1952年Markowitz 提出平均數－變異數投資組合模型（Mean-Variance Model，簡稱MV 模型）後，開創了投資組合理論的先河，他認為風險與報酬是影響資產配置的兩大因素，其中Markowitz在估計共變異數矩陣時，使用樣本共變異數矩陣模型（Sample Covariance Model）做運算。雖然MV 模型具權威性，但仍存在估計誤差的問題，因此許多共變異數矩陣的估計方法應運而生，包括Litterman and Winklemann（1998）的高盛衰退率共變異數矩陣模型以及Ledoit and Wolf（2003）的單一指數濃縮估計法。本文比較各種共變異數矩陣的效率前緣（efficient frontier）；並採用全域最小變異組合（Global Minimum Variance Point），檢驗樣本共變異數矩陣模型、高盛衰退率共變異數矩陣模型及單一指數濃縮估計法所建構的投資組合，其績效是否優於市值加權的台灣50指數；且以滾動視窗（rolling window）方式，比較三種方法績效之異同優劣。本研究實證結果顯示三種方法相對於大盤均有較佳表現，各方法間則以單一指數濃縮估計法表現較佳。 / Markowitz indicated Mean-Variance Model and initiated the portfolio theory in 1952. He proved that risk and return are two important components to impact on asset allocation, and used sample covariance model to calculate covariance matrix. However, MV model exists estimation error. Therefore, many covariance matrix methods was proposed including Goldman Sachs decay rate covariance matrix model of Litterman and Winklemann（1998）, and shrinkage to single-index covariance matrix method of Ledoit and Wolf（2003）. This study compares the efficient frontier build by different covariance matrix methods. Also, this study adopts global minimum portfolio and rolling window to discuss performance of portfolio constructed by these three methods. The conclusion is that the performance of portfolio constructed by these three covariance matrix methods is better than market index, and shrinkage to single-index covariance matrix is the best method to construct portfolio.

本研究經過分析台灣股市中三大法人的持股率與買賣超對於公司財務變數與市場變數的的關係，藉由法人的持股選擇觀點，進而組成具有法人選股特性的投資組合，並驗證其是否具有較佳的績效表現與是否具有擊敗大盤的能力。實證結果發現，外資偏向投資於較大報酬波動率與規模的公司，以及較低負債比率與股利殖利率的公司；投信具有偏好較高的股利殖利率、股東權益報酬率、移動平均報酬率之標準差與規模的公司，以及淨價市值比較低的公司；自營商喜歡較高的負債比率、淨值市價比、移動平均報酬率與規模的公司，以及報酬波動率較低的公司。在驗證經由法人的投資特性組成之投資組合表現中，發現投信之投資組合雖具有較高的平均報酬率，但是考量風險因子後，自營商的績效表現較佳，而且都具有擊敗大盤的績效表現。 / The study analyzed the relationship between Taiwanese institutional investors’ shareholding ratio or net buy-and-sell and the company's financial variables and market variables. Using the result of regression to compose a portfolio with the characteristics of institutional investors, and verification whether it has a better performance than the stock market index. The empirical results show that foreign investors tend to invest in the company with larger volatility and size, and also lower debt ratio and dividend yield; Investment trust investors with a preference for high dividend yields, return on equity, the long-term volatility and size of the company, and tend to invest in lower book-to-market ratio of the company; Dealers like high debt ratio, book-to-market ratio, size and momentum, and also preference for the company of lower volatility. The performance of the portfolio with institutional investors’ characteristics, we found that the investment trust's portfolio had highest average rate of return, but after consideration of risk factors, dealers had better performance. Both of the portfolio beat the stock market index’s performance.

