort Bema housing complex, which is also an exemplary model for hydrological solutions. The study was prepared on the Geographic Information System platform (GIS) using aerial optical images, orthorectified and thus provided with a suitable coordinate system. The use of these data is therefore supported by the accuracy of the resulting infrared channel product with a pixel size of 0.25 m, making the results much more accurate compared to satellite imagery. The results of the SVM, ML and RT classifiers were compared using the confusion matrix, accuracy (Root Mean Square Error /RMSE/) and kappa index. This showed that the three algorithms were able to successfully discriminate between targets. Overall, the three classifiers had errors, but specifically for impervious surfaces, the highest accuracy was achieved with the SVM classifier (the highest percentage of overall accuracy), followed by ML and RT with 91.51%, 91.35% and 84.52% of the results, respectively. A comparison of the visual results and the confusion matrix shows that although visually the RT method appears to be the most detailed classification into pervious and impervious surfaces, the results were not always correct, e.g., water/shadow was detected as an impervious surface. The NDVI index was also mapped for the same spatial study area and its application in the evaluation of pervious surfaces was explained. The results obtained with the GIS platform, presented in this paper, provide a better understanding of how these advanced classifiers work, which in turn can provide insightful guidance for their selection and combination in real-world applications. The paper also provides an overview of the main works/studies dealing with impervious surface mapping, with different methods for their assessment (including the use of conventional remote sensing, NDVI, multisensory and cross-source data, ‘social sensing’ and classification methods such as SVM, ML and RT), as well as an overview of the research results

Project Risk in the Context of Construction Schedules—Combined Monte Carlo Simulation and Time at Risk (TaR) Approach: Insights from the Fort Bema Housing Estate Complex

In this article, we present our own construction process model consisting of 16 stages and eight phases, which is particularly applicable to large investment projects. In the context of each project phase, we examine how the appropriate way of scheduling construction processes affects the problem of the risk of prolonging individual phases and the whole project, as well as of not meeting deadlines (which is one of the main problems faced by management practitioners in the construction industry). There are many methods for assessing risk in this context, but they tend to be overly complex and rarely used by construction practitioners. On the other hand, the risks associated with potential schedule delays can be considered holistically. One tool that can serve this purpose is the combined Monte Carlo simulation and Time-at-Risk (TaR) approach, which originates from the world of finance. We show how the implementation of the process model (individual phases) and the whole project can be considered in the context of the covariance matrix between all its phases and how changes in the arrangement of these phases can affect the risk of time extension of the whole project. Our study is based on simulation data for a large development project (Fort Bema/Parkowo-Le´sne housing estate complex) in Bemowo, a district ofWarsaw, carried out between 1999 and 2012. The entire investment project involved the construction of almost 120,000 m2 of floor space

Spatial planning policy towards floodplains and environmental protection as obstacles to the development of settlements on the Lower Bug

A little over a decade ago, a number of legislative changes were made in Polish law dealing with spatial planning in relation to floodplains and water management. More specifically, the amendments were a consequence of the adoption of the relevant Floods Directive by the European Parliament and the European Council in 2007, which was introduced as a countermeasure to the allegedly increasing flood risks associated with the ongoing urbanisation of floodplains. It was recognised that the risks of material and non-material damage associated with increasing urbanisation are so great that appropriate legal provisions must be introduced to reduce them. More than a decade has passed since the introduction of these provisions (the Floods Directive was adopted in Poland in March 2011). Over time, it has become apparent that the implementation of many legislative changes in Poland related to spatial planning in floodplains has been impractical and has had a very negative impact on the spatial and economic development of these areas. In this article we focus on the Lower Bug Valley and show how these new laws have led to a deterioration of the living situation in the floodplains. Indeed, the problem of economic decline in the floodplains and Natura 2000 sites is very serious and affects people who have lived for years in a 2–5 km wide strip in quiet surroundings flood-prone areas and along the river bend. Restrictions on livestock and the decline of agriculture are compounded by the lack of interest in acquiring habitats and land. These areas are becoming an open-air museum with residents living on social benefits and pension

Application of the Bayesian New Keynesian DSGE Model to Polish Macroeconomic Data

In the paper we estimate a simple New Keynesian Dynamic Stochastic General Equilibrium NK DSGE model on the basis of Polish macro data from the period 2000-2019. The model is specified similarly to Gali (2008) with the use of the Bayesian approach. The NK DSGE model combines the advantages of both structural models and time-series models and, therefore, shows a significant degree of alignment with empirical data. The Bayesian estimation is based on the prior distribution of the model input parameters, which are later compared with the posteriors. The results obtained allow for assessing the persistence of responses to technological, inflationary and monetary policy shocks. On the basis of the NK DSGE model, we formulate a perception of macroeconomic interactions, e.g. nominal interest rates' association with inflation and the output gap. In other words, the NK DSGE model provides a better understanding of the relationship between interest rates, inflation and the output gap. This in turn makes it easier to understand the monetary policy response function

