由於運用特徵價格模型探討影響不動產價格之變數，國內外相關之文獻數量甚為豐富，但對於影響議價空間比率之變數，較少有研究者探討，由於議價空間比率影響賣方及買方之訂價或出價策略與對成交價格之預期，另對於估價人員採用市場比較法時，僅得待售案例時之情況調整亦有所幫助，故本研究試圖從蒐集相關不動產成交案例，探討有關影響其議價空間比率之變數。 因本研究之資料範圍鎖定成屋且透過仲介成交之案件，故透過與仲介經紀從業人員之訪談並與文獻回顧相關理論作相互印證，廣納可能之變數，並搜集台北市、縣成屋實際委託價格及交易資訊。將訪談蒐集所得之交易價格資料及變數，運用Excel 及SPSS統計軟體，透過敘述統計、相關係數分析、折線圖分析、特徵估價法之多元廻歸模型等方法，分析影響議價空間比率之因素，及其影響之程度。 實證結果發現：影響議價空間比率之顯著變數如下： （一）區位變數有：樹林、林口、新莊為正相關，議價空間比率顯著較高，大安區為負相關，議價空間比率相對較低。 （二）成交時間變數有：97年第四季因金融風暴，該季議價空間比率顯著較高。 （三）物件個別屬性變數有：是否1樓、屋齡、平均委託單價與議價空間比率為正相關，透天產品與議價空間比率為負相關，透天產品議價空間比率顯著較低。 （四）總體因素變數有：北市北縣拍賣移轉件數與議價空間比率為正相關，北縣市買賣移轉件數與議價空間比率為負相關。 本研究建議買賣交易人或投資者應針對交易標的所在區位、交易時間點、標的物個別條件以及總體指標需深入了解，賣方在訂價或買方在出價斡旋時，將更能提高交易成功之機率。物件位於相對偏遠地區，由於條件相對較差，賣方在開價上需預留較大議價空間，並有讓價準備，而買方可多收集相關成交資訊，以減少因資訊不充足而支付較高之價格貼水。 另外，當市場上發生重大事件導致房屋市場變動時，此時仲介角色更具挑戰性， 應提供賣方相關分析資訊，協助使其提早瞭解市場變動情況，避免損失加劇。對於一樓產品，買賣雙方價格認知差異較大，應提供相近條件之成交行情，若是店面或商用產品，可再提供租金收益資訊，易使雙方對於價格較有共識，並促進交易價格之合理性。 而不動產估價師執行台北縣、市之估價案件時，若採用市場比較法，收集之比較案例為待售尚未成交之物件，可參考各區位議價空間比率之平均數，再評估上述顯著變數之正負相關性，酌予上下調整，以增進待售價格情況調整之精確度。 / Although there are abundant sources of references regarding the use of Hedonic pricing models to study the relationship between real estate pricing variables and real estate price volatility, relatively few were dedicated to the research of price concession variables. Price concession variables determine sellers' asking prices and buyers' bid prices, or the expected deal price of a bid/ask strategy and even provide useful indications to real estate evaluators taking the market comparison approach when there are no actual deals to compare. Therefore, in this research we aimed to collect samples of actual real estate deals made to determine the variables that affect degrees of price concession by analyzing the degrees of price concession in proportion to bid/ask prices. In this research, we confined our area of study to completed constructions transacted through real estate agencies. Through interviews with real estate agents and reviews of past theoretical references, we attempted to gather all possible variables from the time buyers and sellers approach real estate agencies to the time a deal is made; we also gathered data of bid prices, asking prices and deal prices of completed constructions situated in the various administration districts within Taipei City and Taipei County. Interview results, pricing data and the possible variables we had identified were analyzed using Excel and SPSS; our statistical analysis included descriptive statistics, correlation analysis, line charts and multiple regression of the Hedonic pricing model. The purpose of our analyses was to determine factors that influence the degree of price concession as well as the extent of such influence. Our research results found the following variables that significantly influence the degree of price concession: (1) Location variable: Shulin, Linko and Hsinchuang districts are positively correlated, suggesting a higher degree of price concession; Daan district is negatively correlated, suggesting a lower degree of price concession. (2) Timing variable: The degree of price concession during the fourth quarter of 2008 was significantly higher because of the global financial crisis. (3) Object-specific variables: Whether the property is situated on the first floor and aging variables are positively correlated to the degree of price concession; whether the property is an independent house is negatively correlated to the degree of price concession, suggesting a lower degree of price concession for independent house properties. (4) Macro factors: The number of court auctions in Taipei City and County is positively correlated to the degree of price concession; the number of property sales in Taipei City and County are negatively correlated to the degree of price concession. Through this research, we advise that property buyers, sellers and investors should gain further insights into the location, timing, characteristics and the overall environment relating to the properties they wish to close deals for. These insights will help buyers and sellers set bid/ask prices that are more likely to close deals, thereby reducing the cost of prolonged negotiations. Properties located in remote areas are have a disadvantage; sellers should reserve more room for negotiation and be prepared to make price concessions, while