本論文運用CUSUM、CUSUMSQ與虛擬變數探討台灣股票市場的結構性改變，與各種GARCH模型對台灣股票市場報酬加以解釋。實證結果如下： 1.CUSUM與CUSUMSQ檢定有相當大的差距，這在理論上是不合理的。 2.CUSUMSQ檢定出的結構改變虛擬變數有部份無法掌握。 3.EGARCH模型對金融股解釋力並無較佳，但在營建股上則得到較佳的估計，但與經濟直覺相異的地方在正面干擾對股市的影響較負面為大。 4.GARCH-in-mean模型在金融股上完全無法解釋，即風險與報酬的抵換關係，無法得到印證，但在營建股上以EGARCH為基礎的模型此點可得到印證。 5.以t分配為基礎GARCH模型在概度函數值與AIC、SBC上有較佳的解釋力，但在殘差的峰態檢定上則出現不一致。而此問題在雙變量GARCH模型上出現概度函數值與殘差峰態檢定出現相當大的不一致性。

<p>This work consists of four articles concerning Gaussian probability laws with stochastic means and variances. The first paper introduces a new way of approximating the probability distribution of a function of random variables. This is done with a Gaussian probability law with stochastic mean and variance. In the second paper an extension of the Generalized Hyperbolic class of probability distributions is presented. The third paper introduces, using a Gaussian probability law with stochastic mean and variance, a GARCH type stochastic process with skewed innovations. </p><p>In the fourth paper a Lévy process with second order stochastic volatility is presented, option pricing under such a process is also considered.</p>

Thesis (Ph.D. (Risk Management))--North-West University, Potchefstroom Campus, 2008.

Diss. Stockholm : Handelshögsk.

This work consists of four articles concerning Gaussian probability laws with stochastic means and variances. The first paper introduces a new way of approximating the probability distribution of a function of random variables. This is done with a Gaussian probability law with stochastic mean and variance. In the second paper an extension of the Generalized Hyperbolic class of probability distributions is presented. The third paper introduces, using a Gaussian probability law with stochastic mean and variance, a GARCH type stochastic process with skewed innovations. In the fourth paper a Lévy process with second order stochastic volatility is presented, option pricing under such a process is also considered.

The main purpose of this thesis is to assess the potential of emerging stock markets and commodity markets in attracting the attention of international investors who utilize various portfolio diversification strategies to reduce the cumulative risk of their portfolio. A successful portfolio diversification strategy requires low correlation among financial markets. However, it is now well documented that the correlations among financial markets in developed countries are very high and hence the benefits of international portfolio diversification among these markets have been very limited. This fact suggests that investors should look for alternative markets whose correlations with developed markets are low (or even negative if possible) and which have high growth potentials. In this thesis, two emerging countries&#039 / stock markets and two commodity markets are considered as alternative markets. Among emerging countries, Turkey and China are chosen due to their promising growth performance since the mid-2000s. As commodity markets, agricultural commodity and precious metal markets are selected because of the outstanding performance of the former and the &quot / safe harbor&quot / property of the latter. The structures and properties of dependence between these markets and stock markets in developed countries are examined by modeling the conditional correlation in the dynamic conditional correlation framework. The results reveal that upward trend hypothesis is valid for almost all correlations among market pairs and market volatility plays significant role in time varying structures of correlations.

After a long-time preparation, CSI 300 index futures has made a milestone in the financial market in China in the 16 of April, 2010. In order to know what kind of impact will bring to stock market after the appearance of stock index future, the study discusses volatility and volume separately. On one hand, the study applies Modified Levene and GJR-GARCH as the empirical model, and the result indicates that stock return fluctuation is a short-term phenomenon. However, the result shows that the stock return volatility has no difference in the long-run. Furthermore, it not only reduces the asymmetric return fluctuation from good and bad news cause but improve the information efficiency in the spot market after the introduction of the stock index futures. On the other hand, the study applies multiple regression model and panel model to examine the crowding-out effect and the volume difference after the stock index futures enters the market. First, there is no crowding-out effect in the stock market. Second, both the trading volume of the constituent and non-constituent stocks increase after the introduction of the stock index futures, whereas the level of increasing trading volume of the constituent stocks is larger than non- constituent stocks are.