Stormwater Management in the City of Warsaw: A Review and Evaluation of Technical Solutions and Strategies to Improve the Capacity of the Combined Sewer System

Urban flooding is an increasingly common phenomenon around the world. The reasons are usually attributed to the insufficient capacity of the combined sewer system and its inability to adapt to the changing dynamics of rainfall. This is also the case inWarsaw (the capital of Poland), where the sewage system was designed in the 1960s. The aim of the article is to highlight possible hydrological solutions that would significantly improve Warsaw’s situation in terms of rainfall runoff. The article looks at some solutions that were previously mentioned in the literature and presents an assessment of the possible changes in land use/land cover on the hydrological processes and improvements in the general hydrological situation of Warsaw. In addition, the article points out the need to update the programme and spatial approach to the discharge of water from specific watersheds in Warsaw, as well as to establish a single manager for stormwater drainage in the city of Warsaw. An important issue is the restoration of natural retention basins in the city and the construction of artificial basins in places with frequent local flooding. The article emphasises the importance of building individual detention basins (as well as low-impact developments) for newly planned investments. Other important aspects are as follows: the construction of suitable underground or open channels, the need to disconnect Ursynów’s stormwater runoff from the catchment area of the Słu ˙ zewiecki Stream and to channel it along the southern bypass for Warsaw (S-2) to the dry lakes and ponds in Wilanów. Finally, the article discusses the application of Sustainable Drainage Systems (SuDS) and Real-Time Control (RTC) in urban drainage systems as a possible solution to improve wastewater management in urban areas

The Impact of Opencast Lignite Mining on Rural Development: A Literature Review and Selected Case Studies Using Desk Research, Panel Data and GIS-Based Analysis

The future of opencast mining and energy production based on conventional resources is one of the most important issues being discussed in international forums. The whole discussion is becoming increasingly heated and takes on a special significance with the drastic increase in energy commodity prices that has occurred with the outbreak of war in Ukraine. Especially in a country like Poland, these issues are accompanied by heated discussions between miners, the government and citizens. It should be emphasised that Polish lignite mining currently produces about 35% of the cheapest electricity in Poland and also creates many jobs. The aim of this study is to assess the possibility of continuing opencast mining and its impact on rural development—both from an environmental and socio-economic point of view. The study was conducted for two municipalities in Poland where opencast lignite mining plays an important role, namely Kleszczów and Kleczew. As a result, it was found that in the case of the studied municipalities, the presence of opencast mining has contributed to their development, and the application of modern environmental protection technologies and recultivation have reduced the difficulties associated with mining. On the other hand, the decision to start mining should be the result of a comparison between the potential environmental and social benefits and damages. In some cases, mining is beneficial for community development and leads to new opportunities for agriculture and tourism after reclamation. The study is a combination of different methods, i.e., case studies, GIS remote sensing analysis (based on Landsat data) and econometric analysis for selected socio-economic data.Warsaw University of Technology 504/04513/1060/43.07000

Identification of the key investment project management factors in the housing construction sector in Poland

The aim of this paper is to distinguish a number of factors that allow for a better understanding of investment process management in the housing construction industry. The research work that we performed consisted in conducting a questionnaire survey. A total of 192 Polish companies dealing with housing construction took part in the survey. The collected questionnaire responses were then subjected to a thorough analysis and interpretation, with the use of a method called exploratory factor analysis (EFA). In a nutshell, our analysis consisted in reducing the number of survey variables (73) in order to identify a few pivotal factors (4) with the greatest impact on investment processes management in the field of residential construction in Poland. These factors include: the activity of companies in the market environment (1), pro-social policy of the state (2), highly advanced technologies (3) and the use of appropriate market relations (4). In our study, we aim to show how successful construction processes are perceived by industry professionals. The scientific method that we used allows for assignment of a certain order of priority to specific groups of questionnaire variables, dependent on the eigenvalues-related percentage of explained variation

Quantifying Critical Success Factors (CSFs) in Management of Investment-Construction Projects: Insights from Bayesian Model Averaging

The problem with evaluating investment projects is that there are many factors that determine the degree of their successful conclusion. Consequently, there has been an active debate for years as to which critical success factors (CSFs) contribute most to the performance of construction projects. This is because the practice of empirical research is based on two steps: first, researchers choose a particular model from the space of all possible models, and second, they act as if the chosen model is the only one that fits the data and describes the phenomenon under study. Hence, there are many CSF lists that can be found in the literature, owing to the uncertainty at the model selection stage, which is usually ignored. Alternatively, model averaging accounts for this model uncertainty. In this study, the Bayesian model averaging and data from a survey of Polish construction managers were used to investigate the potential of 28 factors describing a diverse set of characteristics in explaining the performance of construction projects in Poland. Determinants of successful completion of investment projects are categorized by their level of evidential strength, which is derived from posterior inclusion probabilities (PIPs), i.e., providing strong, medium and weak evidence