• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 11
  • 10
  • 1
  • Tagged with
  • 11
  • 11
  • 11
  • 11
  • 11
  • 11
  • 6
  • 6
  • 5
  • 4
  • 3
  • 3
  • 3
  • 3
  • 3
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

固定比例投資組合保險策略之模擬分析 / Simulation Analysis on CPPIs

陳冠宇 Unknown Date (has links)
本篇論文利用CPPI策略模擬信用衍生性商品,進行信用CPPI投資組合淨值分析,並且做其風險衡量和敏感度分析。本篇論文採用Variance Gamma模型,模擬信用價差動態,並且利用Gaussian Copula模擬信用違約的時間點,結合價差動態和信用違約的兩個模型,探討CPPI策略下的投資組合淨值分析與風險探討。 在本文可以看到以下重要結果,首先是模擬信用CPPI的過程,根據CPPI策略底下的拆解項,分析影響策略績效的情形。第二點是CPPI缺口風險的分析探討,列出可能造成缺口風險的原因。第三點為利用不同的目標乘數,模擬信用CPPI資產組合淨值的表現,可以發現在目標乘數比較低的時候,藉由蒙地卡羅模擬,平均CPPI投資組合淨值下來表現較好,反而目標乘數越大,投資組合淨值表現越不好。第四點為敏感度分析,在價差模型中的峰態係數變動下,影響CPPI投資組合淨值較大,峰態係數越大,會導致投資組合淨值表現越差。
2

投資組合保險策略—在台灣股市之相關研究

邱瑜明, Chiu, Yu-Ming Unknown Date (has links)
投資組合保險的概念可運用於較不願承受風險或是對於股市走勢不清楚的投資者身上,這種策略既可以保障原本所投資的本金,又可以參與股票市場的上方獲利,一般大眾可以利用投資組合保險策略作為投資的準則之外,投資組合保險的概念更可以運用在退休基金的管理、保本基金的設計上。 本篇論文主要研究的是動態投資組合保險策略:複製性賣權及固定比例投資組合險兩種策略,利用蒙地卡羅模擬法以及台灣股市從民國78年至88年的實際資料來做驗證,投資組合保險策略是可以有效的降低投資者所面對的投資風險,並且提供投資大眾選擇投資組合保險策略時的準則。 從本論文的模擬和實證的結果,可以得到以下的結論: 一、對市場波動度的預期,會影響複製性賣權與固定比例投資組合保險,當市場的波動越大,就須要採用較為保守的策略,才能有較好的保險效果。 二、投資組合保險的績效和景氣的好壞有密切的關係,在市場為大空頭或是大多頭的時候,投資組合保險策略的績效是最好的。 三、投資組合保險的目的雖然不是為了擊敗大盤,但長期平均而言仍然是可以有優於大盤的表現。 四、減少交易成本可以使投資組合保險策略的績效更好。 五、固定比例投資組合保險策略(CPPI),是可依照個人對於風險不同的偏好來量身定作投資組合保險策略,所以一般投資者在運用上較為簡單方便。 六、複製賣權策略可以從事超額保險、完全保險及不足額保險,三種不同的保險方式,可提供投資人另一種選擇,但是要估計市場的波動度、決定投資資產的部位配置等等,並不容易,所以這樣的投資策略是較合適於專業經理人。
3

