The main aim of this task deals with analysis of the possibility of valuing building budgets in the building information model (BIM). The work is divided into two parts. The first, research part, presents the necessary definitions and concepts, such as definitions of BIM, LOD, CDE, which are needed for working with (BIM) software. The second, practical part, analyses possible ways to determine building budgets using the building information model on one building, which was modeled in the student version of Graphisoft ArchiCAD 24.

Housing is both a durable good and an investment vehicle, which makes it importantin people’s daily life aswell as for a nation’s economy. This thesis innovatively applies the Sharpe ratio on evaluating the performance of the US residentialhousing market within the time period from 2005:Q1 to 2019:Q3, andinvestigates how this performance would react upon macroeconomic shocks,including sudden changes in GDP growth rate and personal income growthrate, by establishing a vector auto-regression model with the lag order of four.The main results are that: (1)in the long run, direct residential investments are not significantly more profitable than treasury bills but not disappointing compared to the market portfolio of Dow Jones Industrial Average; (2)the performance of residential investments seem to slightly and positively co-move withGDP and personal income growth rate; (3)the long-term impacts that sudden GDP and personal income growths have on the performance seem inconspicuous and tend to mitigate within about three years and (4) limited evidence supports the hypothesis that current housing market performance can help predictfuture GDP growth rate. Based on housing’s two purpose of consumption andinvestment and the empirical results showing that direct investments on residentialproperties have similar risk-adjusted return level to short-term treasurybills, I suggest that financially feasible households purchase their own houseinstead of renting for a long time, and that speculative investors avoid puttingmoney in residential properties unless they have access to inside information. / Bostäder kan betraktas både som en hållbar vara och som ett investeringsinstrument.De är essentiella för människors vardag och har en viktig roll förett lands ekonomi. Denna avhandling använder innovativt Sharpe-förhållandet för att utvärdera hur den amerikanska bostadsmarknaden presterade under perioden2005: kvartal 1 till 2019: kvartal 3. Den försöker även undersöka om denna prestation påverkas av makroekonomiska chocker inklusive plötsligaförändringar i BNP-tillväxttakt och personliga inkomsttillväxthastighet. Detta görs genom att upprätta en vektor autoregression modell med en fördröjningsordningför fyra. De viktigaste resultaten är att: (1) på långsikt är direktabostadsinvesteringar inte betydligt mer lönsamma än statsskuldväxlar dock är det hellre inte en besvikelse jämfört med en marknadsportföljen av Dow JonesIndustrial Average; (2) Prestationen av bostadsinvesteringar verkar vara svagt och samverkar positivit både med BNP och tillväxttakten för personinkomst.(3) De långsiktiga effekterna av plötsliga tillväxter av BNP och personliga inkomster har på utvecklingen verkar vara vaga och tenderar att mildra inomcirka tre år och (4) begränsade bevis stöder hypotesen om att nuvarande bostadsmarknadsresultat kan bidra till att förutsäga framtida BNP-tillväxttakten.Baserat på bostädernas två syften inom konsumtion och investeringar, visar deempiriska resultaten att direkta investeringar i bostadsfastigheter har en liknande riskjusterad avkastningsnivå som kortfristiga statsskuldväxla. Därför föreslår jag att ekonomisk stabila hushåll borde köpa ett eget hus istället för att hyraunder en lång tid, och att spekulativa investerare borde undvika att satsa pengar inom bostadsfastigheter såvida de inte har tillgång till insider-information.

The purpose of this study is to examine whether the implementation of quantitative easing (QE) and quantitative tightening (QT) in the United States has detracted from the integrity of the country’s macroeconomic environment. In other words, does QE impact macroeconomic stability? Then, evaluate implications and externalities of stability as they relate to sustainability efforts. QE and QT are relatively new phenomena, understanding their effects and implications for the greater economy is a worthwhile endeavor, not least because QE is a current practice of so many central banks internationally. This study has two parallel investigations; first, a time series analysis conducted with a VAR model investigating the relationship of QE/QT usage by the Federal Reserve (Fed) on the macroeconomic stability of the United States. The data used in this study includes 242 monthly observations spanning January 2003 - February 2023. The second, is an OLS regression analysis evaluating whether macroeconomic stability is potentially correlated with sustainability efforts. For this study, 23 annual observations spanning 1995 – 2017 were used. Due in part to the general unavailability of genuine progress indicator (GPI) data. Based on the analysis conducted using a VAR model at lag t-4, QE has a positive relationship with Producer Price Index (PPI) and Federal Funds Rate (FFR). This is in accord with previous empirical literature on the subject. However, the second path of discovery failed to yield significant results with regard to the link between macroeconomic stability and sustainability efforts. Mention of this study’s limitations as well as avenues for future research can be found in the conclusion of this study.

