Дисертації з теми "Optimal portfolio strategy"
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廖智生 and Chi-sang Liu. "A study of optimal investment strategy for insurance portfolio." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2003. http://hub.hku.hk/bib/B31227636.
Повний текст джерелаGabih, Abdelali, and Ralf Wunderlich. "Optimal portfolios with bounded shortfall risks." Universitätsbibliothek Chemnitz, 2004. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200401202.
Повний текст джерелаGabih, Abdelali, Matthias Richter, and Ralf Wunderlich. "Dynamic optimal portfolios benchmarking the stock market." Universitätsbibliothek Chemnitz, 2005. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200501244.
Повний текст джерелаLi, Zejing [Verfasser], and N. [Akademischer Betreuer] Bäuerle. "Optimal Portfolios in Wishart Models and Effects of Discrete Rebalancing on Portfolio Distribution and Strategy Selection / Zejing Li. Betreuer: N. Bäuerle." Karlsruhe : KIT-Bibliothek, 2012. http://d-nb.info/1033351482/34.
Повний текст джерелаMatamba, Itani. "Estimating the cost of deposit insurance for a commercial bank following an optimal investment strategy." University of Western Cape, 2020. http://hdl.handle.net/11394/7845.
Повний текст джерелаCommercial banks play a dominant role in facilitating the economic growth of a country by acting as an intermediary between the de cit spending unit (borrowers) and the surplus spending unit (lenders). In particular, they transform short-term deposits into medium and long-term loans. Due to their important role in the economy and the nancial system as a whole, commercial banks are subject to high regulation standards in most countries. According to an international set of capital standards known as the Basel Accords, banks are required to hold a minimum level of capital as a bu er to protect their depositors and the nancial market in an event of severe unexpected losses caused by nancial risk. Moreover, government regulators aim to maintain public con dence and trust in the banking system through the use of a deposit insurance scheme (DIS). Deposit insurance (DI) has the e ect of eliminating mass withdrawals of deposits in an event of a bank failure. However, DI comes at a cost. The insuring agent is tasked with estimating a fairly priced premium that the bank should be charged for DI.
Ramkrishnan, Karthik. "Optimal Investment Strategy for Energy Performance Improvements in Existing Buildings." Thesis, Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/19855.
Повний текст джерелаPrezioso, Luca. "Financial risk sources and optimal strategies in jump-diffusion frameworks." Doctoral thesis, Università degli studi di Trento, 2020. http://hdl.handle.net/11572/254880.
Повний текст джерелаWheeler, Douglas J. "Contributing factors to optimal project portfolio selection." Thesis, Queensland University of Technology, 2013. https://eprints.qut.edu.au/61988/2/Douglas_Wheeler_Thesis.pdf.
Повний текст джерелаMtemeri, Nyika. "A model of pension portfolios with salary and surplus process." Thesis, University of the Western Cape, 2010. http://etd.uwc.ac.za/index.php?module=etd&action=viewtitle&id=gen8Srv25Nme4_2931_1364203235.
Повний текст джерелаEssentially this project report is a discussion of mathematical modelling in pension funds, presenting sections from Cairns, A.J.D., Blake, D., Dowd, K., Stochastic lifestyling: Optimal dynamic asset allocation for defined contribution pension plans, Journal of Economic Dynamics and Control, Volume 30, Issue 2006, Pages 843-877, with added details and background material in order to demonstrate the mathematical methods. In the investigation of the management of the investment portfolio, we only use one risky asset together with a bond and cash as other assets in a 
continuous time framework. The particular model is very much designed according to the members&rsquo
preference and then the funds are invested by the fund manager in the financial market. At the end, we are going to show various simulations of these models. Our methods include stochastic control for utility maximisation among others. The optimisation problem entails the optimal 
investment portfolio to maximise a certain power utility function. We use MATLAB and MAPLE programming languages to generate results in the form of graphs and tables
Kacelenga, Evans. "Towards an optimal product portfolio of liquid fuels for the Malawi energy market : development of a strategic framework for enhancing pathways of ethanol production and use." Thesis, University of Bolton, 2017. http://ubir.bolton.ac.uk/2001/.
