How one can get a big fish in the stock market is an intriguing question with no answer. With the assumption of market inefficiency, we design technical trading strategies based on pairs trading which was well known by Wall Street to capture the big fish. A pair is composed of a security over anther, and we attempt to make the pair market neutral. We test the profitability of several trading rules with daily data during the period from Jan.1, 2002 to Mar.31, 2005. We also test the one price law of ADRs, during the sample period from 1996 Jul. to 2005 Apr. We find that the performance of the Moving Average Model is better. In particular, in the Moving Average Model the top 10% trading pairs make an average lucrative 2.07 % return in K5-10 model, 2.95 % return in K5-15 model, and 3.55 % in K5-20 model.

<p>Pairs trading is a relatively new trading strategy, the strategy has only been used during a couple of decades. A study made on the American stock market has shown that the strat-egy has generated a positive result. The purpose of this thesis is to investigate if pairs trad-ing has been able to create a positive result on the Swedish stock market during the time period of 1995-2004.</p><p>The data required for this thesis was collected from Stockholm stock exchange and is ad-justed for splits and issues.</p><p>The pairs trading strategy involves two stages – identification of pairs and trading signals. The pairs were identified during a period of 12 months. During this period a return index was constructed and a correlation matrix was calculated for each period. Out of this corre-lation matrix were then ten pairs with the highest correlation selected. These pairs were then used in the next six-month trading period.</p><p>The study show that the strategy generated a positive result for the time period examined 1995-2004. More than 60 percent of all positions had a positive development and contrib-uted to a positive result. The other positions had a negative development.</p> / <p>Pairs trading är en relativt ny handelstrategi som endast har använts under ett par årtionden. En studie gjord på den amerikanska aktiemarknaden har visat att strategin har genererat ett positivt resultat. Syftet med denna uppsats är att undersöka om pairs trading kunnat skapa ett positivt resultat på den svenska aktiemarknaden under tidsperioden 1995-2004.</p><p>För att kunna genomföra studien, har daglig aktiedata inhämtats från Stockholms fondbörs. Datan som används är justerad för splittar och emissioner.</p><p>Pairs trading strategin involverar två steg – identifiera aktiepar och handelssignaler. Aktieparen identifierades under en tolv månaders period. Då konstruerades ett avkastningsindex och en korrelationsmatris beräknades för varje period. Ur denna korrelationsmatris valdes sedan de tio aktiepar som hade högst korrelation. Dessa aktiepar användes sedan under nästföljande handelsperiod som pågick under sex månader.</p><p>För den undersökta perioden, 1995-2004, uppvisade studien att pairs trading strategin har genererat ett positivt resultat. Mer än 60 procent av alla positioner har haft en positiv utveckling och bidragit till det positiva resultatet. Övriga positioner har haft en negativ utveckling.</p>

Pairs trading is a relatively new trading strategy, the strategy has only been used during a couple of decades. A study made on the American stock market has shown that the strat-egy has generated a positive result. The purpose of this thesis is to investigate if pairs trad-ing has been able to create a positive result on the Swedish stock market during the time period of 1995-2004. The data required for this thesis was collected from Stockholm stock exchange and is ad-justed for splits and issues. The pairs trading strategy involves two stages – identification of pairs and trading signals. The pairs were identified during a period of 12 months. During this period a return index was constructed and a correlation matrix was calculated for each period. Out of this corre-lation matrix were then ten pairs with the highest correlation selected. These pairs were then used in the next six-month trading period. The study show that the strategy generated a positive result for the time period examined 1995-2004. More than 60 percent of all positions had a positive development and contrib-uted to a positive result. The other positions had a negative development. / Pairs trading är en relativt ny handelstrategi som endast har använts under ett par årtionden. En studie gjord på den amerikanska aktiemarknaden har visat att strategin har genererat ett positivt resultat. Syftet med denna uppsats är att undersöka om pairs trading kunnat skapa ett positivt resultat på den svenska aktiemarknaden under tidsperioden 1995-2004. För att kunna genomföra studien, har daglig aktiedata inhämtats från Stockholms fondbörs. Datan som används är justerad för splittar och emissioner. Pairs trading strategin involverar två steg – identifiera aktiepar och handelssignaler. Aktieparen identifierades under en tolv månaders period. Då konstruerades ett avkastningsindex och en korrelationsmatris beräknades för varje period. Ur denna korrelationsmatris valdes sedan de tio aktiepar som hade högst korrelation. Dessa aktiepar användes sedan under nästföljande handelsperiod som pågick under sex månader. För den undersökta perioden, 1995-2004, uppvisade studien att pairs trading strategin har genererat ett positivt resultat. Mer än 60 procent av alla positioner har haft en positiv utveckling och bidragit till det positiva resultatet. Övriga positioner har haft en negativ utveckling.

