The market for decentralised financial instruments, more commonly known as cryptocurrencies, has gained momentum over the past recent years and the application areas are many. Modern portfolio theory has for years demonstrated its applicability to traditional assets, such as equities and other instruments, but to some extent omitted the application of mathematical portfolio theory with respect for cryptocurrencies. This master's thesis aims to evaluate both traditional and DeFi assets from a modern optimization perspective. The focus area includes whichallocation structures that minimize the risk-adjusted return. The optimizations strategies are based on the risk measures, standard deviation, Conditional Value at Risk and First linear partial moment. The method has its structure in different scenarios where the outcome is optimized for traditional assets, DeFi assets and a hybrid set of these. The input data for the optimization methodology is based on weekly and adjusted price data for the assets. The output variables are weight-distribution, risk levels, return, maximum drawdown and graphic visualizations. Our results show that there is a value in incorporating parts of assets from the decentralized financial world in a portfolio provided that the risk-adjusted ratio increases through but through both higher returns and higher potential risk. These results are based on incorporation of certain parts of the new landscape where more established assets such as Bitcoin, Ethereum etc. have proven to perform well while other assets that are less traded shows a significantly worse result relative to risk. / Marknaden för decentraliserade finansiella instrument, mer känt som kryptovalutor, har tagit sin fart de senaste åren och applikationsområdena är många. Modern portföljteori har i åratal visat sin tillämpbarhet på traditionella tillgångar, såsom aktier och andra instrument, men till en viss grad utelämnat applicering av matematisk portföljteori med avseende på kryptovalutor. Denna master uppsats ämnar till att utvärdera både traditionella och DeFi tillgångar ur ett modernt optimerings-perspektiv. Fokusområdet innefattar vilka allokeringsstrukturer som minimerar den risk justerade avkastningen. Optimeringsstrategierna baseras på riskmåtten, standardavvikelse, Conditional Value at Risk samt First linear partial moment. Metodiken har sin grundstruktur i olika scenarion där man studerat optimerade utfall för traditionella tillgångar, DeFi tillgångar samt en hybrid uppsättning av dessa.  Ingångsdatan till optimeringsmetodiken baseras på veckovis och justerad prisdata för tillgångarna. Utgångsvariablerna är allkokeringsfördelning, risknivåer, avkastning, maximum drawdown samt grafiska visualiseringar.  Våra resultat visar att det finns det finns ett värde i att omstrukturera sin portfölj med delar av tillgångar från den decentraliserade finansvärlden under förutsättningarna att riskjusterade kvoten ökar genom men genom både högre avkastning och högre potentiell risk. Dessa resultat bygger på inkorporering av vissa delar av de nya landskapet där mer etablerade tillgångar som Bitcoin, Ethereum etc. har visat sig prestera bra medans andra tillgångar som är mindre omsatta visar ett avsevärt sämre resultat relativt risk.

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).