投資組合保險結合選股策略於台灣股市之實證研究

鄭傑鐸 Unknown Date (has links)
投資組合保險的概念興起於1980年代,其對於無法承受巨大損失風險或是對於股市未來走勢不清楚的投資人而言,是一種很好的投資策略,既可以保障原本所投資的本金,又可以參與上方的獲利。近年來隨著市場發展與金融創新,亦有許多新金融商品依據其概念設計商品,為投資人提供許多較存放定期存款更好的投資選擇。 本研究以台灣上市公司(金融保險類除外)為研究對象,探討選股策略搭配投資組合保險操作進行實證研究。在選股策略的採用以相對評價法中股價/盈餘比、股價/淨值比與股價/銷售比三項選股指標策略所形成之高低兩類投資組合,並搭配固定比率投資組合保險策略、時間不變性投資組合保險策略、固定比例策略及買入持有策略,尋找面對多頭、空頭及盤整不同狀態市場下之最佳投資策略與探討搭配投資組合保險策略後對投資組合績效表現與避險效果的影響。 實證發現,低股價/盈餘比、低股價/淨值比及低股價/銷售比這三類組合在市場下跌及盤整的狀況報酬率均勝過大盤,表現相對抗跌。搭配投資組合保險策略後皆能達到設定的保本比率要求。從機會成本的角度分析,低股價/盈餘比及低股價/銷售比二類組合搭配投資組合保險策略皆損失了機會成本,至於高股價/盈餘比、高股價/淨值比及高股價/銷售比此三類組合則在大盤上漲的年度內有機會成本的損失;從長期相對平均成本的觀點,買入持有策略仍較投資組合保險策略為佳。 在市場上漲年度,高股價/盈餘比、高股價/淨值比及高股價/銷售比此三類組合搭配CPPI策略有最佳的報酬率;大盤盤整年度,六類組合均以搭配CM策略表現最佳。至於六類投資組合在大盤下跌時分別該搭配何種策略較佳,在實證期間內則沒有一致的結論。
4

以類神經網路輔助投資組合保險策略之研究

陳如玲, CHEN, JU-Ling Unknown Date (has links)
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.
5

投資組合保險策略之延伸及應用

林郁棻 Unknown Date (has links)
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.
6

如何應用新金融商品於銀行財富管理以達成績效的均衡表現

洪珠懿, Hung, Chu-I Unknown Date (has links)
隨著台灣將近五十多年來的經濟成果展現,企業界發展蓬勃興盛,加上全球投資理財風氣鼎盛,資金回流到亞洲新興地區,也造成台灣個人財富的迅速累積。除了外商私人銀行搶盡時機、技術優勢,做台灣富人的生意外,近幾年來,台灣本土金融業者也競相推出財富管理業務,期望掌握潮流、開拓先機。 而這些富人們對銀行財富管理的要求是:“投資理財的「客觀建議」、提供跨越世代的理財諮詢顧問,讓財富能穩定成長、夠世代傳承”。因此,銀行財富管理方案最重要的一環,是因應客戶理財目標要求,幫助其對資產進行妥適配置,以實踐穩定均衡的績效。而所謂績效的均衡,意謂回報穩健加上不確定性小,換句話說,即是在相同獲利水準表現之下,風險較低。 隨著二十一世紀與時俱進的新金融商品與財務工程發展,本報告將探索在要求兼顧財富穩定成長與風險最小的原則下,有關選擇權系列的新金融商品,如何創造出最佳資產搭配效果或改變投資組合損益曲線,提昇原有投資組合的報酬率,進行積極面的投資組合與防禦面的風險管理,有效增裕資產價值並防範減損資產損失,達成客戶”維持財富穩定成長、夠世代傳承”的要求。 其他廣泛的財富管理策劃方案,例如房地產投資,黃金白銀、藝術品蒐購等實體資產配置,或保險、信託、養老、遺產、節稅等理財規劃,都不屬於本報告研究範圍。
7

