The aim of this thesis is to design an investment strategy focused on tool called CFD. The first theoretical part contains basic information about financial derivates and explains basic principles of trading on stock market with contracts for difference. Chapter of the investment analysis explains the methods and rules used in trading. The practical part presents the results of my trading CFDs and evaluated my proposed strategy along with the benefits of work.

Doctoral thesis deals with the method of the currency portfolio creation focused on short-term trading, which not exceed one business day. That is the reason why is necessary to increase the profitability of investment positions by using financial leverage. Development of proposed investment strategies is realized with use of computer technology in combination with software that allows direct access to the foreign exchange market. The software enables direct access to a database of historical prices and has an implemented a programming language that allows effective processing of statistical analyzes, which is required for development of investment strategies. The investment strategies are optimized and tested on a database of historical price movements from 1. 1. 2004 to 31. 12. 2012 for the major currency pairs EUR/USD, GBP/USD and USD/JPY. The main assumption of entry to the market for proposed investment strategies is based on specific time intervals during the day, where is an increased probability of new short-term trends beginnings. The doctoral thesis statistically validated this assumption. The proposed method of creation a currency portfolio was applied to real market since 1. 1. 2013 to 30. 9. 2013 and was used for 20 000 $ trading account. Profitability of proposed method of creation a currency portfolio is 26,89%.

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Cryptocurrencies have since the creation in 2008 constituted a unique and modern addition tothe financial setting throughout the world. Such assets are commonly known to be associatedwith great risk but also the possibility of great reward. The corresponding research field hasadapted to the evolution of cryptocurrencies and has for over a decade undergone a constantexpansion. Despite this, there is still plenty of unexplored territory within the particular researcharea and this report seeks to examine a part of it. The central topic of this paper concernscryptocurrencies in relation to Swedish retail investors’ different demographic factors and theeffect those have on investment strategy and behavior. To examine this, the report centersaround two main aspects, the investment purpose which cryptocurrency investors associatetheir investments with and investors’ exposure to herd behavior. Additionally, both aspectswere put in relation to various demographic factors to allow an analysis of whether demographicfactors affect the investors’ strategy and behavior. A quantitative method was used for theprocess of collecting data whereby a survey was constructed and replied to by Swedish retailinvestors active in the cryptocurrency market. The primary data obtained was analyzed andpresented through descriptive statistics, t-Tests, and regression models. By interpreting theresults, it was evident that demographic factors were found to not influence the investmentpurpose or the herd behavior of investors. This contradicts previous findings regardingtraditional markets e.g., the stock market where demographic factors are established as factorsaffecting both aspects. Hence, this report suggests that there are differences between thecryptocurrency market and traditional markets. Further, the research conducted in this paperindicates that a majority of investors associate cryptocurrency investments with speculativetrading and there is also a strong bias toward herd behavior among Swedish retail investorsactive in the cryptocurrency market.

The efficient portfolios for the period 1993 – 2010 based on IPD data have a major portfolio weight in residential properties in the three largest regions Stockholm, Gothenburg and Malmo. The portfolio with the highest risk adjusted return (measured as the highest Sharpe-ratio) combines a large portfolio weight in residential properties with a small weight in industrial properties. During the time period of 2005 – 2010 a majority of the listed real estate companies held a real estate portfolio far below the efficient frontier based on the corresponding IPD data. These companies can increase their total return without taking on any more risk by using the concept of diversification. When including all available diversification categories two out of seven companies can be said to have an efficient real estate portfolio. When we excluded the outperforming residential asset class, however, none of the companies’ portfolios were in fact efficient. The real estate market is inefficient and thus results in the IPD data being less useful as it is based on transactions occurring in this inefficient market. Investors can, in this market, easily find properties with another risk and return profile than what IPD indicates is the market risk and return for a particular property type in a certain region. The inefficiency of the market, together with the IPD data being less useful, thus makes it difficult for the companies to focus on diversification in their investment strategy. Moreover, there are several reasons that explain the discrepancy between the actually held listed real estate portfolios and the optimal portfolio based on IPD data. Since each property is heterogeneous and possesses unique risks, investors are not able to accurately quantify the risk of each investment and thus rely more on their gut feeling. This also results in investors focusing on single investment opportunities rather than looking at all investments from a portfolio perspective.