Повний текст джерелаBERTELLI, BEATRICE. "Investimenti sostenibili: oltre o un passo indietro rispetto gli ESG?" Doctoral thesis, Università degli studi di Modena e Reggio Emilia, 2023. https://hdl.handle.net/11380/1298326.
Повний текст джерелаAgainst the background of the UN 2030 Agenda and the Principles for Responsible Investment (signed in 2006, PRI, 2006), the thesis addresses three main issues in sustainable finance encompassing different types of assets (bonds and stocks) and different model’s objectives (pricing and portfolio). The first issue is the pricing of green bonds, which is central to green finance. The second issue is the performance of stock portfolios based on screening strategies and ESG (Environmental, Social and Governance) scores. The third issue is the setup of an optimal stock portfolio accounting for ESG requirements. The first chapter of the thesis contributes to the literature on green bonds by proposing an original model for bond pricing, which accounts for a systemic green risk factor beside a systemic market risk factor. Using the Fama and MacBeth approach on a sample of Euro-denominated green and conventional bonds over the period 2014-2021, the green premium is estimated disentangling its two components: the sensitivity to systemic greenness and the price of green risk. We find that the price of green risk is on average significant and positive (62.5 bps per annum) and the green premium is on average positive for green bonds and negative for conventional bonds. However, the green risk price becomes negative during Covid-19 pandemic, suggesting greenness is considered a benefit in periods of market stress. The second chapter, framed within the literature on socially responsible investments (SRI), specifically contributes to the literature on the performance of screening strategies for stock portfolios based on ESG scores. Negative and positive screening strategies based on Bloomberg ESG scores and different screening thresholds are set up from the stocks belonging to the EURO STOXX index in the period 2007-2021 and over four short-term subperiods including 2008 global recession and 2020 Covid-19 pandemic. Main results reveal that negative screening strategies overperform a benchmark passive strategy in the long term whereas overperformance is not verified in the short run and when positive screenings are adopted. The last chapter aims to address the optimal portfolio allocation problem over a sample of stocks by considering also non (strictly) financial aspects such as the ESG dimensions. We follow Varmaz et al. (2022) optimization model by minimizing portfolio residual risk and imposing a desired level of portfolio systemic risk and ESG score (measured by Bloomberg ESG score) over both an unscreened and a screened sample based on the stocks of the EURO STOXX Index in the period 2007 –2022. Main results indicate that, regardless of the level of portfolio systemic risk, the Sharpe ratio of the optimal portfolios worsens as the target ESG level increases. Further, negative screenings obtain a superior performance with respect to optimization over an unscreened sample only when adopting a very severe screening, implying that very virtuous companies allow investors to do well by doing good. In sum, overall thesis results suggest that sustainable investing can be considered both beyond and behind ESG: “beyond” because it integrates all E, S, G dimensions together while ESG approaches often focus on single dimensions only; “behind” because a relevant part of sustainable investing still consists of simple strategies (e.g. screening strategies) that do not fully exploit the metrics developing in connection with ESG. Thesis results are of interest for many stakeholders, in particular financial intermediaries that are called by the regulator to manage their portfolio in consideration of climate risk and the asset management industry that must consider clients’ sustainable preferences in compliance of the revision of the EU’s MiFID II directive.
"Optimal immunization strategy in multiple period portfolio selection." 2001. http://library.cuhk.edu.hk/record=b5890789.
Повний текст джерелаThesis (M.Phil.)--Chinese University of Hong Kong, 2001.
Includes bibliographical references (leaves 67-68).
Abstracts in English and Chinese.