buyers should gather more information related to the deal of similar properties to avoid paying higher premiums due to lack of information. Furthermore, the role of real estate agencies becomes more challenging in the occurrence of major events which cause volatility within the real estate market. Real estate agents should provide sellers the relevant data analysis to facilitate early anticipation of market changes, thereby preventing further losses. For properties located on the first floor, since there are relatively wider discrepancies between sellers' and buyers' expectations, real estate agents should provide more information related to the deals of similar properties to reconcile their differences. If the properties are for retail or commercial purposes, real estate agents may also provide information on rental or revenue to reconcile the understanding between buyers and sellers and give more rationality to deal prices. For real estate evaluators attempting to evaluate properties situated in Taipei City and County using the market comparison approach but lacking deal references, they may consider taking the average degree of price concession across all administrative districts and adjust upwards or downwards based on correlations to the above significant variables and produce a more accurate indicator for the properties pending sale.

Made available in DSpace on 2014-12-17T15:55:05Z (GMT). No. of bitstreams: 1 NaraGA_DISSERT.pdf: 1500404 bytes, checksum: 25c744f7a7ac2b02102cad56468c08e6 (MD5) Previous issue date: 2014-02-17 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / Amenities value provided by green areas, sea, river and natural landscapes are hardly perceived and incorporated on urban planning and development. In this work, distance and view to protected and non-protected green areas, sea and river were evaluated as to how they increase the housing prices in Natal. Hedonic pricing methods were used with linear models to estimate the marginal implicit value of environmental, residential and neighborhood features. Results on Chapter 1 demonstrate the view to the sea and protected natural areas were largely capitalized on housing prices, while non-protected natural areas didn t display such effect. Housing prices also increase when close to the sea or to parks entrance. However, housing prices fall when houses are near non-protected natural areas. When estates with sea view were excluded, the protected natural areas view and a longer distance to non-protected natural areas increased dwelling prices. Results on Chapter 2 point the sea view as an hedonic variable the contributes strongly to the property selling prices, even though not always as the greatest contributor; furthermore, the property proximity to Dunas Park or City of the Park entrance increases its price, as does closeness to Dunas Park, view to City of the Park or Dunas Park. On the other hand, selling prices diminish if properties are close to City of the Park or Morro do Careca. Results on this study confirm the hedonic pricing methods is an important intrument, capable of revealing to popullation the importance of enviromental amenities and can be used by public managers for creating public policies for conservation and restoration projects / O valor das amenidades fornecidas por ?reas verdes, o mar, o rio e a paisagem natural s?o dificilmente percebidas e incorporadas no planejamento e desenvolvimento urbano. Neste trabalho foram avaliadas como a dist?ncia e a vista para ?reas verdes urbanas protegidas, n?o protegidas, para o mar e o rio incrementam o valor de resid?ncias em Natal. Foi utilizada a metodologia de pre?os hed?nicos para estimar o valor impl?cito marginal de atributos ambientais, residenciais e urban?sticos atrav?s de modelos lineares. Os resultados do Cap?tulo 1 demonstram que a vista para o mar e para as ?reas naturais protegidas foram amplamente capitalizadas nos pre?os dos im?veis, enquanto que para as ?reas naturais n?o protegidas este efeito n?o foi observado. O pre?o do im?vel tamb?m aumenta se est? pr?ximo ao mar e a entrada de parques. No entanto, os pre?os das habita??es diminuem quando est?o pr?ximas as ?reas naturais n?o protegidas. Quando os im?veis com vista para o mar foram exclu?dos, tanto a vista para a ?rea natural protegida quanto