本篇論文主要在外匯市場建立市場投資組合、利差交易投資組合與動能交易投資組合，探討透過不同情境適當改變投資組合比重配置，是否能夠顯著提升交易策略的報酬表現。 以1999年1月至2015年10月為樣本期間，根據28個國家外匯市場資料建構市場投資組合、利差交易投資組合與動能交易投資組合等，之後根據三種投資組合報酬情況透過馬可夫情境轉換模型區分成三種情境。按三種情境的各種投資組合超額報酬表現，再利用馬可維茲的平均數-變異數投資組合模型配置各情境下各項交易的比重，再依據計算出的預期情境與相對應比重進行投資。其結果顯示在樣本期間內，本篇論文的交易策略相較於外匯市場投資組合、利差交易投資組合與動能交易組合有較佳的投資表現。 在樣本外測試部分，採用自2012年中開始的連續情境二資料進行分析。報酬方面，在其他交易型態呈現負報酬較多情況下，就本文交易策略而言，投資者隨時根據其各種交易平均報酬與共變異數進行交易比重配置，適時放空交易策略或投資無風險資產，產生正報酬。但從標準差可以推斷投資者面對未來的不確定，在整個樣本外期間歷時的34個月當中標準差亦無法有效降低，說明了投資者面對下一期總體環境的高不確定性。 / In this thesis, we mainly investigate whether it could improve the performance of currency portfolio by adjusting weights among carry trade, momentum and market return in foreign exchange market under different kinds of regimes. Based on a sample of 28 market currencies, we form three kinds of transactions in our portfolio, including carry trade, momentum, and market return. Under Markov switching model, we divide the sample period into three regimes, and then determine weights among carry trade, momentum and market return by parameters of each re-gime using Markowitz mean-variance analysis. Finally, we invest different weights among three transactions according to each expected regime. We find the result that although the return of the strategy is just a little higher than the carry trade, the risk is much lower compared to other transactions. In our out-of-sample testing, we analyze the performance by using the data of the regime two which begins September, 2012. With the respect to the return, most of other risky transactions have negative return, but we get positive return by adjusting the long position and short position according to the result of the mean-variance anal-ysis. However, we can not effectively reduce risk by using the strategy, and in the meantime it can explain the high uncertainty investors face toward the next period.

近年來我國產業受全球經濟競爭激烈以及中國低廉生產成本等因素影響，外移情形嚴重，甚而造成國內工業區土地閒置及開發單位資金積壓問題，因此政府為解決上開問題及鼓勵廠商投資以帶動景氣復甦，乃貸款投資取得工業區土地，推出「工業區土地租金優惠調整措施」(○○六六八八優惠出租方案)，以提供廠商承租設廠使用。然如何在有限貸款額度內，提升政府資金運用效率，使能在不增加或減少政府財政負擔前提下，達到擴大出租方案資金規模、提振國家經濟以及償還開發單位墊付之開發費用等效益，從而引發本文以不動產證券化方式針對上述議題進行研究之動機。 　　本研究以我國不動證券化制度為基礎，經由相關文獻回顧歸納整理、指標評點分析法、現金流量分析法及不動產證券化證券設計分析方法，從我國工業不動產證券化投資組合選取、證券化前後現金流量及證券設計模擬分析等面向，進行深入探討，經實證結果顯示，透過不動產證券化之財務工具運用，確實能夠改善投資組合財務結構，並達到提升政府資金運用效率，擴大優惠出租方案規模，以減輕政府財政負擔等目標。

