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Lundvik, Andreas. "Portfolio insurance methods for index-funds." Thesis, Uppsala University, Department of Mathematics, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-121382.
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Steyn, Dirk. "Portfolio construction using index regression models." Master's thesis, University of Cape Town, 2008. http://hdl.handle.net/11427/4933.
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Includes bibliographical references (leaves 130-130).In this dissertation we review the Sharpe Index Model and an innovation on this model introduced by Hossain, Troskie and Guo (2005b). These models are extended to the multi index framework. We then empirically investigate the impact of the models on portfolio creation over an extensive data set. Next we extend these models by modelling the regression residuals as ARMA and GARCH(l, 1) processes and investigate the effect on the resulting portfolios. We then introduce the topic of bounded influence regression and apply it to financial data by down weighting extreme returns prior to regression. A new weighting function is introduced in this dissertation and the effects on the efficient frontiers and resulting market portfolios for the chosen set of shares are investigated.
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Chan, Kwei-sang, and 陳貴生. "Hongkong stock index future and portfolio management." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1989. http://hub.hku.hk/bib/B31264232.
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Sant'anna, Leonardo Riegel. "Essays on index tracking and portfolio optimization." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2017. http://hdl.handle.net/10183/168929.
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Esta tese tem foco no tema de otimização de carteiras de investimento modeladas para estratégia de investimento de index tracking. O conteúdo final é composto por três artigos. O primeiro artigo é intitulado “Index Tracking with Controlled Number of Assets Using a Hybrid Heuristic Combining Genetic Algorithm and Non-linear Programming”, e foi aceito para publicação na revista Annals of Operations Research. O segundo artigo é “Index Tracking and Enhanced Indexing using Cointegration and Correlation with Endogenous Portfolio Selection”, e foi aceito para publicação na revista Quarterly Review of Economics and Finance. Por fim, o terceiro artivo é “Investigating the Use of Statistical Process Control Charts for Index Tracking Portfolios”, o qual já foi submetido e está atualmente em processo de revisão. No primeiro artigo, discutimos a estratégia de investimento de index tracking usando programação matemática. Primeiro, usamos uma formulação de programação não linear para o problema de index tracking, considerando um número limitado de ações. Devido à dificuldade de solução do problema em um intervalo de tempo razoável por pacotes matemáticos comerciais, aplicamos uma abordagem de solução híbrida, combinando programação matemática e algoritmo genético. Com a aplicação de testes, demonstramos a eficiência da abordagem proposta comparando os resultados com soluções ótimas, com métodos previamente desenvolvidos, e com dados reais de índices de mercado. Os experimentos computacionais focam no Ibovespa (o mais popular índice do mercado brasileiro), e também apresentamos resultados para mercados consolidados tais quais S&P 100 (Estados Unidos), FTSE 100 (Reino Unido) and DAX (Alemanha). A estrutura proposta apresenta sua abilidade para obter ótimos resultados (resultados com gap em relação às soluções ótimas menores que 5% em 8 minutos de tempo de processamento) até mesmo para índices de mercado com alta volatilidade em um mercado em desenvolvimento. No segundo artigo, a atenção é voltada para a análise de dois métodos alternativos entre si para solução do problema de otimização de index tracking. Esse artigo investiga o desempenho “fora da amostra” dos métodos de correlação e cointegração para as estratégias de index tracking (IT) e enhanced indexing (EIT) aplicadas aos dados de mercado Brasileiro e Norte-americano. Nosso objetivo é comparar ambos os métodos na medida em que exploramos fortemente a cointegração em relação a estudos prévios: nós transformamos a seleção do portfólio endógena ao problema de otimização nessa abordagem. Os testes foram executados utilizando dados de 2004 a 2014 com amostras de 57 ações para dados brasileiros, e 96 ações para dados dos Estados Unidos; carteiras foram construídas usando combinações de no máximo 10 ações. Apesar da realização de testes extensivos, os resultados gerais demonstraram desempenho similar para ambos os métodos. Para IT no mercado brasileiro, foi verificado um trade-off entre melhor erro de tracking e maior turnover com cointegração (com resultados opostos para correlação), sendo que este mesmo padrão não foi encontrado para dados norte-americanos. Os resultados para EIT também não apresentação claro favorecimento para cointegração ou correlação. Por fim, o terceiro artigo é dedicado à discussão a respeito do uso de processo estatístico de gráficos de controle para regulação de carteiras de index tracking. Nesse artigo, nosso objetivo é introduzir uma abordagem baseada em gráficos de controle (SPC) para monitorar o processo de rebalanceamento de carteiras de index tracking. O método de SPC é derivado da Estatística e da Engenharia, como ferramenta para controle de processos de produção. Para cumprir os objetivos, aplicamos gráficos de controle EWMA (do inglês, exponentially weighted moving average) para monitorar carteiras de IT baseadas no uso combinado de dois gráficos de controle: desempenho de carteiras em termos de erro de tracking e em termos de volatilidade. Assim, visamos tornar endógeno o controle do processo de rebalanceamento das carteiras baseado em seu desempenho e em suas condições de risco ao longo do tempo. Testes computacionais foram realizados para avaliar a abordagem desenvolvida em comparação com a estratégia tradicional de rebalanceamento (que consiste no uso de janelas fixas de tempo para atualização das carteiras), usando dados dos mercados brasileiro e norte-americano de 2005 a 2014. Os métodos de cointegração e correlação foram aplicados para otimização das carteiras. Os resultados demonstraram que a abordagem com SPC pode ser uma alternativa viável para o processo de rebalanceamento de carteiras.
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Van, Dyk Francois. "Portfolio diversification index as a measure to improve investment portfolio performance / Francois van Dyk." Thesis, North-West University, 2008. http://hdl.handle.net/10394/4193.
