In this thesis will the question of how to construct implied volatility surfaces in a robust and arbitrage free way be investigated. To be able to know if the solutions are arbitrage free was an initial investigation about arbitrage in volatility surfaces made. From this investigation where two comprehensive theorems found. These theorems came from Roper in \cite{Roper2010}. Based on these where then two applicable arbitrage tests created. These tests came to be very important tools in the remaining thesis.The most reasonable classes of models for modeling the implied volatility surface where then investigated. It was concluded that the classes that seemed to have the best potential where the stochastic volatility models and the parametric representation models. The choice between these two classes where concluded to be based on a trade-off between simplicity and quality of the result. If it where possible to make the parametric representation models improve its result the best applicable choice would be that class. For the remaining thesis was it therefore decided to investigate this class. The parametric representation model that was chosen to be investigated where the SVI parametrization family since it seemed to have the most potential outside of its already strong foundation.The SVI parametrization family is diveded into 3 parametrizations, the raw SVI parametrization, the SSVI parametrization and the eSSVI parametrization. It was concluded that the raw SVI parametrization even though it gives very good market fits, was not robust enough to be chosen. This ment that the raw SVI parametrization would in most cases generate arbitrage in its surfaces. The SSVI model was concluded to be a very strong model compared to the raw SVI, since it was able to generate completely arbitrage free solutions with good enough results. The eSSVI is an extended parametrization of the SSVI with purpose to improve its short maturity results. It was concluded to give small improvements but with the trade of making the optimization procedure harder. It was therefore concluded that the SSVI parametrization might be the better application.To try to improve the results of the SSVI parametrization was a complementary procedure developed which got named the calibrated SSVI method. This method compared to the eSSVI parametrization would not change the parametrization but instead focusing on calibrating the initial fit that the SSVI generated. This method would heavily improve the initial fit of the SSVI surface but was less robust since it generated harder cases for the interpolation and extrapolation. / I det här examensarbetet undersöks frågan om hur man bör modellera implied volatilitetsytor på ett robust och arbitragefritt sätt. För att kunna veta om lösningarna är arbigtragefria börjades arbetet med en undersökning inom arbitrageområdet. De mest heltäckande resultatet som hittades var två theorem av Roper i \cite{Roper2010}. Baserat på dessa theorem kunde två applicerbara arbitragetester skapas som sedan kom att bli en av hörnstenarna i detta arbete. Genom att undersöka de modellklasser som verkade vara de bästa inom området valdes den parametriseringsbeskrivande modellklassen.  I denna klass valdes sedan SVI parametriseringsfamiljen för vidare undersökning eftersom det verkade vara den familj av modeller som hade störst potential att uppnå jämnvikt mellan enkel applikation samt bra resultat.  För den klassiska SVI modellen i SVI familjen drogs slutsatsen att modellen inte var tillräcklig för att kunna rekommenderas. Detta berodde på att SVI modellen i princip alltid genererade lösningar med arbitrage i. SVI modellen genererar dock väldigt bra lösningar mot marknadsdatan enskilt och kan därför vara ett bra alternativ om man bara ska modellera ett implied volatilitetssmil. SSVI modellen ansågs däremot vara ett väldigt bra alternativ. SSVI modellen genererar komplett aribragefria lösningar men har samtidigt rimligt bra marknadspassning.  För att försöka förbättra resultaten från SSVI modellen, var en kompleterande metod kallad den kalibrerade SSVI metoden skapad. Denna metod kom att förbättra marknadspassningen som SSVI modellen genererade men som resultat kom robustheten att sjunka, då interpoleringen och extrapoleringen blev svårare att genomföra arbitragefritt.