none

none

This study use the daily stock price of the companies simultaneously listed in China and Hong-Kong to study whether there exists a stable linkage between the stock markets in China and in Hong-Kong and whether any structural break happened. The sampling period is from July 1st, 2003 to July 31st, 2007. We apply Johansen¡¦s cointegration test and Hansen¡¦s instability test to investigate whether the prices of A shares and H shares are cointegrated. We also apply Chow test and Quandt-Andrews test to study the potential structural break caused by the change of China¡¦s exchange policy. Main results are following: (1) Johansen¡¦s cointegration tests report that the stock prices of 18 companies (out of 29 companies) are cointegrated. (2) Hansen¡¦s instability tests report more companies¡¦ stock prices are cointegrated. (3) Chow tests reports that the relation between stock prices of A shares and H shares may has a structural break in 20 companies when RMB starts to appreciate. (4) The stock prices of some companies, whose stock prices were not cointegrated during the full sampling period, were cointegrated after structural break. Compared to previous literature, we find that the link between the stock markets in China and Hong-Kong become stronger as the reform of China¡¦s financial market is deeper.

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.

This thesis presents a comparison for modeling and forecasting Chinese futures market of copper and aluminum with single time series and multivariate time series under linear restrictions. For single time series, data transformation for stationary purpose has been tested and performed before ARIMA model was built. For multivariate time series, co-integration rank test has been performed and included before VECM model was built. Based on selected models, the forecasting shows multivariate time series analysis has a better result than single time series, which indicates utilizing the relationships among the series can improve the accuracy of time series forecasting.

On the Canadian Prairies, canola is a main source for biodiesel production and wheat is the primary feedstock for bioethanol production. To raise biofuel production requires a movement of resources and land away from food and grain crops, which would cause food to become scarcer and increase its price. This paper determines the impact of more biofuels production on the food industry. It considers the simultaneous estimation of share equations from both revenue function and distance function. Econometric results exploit the non-stationary nature of the data and the correlations among shares between primal and dual models are exploited by cointegration techniques. Johansen’s maximum likelihood estimator is applied to 1971-2007 data from Manitoba, Alberta and Saskatchewan. Morishima elasticity estimates indicate high long run substitutions among crops (wheat, feed grains and canola). A rise in the production of biofuel crops could cause food prices to increase, both for meat and bread.

This paper provides methods to select pairs potentially profitable within the frame of statistical arbitrage. We employ a cointegration approach on pairwise combinations of five large energy companies listed on the New York Stock Exchange for the period 27th September 2012 to 22nd April 2014. We find one cointegrated pair, for which we further investigate both short and long run dynamics. A vector-error correction model is constructed, supporting a long run relationship between the two stocks, which is also supported by the mean-reverting characteristic of a stationary linear combination of the stocks. Impulse response functions and variance decomposition are also studied to further describe the interrelation of the stocks, supporting a unidirectional causality between the stocks.

Thesis (Ph. D.)--University of California, San Diego, 2000. / Vita. Includes bibliographical references.

Thesis (Ph. D.)--University of California, San Diego, 1997. / Vita. Includes bibliographical references.

Thesis (Ph. D.)--Ohio State University, 2006. / Available online via OhioLINK's ETD Center; full text release delayed at author's request until 2009 Sep 19