Chapter 1 --- Background --- p.1
Chapter 1.1 --- Bond and Yield --- p.1
Chapter 1.1.1 --- Bond [8] --- p.1
Chapter 1.1.2 --- Yields --- p.3
Chapter 1.1.3 --- Qualitative Nature of Price-Yield Curves --- p.5
Chapter 1.2 --- "Duration, Convexity and Time Value" --- p.8
Chapter 1.2.1 --- Duration --- p.8
Chapter 1.2.2 --- Qualitative Properties of Duration --- p.10
Chapter 1.2.3 --- Convexity --- p.16
Chapter 1.2.4 --- Literatures Review of Duration and Convexity --- p.17
Chapter 1.2.5 --- Time Value --- p.20
Chapter 2 --- Management of Interest Rate Risk --- p.22
Chapter 2.1 --- Laddered Strategy --- p.23
Chapter 2.2 --- Dumbbell Strategy --- p.24
Chapter 2.3 --- Immunization Strategy --- p.25
Chapter 2.4 --- Consideration of Convexity for Managing Interest Rate Risk --- p.26
Chapter 2.5 --- Duration Targeting[l2] --- p.28
Chapter 2.6 --- Immunizing Default-Free Bond Portfolios with a Duration Vec- tor [2] --- p.29
Chapter 2.7 --- The need of Dynamic Global Portfolio Immunization Theorem --- p.32
Chapter 3 --- Multi-Period Portfolio Selection --- p.34
Chapter 3.1 --- Objective --- p.34
Chapter 3.2 --- Dynamic Programming Formulation --- p.35
Chapter 3.3 --- Specific Situation --- p.46
Chapter 3.4 --- Summary of Implementation Results --- p.59
Chapter 4 --- Summary --- p.64
Bibliography --- p.67
A Matlab Program of the Dynamic Portfolio Selection --- p.69
CHANG, SU-CHU, and 張素珠. "Optimal Portfolios for Middle-Age and Senior Investors: Portfolio Selection Strategy and Analysis." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/3m92tx.
Повний текст джерела國立高雄科技大學
財務管理系
107
This study discusses strategies of assembling the best investment portfolio for future asset allocation in response to concerns of global trends of population aging, sub-placement fertility, and inadequate post-retirement funds. The empirical study of funds in this study consists of three parts: 1) Global Focus Fund + Global High Yield Portfolio; 2) Global Focus Fund + Corporate US Dollar Bond; 3) Global Focus Fund + Global Funds - Global Government Bond Fund. Four portfolio models are adopted: portfolio 1 (70% stock/30% bonds); portfolio 2 (50% stock/50% bonds); portfolio 3 (30% stock/70% bonds); portfolio 4 (20% stock/80% bonds). Three phases are chosen for testing: 2003/01~2018/01; 2008/02~2018/01; 2013/02~2018/01. Returns performance, volatility, and Sharpe ratios for each of the phases are calculated, in order to model portfolios optimal to specific age groups.
田玲菱. "A Study on ETF Portfolio and Optimal Hedging Strategy." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/99092756726424382938.
Повний текст джерелаLIU, MING-YUAN, and 劉明源. "In Search of an Optimal Portfolio Strategy for Institutional Investors." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/55621298821339539202.
Повний текст джерела世新大學
財務金融學研究所(含碩專班)
102
In order to find an optimal strategy for long-term investor, this paper applies Mean-Variance Portfolio model introduced by Markowitz(1952), and choose Tangency portfolio on efficient frontier. The study tries to find out how long the window width (sample period) fits window step length (holding period) best within recent 5 years sample. The performances of portfolio were also estimated and observed by Shrinkage covariance matrix along with sample covariance matrix. With those findingsthe researcher begins with a measurement of portfolio returns from 1991 to 2014. And it finally turned out MV portfolio an optimal strategy against Dow Jones Industrial Average(DJIA) which is used as a benchmark. There also follows some further results: 1. Is not easy to tell the differents of those two kinds covariance matrix method. ShrinkEstimator can indeed reduce the maximum loss. But its performance is weaker than covEstimator when total return is less than the benchmark. 2. In 18 years investment,MV portfolio has made every one dollar into $3.34 compared with DJIA the benchmark turned it into $2.36. It means 98.75% premium. Three major crises lies in the way, especially the 2008 subprime catastrophe, which should make our portfolio suffered serious loss because the bankruptcy of GM, one of the 30 components of DJIA. Fortunately the MV model is keeping away from these traps, and outperforms 10.61% finally during those hard times.