不同投資策略在確定提撥制下之衡量及分析

謝竣宇 Unknown Date (has links)
確定提撥制是現今退休金制度潮流的趨勢,而在這個制度下,勞工最後所能累積的退休金總額及每月所能領到的月退休金額度和個人帳戶的投資結果有很大的關係,所以個人帳戶的投資績效成為勞工退休生活安全性最重要的因素。 本研究的目的在提供一個方法以評量投資績效,使得在每月提撥一定金額到個人帳戶的情形下,對於投資期間的經濟環境以隨機投資模型或情境分析模型加以考量後,可以在不同的投資策略及起始資產配置下,找到適合投資人的最佳投資策略及起始資產配置。在本研究中考慮了股票和長期債券兩種投資標的,而投資標的之投資報酬率變化則以隨機投資模型(Stochastic Investment Model)及情境分析(Scenario Analysis)兩種模擬方式為之,其中在隨機投資模型模擬的部分,不同的隨機投資模型對於經濟環境有不同的設定,也因此將得到不同的投資結果,本研究採用在英國學術上廣為研究的Wilkie投資模型(1986)及黃泓智等人於2005年證券市場發展季刊所推導之台灣投資模型,並利用蒙地卡羅模擬的方式來建構投資標的之報酬率。而在情境分析模擬的部分,則設定三種基本的投資報酬率趨勢,並假設三種投資報酬率趨勢服從均勻分配,而後考慮投資期間分成前後兩個時期,搭配而得九種情境。 本文將觀察不同的起始資產配置(股票資產配置之權重考慮由0%~100%,間隔為1%,共101組;債券資產的權重則為1-股票資產配置之權重,也就是100%~0%),並以投資組合保險中三種常見的投資策略:買入持有(Buy & Hold;BH)、固定比例混合法(Constant Mixture;CM)及時間不變性投資組合保護(Time-invariant Portfolio Protection;TIPP),作為投資策略。 在三種投資策略及每種投資策略有101個起始資產配置下,將可以得到303組不同的投資結果,而每一組投資結果中,都可找到個人帳戶於退休時的累積金額、在一定目標所得替代率下之破產機率,以及平均投資報酬率和投資報酬率之標準差,並將所得之投資組合報酬率之平均值為縱軸,標準差為橫軸作圖,找出效率前緣;也就是說,可以依個人帳戶持有人的風險,在其所能忍受的風險下,找到最適的起始資產配置及投資策略,及依這樣的起始資產配置和投資策略下所能得到的平均報酬。另外,更進一步以Sharpe ratio及Reward-to-VaR ratio、Reward-to-CTE ratio三個指標來衡量投資表現,找出在這三個指標下的最適起始資產配置和投資策略。 在前述中,都未考慮到交易成本對於投資結果的影響,但在現實的環境中,交易成本對於投資結果是有影響的,所以本研究也會在考慮交易成本下,找到情境分析和隨機模型下的投資結果及效率前緣,並找出三個投資指標的值來衡量投資表現。 / The defined contribution plan is the trend of retirement pension funds management, but under this plan, the total account values accumulated and the retirement benefits paid each month that labors can get are great related to the investment results of the individual accounts. That's why we said that the investment result of the individual accounts is the most important factor the labors care about. In this article, we will focus on the measure of investment results. We consider bond and stock as our holding assets, and set the investment rate of return in two methods, including scenario analysis and stochastic model. In the scenario analysis method, we set fourteen scenarios to reflect the changes of the investment returns of stocks. In the stochastic model method, we take use of Wilkie investment model to set the investment return rate of stocks and bonds and simulate enormous data to find the average investment rate of return. In each method, we will consider 101 different initial ratio of stock value and three different investment strategies: Buy & Hold(BH)、Constant Mixture(CM) and Time-invariant Portfolio Protection(TIPP). After setting the investment rate of return and investment strategies, we can find 303 different investment results under three investment strategies and 101 initial ratios of stock values. In each result, we can get the accumulated amounts, the income substitute rate and the average rate of return, and use the average rate of return as y-axis, standard deviation as x-axis to find the efficient frontier. That is, we can find the optimal investment strategies and initial ratio of stock value under the risk we can tolerant. We will also use Sharpe Ratio、Reward-to-VaR ratio and Reward-to-CTE ratio to measure the investment results, and find the optimal investment strategies and initial ratio of stock value basic on the three ratios. In practice, the transaction cost is an important factor that will affect the investment results, so we also find the investment results under different situations which had considered the transaction cost.
8

固定比例投資組合保險策略動態調整乘數績效研究-運用相對強弱指標為例

金元宇 Unknown Date (has links)
由於固定比例投資組合保險策略(CPPI)能依據投資者本身的風險偏好來選定參數,並透過簡單的公式動態調整風險性資產及保留性資產的部位,以達到投資組合保險的目的,因此成為常用的投資組合保險策略之一。然而在固定乘數的選定中,僅考慮投資人的效用函數而並未考慮市場變化情況,因此投資組合的報酬往往未必為最適化之結果。   本研究以台灣股市為例,旨在討論透過技術分析指標來動態調整乘數,對固定比例投資組合保險策略之影響。實證方面以1992~2003年間台股指數作為研究標的,配合固定時點調整法及相對強弱指標來調整投資組合中風險性資產及保留性資產之投資比例。並討論動態調整與固定乘數在要保誤差、平均報酬、報酬變異、偏態、交易成本及不同市況下績效表現。
9