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Diversification is one of the three most prominent elements of portfolio management with risk and return being the other two. In addition, diversification is a core objective for combining assets and is a central tenet of portfolio construction. It is also widely known that diversification is concerned with the number of unrelated sources of return and in essence the aim of diversification is to eliminate unsystematic risk from an investment portfolio while systematic risk will remain as it can not be diversified away. This study focuses on the concept of diversification in an investment portfolio setting, while specifically investigating a relatively "new" diversification measure, the Portfolio Diversification Index (PDI).
The objectives of this study are twofold. First, establishing whether or not the PDI is a good diversification measure compared to the conventional/traditional and widely used residual variance method. The traditional method of measuring diversification remains inexact as this method measures portfolio diversification relative to a market index. When the market index itself is, however, poorly or not appropriately diversified it becomes problematic as the diversification measurement of the residual variance method is influenced. The PDI is a diversification measurement concept which is essentially free from the influences of the overall market index. This relatively "new" measure of diversification, the PDI, is based on the number of independent factors observed in a portfolio. These independent factors are quantified using Principal Components Analysis (PCA). In ascertaining the first objective the PDI battles "head-to-head" against the residual variance method of diversification by comparing fund ranking results of five South African unit trusts. This method of testing is used as no suitable statistical method exists. The fund ranking results of the two diversification measures are compared to a number of risk performance measures, including the Sharpe- and Sortino ratios. Extensive use is also made of the Omega ratio in this study as the Omega emerges as the dominant risk performance measure.
The second objective of this study is to determine whether the PDI can be used as a tool by fund managers to assist in constructing funds (or changing the composition of existing fund) to reduce (or minimise) portfolio risk without a concomitant reduction in portfolio return. The PDI is used to determine the most independent factors of a South African unit trust where after' this fund is optimised, using the information of the independent factors, in order to reduce the risk of this fund. The Omega ratio is used to evaluate the results of the PDI while the marginal portfolio diversification concept is also investigated.
A thorough literature study also presents the most relevant and important concepts and topics of the theory, management and construction of portfolios. Throughout the literature study the concept of diversification along with the topics most relevant to diversification are extensively focused and elaborated on.
The method of testing used not only confirms that the PDI is a good diversification measure compared to the residual variance method, but that the PDI can also be used as a tool when constructing (or changing the composition of an existing portfolio) in order to reduce the portfolio risk without a concomitant reduction in portfolio return.Thesis (M.Com. (Risk Management))--North-West University, Potchefstroom Campus, 2009.
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Poon, Hing Chuen. "The performance of non-index individual stocks and stock portfolios relative to the index." HKBU Institutional Repository, 2020. https://repository.hkbu.edu.hk/etd_oa/891.
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Extensive empirical evidence shows that passively managed index-tracking mutual funds and exchange-traded funds (ETFs) outperform actively managed portfolios. On the other hand, there are abundant findings that stocks admitted to an index outperform those deleted from the index. This study tests an issue that has been largely ignored in academic studies but is highly related to the above two seemingly disparate areas of researches. The paper examines the long-term performance of non-index individual stocks and stock portfolios relative to the index. The study proposes that the inclusion and maintenance criteria for index component stocks are long-term performance indicators. Therefore, an index can be regarded as a passively managed and highly diversified portfolio of expected outperformers. Using a complete set of H-shares listed on HKEx for the period 2001 to 2017, the study finds that 44.25% (55.75%) of individual stocks have positive alphas (negative alphas) relative to the index. The average alpha for the family of all non-index stock is negative but statistically insignificant, i.e., 77 positive alphas and 97 negative alphas. Most alphas are statistically insignificant, but only 5 are positive, and 2 are negative at 5% significance level. From the risk and return perspective, the index dominates two-third of the non-index H-shares. Regression analyses show that H-index outperforms non-index H-shares in general and the market capitalization and turnover ratio play an important role in determining the long-term performance of H-shares, which are the major factors for the admission and maintenance criteria of H-index. The findings strongly support our conjecture that the index admission and maintenance criteria are the quality assurance of individual constituent stocks of an index. The paper provides incremental evidence on the widely documented result that index trackers outperform actively managed portfolios. Nevertheless, the study extends the recent literature on the long-term performance of stocks that are admitted to (or excluded from) an index. The findings of the study have significant implications for securities markets participants, including index providers and ETF issuers
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Ericsson, Oskar. "Risk Analysis Against Electricity Market Index and Portfolio Optimisation." Thesis, KTH, Matematisk statistik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-146657.
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There has been a lack of a transparent index to compare electricity portfolios against for many years. Most industrial firms hedge the risks for their electricity needs by buying forward contracts which guarantee the price of a certain amount of power for a year or part of a year. The problem is to know if the company has made good deals since the available comparisons are average spot prices. In this thesis the objectives are to construct a relevant index and then evaluate possible portfolios against this index, giving risk measures such as Value-at-Risk and Expected Shortfall. The resulting index buys a small part of the needed power amount to each trading day’s closing price of the forward contracts traded by the portfolio. Thus, the index buys the volume wanted power amount divided by number of trading days of the used forward contracts each trading day the contracts are available. Another objective is to suggest an optimal trading policy that minimise the expected portfolio cost based on historical price data. This is evaluated by constrained optimisation algorithms. Suggestions for the optimal hedge volumes and when to buy the forward contracts are given based on the historical prices. This reveals how expensive different forward contracts are relative to spot prices for the respective period.Det har länge saknats ett transparent index att jämföra elhandelsportföljer med. De flesta industriföretag säkrar priser för sina elektricitetsbehov genom att köpa terminskontrakt som garanterar ett visst pris för ett år eller för delar av år. Detta görs för att inte utsättas för risker med höga spotpriser. Problemet blir för företaget att veta om det har gjort bra affärer eftersom det saknas relevanta jämförelser, till exempel är det missvisande att jämföra mot spotpriser vilka främst påverkas av väderprognoser. Målen med denna uppsats är att skapa ett relevant index, för att sedan jämföra elhandelsportföljer med index genom att ge riskmått som Value-at-Risk och Expected Shortfall. Indexportföljen handlar en liten och lika stor volym till varje handelsdags stängningspris för respektive terminskontrakt. Alltså, index handlar bestämd effekt delat med antal handelsdagar i varje använt terminskontrakt under varje handelsdag som respektive terminskontrakt finns tillgängligt. Ett ytterligare mål med denna studie är att utvärdera handelsstrategier för dessa kontrakt för att föreslå en optimal strategi som minimerar den förväntade portföljkostnaden utifrån historiska priser. Detta görs genom optimeringsalgoritmer. Förslag till optimala volymer som säkras med terminskontrakt och när kontrakten ska köpas ges utifrån historiska priser. Detta anger hur dyra terminskontrakten är relativt spotpriserna för respektive period.