"Optimal execution strategy under CVaR framework." 2013. http://library.cuhk.edu.hk/record=b5549303.
Повний текст джерела由于每次的交易结果都是一个随机变量,为了方便比较,我们可以设置一个比较基准,在本文中我们选用。
本文对之前存在的动态一致性风险测度模型的一大改进是引入了动量效应。在短时的股市中动量效应就有明显效应。
我们的最优策略是当市场朝我们不利的方向变动时我们加速仓位的增加或减少,而朝我们有利的方向变动时我们减缓我们的动作。我们的最优策略每期都会出请或买入一个预先设定的比例的股票,同时我们会在交易的初期加快我们的买卖处理,而在后期放缓动作。
我们的最优策略是时间一致的,并且是一个动态变化的策略。
For an equity trader, one problem he faces is to execute large order of stocks for his clients. The trader seeks to optimize his performance for buying and selling stocks. Basically various costs incurred during the trading includes the commission fees, margin loans, bid-ask spread, price impacts, taxes and other occasional costs. But among the all, the price impact takes the largest part.
In a sell program, the implementation shortfall is the differience between the value of the trader’s initial equity position and the sum of the cash flow he receives from his trading process. Because of the randomness inherited in the stock price process, the resulting implementation shortfall is a random variable, and we should project the random variable into real number to compare. The measure we choose is the dynamic coherent risk measure.
One of the most significant improvements of our model is the inclusion of momentum effect. Momentum is a significant effect when considering stock price dynamics in a daily circle. Another main contribution is the approximation method used in solving our model, which helps reduce much computation burden.
Our strategy applies best to the high frequency trading problem due to the nature of our approximation method. The optimal strategy in our framework is to trade more when the current price drift is negative. This is mainly due to the prevention from future possible negative price drifts. Our strategy also shows that, in addition to liquidate a fixed proportion of inventory at each period, the trader has to trade faster at earlier periods.Our optimal strategy derived from dynamic programming is time consistent and is an adapted process.
Detailed summary in vernacular field only.
Detailed summary in vernacular field only.
Detailed summary in vernacular field only.
Detailed summary in vernacular field only.
Detailed summary in vernacular field only.
He, Mengfei.
Thesis (M.Phil.)--Chinese University of Hong Kong, 2013.
Includes bibliographical references (leaves 132-134).
Abstracts also in Chinese.
Abstract --- p.i
Acknowledgement --- p.iv
Chapter 1 --- Introduction --- p.1
Chapter 2 --- Literature Review --- p.10
Chapter 2.1 --- Model Comparison --- p.10
Chapter 2.1.1 --- Price dynamics --- p.10
Chapter 2.1.2 --- Price impacts --- p.11
Chapter 2.1.3 --- Inventory constraints --- p.14
Chapter 2.1.4 --- Objective functions and risk measures --- p.15
Chapter 2.1.5 --- Discrete or continuous framework --- p.17
Chapter 2.2 --- Work by Bertsimas and Lo --- p.18
Chapter 2.2.1 --- Formulation under Linear Price Impact --- p.21
Chapter 2.2.2 --- Formulation under LPT Law --- p.22
Chapter 2.2.3 --- Formulation under General Price Impact --- p.26
Chapter 2.2.4 --- Portfolio Case --- p.28
Chapter 2.3 --- A Series ofWorks by Almgren --- p.29
Chapter 2.3.1 --- Adaptive Arrival Price --- p.29
Chapter 2.3.2 --- Bayesian Adaptive Trading with a Daily Cycle --- p.32
Chapter 2.3.3 --- Mean-Variance Optimal Adaptive Execution --- p.36
Chapter 2.4 --- Work by Lin and Pena --- p.42
Chapter 2.4.1 --- Multiple Assets --- p.46
Chapter 2.5 --- A Series ofWorks by Forsyth --- p.48
Chapter 2.5.1 --- A Hamilton-Jacobi-Bellman Approach to Optimal Trade Execution --- p.49
Chapter 2.5.2 --- A Mean Quadratic Variation Approach --- p.55
Chapter 2.6 --- A Series ofWorks by Schied --- p.58
Chapter 2.6.1 --- Optimal Trade Execution in Limit Order BookModels --- p.58
Chapter 2.6.2 --- Optimal Trade Execution under Geometric BrownianMotion --- p.66
Chapter 2.7 --- Work byMoazeni --- p.69
Chapter 3 --- Model Setting --- p.71
Chapter 3.1 --- ExecutionModel --- p.71
Chapter 3.2 --- Coherent Dynamic RiskMeasures --- p.81