This study presents our attempt to examine the linkages and to investigate the linkage of stock price indexes among Taiwan, China and its major trading countries. Our empirical analysis employs daily data on stock price indexes over the period of January 2, 2000 to May 10, 2010. The total number of observations is about 2500. This study employ a sequence of time-series methodologies, including unit root test, cointegration test, vector error correction model, Granger causality test, Criterion, autocorrelation test, heteroscedasticity test, GARCH and Bi-GARCH. The findings of this study as follows. First, after first difference, every stock price indexes series all became stationary. Second, we found there has no long-run interrelationship among these stock markets. Third, we found that Taiwan¡¦s stock market exits leading role to China¡¦s stock market, but other countries¡¦ stock market lead Taiwan¡¦s stock market. For China, the stock market of United States, Japan, Taiwan and Hong Kong has a leading role to China¡¦s stock market. Only the rela-tionship between South Korea and China¡¦s stock market is independent. Forth, the result of autocorrelation test and ARCH test indicates that the influence of stock price indexes of major trading countries to Taiwan and China¡¦s stock price index has changed over time. Finally, the result of study indicates that every stock market can forecast its future trend by using its past stock data and investor can use the past stock data of stock market of major trading countries to forecast Taiwan and China¡¦s stock market.

In this dissertation, several essays in the field of bio-security are presented. The estimation of the probability of an FMD outbreak by type and location of premises is important for decision making. In Essay I, we estimate and predict the probability/risk of an FMD outbreak spreading to the various premises in the study area. We first used a Poisson regression model with adjustment dispersion associated with random simulation results from the AusSpead model to estimate the parameters of the model. Our estimation and prediction show that large cattle loss could be concentrated in three counties-Deaf Smith, Parmer, and Castro. These results are based on approximately 70% of the feedlots with over 10,000 cattle located in the three counties previously mentioned. In Essay II, our objective is to determine the best mitigation strategies in minimizing animal loss based on AusSpead simulation model. We tested 15 mitigation strategies by using multiple comparison. The results show that the best mitigation strategies for all four scenarios are regular surveillance, slaughter of the infected animals, and early detection. We then used the Mixed Integer Programming to estimate costs of disposing of animal carcasses and transportation. Results show that the unit disposal cost will vary with carcass scale and the unit transportation cost also varies with the distribution of the infected premises and disposal locations. FMD seems to have varying impacts on equity markets. In Essay III, we studied returns at three different levels of the stock market. We determined results in a structural break, and then estimated the impact of the announcement of confirmed cases of FMD disease on the volatility of stock market returns by using a GARCH-Mean model. Our results show that the structure break occurs on the day with the largest number of confirmed cases for meat product firms rather than the day of the first confirmed case. We found that the conditional volatilities over the FMD period are higher than those over the sample period. The announcement of confirmed cases had the largest marginal impact on meat products. Investors may always consider maintaining a portfolio consisting of index funds or hedge funds.

An recent finding shows that heart rate data possess self-similar property, which is characterized by a parameter H, as well as a long range dependent parameter d. We estimate H by the EBP(Embedded Branching Process) method to derive the fractional parameter d in the first part. The heart rate and R-R interval data are found to have high differencing parameter(d=0.8 ~0.9) and against the normality assumption. Thus the heart rate and R-R interval data are first fractionally differenced of order 0.5 to achieve stationarity. In the second part, we analyze the RR-interval data on the physionet and obtain the long range parameters. After fractionally differencing 0.5 order, the EBP method is adapted to estimate the long range parameter d. The EWMA and EWRMS control charts of the I(d) processes are constructed to monitor the heart rate mean level and variability, respectively for the 18 RR-interval data sets from the physionet. For the EWMA control chart the out of control percentages are chosen to the nominal probability. However, the out of control percentages are affected by the skewness and kurtosis of the process distribution for the EWRMS control carts. Generally speaking, the I(d)-EWMA and I(d)-EWRMS control charts provide a proper monitor system for heart rate mean level and variability.