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Mezali, Hakim. "Methods for solving problems in financial portfolio construction, index tracking and enhanced indexation." Thesis, Brunel University, 2013. http://bura.brunel.ac.uk/handle/2438/10183.
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The focus of this thesis is on index tracking that aims to replicate the movements of an index of a specific financial market. It is a form of passive portfolio (fund) management that attempts to mirror the performance of a specific index and generate returns that are equal to those of the index, but without purchasing all of the stocks that make up the index. Additionally, we consider the problem of out-performing the index - Enhanced Indexation. It attempts to generate modest excess returns compared to the index. Enhanced indexation is related to index tracking in that it is a relative return strategy. One seeks a portfolio that will achieve more than the return given by the index (excess return). In the first approach, we propose two models for the objective function associated with choice of a tracking portfolio, namely; minimise the maximum absolute difference between the tracking portfolio return and index return and minimise the average of the absolute differences between tracking portfolio return and index return. We illustrate and investigate the performance of our models from two perspectives; namely, under the exclusion and inclusion of fixed and variable costs associated with buying or selling each stock. The second approach studied is that of using Quantile regression for both index tracking and enhanced indexation. We present a mixed-integer linear programming of these problems based on quantile regression. The third approach considered is on quantifying the level of uncertainty associated with the portfolio selected. The quantification of uncertainty is of importance as this provides investors with an indication of the degree of risk that can be expected as a result of holding the selected portfolio over the holding period. Here a bootstrap approach is employed to quantify the uncertainty of the portfolio selected from our quantile regression model.
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Mayorca, Huamán Ellen, and Andía Giovanna Aguilar. "Competition and loan portfolio quality in the Peruvian microfinance market, 2003-2015." Economía, 2017. http://repositorio.pucp.edu.pe/index/handle/123456789/117172.
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The aim of this study is to analyze the relationship between competition and loan portfolio quality in the Peruvian microfinance sector. To make this analysis the market is segmented into three groups of microfinance microfinance institutions IMFs), considering the average volume of its loans. So that, in the first group (large IMFs) entities of higher average volume of loans are located, in the second group (medium IMFs) entities with an average volume of loans are located and finally, in the third group (small IMFs) are entities with lower average loan volumes.This segmentation reflects the heterogeneity of size for loans between IMFs. The results show the Lerner index decreasing over time, for both the group of large IMFs and the group of small IMFs, showing a decrease of market power and increased competition in these two groups of entities. In the group of medium IMFs behavior Lerner index shows a growing trend in the last months of the period studied thus indicating a greater market power and less competition in this group of microfinance operators. On the other hand, an inverse relationship between the Lerner index over delinquency rate in the three groups of IMFs is found, implying that increased competition in the Peruvian microfinance market has deteriorated the quality of loan portfolio the period analyzed. This result is obtained by controlling the behavior of other important variables to explain the delinquency rate such as the business cycle, credit expansion, efficiency and profitability of institutions, and the effect of the international financial crisis of 2008.El objetivo de este estudio es analizar la relación que existe entre la competencia y la calidad de cartera en el sector microfinanciero peruano en el periodo 2003-2015. Como indicador de competencia se emplea el poder de mercado estimado por el Índice de Lerner y como indicador de calidad de cartera se utiliza la tasa de morosidad. El análisis segmenta el mercado microfinanciero en tres grupos de instituciones microfinancieras (IMF), considerando el volumen promedio de sus colocaciones, de manera que, en el primer grupo se ubican las entidades con un mayor volumen promedio de colocaciones, en el segundo grupo se encuentran las entidades con un volumenmedio de colocaciones y finalmente, en el tercer grupo se ubican las entidades con menor volumen promedio de colocaciones. Esta segmentación refleja la heterogeneidad de tamaño que existe entre estas entidades. Los resultados muestran un Índice de Lerner decreciente, para el primer y el tercer grupo, evidenciando una mayor competencia. En el segundo grupo, el comportamientodel Índice de Lerner muestra una tendencia creciente en los últimos meses del periodo estudiado, reflejando una menor competencia. Por otro lado, se evidencia una relación inversa entre el Índice de Lerner y la morosidad en los tres grupos, lo que implica que el aumento de competencia en el mercado microfinanciero ha generado un deterioro en la calidad de cartera crediticia. Esteresultado se obtiene controlando el comportamiento de otras variables como son: el ciclo económico, la expansión de los créditos, la eficiencia y la rentabilidad de las instituciones, además del efecto de la crisis financiera internacional del 2008.