Chapter 3.3 --- Optimization Formulation --- p.84
Chapter 4 --- Solution Methodologies --- p.89
Chapter 4.1 --- BinomialModel --- p.89
Chapter 4.2 --- Linear Approximation --- p.92
Chapter 4.3 --- Numerical Results --- p.107
Chapter 4.4 --- Simulation Results --- p.110
Chapter 4.5 --- Efficient Frontier --- p.111
Chapter 4.6 --- CVaR Case --- p.113
Chapter 5 --- Conclusions and Future Research --- p.119
Chapter 5.1 --- Conclusions --- p.119
Chapter 5.2 --- Future Research --- p.121
Chapter A --- Equation Derivation --- p.124
Bibliography --- p.132
Huang, Chao-Ta, and 黃肇達. "Optimal Strategy Portfolio and Risk Management--Case Study of Taiwan LCD-TV Industry." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/25120450811097869770.
Повний текст джерела國立交通大學
管理學院碩士在職專班科技管理組
93
When corporation is operating, it would encounter operational risk, strategic risk and financial risk because of the uncertainty of environment. If corporation can take proper risk , corporation can build up core competence. However , corporation could fail if corporation does not manage risks properly. After the success of Taiwan’s semiconductor foundry industry , corporations are investing intensively to TFT-LCD industry by the same manufacturing-base core competence although they do not evaluate the strategic risk systematically. The objective of this research is to build up a ‘strategic risk management model’ by applying the concepts in financial engineering and to help Taiwan’s TFT-LCD TV corporations to develop optimal strategy portfolio for risk management. In this resarch, ‘strategic risk’ can be defined as factors which will effect the goal of the strategy. After applying ‘strategic risk management model’ to Taiwan’s TFT-LCD TV industry, the critical risks can be identified by this research. They are risk of marketing, risk of technology innovation and risk of intensive investment. This research suggests that Taiwan’s TFT-LCD TV corporations can form optimal strategy portfolio for these risks by proper risk handling techniques such as ‘risk exchange’ and ‘risk diversification’.
Hong, De Chuan, and 洪德全. "An optimal strategy of natural hedging for a general portfolio of insurance companies." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/45876141331113264602.
Повний текст джерела國立政治大學
風險管理與保險研究所
98
The mortality rate of human being has decreased year by year due to the improvement of medical and hygienic techniques. With the mortality improvement over time, life insurers may gain a profit and annuity insurers may suffer losses because of longevity risk. However, natural hedging is a feasible strategy to hedge mortality risk and interest risk at the same time. In this paper, we investigate the natural hedging strategy and try to find an optimal collocation of insurance products to deal with longevity risks for the insurance companies. Different from previous literatures, we use the experienced mortality rates from life insurance companies rather than population mortality rates. This experienced mortality data set includes more than 50,000,000 policies which are collected from the incidence data of the whole Taiwan life insurance companies. In general, insurance companies use population mortality rates to price life insurance and annuity products. Nevertheless, the mortality rate of annuity purchasers is averagely lower than that of life insurance purchasers. This situation leads to mispricing problem of both life insurance and annuity products. So in this paper, we can construct four mortality tables (gender, product) and investigate the correlation of these stochastic variation terms of four mortality rates. According to the correlation relation between these four mortality rates, we can offset the variance of portfolio’s change and difference of mispricing. On the basis of the experienced mortality rates, we demonstrate that the proposed model can lead to an optimal collocation of insurance products and effectively apply the natural hedging strategy to a more general portfolio for life insurance companies.