面對市場未來趨勢的不確定性，投資者可以運用「投資組合保險」的概念，既能保障原本所投資的資產價值，又可以參與市場上漲時的獲利。本研究以類神經網路來研究證券市場的現象，一方面是已經有許多類神經網路在財務分析上的研究成果，另一方面是其具有學習以及預測的能力。 本研究首先探討投資組合保險策略，接著再比較投資組合保險策略在不同市況下的績效表現，隨後提出兩個階段的研究架構，經過設計與建置，以類神經網路模型進行對大盤未來漲跌型態的模擬預測，並利用預測的結果，輔助投資組合保險策略的決策，最後並將研究結果與大盤績效做綜合分析比較。 本研究的資料採取自台灣證券集中交易市場，期間為1991年1月3日至2002年12月31日，共3306個交易日，取大盤每日交易之歷史資料，經過處理後建立資料庫。類神經網路模型具有預測未來大盤漲跌區間的能力，在本研究所提出的漲跌區間劃分方式上，其預測正確率達到55%，預測的結果與實際漲跌完全相反的比例僅10%，其餘的35%為相鄰區間的預測誤差，其預測能力有助於投資組合保險策略的進行。 經過類神經網路模型輔助而進行的停損策略（SL），其年報酬率以及Sharpe Ratio，在大盤下跌的期間，兩個績效指標衡量結果皆為正值（21.125%＞0以及980.493＞0），充分發揮保險功能；而在大盤上漲的期間，兩個績效指標衡量結果皆優於大盤（46.544%＞17.137%以及393.808＞110.069）。 在年報酬率與Sharpe Ratio之間，本研究主張在探討投資組合保險時應著重風險的衡量，因此經過類神經網路模型輔助而進行的固定比例投資組合策略（CPPI），搭配槓桿乘數M值的調整，在大盤下跌的期間，其Sharpe Ratio依然可以維持正值，達到保險的效果，保護投資人的資產免於損失；而在大盤上漲的期間，其Sharpe Ratio更是高於大盤，可以享受資產價值提昇的獲利。 / Facing the uncertainty of the market trend, an investor can use the concept of “ Portfolio Insurance ” to protect the value of his portfolio in bear market and earn the benefit from bull market. There have been many researches about applying Neural Network in the financial analysis and Neural Network has the abilities to learn and forecast. This research evaluates the performances of the portfolio insurance strategies in different market trends. Then two-stage research structure has been designed and built. The first stage is forecasting the up-and-down trends of the equity market index by Neural network model. The second stage is using the forecasted results assisting the portfolio insurance decisions. Finally, the results of this research have been analyzed and compared with the benchmark. The Neural Network is able to forecast the future up-and-down trends. The accurate rate is 55%. During the bear market（2002）, the annual rate of return and Sharpe Ratio of the stop loss（SL） strategy which is assisted by NN are both positive（21.125%＞0 and 980.493＞0）. During the bull market（2001）, they both outperform the benchmark（46.544%＞17.137% and 393.808＞110.069）. The annual rate of return is more important than Sharpe Ratio because the risk measurement is an important factor in portfolio insurance strategy. Sharpe Ratios of the CPPI strategy which is assisted by NN outperform the benchmark in both above mentioned bear and bull market. In short, the SL and CPPI strategy assisted by NN not only protect the value of the portfolio from losing in bear market but also gain profit in bull market, so they are the ideal portfolio insurance strategies.

隨著社會的進步、經濟的發展與個人化知識水準的提昇，再加上銀行定存利率趨低，個人理財的重要性愈顯重要。但是，現有文獻及實務上之理財服務功能仍屬片面，缺乏一套完整的流程模式可支援整體之個人理財規劃，如含個人保險組合、資產配置與投資組合等之規劃流程。因此，本研究之目的即在提出一個整合性的個人理財服務之流程模式，含理財流程中不同階段的服務功能與作業流程、理財決策模式及相關推論法則等，同時也將應用現有之系統發展法，建構一套完整的個人理財模式基底網路服務應用系統的架構，設計並建置一原型系統，驗證所提出的架構、流程、模式與方法的可行性與績效。 / Promote along with the development and personalization knowledge level of progress, economy of society, and the bank Certificate of Deposit interest rate tends low, the importance of personal financial planning shows the importance more. But, the existing cultural heritage and the financial planning on the actual situation service function are still unilateral, the process mode that lacks of a set of integrity can support whole of personal financial planning programs, if contain personal insurance planning, asset allocation and portfolio selection programming process of etc. Therefore, the purpose of this research is putting forward an integrated process model of personal financial planning service, the service function with financial planning process in different stage and the homework process, the financial planning decision model and the related reasoning rule etc., also will apply the existing system development method, personal financial planning model base network service that constructs a set of integrity applies the structure of the system, designing and building one prototype system, identifying the structure, process, model and the feasibility and the results of the method put forward.