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Otto, Hans-Philipp. "Portfolio optimization : equally weighting strategies vs. index investing vs. efficient frontier portfolios : an empirical analysis." Thesis, Stellenbosch : Stellenbosch University, 2012. http://hdl.handle.net/10019.1/95621.
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Thesis (MBA)--Stellenbosch University, 2012.This research report is conducted in the field of portfolio optimization. Regarding the existing literature this research paper is set in context of the academic discussion triggered by DeMiguel, Garlappi and Uppal (2009) concerning the perfomance of the naïve investment strategy in comparison to optimized portfolios and extended by the indexing approach. Therefore, it investigates on the question whether the naïve investment strategies outperform the strategy of index investing as well as the minimum and mean variance portfolios in the investment horizon of the EURO STOXX 50 in the timeframe from 03.01.2003 to 02.07.2010. Outperforming is defined via the following measurements, namely return, variance, Sharpe ratio, value at risk, certainty equivalent return and turnover rate. In addition, modifications of the investment strategies are applied such as the rebalancing of the naïve investment strategy and different scenarios are included such as the consideration of transaction costs and costs of index investing as well as the usage of two different data frequencies in order to conduct the robustness test. The two main measurements Sharpe ratio and value at risk are verified regarding their explanatory power by the usage of the robust inference method for the bootstrapping of the Sharpe ratio and the Jarque-Bera test for the normal distribution required for the value at risk measurement. The research in this paper is conducted through MATLAB which is a numerical computing environment and fourth-generation programming language. The aggregated outcome of this research paper in regard to the respective timeframe and investment horizon is that in the main scenario which is based on weekly input data the minimum variance investment strategy outperforms all other investment strategies consistently in all measurements except for the turnover which is compensated by consistent results in case of inclusion of transaction costs and costs of index investing. Furthermore, the rebalanced naïve investment strategy and the index investing strategy share the second place with a slight advantage in the overall perspective for the rebalanced naïve investment strategy as it dominates the index investing strategy in regard of return, Sharpe ratio and certainty equivalent return while it is only outranked by the index investing strategy in the risk related measurements variance and value at risk. All other investment strategies underperform their peers.
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Kim, Dongwook S. M. Massachusetts Institute of Technology. "Adjusted pure-play portfolio REIT equity index : historical performance of public and privacy real estate investment." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/42041.
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Thesis (S.M. in Real Estate Development)--Massachusetts Institute of Technology, Dept. of Architecture, 2007.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references (leaf 42).
The public real estate market was initiated by the Real Estate Investment Trust Act of 1960. Since then, investors have been concerned with the assessment of performance comparisons between publicly held assets and privately held assets. The main concern for the assessment is to reveal historically which type of ownership provided the more efficient vehicle for the investors. The National Council of Real Estate Investment Fiduciaries (NCREIF) provides the investment performance of privately held commercial real estate, and the National Association of Real Estate Investment Trust (NAREIT) provides that of publicly held commercial real estate by REITs. However, direct comparison between the two indexes is problematic due to the different characteristics of each market and the lack of historical data for accurate assessment. The primary purpose of this study is to adjust characteristics of commercial REIT assets underlying one portfolio to match the characteristics of privately held commercial assets. Since SNL data base provides hedonic data from 1995 and CRSP & Compustat merged data base provides up to 2005 Q4, the sample period of this research is from 1995 Q1 to 2005 Q4. This quarterly assessment is conducted at the property sector (retail, apartment, office and industrial), then at the aggregate level. The main research of this thesis is to create adjusted REIT equity index that is derived from the following treatments in the thesis. Pure-Play' Portfolio Methodology will be applied to replicate the performance of four real estate property-type sectors defined by NCREIF - Implemented updated Equity to Total Asset ratio from De-leveraging REIT returns by WACC formula based on CRSP and Compustat merged data to obtain the value weights of equity, debt and total assets.
(cont.) As a proxy for the returns of debts held by REITs, Gilberto-Levy Historical Mortgage Rate will be used as a proxy for the returns of debts held by REITs. Sector-Mix Adjustment according to NCREIF sector weights. REIT index investment cost proxied by Vanguard REIT fund expense (95-05) will be deducted from adjusted REIT equity index. In this thesis, private real estate equity investment performance is represented by the MIT Transaction Based Index (TBI) and NCREIF Property Index (NPI). Both TBI and NPI returns are deducted by asset management fees estimated by the NFI-ODCE index (NCREIF) over the same time period. Purpose of these adjustments is to improve evaluation of publicly and privately held commercial real estate asset investment performances relative to one another. Preliminary comparison between NAREIT equity REIT index and NPI quarterly returns from 1995-2005 was conducted to collect the mean return difference. Then the difference after the treatments was compared to observe the effects of the author's method. The results demonstrate that at the aggregate level the difference between REIT and NPI returns reduced from 1.08% to 0.74%, and the difference between REIT and TBI returns reduced from 1.64% to 0.18%.
by Dongwook Kim.
S.M.in Real Estate Development
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Ngundze, Unathi. "Statistical comparison of international size-based equity index using a mixture distribution." Thesis, Nelson Mandela Metropolitan University, 2011. http://hdl.handle.net/10948/d1012367.
