In retrospect, telecommunication technology and services have seen incessant renovation and development. The wave of liberalization is also the inexorable trend in the global telecommunications industry, the telecommunications industry in Taiwan can not be excluded itself from the trend. The telecommunications industry in Taiwan has been opened by degrees and sought to establish a fair competitive environment. In the meantime, there are several important changes no matter in facets of regulatory regimes, industrial structure, technology, or market demand, etc. The environment of telecommunications industry became more volatile than the monopoly one's. We extend the opinion of Noam (2006) who observed the long-term upturn and downturn in the American telecommunications industry and concluded that that volatility and cyclicality will be an inherent part of the telecommunication sector in the future. First, in our thesis we explore the cyclical behavior of Taiwan telecommunications industry. As the turning point of the telecommunications industry may be obscure, we adopt a Markov Regime-Switching model with two regimes representing contraction and expansion. This nonlinear, two states, regime-switching model shows that Taiwan telecommunications industry has suffered from the cyclic fluctuation since the liberalization had been followed out. We focus on the mobile phone industry thereafter in this study. Since three telecommunication-related laws passed in 1996, the mobile phone industry is the first industry implemented the liberalization policy. In the process of the mobile phone industry's evolution, the carriers in this industry all experience the rapid growth in the mobile phone penetration rate and the fierce competition. Hence, to identify the main explanatory factors of the mobile phone industry fluctuation and cycles we introduce an 11-variable vector autoregressive (VAR) model. The empirical results confirm that the mobile phone industry' output can be influenced by five factors mainly including the macroeconomic status, demand, network effect, relative equipment import price, and output price, and furthermore, the impetus of the liberalization policy and the progress of the technology also play an important role beyond the five main factors in terms of the separate carriers' analysis.

In this thesis, the regime dependent mean and abnormal returns are studied to examine whether socially responsible mutual funds have a different performance from traditional mutual funds, since there may be different patterns in the economy. Five economic factors - stock returns, treasury yield spread, credit spread, economic confidence and building permits - are used to identify the market regimes, which are determined as bear and bull markets. The regime-dependent abnormal returns are calculated with a regime-switching Fama & French three factor asset-pricing model. The empirical results show that socially responsible mutual funds have statistically higher mean return than non-socially responsible mutual funds in both bear and bull markets. However, using the measurement of the abnormal returns, socially responsible mutual funds statistically underperform non-socially responsible mutual funds in bull market, while the performance of the two types of funds are not statistically differentiable in the bear market.

In order to catch up the international trend, ¡§Expensing employee bonus¡¨ has been implemented in Taiwan since year 2008. Hence, all the cost concerning employees¡¦ bonuses have been recorded as expense in the income statement and recognized by fair market value. Since the company decides total amount of employees¡¦ bonuses after authorized by the board and annual general meeting, it can distribute the proportion of cash and stock bonuses. As the result of calculating the stock bonus by stock¡¦s fair value, employees gain much less stocks than before, which lessen the encouragement effect. Therefore, enterprises begin to increase the standard salary of employee or proportion of cash bonus. This study collects the data from the fourth quarter of year 1989 to the third quarter of 2009, and chooses the Taiwan Weighted Stock Index and the stock prices of listed electronic firms in Taiwan. Using the Markov Regime Switching Model as the research method, and add the macroeconomic and financial variables to separate the stock price into two regimes- recession and expansion regime. This research is in the employee¡¦s shoes, and to study what stock incentives strategies the company should adopt under the required expensing of employee stock bonus. The empirical results are summarized as follows: 1.Under the expansion regime, if the company¡¦s stock price was affected by both macroeconomic and financial variables, it will more likely rise further, which leads to the large gap between two regimes. For example: Cyberlink, Acer and Mediatec, which stock price gaps are over ten dollars. 2.According to the two arguments of this study: the company with long duration of expansion regime and is influenced by macroeconomic and financial variables should adopt the strategies based on stock bonus. Therefore, according to the empirical results, the study suggests that Acer is the suitable company to do the strategies.

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In order to get maximum profit, investors start to high attention on risk management after financial crisis in 2008. Therefore, risk management and predict become more and more complex. This paper mainly focuses on two risks, including non-systematic risk and credit risk. After financial crisis, countries pay more attention on credit risk, and now because of Europe debt crisis, investors and governments are also concerned with the messages about credit rating which are published by Credit Rating Agency. Besides credit risk, the firm¡¦s specific risk (i.e. non-systematic risk) is also more important than before. Recent empirical studies find that the stock is not on affected by systematic risk, but also affected by non-systematic risk. According to Kuo and Lu (2005), this thesis uses two models: Moody¡¦s KMV credit model and Markov regime switching model to estimate credit risk and non-systematic risk. The period is from January 2002 to November 2010. Testing samples are data from constituent stocks of the Taiwan 50. The purpose of this paper is researching the relationship between credit risk and non-systematic risk. The empirical results show that there is the positive relationship between non-systematic risk and credit risk. And among different industries, non-systematic risk or credit risk also shows the significant differences. For plastic industry and communications network industry, there is lower credit risk. However, for electronics industry and financial industry, there is higher credit risk. The study also found that even in the same industry, each company will face different risk level.