This study examines how investors can take advantage of Black Swan events by applying an investment strategy that involves investing in stocks that have performed badly during Black Swan events. The stocks are chosen from and compared to the Dow Jones Industrial Average Index. The purpose is to find out if the investment strategy has had a higher return than the benchmark index DJIA. The results show that the investment strategy outperforms the DJIA by 111% between the years 2000 to 2020, however, the results show no statistical significance. Beta is used as risk measurement to explain the correlation between the portfolios and the benchmark index by calculating CAPM. Standard deviation is used to calculate the Sharpe ratio and thereby assess a risk-adjusted result.

本研究之目的為設計一應用框架供建置投資策略之用，其方法是自一般投資活動中整理出常用的投資方式，再自投資方式中萃取出抽象化之結構，並以標的模型為基礎，將其轉換為應用框架。本研究之貢獻為投資人可建置各式各樣之投資策略於框架中，並且透過框架達到自動化執行投資策略。除了定義投資策略框架結構與投資策略建置流程，本研究也透過建置三種不同性質之投資策略來驗證其適用性。 / The purpose of this research is to design an application framework for the use of constructing investment strategies. The research method is to sum up the whole ordinary investment types, generalize the structure of those, and transfer them into application framework based on object model. This application framework can assist investors flexibly constructing their investment strategies and executing it automatically. This research not only defined both the structures and construct procedures of investment strategies, but also tested the application framework with three different investment strategies in order to verify applicability. Finally, this research has imitated the layout of system when constructed.

現行各國的退休金計畫逐漸地由確定給付制轉變為確定提撥制。這表示投資的風險由原本退休金計畫的發起者(雇主)轉移到了參與者(員工)的身上。為了減少每個確定提撥制計畫參與者的投資風險，本文中採用退休時所得替代率為預估的目標，藉由模擬與最適化的方法找到最適投資策略與最適提撥率。 能反映出時間性的隨機模型在精算科學的領域是日漸重要，本文試著藉由隨機性的變化來估計代替以往精算上各種假設下所求得的負債。本文藉由隨機模擬的方式，得到各種資產在市場上或者是經濟上的價值來建構相關投資標的之報酬率，並利用動態隨機規劃模型去改善財務上避險以及資產負債管理。此外，為了避免模擬分析時間過長的問題，本文採用了情境抽樣的方法去改善電腦模擬分析計算時的效率。 我們主要得到以下結論： (一)確定提撥制下的負債受薪資水準波動的影響，所以此時會持有較 多的指數連結型債券以反應薪資水準及通貨膨脹的影響。整體投 資的結果與Vigna & Haberman (2001) 文中的結果及實務上生命 週期型態(lifestyle)投資方式呈現相同的現象。 (二)考慮每期下跌風險(downside risk)時，期中的投資可能會偏向 於投資風險較高的股票。在每年觀察下跌風險的情況下其投資因 為必須考慮避免每一年的下跌風險，需要比每五年觀察下跌風險 的情況做風險較大的投資，以達到其目標。 (三)在本文的調整投資組合策略下，因為調整次數不多，所以在考慮 交易成本的情況，當交易成本很小時對於整體的最適化資產配置 與最適化提撥率的影響是很小的。在本文的調整投資組合策略 下，交易成本的影響只有在交易成本非常大的情況下才能看得出 來。 (四)均勻抽樣法抽出的400組情境幾乎可以完全的代替4000組情境， 其結果可以看出與未抽樣相同的生命週期型態(lifestyle)投資 方式。而隨機抽樣法的結果雖然也可看出趨勢，但準確性相對於 均勻抽樣法仍稍嫌不足，並不適合用來代替原先的4000組情境。 / A shift from defined-benefit pension plan towards defined-contribution pension plan is currently popular around the world. This means that a serious investment risk transfers from defined-benefit sponsors to the individual members of defined-contribution plans. In order to reduce the risk of individual DC member, we investigate the methodology of finding the optimal contribution rate and asset allocation to reach a certain target of the retirement replacement rate in this paper. Stochastic processes are getting more important to the field of actuarial science. Instead of trying to approximate liabilities by a single deterministic set of actuarial assumption, we seek to take account of market or economic valuation for both assets and liabilities using stochastic simulation. We applied dynamic stochastic programming models to improve financial hedging and asset liability management. Moreover, in order to avoid the problem of time-consuming, we use scenario sampling method to improve the efficiency of computer calculation. We draw four conclusions from our investigations： (1)We will hold more assets in indexed-linked bonds because the pension liability is highly related to the wage- index and inflation rate. The optimal investment strategy is very like the so called "lifestyle" investment strategy. (2)When we consider downside risk, we should hold more risky equities. The investment strategy is more risky when we consider downside risk every year than every 5 years. (3)Under our rebalancing strategy, if the transaction cost is small, the influence on the investment strategy and contribution rate is small. We can see the influence of the transaction cost in a situation that the transaction cost is very big only. (4)There are almost no different between uniform sampling scenarios and original simulation scenarios, so uniform sampling scenarios may replace the original simulation scenarios perfectly. And random sampling method is unsuitable to replace the original simulation scenarios.