Companies in the spare part industry can implement a variety of different pricing techniques, which have traditionally been done through personnel know-how and industry conventions. One such technique is the use of price indices to track sales performance. This thesis investigates if machine learning or time series analysis can predict revenue using price and price indices in a data-driven manner which can potentially validate current pricing strategies or serve as a basis for sales teams pricing decisions. Price indices used were the Fisher Index and the Törnqvist Index. The data came from a spare parts supplier and consisted of daily transactions. Two target variables were tested: revenue as a continuous and categorical variable. The continuous target variable represented revenue the following day, while the categorical variable represented either an increase or decrease the following day. Models tested were OLS, XGBoost, ARIMAX and LSTM for the continuous case and Logistic Regression and XGBoost in the categorical case on several different feature sets. In the continuous case, ARIMAX outperformed the other models, but the best model was produced by the feature set not containing any indices. In the categorical case on a feature set containing price indices, XGBoost yielded an accuracy of 68% in classifying revenue increases or decreases. This study suggest that price indices contain some information about whether a revenue movement is going to happen, but not the magnitude of it. / Företag som säljer reservdelar kan implementera olika prissättningsstrategier. Dessa har traditionellt baserats på personalkunnande och branschkonventioner. En strategi som tillämpas är prisindex för att följa upp försäljning. Detta examensarbete undersöker om maskininlärning eller tidsserier kan prediktera omsättning med hjälp av pris- och prisindex på ett datadrivet sätt som kan potentiellt validera nuvarande strategier eller agera underlag för prissättningsbeslut. Prisindex som användes var Fisherindex och Törnqvistindex. Datan kom från en reservdelsleverantör och bestod av dagliga transaktioner. Två beroende variabler testades: omsättning som en kontinuerlig och omsättning som kategorisk variabel. Den kontinuerliga variabeln representerade omsättning nästa dag, medan den kategoriska variabeln representerade utfallet ökning eller minskning av omsättning nästa dag. Modellerna som tränades var OLS, XGBoost, ARIMAX och LSTM i det kontinuerliga fallet och Logistisk Regression och XGBoost i det kategoriska fallet. De tränades på flera uppsättningar av oberoende variabler. I det kontinuerliga fallet presterade ARIMAX bäst, men den bästa modellen tränades på en uppsättning oberoende variabler som inte innehöll några index. I det kategoriska fallet gav XGBoost en noggrannhet på 68% vid klassificering av omsättningsökningar eller minskningar. Detta på en uppsättning oberoende variabler som innehöll prisindex. Resultaten antyder att prisindex innehåller viss information om huruvida en omsättningsrörelse kommer att ske, men inte storleken på den.