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Investors and financial analysts spend an inordinate amount of time, resources and effort in an attempt to perfect the science of maximising the level of financial returns. To this end, the field of distribution modelling and analysis of firm size effect is important as an investment analysis and appraisal tool. Numerous studies have been conducted to determine which distribution best fits stock returns (Mandelbrot, 1963; Fama, 1965 and Akgiray and Booth, 1988). Analysis and review of earlier research has revealed that researchers claim that the returns follow a normal distribution. However, the findings have not been without their own limitations in terms of the empirical results in that many also say that the research done does not account for the fat tails and skewness of the data. Some research studies dealing with the anomaly of firm size effect have led to the conclusion that smaller firms tend to command higher returns relative to their larger counterparts with a similar risk profile (Banz, 1981). Recently, Janse van Rensburg et al. (2009a) conducted a study in which both non- normality of stock returns and firm size effect were addressed simultaneously. They used a scale mixture of two normal distributions to compare the stock returns of large capitalisation and small capitalisation shares portfolios. The study concluded that in periods of high volatility, the small capitalisation portfolio is far more risky than the large capitalisation portfolio. In periods of low volatility they are equally risky. Janse van Rensburg et al. (2009a) identified a number of limitations to the study. These included data problems, survivorship bias, exclusion of dividends, and the use of standard statistical tests in the presence of non-normality. They concluded that it was difficult to generalise findings because of the use of only two (limited) portfolios. In the extension of the research, Janse van Rensburg (2009b) concluded that a scale mixture of two normal distributions provided a more superior fit than any other mixture. The scope of this research is an extension of the work by Janse van Rensburg et al. (2009a) and Janse van Rensburg (2009b), with a view to addressing several of the limitations and findings of the earlier studies. The Janse van rensburg (2009b) study was based on data from the Johannesburg Stock Exchange (JSE); this study seeks to compare their research by looking at the New York Stock Exchange (NYSE) to determine if similar results occur in developed markets. For analysis purposes, this study used the statistical software package R (R Development Core Team 2008) and its package mixtools (Young, Benaglia, Chauveau, Elmore, Hettmansperg, Hunter, Thomas, Xuan 2008). Some computation was also done using Microsoft Excel. This dissertation is arranged as follows: Chapter 2 is a literature review of some of the baseline studies and research that supports the conclusion that earlier research finding had serious limitations. Chapter 3 describes the data used in the study and gives a breakdown of portfolio formation and the methodology used in the study. Chapter 4 provides the statistical background of the methods used in this study. Chapter 5 presents the statistical analysis and distribution fitting of the data. Finally, Chapter 6 gives conclusions drawn from the results obtained in the analysis of data as well as recommendations for future work.
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Sacks, Maxwell. "Neural Networks: Building a Better Index Fund." Scholarship @ Claremont, 2017. http://scholarship.claremont.edu/cmc_theses/1666.
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Big data has become a rapidly growing field amongst firms in the financial sector and thus many companies and researchers have begun implementing machine learning methods to sift through large portions of data. From this data, investment management firms have attempted to automate investment strategies, some successful and some unsuccessful. This paper will investigate an investment strategy by using a deep neural network to see whether the stocks picked from the network will out or underperform the Russell 2000.
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Singh, Alex. "A risk-transaction cost trade-off model for index tracking." Thesis, KTH, Matematisk statistik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-143807.
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This master thesis considers and evaluates a few different risk models for stock portfolios, including an ordinary sample covariance matrix, factor models and an approach inspired from random matrix theory. The risk models are evaluated by simulating minimum variance portfolios and employing a cross-validation. The Bloomberg+ transaction cost model is investigated and used to optimize portfolios of stocks, with respect to a trade off between the active risk of the portfolio and transaction costs. Further a few different simulations are performed while using the optimizer to rebalance long-only portfolios. The optimization problem is solved using an active-set algorithm. A couple of approaches are shown that may be used to visually try to decide a value for the risk aversion parameter λ in the objective function of the optimization problem. The thesis concludes that there is a practical difference between the different risk models that are evaluated. The ordinary sample covariance matrix is shown to not perform as well as the other models. It also shows that more frequent rebalancing is preferable to less frequent. Further the thesis goes on to show a peculiar behavior of the optimization problem, which is that the optimizer does not rebalance all the way to 0 in simulations, even if enough time is provided, unless it is explicitly required by the constraints.
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Blomkvist, Oscar. "Smart Beta - index weighting." Thesis, KTH, Matematisk statistik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-168745.
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This study is a thesis ending a 120 credit masters program in Mathematics with specialization Financial Mathematics and Mathematical Statistics at the Royal Institute of Technology (KTH). The subject of Smart beta is defined and studied in an index fund context. The portfolio weighting schemes tested are: equally weighting, maximum Sharpe ratio, maximum diversification, and fundamental weighting using P/E-ratios. The outcome of the strategies is measured in performance (accumulated return), risk, and cost of trading, along with measures of the proportions of different assets in the portfolio. The thesis goes through the steps of collecting, ordering, and ”cleaning” the data used in the process. A brief explanation of historical simulation used in estimation of stochastic variables such as expected return and covariance matrices is included, as well as analysis on the data’s distribution. The process of optimization and how rules for being UCITS compliant forms optimization programs with constraints is described. The results indicate that all, but the most diversified, portfolios tested outperform the market cap weighted portfolio. In all cases, the trading volumes and the market impact is increased, in comparison with the cap weighted portfolio. The Sharpe ratio maximizer yields a high level of return, while keeping the risk low. The fundamentally weighted portfolio performs best, but with higher risk. A combination of the two finds the portfolio with highest return and lowest risk.Denna studie är ett examensarbete som avslutar ett 120 poängs mastersprogram i Matematik med inriktning mot Finansiell Matematik och Matematisk Statistik på Kungliga Tekniska Högskolan (KTH). Ämnet Smart beta studeras i kontexten av en indexfond, där de olika testade principerna för viktning i portföljerna är: likaviktad, maximerad Sharpe-kvot, maximerad diversifiering, och fundamental viktning användandes av P/E-tal. Utfallet i testerna utvärderas i ackumulerad avkastning, portföljrisk, kostnad att handla i portföljen, och ett antal mått på fördelningen av tillgångarna. Studien går stegvis igenom processen för att samla in, ordna, och ”tvätta” data. En kort förklaring av historisk simulering, metoden för att estimera stokastiska variabler såsom kovariansmatriser, är inkluderad, såväl som en analys av distributionen av data. Processen för att optimera portföljerna och hur regler för att vara en UCITS-fond kan omformas till optimeringsvillkor beskrivs. Resultaten indikerar att alla utom den mest diversifierade portföljen har högre ackumulerad avkastning än den marknadsviktade portföljen under testperioden. I alla testade fall ökar handelsvolymen liksom marknadspåverkan när en annan strategi än marknadsviktad används. Portföljen med maximerad Sharpe-kvot ger en hög avkastning med bibehållen låg risk. Den fundamentalt viktade portföljen ger bäst avkastning, men med en litet förhöjd risk. Kombinationen av de båda metoderna ger den portföljen med högst ackumulerad avkastning och samtidigt lägst risk under testperioden.