本研究希望以個案研究的方式來探討多事業部的跨國公司的投資策略之組合，於有限的資源下，跨國公司必須以何種客觀及有效率的方法，來配置其所擁有的資源於其總公司之下所屬的事業部，以使其投資效益達到最大，進而增加股東價值。 　　本研究是以波士頓矩陣的理論架構，配合波特的五力分析，並運用產業分析的架構來進行外部分析，以及公司的優劣勢的內部分析，來訂位公司之投資策略方向。整個研究分為五個階段（1）先擬定可運用於本研究的理論模式及架構，將特用化學產業的投資模式加以量化及定位（2）分析外部產業的機會與威脅以及公司內部分析的優劣勢（3）根據上述分析定位出各事業部於波士頓矩陣中所處的四個象限（4）根據事業部之定位以及事業現況，擬定投資策略建議（5）投資策略規劃的回饋及修正。 　　有效率的資源配置，能夠確保良好的投資報酬率，增加股東權益，使企業能夠永續經營，本研究分析後發現特用化學產業的投資策略，必須結合外部產業分析與內部績效評估，以取得最客觀的決策資訊，並且做出最佳的投資決策。全球化趨勢下，企業必須有全球佈局與管理跨國企業之能力，本研究對於國內企業於邁向國際化的腳步過程中的建議，是如何培養並建立起管理國際企業之核心能力，是企業負責人的首要課題。

近年來，投資理財已經成為全民運動，昔日的定存族早已不復見，投資人在進行資產配置時，除了希望能有固定的保障本金及配息之外，更希望能在市場走勢看好時同時享有增值的利益，而投資組合保險便能滿足這些投資人的需求，部分的投資者及基金經理人，也開始運用投資組合保險進行資產配置。 為了更進一步瞭解投資組合保險策略實際上的運作及其特性，本研究利用蒙地卡羅模擬法，針對不同市場（多頭、空頭、盤整）以及資產間相關係數不同下（高度正相關、低度正相關），模擬多支股票所形成的投資組合，探討「複製性賣權策略（SPO）」、「固定比例投資組合保險策略（CPPI）」、「時間不變性投資組合保險策略（TIPP）」、「固定比例策略（CM）」、「買入持有策略（BH）」在不同市場走勢下相對的績效，並找出在不同市場下最適合各種策略的調整法則。此外，針對CPPI與TIPP策略提出動態調整風險參數m值的概念（MCPPI、MTIPP策略），試著改進此兩種策略在傳統上風險參數固定不動的缺點。在實證部分，除了驗證MCPPI與MTIPP的績效是否真的較佳，並檢驗蒙地卡羅模擬中模擬適合不同策略的調整方式的結果是否正確。 經由模擬可發現：多頭時期，SPO與CPPI策略以每日調整為佳，TIPP及CM策略以5%落差調整為佳，而且SPO策略的平均報酬最高；盤整時期，SPO、CPPI、TIPP策略以5%落差調整較好，CM策略以1%落差調整較好，期末報酬以TIPP策略為佳；空頭時期，SPO與TIPP策略以每日調整為佳，CPPI策略以1%落差調整較好，CM策略以5%落差調整較佳，期末報酬也以TIPP策略為優。經由實證可以證明，不論市場走勢為何，MCPPI、MTIPP策略的績效均比傳統的CPPI、TIPP來的好，顯示動態調整風險參數確實能增加投資組合的績效；此外，若能正確預測市場走勢，並依照蒙地卡羅模擬的結果選擇正確的調整法則，將能有效的提升投資組合保險策略的績效。 / In order to find out the characteristic and operation of portfolio insurance strategies, this study makes an extensive Monte Carlo simulation comparison of five portfolio insurance strategies (Synthetic put option (SPO), Constant Proportion Portfolio Insurance (CPPI), Time-Invariant Portfolio Protection (TIPP), Constant Mix (CM), Buy and Hold (BH) ) . For each strategy, some measures (average return, standard deviation, protection error and opportunity cost) are calculated to compare its performance. Besides, these strategies are compared in different market situations (bull, bear, no-trend markets) and with different asset correlation (highly correlated, low correlated), taking into account transaction costs and the price limit. The Monte Carlo simulations show the optimal rebalancing discipline of different portfolio insurance strategies in different markets; moreover, via the simulation process, we can find out a dominant role of TIPP strategies in bear and no-trend markets and a preference for SPO strategies in bull markets. These results are independent of the asset correlation. In historical simulations, we bring out an extended method for CPPI and TIPP strategies, called MCPPI and MTIPP strategies, which increase the risk multiplier (m) when market price goes up and decrease the risk multiplier when market price goes down. Comparing the portfolio insurance strategies mentioned above (SPO, CPPI, TIPP, CM, BH, MCPPI, MTIPP) ,we can find out that MCPPI and MTIPP strategies can dominate CPPI and TIPP strategies in all market ; besides, if we can use the optimal rebalance discipline correctly, it will effectively enhance the performance of portfolio insurance strategies. Although in historical and Monte Carlo simulations, we can’t conclude any strategy which is dominant in all market situations, but we can summarize that SPO strategy can dominate other strategies in bull market, and MTIPP and TIPP strategies can dominate other strategies in bear and no-trend market.