Since reformed of banking structure in China, banks have been gradually developed their operation system. Moreover, the restructure in commercial bank after joined WTO had established China¡¦s banks performance and international reputation. Since 2007, many large commercial banks have strength its risk management based on the commitments made by China Banking Regulatory Commission (CBRC) to follow the New Basel Capital Accord. When the global banking industry is devastated by global financial crisis (GFC) during 2008, China¡¦s banks are less affected by GFC. In addition, the capital scale and revenues performance were thrived during GFC. Therefore, it shows that banks in China had improved the resilience ability during financial crisis. However, being originated in China¡¦s loose monetary policy and economic stimulus package after GFC, investors worried that domestic banks might bear high risks. Notably, the risk is specific risk from each bank instead of system risk. This study employs Markov regime-switching model to examine 14 China banks¡¦ stock prices. The empirical evidence supports our hypothesis that behavior of China banks¡¦ stock prices has confronted structural change after GFC. Furthermore, this research presents that unsystematic risks from each bank were significantly decreased after GFC. It indicates that investors are too pessimistic on the banks in China might suffer high risk after government interventions.

This study tires to find out how a firm¡¦s advertising and customer satisfaction influence firms¡¦ abnormal return and we uses the abnormal return (i.e. Jensne¡¦s £\) as the proxy of firm¡¦s shareholder value. We expect firms¡¦ advertising and customer satisfaction will have a positive impact on abnormal return while having a negative impact on firms¡¦ risk. In addition, we also consider under different market state whether advertising and customer satisfaction have an asymmetric effect. Compare with Carhart (1997) four factor model, this paper also takes the factor of VIX into account, and we use Markov regime switching model to recognize bull market and bear market because it can help us get a more accurate estimation. We choose the Generalized method of moments (GMM) to estimate the impact of advertising and customer satisfaction on shareholder value and discuss that whether advertising and customer satisfaction are able to lift up shareholder value or not. The outcome shows that advertising doesn¡¦t have significantly positive impact on firms¡¦ abnormal return under bull market and bear market. However, customer satisfaction has a significantly positive relationship with firms¡¦ abnormal return under bull market and bear market. And we find that if firms maintain the level of customer satisfaction under bear market, it will be more efficiently to lift up firms¡¦ abnormal return rather than spending more money on advertising.

This dissertation investigates the pricing behaviors of two major energy commodities, U.S. natural gas and crude oil, using times series models. It examines the relationships between U.S. natural gas price variations and changes in market fundamentals within a two-state Markov-switching framework. It is found that the regime-switching model does a better forecasting job in general than the linear fundamental model without regime-switching framework, especially in the case of 1-step-ahead forecast. Studies are conducted of the dynamics between crude oil price and U.S. dollar exchange rates. Empirical tests are applied to both full sample (1986—2010) and subsample (2002—2010) data. It is found that causality runs in both directions between the oil and the dollar. Meanwhile, a theoretical 5-country partial dynamic portfolio model is constructed to explain the dynamics between oil and dollar with special attention to the roles of China and Russia. It is shown that emergence of China‘s economy enhances the linkage between oil and dollar due to China's foreign exchange policy. Further research is dedicated to the role of speculation in crude oil and natural gas markets. First a literature review on theory of speculation is conducted. Empirical studies on speculation in commodity markets are surveyed, with special focus on energy commodity market. To test the theory that speculation may affect commodity prices by exaggerating the signals sent by market fundamentals, this essay utilizes the forecast errors from the first essay to investigate the forecasting ability of speculators' net long positions in the market. Limited evidence is provided to support the bubble theory in U.S. natural gas market. In conclusion, this dissertation explores both fundamentals and speculators' roles in the U.S. natural gas and global crude oil markets. It is found that market fundamentals are the major driving forces for the two energy commodities price booms seen during the past several years.

This thesis examines stock price bubbles in the Stock Exchange of Thailand (SET) from its establishment in April 1975 until December 2012 using regime-switching bubble models, on the main aggregated market index, called the SET Index, and several disaggregated stock indices by industrial sector. The results suggest some evidence of bubble-like behaviour in these indices, most especially when a structural break is included at July 1997, the date when Thailand switched to adopting a managed floating exchange rate system. Given the limitations of published stock price indices in Thailand a new, consistent index was computed the K-NI. The econometric test results using this new index indicate strong evidence of stock price bubbles in several industrial sectors and at least some evidence of bubbles in all industry groups in the SET. Finally, the standard model is extended to study the transmission of bubbles between industry groups. The results indicate some levels of contagion in the Technology sector, as well as, in several other industry groups, while the Resources sector seems to be relatively isolated.

This thesis investigates the application of Hidden Markov Models (HMMs) to model financial volatility-regimes and presents a parameter learning approach using real-world data. Although HMMs as regime-switching models are established, empirical studies regarding the parameter estimation of such models remain limited. We address this issue by creating a systematic approach (algorithm) for parameter learning using Python programming and the hmmlearn library. The algorithm works by initializing a wide range of random parameter values for an HMM and maximizing the log-likelihood of an observation sequence, obtained from market data, using expectation-maximization; the optimal number of volatility regimes for the HMM is determined using information criterion. By training models on historical market and volatility index data, we found that a discrete model is favored for volatility modeling and option pricing due to its low complexity and high customizability, and a Gaussian model is favored for asset allocation and price simulation due to its ability to model market regimes. However, practical applications of these models were not researched, and thus, require further studies to test and calibrate.