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Grishina, Nina. "A behavioural approach to financial portfolio selection problem : an empirical study using heuristics." Thesis, Brunel University, 2014. http://bura.brunel.ac.uk/handle/2438/9173.
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The behaviourally based portfolio selection problem with investor's loss aversion and risk aversion biases in portfolio choice under uncertainty are studied. The main results of this work are developed heuristic approaches for the prospect theory and cumulative prospect theory models proposed by Kahneman and Tversky in 1979 and 1992 as well as an empirical comparative analysis of these models and the traditional mean variance and index tracking models. The crucial assumption is that behavioural features of the (cumulative) prospect theory model provide better downside protection than traditional approaches to the portfolio selection problem. In this research the large scale computational results for the (cumulative) prospect theory model have been obtained. Previously, as far as we aware, only small laboratory (2-3 arti cial assets) tests has been presented in the literature. In order to investigate empirically the performance of the behaviourally based models, a differential evolution algorithm and a genetic algorithm which are capable to deal with large universe of assets have been developed. The speci c breeding and mutation as well as normalisation have been implemented in the algorithms. A tabulated comparative analysis of the algorithms' parameter choice is presented. The performance of the studied models have been tested out-of-sample in different conditions using the bootstrap method as well as simulation of the distribution of a growing market and simulation of the t-distribution with fat tails which characterises the dynamics of a decreasing or crisis market. A cardinality and CVaR constraints have been implemented to the basic mean variance and prospect theory models. The comparative analysis of the empirical results has been made using several criteria such as CPU time, ratio between mean portfolio return and standart deviation, mean portfolio return, standard deviation , VaR and CVaR as alternative measures of risk. The strong in uence of the reference point, loss aversion and risk aversion on the prospect theory model's results have been found. The prospect theory model with the reference point being the index is compared to the index tracking model. The portfolio diversi cation bene t has been found. However, the aggressive behaviour in terms of returns of the prospect theory model with the reference point being the index leads to worse performance of this model in a bearish market compared to the index tracking model. The tabulated comparative analysis of the performance of all studied models is provided in this research for in-sample and out-of-sample tests.
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Petzer, Greydon E. "Portfolio asset selection through the use of modified moving averages and steepest gradient techniques." Thesis, Stellenbosch : Stellenbosch University, 2001. http://hdl.handle.net/10019.1/52406.
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Thesis (MBA)--Stellenbosch University, 2001.ENGLISH ABSTRACT: Many tracker funds exist in the South African market in which investors can invest their money. Growing in:popularity is the index funds that, instead of investing in individual shares invest into funds that track and guarantee returns related to specific indices. One such fund is the All Share Index 40 (ALSI40) Tracker Fund. The index is equity based to reflect the performance of the ordinary South African share market. Companies selected for inclusion in the ALSI40 Index are generally larger companies of sound financial standing having widely traded and marketable securities. As the ALSI40 is therefore a reflection of the total market as a whole, investing into such a Tracker Fund would only gain average returns over the long run. A modeled developed through using a twenty-day moving average to signal buy and sell periods, coupled with individual share gradients likened to future share growth potential is evaluated to determine if such a model would gain returns above the Tracker Fund and therefore gain returns above the ALSSI40 Index. The study project is wholly based on technical analysis, specific to the shares that constitute the ALSI40 Index. Through the selection of these shares fundamental analysis is taken care of and emphasis is placed on a technical trading technique developed. The technique is based on a two-stage model. Firstly, switch points are determined that indicate buy and sell signals through applying a 20-day moving average to the daily closing price of the selected shares. When the moving average is tracking below the closing price a buy signal is generated, and when the gradient of the moving average turns negative a sell signal is generated. Using these 'switch points', the second stage of the model is entered into through the allocation of weights to individual shares that conform to the buy selection criteria. The weights are determined using the gradient of the linear regression analysis equation. The gradient is synonymous with the growth potential of the share at the time a switching takes place. Through the use of the above model it was found that returns well above the holding period return of the ALSI40 Index are achievable. Evaluation of the model on a calendar year basis yielded a 113% over and above the return yielded by the ALSI40 Index for 1999. Similarly, positive returns were yielded for the 2000 calendar year and thus entrenching the trading technique as being successful. The major downside to the model is the number of switches dictated through strict adherence to the developed model. For example, 110 switches were necessary during 1999 to achieve the 113% over and above yield. Assuming switching fees of 1% per switch, margins that beat the holding period return of the ALSI40 would rapidly be eroded away. Although successful in achieving the aim of beating returns of the ALSI40, the model and computer code developed is robust and primitive in form. Numerous options exist to optimise the model, and thereby the potential to generate even greater returns. Optimisation would include a better 'gradient' function and procedure to reduce switching costs. The switching technique used is the most efficient obtainable from a single moving average.