uma maior dist?ncia da ?rea natural n?o protegida aumentaram o pre?o da propriedade. Os resultados do Cap?tulo 2 indicaram que a vista para o mar ? uma vari?vel hed?nica que contribui muito para o pre?o de venda do im?vel, embora nem sempre seja a que mais contribui; ainda, a proximidade do im?vel em rela??o ? entrada do Parque das Dunas ou do Parque da Cidade aumenta o seu pre?o, como tamb?m aumenta se est? pr?ximo ao Parque das Dunas e se tem vista para o Parque da Cidade ou para o Parque das Dunas. Por outro lado, os pre?os de venda diminuem se as propriedades est?o pr?ximas ao Parque da Cidade ou ao Morro do Careca. Os resultados deste estudo confirmam que a metodologia de pre?os hed?nicos ? um instrumento importante capaz de revelar ? popula??o a import?ncia das amenidades ambientais e pode ser utilizada por gestores p?blicos na cria??o de pol?ticas p?blicas para projetos de conserva??o e recupera??o do meio ambiente

Este estudo visa compreender a relação entre os atributos intrínsecos e extrínsecos do produto calça jeans e o seu preço no varejo, tendo como objetivo específico analisar a influência separadamente dos atributos intrínsecos e extrínsecos sobre os preços. Para tanto, utiliza-se da teoria de atributos proposta por Lancaster (1966) e dos métodos de preços hedônicos propostos por Rosen (1974), por meio dos quais é possível observar a importância dos pacotes de atributos intrínsecos e extrínsecos sobre os preços, bem como observar a constituição de pacotes de atributos para diferentes perfis econômicos de consumidores. Foram analisadas 12 categorias de atributos sendo 5 de atributos intrínsecos e outras 7 de atributos extrínsecos. A coleta de dados foi realizada por meio de observação e a pesquisa foi realizada no período de 01 de julho a 31 de julho de 2015 nos maiores shoppings centers e principais lojas de ruas de São Paulo. A partir dos dados coletados, foram realizadas regressão múltipla e a regressão quantílica. A regressão múltipla apresentou o R2 de 58%, nessa análise os principais atributos que influenciam são: loja premium, venda assistida, origem da loja, tamanho da loja (megaloja), tamanho da loja (ampla), lavagem destroyed, resina, modelo flare, lavagem dirty, localização da loja (rua ou shopping), complementos, modelo skinny insumos elastano e poliéster. A regressão quantílica proporciou a análise para 10% das calças mais caras e para os 10% das calças mais baratas. Para as calças mais caras o R2 é de 45% para as calças mais caras há mais atributos extrínsecos do que atributos do produto interferindo no preço, são eles: os insumos poliéster e elastano, lavagem e resinagem, origem da marca da loja, posicionamento da marca, venda assistida, localização da loja, cartão de crédito - private label (nesse caso influenciando negativamente), e tamanho da loja, todos extrínsecos ao produto, se mostraram relevantes para o processo de precificação das calças jeans mais caras observadas nesse estudo. Já para as calças mais baratas, com R2 de 27%, parece haver um equilíbrio entre o número de variáveis intrínsecas e extrínsecas que interferem no preço das calças jeans mais baratas, pois somente a modelagem (atributo intrínseco) e cartão private label (atributo extrínseco) parecem não interferir na precificação. Concluiu-se que há mais atributos extrínsecos que influenciam o preço da calça jeans no varejo. / This study aims to understand the relationship between intrinsic and extrinsic attributes of jeans and its retail price, with the specific objective to analyze the influence separately from intrinsic and extrinsic attributes on prices. To do so, it uses the attributes of theory proposed by Lancaster (1966) and hedonic pricing methods proposed by Rosen (1974), through which it is possible to see the importance of intrinsic and extrinsic attributes packages on prices and to observe the constitution attributes of economic packages for different consumer profiles. 