本文包含關於估計風險與動態資產配置的兩篇研究。第一篇研究主要就當須估計的投資組合其投入參數具有高維度特質的觀點下，探究因忽略不確定性通膨而對資產配置過程中帶來的估計風險。此研究基於多重群組架構下所發展出的新投資決策法則，能夠確實地評價不確定性通膨對資產報酬的影響性，並在應用於建構大規模投資組合時，能有效減少進行最適化投資決策過程中所需的演算時間與成本。而將此模型應用於建構全球ETFs投資組合的實證結果則進一步顯示，若在均值變異數架構下，因建構大型投資組合時須估計高維度投入參數而伴隨有大量估計風險時，參數估計方式建議結合採用貝氏估計方法來估算資產報酬的一階與二階動差，其所對應得到的投資組合樣本外績效會比直接採用歷史樣本動差來得佳。此實證結果亦隱含：在均值變異數架構下，穩定的參數估計值比起最新且即時的參數估計資訊對於投資組合的績效來得有益。同時，若當投入參數的樣本估計值波動很大時，增加放空限制亦能有利投組樣本外績效。 第二篇文章則主要處理當處於對數常態證券市場下時，投資組合報酬率不具有有限動差並導致無法在均值變異數架構下發展出最適化封閉解時的難題。本研究示範此時可透過漸近方法的應用，有效發展出在具有放空限制下，考量了估計風險後的簡單投資組合配置法則，並且展示如何將其應用至實務上的資產配置過程以建構全球投資組合。本文的數值範例與實證模擬結果皆顯示，估計風險的存在對於最適投資組合的選擇有實質的影響，無估計風險下得出的最適投資組合，不必然是存有估計風險下的最適投資組合。此外，實證模擬結果亦證明，當存有估計風險時，本文所發展的簡單法則，能使建構出的投資組合具有較佳的樣本外績效表現。 / This dissertation consists of two essays on dynamic asset allocation with regard to dealing with estimation risk as being in different uncertainties in the mean-variance framework. The first essay concerns estimation errors from disregarding uncertain inflation in terms of the need in estimating high-dimensional input parameters for portfolio optimization. This study presents simplified and valid criteria referred to as the EGP-IMG model based on the multi-group framework to be capable of pricing inflation risk in a world of uncertainty. Empirical studies shows the proposed model indeed provides a smart way in picking worldwide ETFs that serves well to reduce the amount of costs and time in constructing a global portfolio when facing a large number of investment products. The effect of Bayesian estimation on improving estimation risk as the decision maker is subject to history sample moments for input parameters estimations is meanwhile examined. The results indicate portfolios implementing the Stein estimation and shrinkage estimators offer better performance compared with those applying the history sample estimators. It implicitly demonstrates that yielding stable estimates for means and covariances is more critical in the MV framework than getting the newest up-to-date parameters estimates for improving portfolio performance. Though short-sales constraints intuitively should hurt, they do practically contribute to uplift portfolio performance as being subject to volatile estimates of returns moments. The second essay undertakes the difficulty that the probability distribution of a portfolio's returns may not have finite moments in a lognormal-securities market, and thus leads to the arduous problem in solving the closed-form solutions for the optimal portfolio under the mean-variance framework. As being in a lognormal-securities market, this study systematically delivers a simple rule in optimization with regard to the presence of estimation risk. The simple rule is derived accordingly by means of asymptotic properties when short sales are not allowed. The consequently numerical example specifies the detailed procedures and shows that the optimal portfolio with estimation risk is not equivalent to that ignoring the existence of estimation risk. In addition, the portfolio performance based on the proposed simple rule is examined to present a better out-of-sample portfolio performance relative to the benchmarks.

對於商業保險公司和政府單位而言，死亡率的改善和未來死亡率的預估一直是一大重要議題。特別是對於退休金相關的社會保險、勞退或是商業年金、壽險等等，如何找尋一個準確的預估模式對未來的死亡率改善情況進行預測，並釐訂合理的保費及提列適當的準備金，是對於一個保險制度能否永續經營的重要因素。過去所使用的配適方法，大多僅以單一群體的過去資料輔助未來的預測，例如 Li and Carter (1992)所提出的 Lee-Carter Model，或是 Bell (1997)使用主成分分析法 (Principal Component Analysis, PCA)等僅針對單一群體本身變數進行分析之方式。然而綜觀全球死亡率改善趨勢，可發現國與國間、組與祖間雖有不同，但仍具備共同的趨勢。因此在考慮未來的死亡率配適方面，應加入組與組間的共同因子 (common factors) 進行考量。 Li and Lee (2005)曾提出 Augmented Lee-Carter Model，即對原本的Lee-Carter Model進行修正，加入共同因素項，並且得到更好的預測效果。 本文則採用考慮共同因子之主成分分析原理建構多重群體死亡率模型，即透過主成分分析法，同時考慮不同群體間的死亡率，並以台灣男性和女性1970年至2010年的死亡率資料，做為兩個子群體進行分析。本文使用之主成分分析法模式，和 Lee-Carter Model (Li and Carter, 1992) 和 Augmented Lee-Carter Model (Li and Lee, 2005)，以MAPE法對個別的預測能力進行分析，並得出採用PCA的模式，在預測男性短年期(5年)內的預估能力屬精確(MAPE 介於10%~20%之間)，然而在長期預估下容易失準，且所有使用的模型，在配適台灣資料時皆發生無法準確預估嬰幼兒期(0~3歲)和老年期(80歲以上)之情形。本文並以所有模型預估之死亡率計算保險公司之準備金與保費提列，並與第五回經驗生命表進行比較。 / For governments and life insurance companies, mortality rates are one of the key factors in determining premiums and reserves. Ignoring or miscalculating mortality rates might have negative influences in pricing. However, most of the mortality models do not consider the common trends between groups. In this article, we try to construct the mortality structure which considering common trends of multi-groups populations with principal component analysis (PCA) method. We choose 9 factors to set up our model and fit with the actual data in Taiwan’s gender mortality. We also compare the Lee-Carter Model (Lee and Carter, 1992) and the augmented Lee-Carter Model (Li and Hardy, 2012) with our common factors PCA model, and we find that the PCA model has the least MAPE than other model in five years forecasting in both genders. After finishing basic analysis, we use the mortality data of Taiwan (1970 to 2010) from human mortality database to construct the life expectancy model. We adopt the same criteria to choose the components we need. We also compare the level premium and reserves by different forecasting mortality rates. All of the models indicate life insurance companies to provide higher reserves and level premium than using the 5th TSO experience mortality rare. We will do following research by using company-specific data to construct unique life expectancy model.

Opportunities that we have in today's world are sharply evolving, and the world is changing all together with these changes. This development is noticeably observed within the topic of global movement of (not only) population, which has changed fundamentally, both economically, politically and socially. Today's so much diversified form of migration, which has lost its transparency it used to has, is a very up to date and debated topic currently almost all over the world. Because of high importance of the topic "migration" it is often subject of research and number of surveys. One of the most examined area within the topic migration is attitudes of people towards immigration and immigrant, oftentimes together with investigating cause leading to particular attitude. Due to the international reach of the topic, these attitudes are often subject of cross-national research or national research, which, however, use data from international surveys. There is a clear disparity across European states in these attitudes towards immigration and, above all, the immigrants themselves. Given this nature of cross-national surveys measuring attitudes towards immigrants, it is important to focus on the measurement quality, which is becoming increasingly complex in the perspective of international research. It is...