Syftet med denna studie var att förklara olika konjunkturlägens påverkan på totalavkastningen samt den riskjusterade avkastningen för tre olika investeringsstrategier. Dessa var Stock Selection for the Defensive Investor samt indexen OMX Stockholm 30 och OMX Stockholm Small Cap Price Index. Den förstnämnda strategin utgår ifrån det 14:e kapitlet i Benjamin Grahams bok, The Intelligent Investor. Genom att ställa höga krav på faktorer som lönsamhet, kontinuitet av utdelningar och låg värdering m.m. filtrerar denna aktiva investeringsstrategi bort många bolag och lämnar kvar stabilare bolag med lägre risk. OMX Stockholm Small Cap Price Index valdes eftersom det innehåller helt andra sorters bolag än Stock Selection for the Defensive Investor, vilket är småbolag. OMX Stockholm 30 valdes i sin tur för att bolagen i detta index, likt de Stock Selection for the Defensive Investor väjer ut, är stora bolag som ofta associeras med lägre risk. Detta genomfördes med syftet att hitta större kontraster mellan strategierna. Dessa strategier undersöktes under lågkonjunkturen 2007-2011, högkonjunkturen 2016-2019 samt under 15-årsperioden 2007-2021. Avkastningarna mättes i totalavkastning och CAGR medan deriskjusterade avkastningarna mättes med hjälp av Sharpekvot, Treynorkvot samt Jensen’s Alpha. Denna studie kom fram till att totalavkastningen för de olika strategierna skiljer sig åt mellan de olika perioderna. OMXS30 genererade högst totalavkastning under lågkonjunkturen medan OMXSSCPI genererade högst avkastning under både högkonjunkturen och under 15-årsperioden. Resultaten för de riskjusterade måtten visade på att det inte fanns någon statistisk signifikant skillnad mellan strategierna, vilket indikerar att skillnaderna i totalavkastningen beror på den risk som tas. / This study aimed to explain the impact of different economic conditions on the total return and riskadjusted return of three investment strategies: Stock Selection for the Defensive Investor, OMXStockholm 30, and OMX Stockholm Small Cap Price Index. The first strategy is based on the 14th chapter of Benjamin Graham's book, "The Intelligent Investor." By demanding high profitability, dividend continuity, low valuation, and other criteria, this active investment strategy filters out manycompanies and focuses on more stable companies with lower risk. OMX Stockholm Small Cap Price Index was chosen because it includes a different set of companies compared to Stock Selection for the Defensive Investor, specifically small-cap companies. On the other hand, OMX Stockholm 30 was selected because the companies in this index, similar to those preferred by Stock Selection for the Defensive Investor, are large companies often associated with lower risk. This was done in orderto identify more significant contrasts between the strategies. These strategies were examined during the recession 2007-2011, the economic boom 2016-2019, and a 15-year period 2007-2021. Returns were measured in terms of total return and compound annual growth rate (CAGR), while risk-adjusted returns were assessed using the Sharpe ratio, Treynor ratio, and Jensen's Alpha. This study found that the total returns of the different strategies varied across the different periods. OMX Stockholm 30 generated the highest return during the low economic cycle, while OMX Stockholm Small Cap Price Index produced the highest return during both the high economic cycle and the 15-year period. The results for the risk-adjusted measures indicated no significant differences between the strategies, suggesting that the variations in total returns are attributable to the level of risk undertaken.

自從2007年發生金融海嘯後，歐盟貨幣整合問題持續被討論，其中，歐盟成員國各國經濟狀況差距過大被認為是這次經濟危機爆發出種種問題的主要原因。而近幾年，在國際其他地區區域性整合刺激之下，亞洲各國開始重視簽屬自由貿易協定的重要性，甚至未來朝區域貨幣整合作發展。 此論文主要是探討東亞國家是否具備成立亞元區的條件。我們探討東亞各國2004-2015年間對美元匯率以及消費者物價指數(CPI)變化是否有一致的趨勢，主要使用MST及HC、DCG tree機器學習分群演算法作為分析工具，對於東亞十個國家，包含台灣、日本、中國、南韓、香港、印尼、泰國、馬來西亞、菲律賓、新加坡以及用於對照的世界上其他國家作分析，以2008年金融海嘯以及2013年日本提出新經濟政策作為分界點，分為三個時期做討論。 研究結果顯示，三個時期，東亞國家匯率變動相較於世界其他國家皆較有一致的趨勢，而更進一步檢視，我們發現在日本提出新經濟政策前後，東亞國家匯率結構發生明顯的變化。物價指數方面同樣也是東亞國家有較集中的趨勢，但物價指數不向匯率，不同時期並無明顯變化。我們進而推論東亞國家以符合成立亞元區最基本的條件，匯率和物價指數的一致性，但是有幾個結果不能忽略，日本對於東亞國家匯率結構的影響力以及人民幣、日圓等強勢貨幣匯率變動趨勢在分析結果中和其餘東協國家還是有些差距，這些可能是在未來貨幣整合過程中市所需要注意的部分。 / After the global financial crisis, European Union (EU) faced a range of economic and political problems, including the Greek debt crisis and the upcoming UK referendum on EU membership. People start to think what factors cause these problems. A large literature has emerged discussing this issue and examining the future directions of monetary and exchange rate agreements of many countries in the region. One of the popular questions has raised researchers’ interests: Are East Asian countries possible to be the next monetary integrated area? This paper investigates the similarity of exchange rates and consumer price index (CPI) in the East Asian region, Taiwan, Japan, China, Hong Kong, South Korea and five ASEAN member countries by cluster analysis. We use HC tree and DCG tree to discuss the structures of these two macro economic factors and whether major economic events between 2004~2015 such as global financial crisis and Japan’s new economic policy influenced the structure. The exchange rates and CPI are both found to be more consistent among East Asian countries, including that these countries already have the basic condition to be the monetary integrated area. However, it is important to pay attention to Japan’s new economic policy, which influenced the structure a lot, and that Japanese yen and Chinese yuan still have gaps with ASEAN member countries.