12 categories of attributes, 5 of intrinsic attributes and other 7 extrinsic attributes were analyzed. Data collection was carried out through observation and the survey was conducted in the period from July, 1st to July, 31st, 2015 in major shopping malls and main streets of São Paulo stores. The collected data was analyzed through multiple regression and quantile regression. Multiple regression showed a R2 of 48%, according to this analysis the attributes that influence are: premium store, assisted sale, shop origin, size of the store (superstore), store size (large), destroyed wash, resin application, flare model, dirty wash, store location (street or shopping), accessories, skinny model spandex inputs and polyester. The quantile regression, pointed analysis for 10% of the most expensive jeans and for 10% of the cheapest jeans. For the most expensive pants, R2 is 45% the extrinsic attributes interfering in the price more than product attributes, they are: polyester inputs and spandex, washing and resin application, the origin for store brand, brand positioning, assisted sale, store location, credit card -private label (in this case presenting a negative influence) and size of the store, all extrinsic to the have shown to be relevant to the process of pricing of the most expensive jeans observed in this study. As for the cheapest pants, with R2 of 27% seems to be a balance between the number of intrinsic and extrinsic variables that affect the price of the cheapest jeans, modeling (intrinsic attribute) and private label (extrinsic attribute) do not seem to interfere in pricing. It was concluded that there are more extrinsic attributes that influence the jeans of the retail price.

O presente estudo mensura o impacto no preço dos atributos de qualidade nos tourinhos da raça Nelore comercializados em leilões por meio de uma metodologia específica, baseada na Teoria dos Preços Hedônicos. Para tanto, utilizou-se como amostra três leilões - 368 observações - de uma fazenda padrão, o Nelore Jandaia. Assim, os atributos dos animais que mais contribuíram para a formação dos preços, em um primeiro plano, foram: a qualidade genética como um todo, expressa através do Mérito Genético Total - MGT, e a qualidade fenotípica global, demonstrada pelo índice EPMURAS. Em um segundo plano, mais específico, agregaram mais valor aos jovens reprodutores características relacionadas à precocidade e fertilidade do lado genético a Diferença Esperada na Progênie - DEP para perímetro escrotal aos 365 dias (dpe365) e no lado fenotípico a nota de precocidade. Por exemplo, os animais com MGT excelente tiveram um prêmio médio de 22% a mais em relação aos considerados como bons, paralelamente os com EPMURAS excelente tiveram um prêmio de 11% em relação aos classificados como muito bons, ceteris paribus. Para cada ponto a mais na precocidade e na DEP dpe365 o valor dos animais comercializados aumenta em, respectivamente, 5% e 5,8%, ceteris paribus. Do exposto, pode-se concluir que se os pecuaristas dedicados ao melhoramento dos seus rebanhos privilegiarem em seus objetivos de seleção animais com excelentes atributos de fertilidade e precocidade receberam prêmios superiores por isso. Em outras palavras, focar a seleção em precocidade e fertilidade agrega valor aos animais. / This study measures the impact on the price of quality attributes in Nelore steer sold at auction by a particular methodology, based on the theory of hedonic prices. To this end, we used as a sample three auctions - 368 observations of a standard farm, Nelore Jandaia. Thus, the attributes of animals that contributed most to the price formation were the genetic quality as a whole, expressed through the Total Genetic Merit - MGT, and the overall phenotypic quality, as demonstrated by the index EPMURAS. In a second model, more specific, added more value to young breeding characteristics related to precocity and fertility - the genetic side of the Expected Progeny Difference - EPD for scrotal circumference at 365 days (dpe365) and on the phenotypic note of precocity. For example, animals with excellent MGT had an average premium of 22% more than for those considered as good, along with the excellent EPMURAS had a premium of 11% over rated as very good. For each point on precocity and DEP dpe365 the value of animals traded increases, respectively, 5% and 5.8%, ceteris paribus. From the above, we conclude that if the farmers devoted to the improvement of their herds give priority in their selection goals animals with excellent attributes of fertility and precocity will receive premium for it. In other words, focus the cattle selection on fertility and precocity adds value to animals.