近年來(2005-2014)，因子投資在市值、帳面市值比和動能在美國股市無法得到比大盤更好的表現，所以本研究以五因子亦即市值因子、帳面市值比因子、動能因子、低市場因子和品質因子，進行特定產業美國科技股研究，不同於大部分因子投資研究都以地區作為區分標準，期望可以得到不同的因子投資策略。研究結果發現無論是個別因子投資或是因子投資組合確實可以在美國科技股中提高夏普指標並擊敗那斯達克指數，此外檢視因子投資組合在不同時間的投資效益，發現因子投資組合在金融海嘯的壞時機期間，相對於投資那斯達克，更具有抗跌作用、投資的效益，在經濟穩定的好時機時，也能具備足夠的收益率並能夠提供投資者更好夏普指標，顯示因子投資在美國科技股中是一個可以成功的投資策略。 / Recently, factor investing in market value, book/market ratio and momentum had no outperformance comparing to the market index in terms of return and sharpe ratio. The research focus on technology stocks in U.S to construct 5 factors which are market value, book/market ratio, momentum, betting against beta, quality. Unlike other regional-based researches, this paper is industrial-based and aims to create a new factor investing strategy. The result shows that some factors and factory portfolios do outperform NASDAQ index with higher sharpe ratio. Moreover, analyses in timing for factor portfolios show that factor portfolios provide better return and sharpe ratio during financial crisis in U.S. On the other hand, under stable economy circumstance, factor portfolios still beat NASDAQ in terms of higher sharpe ratio.

由於扶養比降低與平均餘命增加，退休理財規劃已被國人所重視。本研究首先介紹退休規劃的流程，依照世界銀行1994年所提出之退休所得三層架構，第一層為強制性社會安全制度的保障，第二層為退休金制度，以及第三層為自願性商業保險儲蓄制度。當退休前的自願儲蓄不足時，即可能產生退休不足度的問題，解決方式為設法提高退休所得；而影響退休所得有三個主要因素，其一為金額之多寡，其二為累積時間之長短，而最為個人能掌握的第三個重要因素為「投資報酬率」之高低，因此如何利用較佳的投資策略與報酬，減少退休所得不足的問題即為一種大課題。本研究主要的目的為考量風險因素後，分析各種投資策略的績效與檢視交易成本對其之影響，並且設法在有無限制風險程度下，找出最大報酬率的策略。分析結果發現固定比例混合法投資策略在各績效衡量指標下與加入交易成本考量皆有較佳的表現，且在限制風險找尋最大報酬的情形下也是如此；但如果是在沒有限制風險找尋最大報酬的情形，固定比例混合法投資策略在以尾端風險為考量之決策目標時，即非最好的策略。 關鍵字：退休規劃、資產配置、投資策略