Sammanfattning Examensarbete i finansiering, Civilekonomprogrammet Ekonomihögskolan vid Linnéuniversitetet, VT-2017 Författare: Emma Magnusson & Jonathan Hillgren Handledare: Håkan Locking Examinator: Andreas Stephan Titel: For better or for worse – A study on the impact of exchange rate volatility on trade   Bakgrund: Växelkurssvängningar har studerats av flertalet forskare då detta anses vara en osäkerhet vars effekt inte är säkerställd. Då internationell handel är en viktig faktor för tillväxt och välstånd i en nation är dess samband med volatiliteten betydelsefullt att fastställa för att identifiera huruvida inverkan på landet är positiv eller negativ.   Problemformulering: Har volatiliteten i eurons växelkurs mot rörliga valutor någon påverkan på den bilaterala handeln mellan eurozonen och andra europeiska länder?   Syfte: Att kunna urskilja effekten av växelkursvolatilitetens påverkan på export och import vilket kan gynna företag i dess handelsbeslut, strategier och framtidprognostisering.    Metod: Undersökningens tillvägagångssätt grundar sig i en tidsserieanalys där beräkningar för volatiliteten ligger som grund till förklaringsvariabeln i modellen för att studera dess effekt på handeln, vilket skattas genom en noga utvald ARDL-metod. Regressionerna ger både ett lång- och kortsiktigt samband för att visa skillnader i influenser från volatiliteten på export och import för Sverige och Norge som studeras i rapporten.   Slutsatser: De erhållna resultaten för både Sveriges och Norges export visar att ingen påverkan alls kan urskiljas från växelkurssvängningar vilket innebär att exporten fortskrider oavsett grad av volatilitet vilket kan förklaras genom dess förmodade likheter i handelsmönster, varukategorier och exponering mot euroländerna. En möjlig slutsats är även att det inte är volatiliteten i sig som påverkar handeln, utan underliggande faktorer som inte kontrollerats för, vilket åskådliggjordes när oljeprisindex inkluderandes och eliminerade volatilitetens effekt på Norges export. Importen visade en långsiktig negativ effekt av volatiliteten för Norge och en kortsiktig positiv påverkan för Sverige. Skillnader i importen antas bero på olikheter i valutasäkring, trögheter i ekonomin och relationen till EU. / Abstract   Master Thesis in finance, Business and Administration School of Business and Economics at Linnaeus University, VT-2017 Authors: Emma Magnusson & Jonathan Hillgren Advisor: Håkan Locking Examiner: Andreas Stephan Title: For better or for worse – A study on the impact of exchange rate volatility on trade   Background: Exchange rate fluctuations have been studied by numerous researchers, since it is thought of as an uncertainty whose effect is not guaranteed. Because international trade is an important factor to growth and wealth for a country, its connection to volatility is important to establish in order to identify whether the influence on the nation is positive or negative.   Problem: Does the volatility in the exchange rate between the euro and floating currencies affect bilateral trade between the euro area and other European countries?   Purpose: The purpose of the study is to distinguish the effect of the exchange rate volatility on export and import, which can favor companies in their trade decisions and strategies.   Method: The approach of the study is built on a time series analysis where estimates of volatility are underlying the explanatory variable to find its effect on trade, which is calculated by a carefully selected ARDL method. The regressions obtain both long-term and short-term relationships to show differences in the effect from the volatility on export and import for Sweden and Norway, the studied countries in this report.   Conclusions: The results for the export of both Sweden and Norway do not show any impact from the exchange rate fluctuations, which means the export continues regardless of the level of volatility. This can be explained by their similarities in the pattern of trade, products and exposure to the euro countries. Another possible conclusion is that the volatility itself is not affecting trade but that the underlying factors not being controlled for are, which was shown when the oil price index was included and eliminated the effect of the volatility on Norwegian exports. The import exposed a long-term negative effect of the volatility for Norway and a short-term positive effect for Sweden. The disparities are assumed to be due to differences in the use of hedging, inertia in the economy and the relationship with the European Union.

