The modelling of financial markets have attracted a lot of interest during the recent years. Fluctuations in prices are examples of random phenomena and therefore financial mathematics is to a large extent a part of mathematical statistics.     Examples of stochastic models used in the modelling of financial markets are regression models trying to capture relations between different economic factors, time series models that can model the evolution in time of various economic quantities. Stochastic calculus is an important instrument in the pricing of derivatives and more generally in the theory of capital markets. The department of mathematics offers courses that treats these areas.     Studies in financial mathematics means studies in design and analysis of models for random phenomena and studies of a wide range of mathematical, probabilistic and statistical techniques. Although the focus lies on understanding and solving problems that appear on financial markets, the broad knowledge accuired from studies in financial mathematics is applicable in a variety of different fields.     Here is a pdf-file "on becoming a quant". It is written for British circumstances, but it can be of interest anyway. Courses SF2701 Financial Mathematics, 7.5 credits, period 4, level D SF2940 Probability Theory, 7.5 credits, period 1, level D SF2943 Time Series Analysis, 7.5 credits, period 4, level D SF2950 Applied mathematical statistics, 7.5 credits, period 3, level D SF2955 Computer Intensive Methods in Mathematical Statistics 7.5 credits, period 4, level D SF2970 Martingales and Stochastic Integrals, 6 credits, period 2, level D SF2972 Game Theory 7,5 credits, period 3, level D (given every second year, next time in 2015) SF2942 Portfolio Theory and Risk Management 7.5 credits, period 1, level D SF2975 Financial Derivatives 7.5 credits, period 3, level D SF2980 Risk Management 7.5 credits, period 2, level D Optional courses in insurance mathematics given at Stockholm University fit nicely into the studies. See this link for further details. A suitable optional course for students in Financial Mathematics is ME2031 – Behavioral Finance given by the School of Industrial Engineering and Management. It is also suitable to supplement studies in Financial Mathematics with studies in micro and macro economics. Suitable optional courses for students in Financial Mathematics are courses in computational mathematics and courses in optimization and systems theory as well as other courses in mathematics at the advanced level. More information about courses in mathematical statistics can be found at our webpage on undergraduate studies. In order to write a master thesis in Financial Mathematics you must take the courses SF2940 Probability Theory SF2942 Portfolio Theory and Risk Management SF2943 Time Series Analysis or SF2950 Applied Mathematical Statistics SF2701 Financial Mathematics Furthermore, you must accuire special qualification within a field, which can be Financial Derivatives: SF2970 Martingales and Stochastic Integrals and SF2975 Financial Derivatives or Risk Management: SF2980 Risk Management. KTH's rules for master theses (There is an "in English" link near the bottom of that page.) Contact: Jimmy Olsson, jimmyolkth.se, tel: 790 7201 Contacts with the financial industry      Seminars called "Finans­kontakt" in cooperations between KTH and Algorithmica Research AB are arranged on a yearly basis. The aim is to provide a link between academia and the financial industry and it is a good opportunity for students to get contacts in the financial industry. The seminars are talks on financial problems and applied mathematics with applications to real-world problems in the area of finance. The following persons supervise master theses in Financial Mathematics Boualem Djehiche. email: boualem@math.kth.se, Tel: 790 7875 Henrik Hult. email: hult@kth.se Tel. 790 6911 Timo Koski. email: tjtkoskikth.se Tel. 790 7134 Camilla Landén email: camilla@math.kth.se Tel: 790 8466 Tatjana Pavlenko email: pavlenko@math.kth.se Tel. 790 8466 Anders Szepessy (Numerisk analys). email: szepessy@nada.kth.se Tel. 7907494