Magister Economicae - MEcon / This study identifies the determinants of sheep prices for small-scale sheep farming households in two districts of the Eastern Cape, namely Amathole and Ukhahlamba (Joe Xabe). Output prices that small farm households receive for their sheep affect their incomes from agriculture (knowing that revenue is a product of quantity and price), which, in turn, influence their living standards. The study isolates three sets of determinants of price formation in local agricultural markets - structural drivers, institutional factors and livelihood shocks - to account for the variations in prices that smallholder farmers receive. Data were collected from 134 households that were selected using purpose sampling and preceded by key informant and focus groups interviews with actors along the sheep value chain. A questionnaire consisting of both open-ended and quantitative questions was used. The relationship between output price formation and clusters of determinants is a typical hedonic pricing framework, which is fitted using a backward stepwise econometric technique that is a widely used experimental tool to identify significant determinants. / South Africa

The aim of this diploma thesis is the estimation of the influence of green areas on real estate prices in Bratislava, SK. Being not a public good green areas are not market valuated which makes the decision about its size and placement in urban areas problematic. This thesis was written with an aim to evaluate the benefit of greenery and help future decision making concerning green urban areas in Bratislava. Theoretical part points out current situation of green urban areas in Bratislava and real estate market development. It also demonstrates some of the benefits coming from urban greenery and defines hedonic pricing method. Practical part is focused on greenery value estimation using HPM. It analyzes geografical data altogether with real estate data and based on five regression models using various groups of environmental variables estimates the impact of different types of greenery on the real estate prices in Bratislava.

Background: This study discusses the phenomenon of luxury goods as investment assets,focusing on luxury watches in particular. The rise of globalization and increased wealth,particularly among the middle and high-income groups in developing countries, hascreated a larger potential customer base for luxury items. This has led to an increasing interest in luxury goods as investment assets, including collectibles such as cars, art, andwine. The recent development of online niche marketplaces for luxury goods has enabledthe systematic collection of data, facilitating research on Veblen goods as alternativeinvestment assets. Therefore, it is interesting to analyze the financial performance ofinvestments in luxury watches as compared to traditional assets. Purpose: The purpose of this study is to analyze the comparative performance ofinvesting in luxury watches versus traditional assets such as equities and bonds. Methodology: This study collects data on luxury watch prices and characteristics. Thehedonic pricing method is used to regress the price of the watches on their characteristics.The regression results are used to analyze the price impact of the characteristics, as well asto create a watch price index. In order to evaluate the index performance, data is collectedfor the MSCI World Index and the Bloomberg U.S. Aggregate Bond Index. For all the indices, the financial metrics of the Sharpe ratio, Treynor ratio, CAPM, and Jensen’s alphaare calculated. Conclusion: This study suggests that luxury watches, with their wide price ranges and high resale value, have been a viable option for portfolio diversification during thestudied five-year period between 2018 and 2023. The watch index yields an averagereturn of 2.01 % and a cumulative return of 49.35 %, outperforming the MSCI World Indexwith average returns of 1.38 % and the Bloomberg U.S. Aggregate Bond Index with -0.01%, and cumulative returns of 31.90 % and -0.15 %, respectively. The watch index alsooutperforms the compared indices in terms of the financial metrics Sharpe ratio, Treynorratio, CAPM, and Jensen’s alpha. The results suggest that the most important valuedrivers for luxury watches are: Brand (Audemars Piguet, Patek Philippe, and VacheronConstantin), Features (Chronograph, tourbillon, and rotating bezel) and Case Material(bronze, rose gold, and yellow gold).