This thesis explores whether scanner data can be used to inform Consumer Price Index (CPI) construction, with particular reference to the issues of substitution bias and choice of aggregation dimensions. The potential costs and benefits of using scanner data are reviewed. Existing estimates of substitution bias are found to show considerable variation. An Australian scanner data set is used to estimate substitution bias for six different aggregation methods and for fixed base and superlative indexes. Direct and chained indexes are also calculated. Estimates of substitution bias are found to be highly sensitive to both the method of aggregation used and whether direct or chained indexes were used. The ILO (2004) recommends the use of dissimilarity indexes to determine the issue of when to chain. This thesis provides the first empirical study of dissimilarity indexes in this context. The results indicate that dissimilarity indexes may not be sufficient to resolve the issue. A Constant Elasticity of Substitution (CES) index provides an approximate estimate of substitution-bias-free price change, without the need for current period expenditure weights. However, an elasticity parameter is needed. Two methods, referred to as the algebraic and econometric methods, were used to estimate the elasticity parameter. The econometric approach involved the estimation of a system of equations proposed by Diewert (2002a). This system has not been estimated previously. The results show a relatively high level of substitution at the elementary aggregate level, which supports the use a Jevons index, rather than Carli or Dutot indexes, at this level. Elasticity parameter estimates were found to vary considerably across time, and statistical testing showed that elasticity parameter estimates were significantly different across estimation methods. Aggregation is an extremely important issue in the compilation of the CPI. However, little information exists about 'appropriate' aggregation methods. Aggregation is typically recommended over 'homogenous' units. An hedonic framework is used to test for item homogeneity across four supermarket chains and across all stores within each chain. This is a novel approach. The results show that treating the same good as homogenous across stores which belong to the same chain may be recommended.

There is a series of different types of risk on the housing market and related industries.  The six papers in this doctoral dissertation are about a number of the many dimensions of risk management on the housing market. The main message of this thesis is that it should be possible for different actors in the housing market to improve risk management. Indeed, the last years’ financial turmoil has revealed that it should not only be possible, but also necessary, to improve risk management at all levels of the economy: at household, corporate, regional, national and international level. Although the complexity of the environment in which we live and act makes it very difficult to predict and quantify risk, the development of risk management techniques should make it possible to better indentify, and reduce risk. The first paper provides a systematic overview of a wide selection of methods or strategies used in different countries to expand but also to maintain home ownership among low income households. The second paper further discusses mortgage and home equity insurance instruments discussed in the first paper. This paper also discusses how a rental insurance policy, as an alternative to traditional rent regulation, may be constructed. Paper 3 develops a formula that might be used in order to value the rental insurance option discussed in paper 2. The fourth paper focuses on the housing building sector by discussing potential benefits of strategic alliances that the different actors in the housing construction market may establish in order to pool resources and manage development risks. The challenge of constructing reliable home price indexes has attracted scholars for many years. Paper 5 develops monthly quality-adjusted price indexes for condominiums (housing cooperative apartments) based on a unique dataset covering sales in the whole of Stockholm municipality from January 2005 to June 2009. Finally paper 6 pays attention to the large increase in housing cooperative conversions sine the 1990s, by deriving a closed-form valuation formula that might be used to value the embedded option an owner of a multi-family rental property has to sell it to a housing cooperative. / QC 20100810

In South Africa various financial institutions and independent vendors have developed residential property valuation models to estimate the current value of historically traded properties. A natural extension to these models has been to develop historical property price indices. In this dissertation, three of the four approaches to developing property price indices will be examined. Through back–testing and other statistical methods, the most accurate and robust approach will be determined. The four major approaches available are the mean valuation per suburb, the median valuation per suburb, the repeat sales approach and hedonic regression. The mean valuation per suburb approach can be biased because of outliers in property prices. However, outliers in property prices will not influence the median valuation per suburb approach, but in cases where property values in a suburb have a skewed distribution, the valuation amount could be distorted. Neither of the above mentioned shortcomings influences the repeat sales or the hedonic regression approach. To follow the hedonic regression approach, the characteristics of the property need to be known. In South Africa, however, the available property data lacks detailed characteristics of traded properties. This dissertation will therefore focus on the first three methods. The repeat sales approach measures the growth in property prices by applying a generalized linear model to properties that have traded more than once. This approach is only possible if there is a representative amount of repeat sales able to fit a model. The focus of this project will be on the repeat sales approach, but all three the approaches discussed will be analysed to prove that the repeat sales approach is the most accurate in developing a property price index for properties in South Africa. / Thesis (M.Sc. (Risk Analysis))--North-West University, Potchefstroom Campus, 2011.