模擬最適化運用於資產配置之驗證 / The Effectiveness of the Asset Allocation Using the Technique of Simulation Optimization

劉婉玉 Unknown Date (has links)
本文利用模擬最適化(Simulation Optimization)的技術,來找出適合投資人之最佳資產配置。模擬最適化係為一種將決策變數輸入而使其反應變數得到最佳化結果之技術,在本篇中,決策變數為各種投資標的之資產配置,而反應變數則為投資結果之預期報酬與標準差,模擬最適化可視為一種在可行範圍內尋求最佳解之過程。本篇中模擬最適化之方法係採演化策略法,最適化問題則為具放空限制之多期架構。我們亦進一步與各種傳統的投資保險策略比較,包括買入持有策略(Buy-and-Hold)、固定比例策略(Constant Mix)、固定比例投資保險策略(Constant Proportion Portfolio Insurance)及時間不變性投資組合保險策略(Time-Invariant Portfolio Protection),以驗證模擬最適化的有效性,並以多種評估指標來衡量各種策略績效之優劣。 由實證結果發現,利用模擬最適化求解出每月的最適資產配置,雖然造成每期因資金配置比例變動而提高波動性,另一方面卻能大幅的增加報酬率。整體而言,模擬最適化技術的確能夠有效提升投資績效,使得最終財富增加,並且得到較大的夏普指數及每單位風險下較高的報酬。 / This paper applied simulation optimization technique to search for the optimal asset allocation. Simulation optimization is the process of determining the values of the decision variables that optimize the values of the stochastic response variable generated from a simulation model. The decision variables in our case are the allocations of many kinds of assets. The response variable is a function of the expected wealth and the associated risk. The simulation optimization problem can be characterized as a stochastic search over a feasible exploration region. The method we applied is the evolution strategies and the optimization problem is formulated as a multi-period one with short-sale constraints. In order to verify the effectiveness of simulation optimization, we compared the resulting asset allocation with allocations obtaining using traditional portfolio insurance strategies including Buy-and-Hold, Constant Mix, Constant Proportion Portfolio Insurance, and Time-Invariant Portfolio Protection. We also used many indexes to evaluate performance of all kinds of strategies in this paper. Our empirical results indicated that using simulation optimization to search for the best asset allocation resulted in large volatilities, however, it significantly enhanced rate of return. As a whole, applying simulation optimization indeed gets the better performance, increases the final wealth, makes Sharpe Index large, and obtains the higher return under per unit risk.
10