Tsai, Hui-Hua, and 蔡惠華. "Constructing the Optimal Portfolio in Value Stock Picking Strategy: Evidence from Taiwan Stock Market." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/bxtme6.
Повний текст джерела國立彰化師範大學
財務金融技術學系
104
Abstract This study uses Buffet’s, John Neff’s and Trinity Investment Management’s value investing principles to filter out the qualified value stocks by converting stocks every year, and create investment portfolios by those stocks, then compare the portfolios with stock market return rate to see if they bring any abnormal returns. The subjects for this study are Taiwan public limited companies from 2005 to 2014. Then, Treynor Index, Sharpe Index and Jensen Index are used to evaluate the performance of the portfolios, next evaluate the stock selection and timing ability of the portfolios by applying the models of Treynor and Mazuy (1966) and Change and Lewellen (1984), and finally evaluate the long-term performance of the portfolios. The empirical results show as follows: 1.The three value investing principles all bring positive abnormal returns, especially the significance level of John Neff’s principle is higher than Buffett’s. 2.As for the performance evaluation, Treynor and Jensen indexes both evaluate performance with systematic risk β and the result shows the investment portfolio created by applying John Neff’s principle has better performance. As regards Sharpe index, the investment portfolio created by applying Buffet’s principle has better risk diversification effect. 3.As for the stock selection and timing ability, in Treynor and Mazuy model, it shows the investment portfolio created by applying John Neff’s principle has better stock selection ability; besides, only the investment portfolio created by applying Trinity Investment Management’s principle has timing ability. On the other hand, in Change and Lewellen model, it shows only the investment portfolio created by applying John Neff’s principle has better stock selection ability; as for the timing ability, the three value investment portfolios all have timing ability. 4.As for the long-term performance evaluation, the investment portfolios created by the three value investing principles all show long-term positive performance, and among the three principles, in Taiwan’s stock market, John Neff’s principle is more suitable than Buffet’s for long-term holding.
Lin, Feng, and 鳳霖. "Constructing the Optimal Portfolio in Value Stock Picking Strategy─A Case of the Taiwan Stock Market." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/mu8pr4.
Повний текст джерела國立屏東科技大學
財務金融研究所
101
The position of the investors to verify the modern investment Master’s surprisingly winning stock picking strategy in this study. Make good use of Warren Buffett combination of Peter Lynch wisdom their successful strategy. By analysis of the fundamentals to find the Value Stock and as the purpose of the investment. The selection of the company has the potential with the core of value Investing. Buy a reasonable price when the share price fell sharply. On the contrary, sell when the share price rose sharply. In this study,we take Price/Earnings Ratio, P/E、Price to Book Ratio,P/B、Price/Sales Ratio,P/S、Earning per share,EPS、Current Ratio 、Earnings Growth Rate for measurable indicators. The deeper meaning of depth behind the reported figures, the simple and profitable stocks election rule from the induction. To avoid errors,We execute the normal distribution test to screened out Value Stock. Using the Markowitz「Mean-Variance optimization」to obtain the Efficient Frontier, and portfolio performance evaluation. We can find a consequent of the empirical Investment Law in the Taiwan Stock Market in this study. Warren Buffett combined with Peter Lynch, elect the stocks which is stable growth of the company. Average more than 15% growth of the level in Returns on Equity every year. It can be transcend market index,when the portfolio performance is up to 10.29% the risk-free rate of investment performance. R / R Ratio and M2 Index to sixmonths of investment strategy obtain the best performance. Make funds in a safe and efficient market as a referable principle of stock picking strategy retail investors which in the Taiwan Stock Market.
Klůjová, Jana. "Stínové ceny a řízení portfolia s proporcionálními transakčními náklady." Master's thesis, 2013. http://www.nusl.cz/ntk/nusl-321391.
