published_or_final_version / Business Administration / Master / Master of Business Administration

published_or_final_version / abstract / China Development Studies / Master / Master of Arts

published_or_final_version / Business Administration / Master / Master of Business Administration

With the implementation of the pilot Emission Trading Schemes (ETSs) in China since 2013, there emerges a new opportunity for investing in Chinese green technology (greentech) projects. Apart from trading the international CERs (Certified Emissions Reductions), investors nowadays can also trade the CCERs (Chinese Certified Emissions Reductions) in the domestic carbon market. However, the pricing of CCERs is different from that of CERs due to the distinct climate policies in China, thus making the investment decisions in Chinese greentech projects a complicated problem. This study is, to our knowledge, the first attempt to evaluate greentech projects under uncertain climate policies in developing countries like China. To identify the investment environment of Chinese greentech projects, a qualitative research on the development of climate policies and greentech market is first conducted. Based on the study of international climate polices and carbon markets, the pricing mechanisms of carbon assets (carbon allowances and carbon offsets) are investigated. Furthermore, China’s climate polices, including the energy policies and emission reduction policies, are analysed in detail. In addition, both the administrative and economic instruments used in China’s climate policies are investigated. Then, business opportunities and challenges in greentech market are investigated. It is shown that there is substantial demand for greentech projects, and the uncertainties embedded a Chinese greentech project in power sector mainly come from the CCER price and electricity price. To integrate the different stochastic price processes, a real-options-based greentech investment (ROGI) model is developed to derive the investment options value and the optimal investment timing. Considering the possible interventions of the government, the CCER price is modelled as mean-reverting process with jump and cap-floor. In addition, an equivalent electricity price is developed and also described by a mean-reverting process. To solve the ROGI model with various uncertainties involved, a least-square Monte Carlo (LSM) approach is developed. The proposed LSM algorithm is built within the dynamic programming framework. It is shown that the optimal investment strategy can be characterized by a continuation region. The proposed ROGI model is verified by a real case of wind power project investment in China. Sensitive analysis is conducted to examine the effects of the model parameters on the investment decisions. Different climate policy scenarios are then tested, including carbon price jump, carbon price cap and floor, and carbon tax. Several interesting findings are concluded from the results analysis in this study. First, it is found that investors are relatively insensitive to the jump in the CCER price, the volatility of the CCER price, or the mean-reverting speed. Second, the CCER price floor set by the government can effectively encourage greentech investments while the price cap is not a major concern of investors. Finally, the long-term growth rate of the CCER price as well as the carbon tax rate can also plays a significant role in investment decisions. / published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy

China’s stock markets have become the second largest in the world after that of the United States. Both the Chinese institutional setting and the behaviors of the populous Chinese investors and listed firms provide novel opportunities to explore the classical theories in the field of economics and finance. Using two natural experiments, this thesis attempts to shed new light on these theories. The local bias puzzle was originally proposed from the analysis of investors’ investment portfolios. In the first essay, I test and confirm the hypothesis that local bias has already existed in investor attention subconsciously regardless of their investment. In contrast to literature which focuses on investment accounts, I examine local bias in investor attention by analyzing investor messages posted on China’s Internet stock message boards. I find that individual investors pay more attention to the stocks of local companies. This finding is strong and robust to local-bias proxy variables. By examining factors that affect investor attention local bias, I find that local bias is particularly strong in underdeveloped regions, for SOEs, for small-investor base and low-turnover stocks, and for stocks with name indicating locality. Furthermore, distance plays a significant role: the marginal effect of local bias is much stronger for distances within 500 kilometers. All these results are consistent with my explanation that local bias is affected by factors which can attract investors’ attention. Thus, investment local bias is the natural consequence of investor attention local bias, and I attribute the local bias puzzle to limited investor attention. Chinese stock market has plunged into an unlocking flood of non-tradable shares since June 2006. This radical transition provides a unique natural experimental setting to ascertain earnings management incentives. In the second essay, I explore whether earnings management behavior exists in listed Chinese firms during the unlocking process. I find that non-tradable shareholders opportunistically manipulate earnings upward to offset price pressures for subsequent selling. Firms have higher levels of accruals when unlocking incentive is higher. Furthermore, actual selling incentive is higher in firms which have higher levels of accruals. The results document a novel case that equity incentives give rise to the incidence of earnings management. / published_or_final_version / Economics and Finance / Doctoral / Doctor of Philosophy

Thesis (Ph. D.)--Drexel University, 2005. / Vita. Includes bibliographical references (leaves 74-85).

published_or_final_version / Business Administration / Master / Master of Business Administration

published_or_final_version / Business Administration / Master / Master of Business Administration

published_or_final_version / Urban Studies / Master / Master of Social Sciences

published_or_final_version / Real Estate and Construction / Master / Master of Science in Real Estate and Construction Development