This paper aims to determine the value of the product based on the mathematical concept of Differential Privacy, by assessing the value of the business opportunities it enables and the value of the possible GDPR-fines it prevents. To delimit the scope of the research the analysis will focus on what the value of personal data is for companies within the mobility sector. Mobility is a cross-industrial sector consisting of companies within connectivity-technology, transportation, and automotive. The method used to assess the final value of anonymizing personal data, such as consumer data, using a DP-solution (meaning, an implementation of the theory) has consisted of both quantitative and qualitative analysis. The quantitative analysis aims to assess the ‘Cost of Risk’ for mobility companies that are exposed to personal integrity regulation due to data processing. To further conclude the true cost of the financial impact caused by getting fined for infringing on privacy regulation because of unlawful data processing is done through a complementary qualitative assessment. Lastly, the 'Opportunity Cost', or rather the cost of missed financial opportunities, is determined qualitatively for a case study company within Sweden’s mobility ecosystem to conclude the overall value of a DP-solution for a specific company. The final product of this research paper is to provide a framework assessing the total value, for specifically companies in the mobility sector, of implementing differential privacy solutions. / Syftet med denna uppsats är att fastställa värdet av anonymisering baserat på det matematiska konceptet Differential Privacy, genom att bedöma värdet av de affärsmöjligheter det skapar, samt värdet av de möjliga GDPR- böter det förhindrar. För att avgränsa studiens omfattning består analysen endast av att uppskatta dessa värden för företag inom mobilitetssektorn. Mobilitetssektorn är en tvärindustriell sektor som består av företag inom uppkoppling-, transport- och bilindustrin. Metoden som använts för att ta fram det slutliga värdet av att anonymisera persondata genom en differential privacy lösning, består både av en kvantitativ och en kvalitativ analys. Målet med den kvantitativa analysen är att estimera kostnadsrisken för företag inom mobilitetssektorn som exponeras mot GDPR-böter med avseende på dess datahantering. För att vidare ta reda på den totala finansiella inverkan av sådana böter, kompletteras analysen av en kvalitativ studie, som delvis omfattas av de finansiella möjligheterna ett företag går miste om i en sådan situation. Den kvalitativa analysen består också av en fallstudie av ett svenskt företag inom mobilitetssektorn, med målet att estimera värdet av de affärsmöjligheter som uppstår med hjälp av anonymisering av data. Slutligen är målet med denna uppsats att förse läsaren med att ramverk för att estimera det totala värdet av att implementera differential privacy lösningar i företag inom mobilitetssektorn.

This study utilized hedonic pricing models and regression analysis to evaluate if, and to whatextent distance to certain logistics nodes impact the transactional value of warehouses andlogistics properties. The study is conducted in Sweden, using data collected from transactionsthat have been conducted in the three largest cities in Sweden between the years 2016 - 2022.The logistical nodes that are tested within the study are the biggest seaports, airports andhighways in the big city regions. Furthermore, the distances to the central business districts ineach respective city are included in the analysis as well. The distances are collected bymeasuring the shortest road travel routes using Google Maps. Aside from the aforementionedlocational attributes that were tested, physical variables and dummy variables were includedin the model to investigate their effect on the transaction value of the logistics properties.Furthermore, these were included to prove the robustness of the proposed models. The results from the study indicate that all the logistical nodes tested are significant for thevalue of the industrial properties. Proximity to seaport, central business district and highwayshave a negative gradient, indicating a higher value of the logistics properties if in proximityto these nodes. While the distance to the airport is significant for the value of the logisticsproperties, the proximity to the airport does not induce a higher transaction value. The studyconcluded that the distance to seaport had an effect of -0,50%, CBD -0,83%, Highway-0,62% and Airport 0,47% per kilometer of change. This study aims to