Повний текст джерелаNěmec, Jan. "Dynamické strategie obchodování." Master's thesis, 2015. http://www.nusl.cz/ntk/nusl-336719.
Повний текст джерелаNěmec, Jan. "Dynamické strategie obchodování." Master's thesis, 2014. http://www.nusl.cz/ntk/nusl-340906.
Повний текст джерелаHerzog, Florian. "Strategic portfolio management for long-term investments : an optimal control approach /." 2005. http://e-collection.ethbib.ethz.ch/ecol-pool/diss/abstracts/p16137.pdf.
Повний текст джерелаChen, Yun-Hui, and 陳芸慧. "Optimal Data Size in the Investment Strategy Combining the Bear and the Bull Market Portfolios." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/95s2vp.
Повний текст джерела銘傳大學
經濟學系碩士班
95
A new approach of technical analysis with respect to portfolio investment is suggested from this study, as it combines both the bull and the bear market portfolios without taking any hedging position from related derivative markets. At the beginning, a combinatory strategy of having both bull and bear market portfolios as the investment and the hedging positions or vice verse is empirically studied. However, it is found that this kind of investment strategy may be theoretically but not empirically applicable. Since both bull and bear market portfolios are negatively correlated with each other in nature, it is absolutely wise to take at a time only the right side to invest. Obviously, the key to make a successful execution is to have a good control on the timing of switch between the bull and the bear market portfolios, and this in turn, relies totally on the optimal data size to be used in the analytical work. Furthermore, in order to dissolve the concern of having no hedging position, applying additional stock price data in shorter tern for more analyses will be suggested from this study, and this also serves as the continued effort of this study in the future.
Sulima, Anna. "Optimal portfolio selection in an Itô-Markov Black-Scholes-Merton market." Praca doktorska, 2019. https://ruj.uj.edu.pl/xmlui/handle/item/87990.
Повний текст джерелаMajhi, S. G., A. Anand, A. Mukherjee, and Nripendra P. Rana. "The optimal configuration of IT-enabled dynamic capabilities in a firm’s capabilities portfolio: A strategic alignment perspective." 2021. http://hdl.handle.net/10454/18497.
Повний текст джерелаAlthough IT-enabled dynamic capabilities (ITDCs) add value to firms operating in turbulent and rapidly changing environments, firms face several challenges in developing, deploying, and maintaining the right portfolio of ITDCs. Since ITDCs are not uniformly advantageous, firms need to make strategic decisions in order to accomplish the complex task of achieving optimal ITDC configurations. This conceptual paper draws on the strategic alignment perspective to identify the optimal configuration of ITDCs for a firm based on its business strategy orientation indicated by the Miles and Snow typology. This paper first explicates the theoretically ideal configurations of ITDCs based on the competitive strategy patterns associated with each Miles and Snow archetype and then develops a model for measuring the strategic fit of ITDCs. This paper contributes to the literatures on ITDCs and strategic alignment by identifying optimal ITDC configurations and by conceptualizing the strategic fit of ITDCs respectively.
The full text will be available at the end of the publisher's embargo: 24th May 2022
Wei-JhihJhuang and 莊崴智. "The Study of Optimum Bid Decision of Construction Portfolios Based on Integrated Bidding Strategy Model." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/31489513947404451978.
Повний текст джерела國立成功大學
建築學系
103
This research aims to establish a complete bidding strategy model when bidders have multiple bidding options. First, the bidding behavior was discussed by reviewing the literature, then the existing bidding strategy model was conceived. The applicability and advantage or disadvantage of the theory and required tools used for such a model was analyzed. The major problem of the bidding strategy was defined and the Optimal Bid Decision of Construction Portfolios Based on Integrated Bidding Strategy Model was then developed. Finally, the feasibility of the proposed model was validated by an individual case study, which was then compared with the highest expected utility of Carr. The result shows that the bidding suggestion obtained from the proposed model exhibits a higher expected utility, revenue and net present value, which is more accurate and practical.