Pairs trading has been a popular statistical arbitrage strategy among hedge funds. One important research field in pairs trading is to maximize the return under differential constraints and assumptions. In this thesis, we develop two models to optimize the performance of pairs trading. In the static model, we find the analytic solution of optimal thresholds for pairs trading to maximize the long run profit per unit time. Comparison is made between the optimal rules we developed and the common practice. To overcome limitations of the static model, we extend our research to dynamic pairs trading, where a continuous time Markov chain is used to model the change of parameters. Our objective is to maximize the expected return in the finite horizon under the Constant Relative Risk Aversion (CRRA) utility. Numerical examples are presented to illustrate the impact of price limits, risk aversion rate and regime switching on consumers' investment decision.

This thesis investigates the long-run stability of Cointegrated pairs in the Swedish Equity Market. Stability is evaluated by estimating pairs in an in-sample period then rolling the win- dow forward. A Pairs Trading strategy is then applied to the estimated pairs and traded out-of-sample. The relationships are found to diminish over time and most break o. Negative compound annual growth rates are obtained for the period. However there are enough lasting cointegrating relationships for the strategy to be applicable but the returns are highly dependent on the complexity of the trading rules.

This paper assesses the aspect of market neutrality for a pairs trading strategy built on cointegration. This was conducted by evaluating the strategy?s performance during a negative market environment, 2007-06-01 to 2008-12-30, and a positive market environment, 2013-05-31 to 2014-12-30, for the stocks listed in the OMXS30 index. The results indicate market neutrality and that profitability of pairs trading is higher in prolonged periods of turbulence.

Since its’ invention at Morgan Stanley in 1987 pairs trading has grown to be one of the most common and most researched strategies for market neutral returns. The strategy identifies stocks, or other financial securities, that historically has co-moved and forms a trading pair. If the price relation is broken a short position is entered in the overperforming stock and a long in the underperforming. The positions are closed when the spread returns to the long-term relation. A pairs trading portfolio is formed by combining a number of pairs. To detect adequate pairs different types of data analysis has been used. The most common way has been to study historical price data with different statistical models such as the distance method. Gatev et al (2006) used this method and provided the most extensive research on the subject and this study will follow the standards set by that article and add new interesting factors. This is done through an investigation on how the analysis can be improved by using the stocks fundamental data, e.g. P/E, P/B, leverage, industry classification. This data is used to set up restrictions and Lasso models (type of regression) to optimize the trading portfolio and achieve higher returns. All models have been back-tested using S&amp;P 500 stocks between 2001-04-01 and 2015-04-01 with portfolios changed every six months. The most important finding of the study is that restricting stocks to have close P/E-ratios combined with traditional price series analysis increases returns. The most conservative measure gives annual returns of 3.99% to 4.98% depending on the trading rules for this portfolio. The returns are significantly (5%-level) higher than those obtained by the traditional distance method. Considerable variations in return levels is shown to be created when capital commitments are changed and trading rules, transaction costs and restrictions on unique portfolio stocks are implemented. Further research regarding how analysis of P/E-ratios can improve pairs trading is suggested. The thesis has been written independently without an external client and studied an area that the author found interesting.

No description available.

The aim of this research is to investigate the long-run co-integrating relationships in the Asian markets. Our research focuses on 4 areas; pair trading, out-of-sample forecasting, testing the unbiased forward exchange rate hypothesis and testing the expectation hypothesis of the term structure of interest rates. The introduction is provided in chapter one. In chapter two, we develop a pairs trading strategy using individual stocks listed in the Stock Exchange of Thailand. Engle and Granger approach is used to identify the potential pairs that are cointegrated. The results show that pairs trading strategy is profitable in this market. Chapter three examines the forecasting performance of the error correction model on daily share price series from the Stock Exchange of Thailand. The disequilibrium term is classified into “correct” and “mix” sign based on Alexander (2008)’s criterion; the results indicate that the error correction component can help to improve the predictability in the long run. Chapter four tests the unbiased forward rate hypothesis of 11 Asian exchange rates using linear conventional regression, ECM and logistic smooth transition regression with the forward premium as the transition variable. Out-of-sample forecasting results also suggest that inferior forecasting performance could be obtained as a result of using linear models. In chapter five, we investigate the expectation hypothesis of the term structure of interest rate for four Asian countries. We employ linear models and nonlinear approaches that allow to capture asymmetric and symmetric adjustments. The result also indicates that the term structure can be better modeled by means of LSTR models. The forecasting exercise also confirms these findings.

Thesis (M. Phil.)--University of Hong Kong, 2008. / Includes bibliographical references (leaf 99-108) Also available in print.