contribute to theexpanding literature on the topic of optimal warehouse location and to inform propertyowners of what attributes to consider when constructing logistic properties. / Denna studie använder hedoniska prismodeller och regressionsanalys för att utvärdera om,och i vilken utsträckning avstånd till logistiknoderna hamn, flygplats och motorväg påverkartransaktionsvärdet för lager och logistikfastigheter. Studien genomfördes i Sverige med hjälpav data insamlad från transaktioner som har genomförts i de tre största städerna i Sverigemellan åren 2016 - 2022. Transaktionsdatan samlades in genom Datscha. Vidare utreds ävenhuruvida avstånd till central business districts har en inverkan på transaktionspriset.Avstånden mäts genom att mäta de kortaste transportsträckorna mellan fastighet och nod.Avstånden i fråga har samlats in med hjälp av Google Maps. Resultaten från studien tyder påatt alla logistiknoder som testats har betydelse för fastighetens värde. Närhet till hamn, CBDoch motorvägar har en negativ koefficient, vilket indikerar ett högre transaktionsvärde påfastigheten i de fall de är belägna i närheten dessa noder. Avståndet till flygplatsen har ocksåbetydelse för värdet på fastigheterna. Denna variabel har dock en positiv koefficient, vilketindikerar att närhet till denna logistiknod har en negativ inverkan på transaktionspriset.Slutsatsen från analysen indikerar att avståndet till hamn hade en effekt på -0,50%, CBD-0,83%, motorväg -0,62% och flygplats 0,47% per kilometer av förändring. Denna studiesyftar till att bidra till den växande litteraturen om ämnet optimal lagerlokalisering och attinformera fastighetsägare om vilka attribut som ska beaktas när de bygger logistikfastigheter.

Property valuation is a critical concept for a variety of applications in the real estate market such as transactions, taxes, investments, and mortgages. However, there is little consistency in which method is the best for estimating the property value. This paper aims at investigating and comparing the differences in the Stockholm residential property valuation results among parametric hedonic pricing models (HPM) including linear and log-linear regression models, and Random Forest (RF) as the machine learning algorithm. The data consists of 114,293 arm-length transactions of the tenant-owned apartment between January 2005 to December 2014. The same variables are applied on both the HPM regression models and RF. There are two adopted techniques for data splitting into training and testing datasets, randomly splits and splitting based on the transaction years. These datasets will be used to train and test all the models. The performance evaluation and measurement of each model will base on four performance indicators: R-squared, MSE, RMSE, and MAPE.   The results from both data splitting circumstances have shown that the accuracy of random forest is the highest among the regression models. The discussions point out the causes of the models’ performance changes once applied on different datasets obtained from different data splitting techniques. Limitations are also pointed out at the end of the study for future improvements. / Fastighetsvärdering är ett kritiskt koncept för en mängd olika applikationer på fastighetsmarknaden som transaktioner, skatter, investeringar och inteckningar. Det finns dock liten konsekvens i vilken metod som är bäst för att uppskatta fastighetsvärdet. Denna uppsats syftar till att undersöka och jämföra skillnaderna i Stockholms fastighetsvärderingsresultat bland parametriska hedoniska prissättningsmodeller (HPM) inklusive linjära och log-linjära regressionsmodeller, och Random Forest (RF) som maskininlärningsalgoritm. Uppgifterna består av 114,293 armlängds-transaktioner för hyresgästen från januari 2005 till december 2014. Samma variabler tillämpas på både HPM-regressionsmodellerna och RF. Det finns två antagna tekniker för uppdelning av data i utbildning och testning av datamängder: slumpmässig uppdelning och uppdelning baserat på transaktionsåren. Dessa datamängder kommer att användas för att träna och testa alla modeller. Prestationsutvärderingen och mätningen av varje modell baseras på fyra resultatindikatorer: R-kvadrat, MSE, RMSE och MAPE. Resultaten från båda uppdelningsförhållandena har visat att noggrannheten hos slumpmässig skog är den högsta bland regressionsmodellerna. Diskussionerna pekar på orsakerna till modellernas prestandaförändringar när de tillämpats på olika datamängder erhållna från olika datasplittringstekniker. Begränsningar påpekas också i slutet av studien för framtida förbättringar.