AFRIKAANSE OPSOMMING: Daar bestaan vele 'tracker" fondse in Suid-Afrika waarin beleggers hulle geld kan belê. Die mees gewilde van hierdie fondse is die indeksfondse wat groei verwant aan spesifieke indekse waarborg, en dus direkte belegging in individuele aandele vervang. Een so 'n indeksfonds is die "All Share Index 40 (ALSI40) Indeks "Tracker" Fonds. Hierdie indeks is gebaseer op aandeelhouersbelang (gewone aandele) om die opbrengs van die gewone Suid-Afrikaanse aandelemark te reflekteer. Die gekose maatskappye vir insluiting in die ALSI40 indeks is gewoonlik die groter maatskappye met 'n gesonde finansiële status, met verhandelbare en verkoopbare sekuriteite. Aangesien die ALSI40 dus 'n weerspieëling is van die totale Suid-Afrikaanse aandelemark as 'n geheel, sal belegging in 'n 'tracker" fonds slegs gemiddelde groei oor die langtermyn lewer. 'n Model ontwikkel deur middel van die gebruik van 'n 20 dag bewegende gemiddelde om koop en verkoop tydstippe aan te dui, gekoppel aan individuele aandeelhellings te einde toekomstige aandeelgroei-potensiaalaan te toon, word beoordeel om te bepaal of so 'n model groei bo the 'tracker" fonds sal lewer, en dus ook groei bo die ALSI40 Indeks. The studieprojek is in geheel gebaseer op tegniese analise, met spesifieke verwysing na die aandele wat in die ALSI40 Indeks bestaan. Deur die seleksie van hierdie aandele is die fundamentele analise by implikasie reeds aangespreek en word die ontwikkelde tegniese verhandelingstegniek beklemtoon. Die tegniek is gebaseer op 'n twee-fase model. Eerstens, herbelegginspunte word bepaal, welke punte koop- en verkoopseine aandui deur middel van die toepassing van 'n 20 dag bewegende gemiddelde op die daaglikse sluitingsprys van die aandele. Wanneer die bewegende gemiddelde benede die sluitingsprys beweeg, word 'n koopsein genereer, en wanneer die helling van die bewegende gemiddelde negatief draai, word 'n verkoopsein genereer. Deur hierdie punte te gebruik, word die tweede fase van die model binnegetree deur die allokasie van gewigte aan die individuele aandele wat voldoen aan die koop-seleksie kriteria. Die gewigte word bepaal deur die helling van die lineêre regressie vergelyking. Die helling is sinoniem met die groeipotensiaal van die aandeel soos op die tydstip wat die herbelegging plaasvind. Deur gebreuik te maak van die bogenoemde model, is dit bevind dat die groei bo die hou periode van die ALS140 bereik kan word. Beoordeling van die model gebaseer op 'n kalenderjaar, het groei van 113% bo die 1999 groei van die ALS140 indeks gelewer. Soortgelyk is positiewe groei vir die 2000 kalenderjaar gelewer, wat derhalwe die verhandelingstegniek as suksesvol bevestig. Die grootste teenkant van die model is die aantal herbeleggings wat genereer word deur streng toepassing van die model. Byvoorbeeld, 110 herbeleggings was nodig gedurende 1999 om die 113% groei bo die indeks te bereik. Met die aanname dat herbeleggingskostes van 1% per herbelegging gehef word, word marges wat deur die houperiode-opbrengs van die ALS140 bereik kan word, vinnig uitgeroei. Alhoewel die model suksesvol is in die bereiking van die doel om die ALS140 opbrengs te verbeter, is die model en die rekenaarprogram wat ontwikkel is kragtig en primitief. 'n Groot aantal opsies is beskikbaar om die model te verbeter, en derhalwe die potensiaal om selfs hoër groei te genereer. Sulke opsies sal 'n verbeterde helling-funksie insluit asook 'n proses om herbeleggingskostes te verminder. Die herbeleggingstegniek wat gebruik is, is die effektiefste tegniek wat beskikbaar is vir 'n enkele bewegende gemiddelde.
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Bigdeli, Sam, and Filip Bengtsson. "Portfolio Optimization : A DCC-GARCH forecast with implied volatility." Thesis, Linnéuniversitetet, Institutionen för ekonomistyrning och logistik (ELO), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-85992.
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This thesis performs portfolio optimization using three allocation methods, Certainty Equivalence Tangency (CET), Global Minimum Variance (GMV) and Minimum Conditional Value-at-Risk (MinCVaR). We estimate expected returns and covariance matrices based on 7 stock market indices with a DCC-GARCH model including an ARMA (1.1) process and an external regressor of an implied volatility index (VIX). We then simulate returns using a rolling window of 500 daily observations and construct portfolios based on the allocation methods. The results suggest that the model can sufficiently estimate expected returns and covariance matrices and we can outperform benchmarks in form of equally weighted and historical portfolios in terms of higher returns and lower risk. Over the whole out-of-sample period the CET portfolio yields the highest mean returns and GMV and MinCVaR can significantly lower the variance. The inclusion of VIX has marginal effects on the forecasting accuracy and it seems to impair the estimation of risk.
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Fernandes, Cristiano Mateus Cunha. "The efficiency in Markowitz, minimum-variance and naïve portfolios applied to smi." Master's thesis, Instituto Superior de Economia e Gestão, 2015. http://hdl.handle.net/10400.5/8199.
