The study investigates the presence of the momentum effect in the Swedish stock market by utilizing both cross-sectional introduced by Jegadeesh and Titman (1993) and time-series momentum introduced by Moskowtozt et al. (2011). The period of analysis is between 1998 to 2022. Additionally, the study compares the performance of these two momentum strategies by creating portfolios with varying lookback and holding periods. However, the primary focus is on the strategy with a 12-month lookback and a 1-month holding period. The results indicate that both momentum strategies generated positive returns over the analyzed period. However, time-series momentum was more effective for longer lookback periods, while cross-sectional momentum was more effective for shorter periods. Nevertheless, none of the findings for either momentum strategy were statistically significant in the Swedish stock market. / Syftet med denna studie är att studera lönsamheten för momentumstrategier på den svenska marknaden för perioden januari 1998 till december 2022, med hjälp av de cross-sectional och time-series momentum som introducerades av Jegadeesh och Titman (1993) och Moskowitz et al. 2011), respektive. Resultaten visar att momentumstrategier har positiv avkastning på den svenska marknaden, men resultaten är inte statistiskt signifikanta. Under den tidsperiod under vilken momentumstrategier testades visade cross-sectional momentum bättre resultat under kortare utvärderingsperioder jämfört med time-series momentum, som presterade bättre under längre utvärderingsperioder. Det är dock värt att notera att även om momentumportföljers positiva avkastning inte är statistiskt signifikanta, kan de fortfarande vara fördelaktiga för avkastningssökande investerare. Dessutom fann studien att den positiva avkastningen inte enbart beror på momentumfaktorn utan kan också bero på portföljens exponering mot Fama French SMB-faktorn.

Paper [I] tests the success rate of trades and the returns of the Opening Range Breakout (ORB) strategy. A trader that trades on the ORB strategy seeks to identify large intraday price movements and trades only when the price moves beyond some predetermined threshold. We present an ORB strategy based on normally distributed returns to identify such days and find that our ORB trading strategy result in significantly higher returns than zero as well as an increased success rate in relation to a fair game. The characteristics of such an approach over conventional statistical tests is that it involves the joint distribution of low, high, open and close over a given time horizon. Paper [II] measures the returns of a popular day trading strategy, the Opening Range Breakout strategy (ORB), across volatility states. We calculate the average daily returns of the ORB strategy for each volatility state of the underlying asset when applied on long time series of crude oil and S&P 500 futures contracts. We find an average difference in returns between the highest and the lowest volatility state of around 200 basis points per day for crude oil, and of around 150 basis points per day for the S&P 500. This finding suggests that the success in day trading can depend to a large extent on the volatility of the underlying asset. Paper [III] performs empirical analysis on short-term and long-term Commodity Trading Advisor (CTA) strategies regarding their exposures to unanticipated risk shocks. Previous research documents that CTA strategies offer diversification opportunities during equity market crisis situations when evaluated as a group, but do not separate between short-term and long-term CTA strategies. When separating between short-term and long-term CTA strategies, this paper finds that only short-term CTA strategies provide a significant, and consistent, exposure to unanticipated risk shocks while long-term CTA strategies do not. For the purpose of diversifying a portfolio during equity market crisis situations, this result suggests that an investor should allocate to short-term CTA strategies rather than to long-term CTA strategies.