不同投資策略應用於基金及投資聚集效果之研究

王堃峰 Unknown Date (has links)
隨著時間的發展,基金的種類與數量成倍數增長,導致投資人在挑選基金時,亦面臨了選擇股票時的窘境:投資標的數目過多、複雜度高,身陷其中,而不知如何挑選理想的投資組合。目前由於人們對於退休金的相關規劃愈益重視,遂有基金商品針對此概念來設計。 生命週期基金基本上符合這樣的概念,生命週期基金基本上是屬於一種組合型基金,但是並不一定要以組合型基金的型態來顯現,美國80只生命週期基金中將近半數為基金的基金。生命週期基金是為了滿足某個年份左右退休投資者的退休投資目標的基金,如FidelityFreedom系列、FrankRussell Life Points系列、T.Rowe PriceRetirement系列、Vanguard LifeStrategy系列等。例如FidelityFreedom2020是針對2020年左右退休的投資者設計的,為實現投資者退休的投資目標的基金,主要投資在Fidelity旗下股票型基金、債券型基金和貨幣市場基金等各類基金。我們便想要了解此種商品的投資型態下具有何種特色。 我們首先要探討基金在不同投資策略其表現如何,而我們衡量的方式---簡單的說是以是否能夠達到投資人的要求報酬率為基準,以投資報酬率來建構出年金終值,最後以各種投資策略所得到的最終價值之差距做為成本的衡量,之後我們則根據生命週期基金的樣態,自行設計出兩種投資模式同樣來探討不足要求資本的相關概念。 再來以投資聚集效果(pooling effect)為主題,因為在基金存在著不同風險容忍程度的投資人,所以我們希望探討在不同投資策略下所建構的效率前緣對於不同風險忍受程度的投資人是否具有超額報酬。 首先我們就兩種投資標的(股票、債劵)之投資報酬率變化以下列方式作設定---利用隨機模型(Stochastic Model):並利用蒙地卡羅模擬的方式來建構投資標的之報酬率。 我們觀察不同的起始投資比重(股票資產權重考慮由0%~100%,間隔為1%,共101組;債券資產的權重則為1-股票資產權重,也就是100%~0%),並以投資組合保險中三種常見的投資策略:買入持有(Buy & Hold;BH)、固定比例混合法(Constant Mixture;CM)及時間不變性投資組合保護(Time-invariant Portfolio Protection;TIPP),作為投資策略。在完成對投資標的之報酬率變化及投資策略的設定後,就可以在三種投資策略及每個投資策略有101個起始權重下,得到303組不同的投資結果,如此我們就可以得到帳戶的最終價值,就可以針對是否符合投資者要求的報酬率做相關的研究。 同樣的我們可以就個別的投資策略建立個別的效率前緣。之後我們就不同風險容忍程度的投資大眾,以Harry M.Markowitz等人所提出的optimal frontier的概念加以設定風險點(risk point) ,各種不同風險程度的投資人即代表不同的風險點,如此我們便可以就不同的投資模型來探討基金的投資聚集效果(pooling effect) 。 最後我們想探討的部分則是希望讓投資大眾知道如果其處於何種經濟體之下,應該採用何種投資方式,或者是在投資人的不同要求之下,可以知道採取何種投資策略,以求學術上的操作可以應用到實務上,並求取更佳的效果。 / With the development of time, the kind and quantity of the fund become multiples to increase, cause investors to face the awkward situation while choosing the stock when they select funds: There is too much figure of the investment object marking investment complexity more diffcult , and does not know how to select ideal investment combination. Nowdays, people put emphasize on retirement plan more and more. so some mutual funds are designed for this concept. Lifecycle fund is identical to this concept .Lifecycle fund is a kind of Fund of Funds basically, but might not appear like the Fund of Funds , 80 Fund of Funds in U.S.A. nearly half appear like Fund of Funds . Lifecycle fund is for the fund of retired investors' retired investment needs which is different from age-changed , such as Fidelity Freedom series, Frank Russell Life Points series , T.Rowe Price Retirement series , Vanguard Life Strategy series ,etc.. For example Fidelity Freedom2020 is designed for pensioner's investor to retire about 2020 year, the fund that in order to realize the goal of investors when they retired, make an investment in many objectives, such as stock fund ,bond fund and money market fund ,etc. under command of Fidelity mainly. I want to know the characteristic of lifecycle fund and based on this concept to design mutual fund. I will discuss behavior of fund in different investment strategies, and the way which we measure ---It is to set the rate of returns by meeting investor's requirement as the datum, build and pay the end value of the annuity to construct by investing in the rate of returns, for the measurement of " bankrupt " with the disparity of the final value got of various kinds of investment strategies , later I designed two kinds of investment ways according to the concept of lifecycle fund and also discuss the concept of " bankrupt ". This research will also make emphasize on pooling effect , There are a lot of investors of different risk tolerance in the fund ,so I hope to discuss investor of different risk tolerance will have abcdrmal return under different efficiency frontier which are derived by different invest model and strategies. First, two kind investment target (stock, bond) Investment rate of returns by way of the following to settle ---Utilize Stochastic Mode: Wilkie investment model, Taiwan investment model and the rate of returns of the one that make use of simulation that build and construct investment terms. In each method, we will consider 101 different initial ratio of stock value and three different investment strategies: Buy & Hold(BH)、Constant Mixture(CM) and Time-invariant Portfolio Protection(TIPP).According to theses investment combination, I can construct different efficiency frontier under different investment models and strategies. Such final value of the account that we can receive so I can do relevant research to the rate of returns according with investor's request . Later, according to investor of different risk tolerance , set some risk point with the concept of optimal frontier published by Harry M.Markowitz, the investors of different risk degrees represent risk point, I can discuss pooling effect in fund under different investment model and strategies. Finally, the topic I want to discuss is let the investor know at which kind of economy , should adopt the investment strategies , or under investors' different requests, can know which kind of investment tactics are adopted , so that the operation on academy can be applied to the practice , and ask for better result.

Page generated in 0.0242 seconds