採用風險值取代標準差來衡量投資組合的下方風險，除了更符合投資人的對風險的態度，也更貼近目前金融機構多以風險值作為內部控管工具的情形。但除了風險的事後衡量，本篇論文希望能夠事前積極地控制投資組合風險值，求得最適投資組合的各資產配置權重。故本篇論文研究方法採用了Rockafellar and Uryasev.(2000)的極小條件風險值最適投資組合模型先建立Mean-CVaR效率前緣，並將此效率前緣上的投資組合風險以風險值衡量，再應用電腦上的探索方法進一步求得風險值更低的投資組合，逼近求得Mean-VaR效率前緣，最後利用Mean-VaR效率前緣採用Campbell，Huisman與Koedijk(2001)模型求得控制風險值下的最適投資組合。 在實證分析上，本篇論文採用國內三檔股票為標的，首先在實證標的資產報酬檢定為非常態分配下，使用歷史模擬法，以資產實際非常態報酬分配估計VaR，驗證了使用本篇論文研究方法極小CVaR投資組合與探索方法，可以適當逼近真實的Mean-VaR效率前緣。再者研究比較不同信賴水準、不同資產報酬分配假設與不同權重產生方式下的Mean-VaR效率前緣與Ｍean- 效率前緣效果差異，最後求得控制風險值下的最適投資組合。 / In contrast to the role of variance in the traditional Mean-Variance framework, in this thesis we introduce Value-at-Risk (VaR) as a shortfall-constraint into the portfolio selection decision. Doing so is much more in fitting with individual perception to risk and in line with the constraints which financial institutes currently face. However, mathematically VaR has some serious limitations making the portfolio selection problem difficult to attain optimal solution. In order to apply VaR to ex ante portfolio decision, we use the closely related tractable risk measure Conditional Value-at-Risk (CVaR) in this thesis as a proxy to find efficient portfolios. We utilize linear programming formulation developed by Rockafellar and Uryasev(2000) to construct a Mean-CVaR efficient frontier. Following which the VaR of resulting portfolios in the Mean-CVaR efficient frontier is reduced further by a simple heuristic procedure. After constructing an empirical Mean-VaR efficient frontier that can be proven an useful approximation to the true Mean-VaR efficient frontier, the Campbell, Huisman and Koedijk(2001) model is used to find the optimal portfolio. Three Taiwan listing stocks are used to build the Mean-VaR efficient frontier in the empirical study. And the Mean-VaR efficient frontier of different confident levels, under different asset return assumptions, and different optimal portfolio selection models are compared and results analyzed.

在此篇論文中我們考慮連續時間架構下, 加入匯差風險與利率風險之跨國投資組合問題. 延續 Lioui, Poncet (2003) 的研究架構, 我們考慮 國內外債券股票與現金的投資組合, 以martingale方法求解避險操作與最佳投資策略. / In this study, we investigate the hedge demands in international portfolio management under a general continuous time framework for constant relative risk averse investors where, in particular, exchange rate risk and the interest rate risk are incorporated. Within this international economy, the changes of real exchange rates, real interest rates and stock prices are assumed to follow the Markovian processes whose drifts and diffusion parameters are driven by certain state variables. Our approach is through the use of the martingale methodology developed by Cox and Huang (1989, 1991) as proposed in the work of Lioui and Poncet (2003). Following their framework, we consider the economy of the investors that consists of one foreign currency and the domestic one, together with their bond portfolios and stock indices. Adding to the previous works, we have compared the obtained optimal strategies with some prevailing ad hoc ones in order to clarify the hedge effects in financial decision from the long term perspective.