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Mestrado em FinançasEsta dissertação tem como objectivo analisar vários modelos de gestão de carteiras, tendo em consideração gestão activa e passiva e o seu impacto na escolha eficiente de uma carteira ótima composta por activos do índice bolsista Suiço - SMI. A minha escolha recaíu sobre a Suiça por várias razões. Em primeiro lugar, seria interessante perceber o comportamento de um mercado europeu que não utilizasse a moeda única. Outra das razões foi por este mercado incorpora algumas grandes empresas multinacionais, tais como a Nestlé e a Swatch. A análise histórica das carteiras teve em conta o modelo Markowitz (média-variância), modelo Mínima-Variância e o modelo Naïve (pesos iguais). O horizonte temporal utilizado neste estudo foi de 10 anos, considerando o período de Janeiro de 2004 a Dezembro de 2013. Os dados foram retirados da base de dados académica Datastream. Para calcular o peso a investir em cada ativo, foram utilizados os sistemas de ?janelas de dados? a 1 e 2 anos. Por fim, será possível observer se, para 12 meses, existem ou não diferenças significativas entre os modelos de gestão de carteiras estudados nesta dissertação. Será também possível analisar se, para rendibilidades e rácios de Sharpe mais elevados, a carteira ótima é a melhor opção.
This study aims to analyze various models of portfolio management, underlying the active and passive management and its impact on the efficient choice of an optimal portfolio composed by assets from Swiss shares index - SMI. I chose Swiss market for a couple of reasons. First of all, it would be interesting to analyze the behavior of an European market that doesn't belong to Euro. Another reason was the fact of this market have some big international companies such as Nestlé and Swatch. Historical portfolio analysis took into account the Markowitz model (mean-variance), the Minimum Variance model and the Naïve model (equal weights). The time horizon used in this dissertation was 10 years and considers the period between January, 2004 and December, 2013. The data were obtained from academic database Datastream. To compute the weight to invest in each asset, ?data window system' for 1 and 2 years will be used. To conclude, we will be able to see if, for 12 months, there are or not significant differences between the types of portfolio management treated throughout the dissertation. Further on, we may consider if for higher returns and Sharpe Ratio, the optimal portfolio is the best option.
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Švec, Kamil. "Teorie koalic a koaliční vztahy na regionální úrovni." Doctoral thesis, 2013. http://www.nusl.cz/ntk/nusl-327227.
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The presented dissertation dealed with the process of forming the goverments on the regional level. On the example of the Czech Republic it analysed forming of the executive coalitions in the regions - the upper regionally autonomous units. The text is focused on four electoral periods: 2000-2004, 2008-2008, 2008-2012 and after the elections in 2012. The endeavour of the dissertation was to answer the question which factors are important for constitution of the governments on the regional level and what particularities belong to this process in comparison with the national level. On the level of the national governance the forming process of the government is compiled relatively extensively, however on the regional level, respectively sub-national level, the application of the theoretical information is difficult and the rules are not the same . The theoretical part is described in details. During the analysis it is necessary to bear in mind the theory of the second order elections. The electors prefer various political parties than in the first order election. The theories of games and racional choice are the second level of the theoretical base. Because of these two it is possible to think about a payoff of the individual participants who gain their utility. The theory of coalitions is principal as it...
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Hsu, Hsiang-An, and 許象安. "Target index tracing through portfolio optimization." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/f4ztnw.
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碩士國立中央大學
統計研究所
107
Tracing index in the market is now a crucial and popular topic in finance. In practice, the technical analysis for forecasting the direction index based no the past market data is widely used. In this paper, we construct a model to trace an index based on the technique of the portfolio optimization problem through the linear quadratic regulator. We solve the optimal strategy using the dynamic programming and the corresponding HJB equation. The verification theorem is also provided. Furthermore, the sensitive analysis is illustrated through the numerical study. Finally, we examine the proposed strategy is by real data included S&P 500 and several individual stocks in the U.S.
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CHENG, XIN-RAY, and 鄭欣瑞. "Apply Fundamental Index for Sector Portfolio." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/w686t9.
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Chu, Chih Ta, and 朱志達. "Portfolio optimization models for enhanced index investment." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/12486939618119544503.
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碩士國立政治大學
應用數學研究所
98
Setting up an index fund usually uses techniques of index-tracking that choosing few stocks forming a portfolio to obtain the same return rate as the benchmark index. Similarly we can use the same concept to set up a portfolio such that the performance is better than index’s. In this thesis we use index-tracking methods and minimax rule to obtain a portfolio which outperforms the benchmark index. In the proposed mathematical model we will consider the transaction costs, integer trading unit volume, and the total number of assets in the portfolio. Therefore the resulting model is a mixed integer nonlinear programming including integer variables and binary variables. Finally, the empirical study will be performed by using the data from the Taiwan stock market to verify the performance of our model. The empirical study shows that the portfolios created by our models outperform the benchmark index up to 25% in average.
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Wu, Si-Shuang, and 吳思萱. "Empirical Studies of Different Index Portfolio Construction Models." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/55235296815508922290.
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碩士實踐大學
企業管理研究所
90
Portfolio can be divided into two main groups by investors’ conception: active and passive operation. Active operation investors think they can find a portfolio with better performance than benchmark index. Passive operation investors think that the stock market is efficient, they just want to predict the movement of benchmark index. Passive portfolio is also called index portfolio. The objective of index portfolio is to construct a portfolio for tracking the movement of the benchmark index. The study tries to construct index portfolio by different approaches in Excel environment. And we also consider the real situation of trading that we cannot trade remnant stocks. This study constructs four index portfolio models with two optimization approaches: Genetic Algorithm and Mathematical Planning. These four models are “Genetic Algorithm Index Portfolio Model”、 “Mathematical Planning Index Portfolio Model”、 ”Mathematical Planning Model under Even Stock Index Portfolio”、”Genetic Algorithm Model under Even Stock Index Portfolio Model”. We use the “Mean Square Error” and “Mean Absolute Error” as the measurement indexes to analyze and compare the performance of these two optimization approaches in different training period. The major empirical results are as following: 1. “Genetic Algorithm Index Portfolio Model” have better tracking ability than“Mathematical Planning Index Portfolio Model” in out-sample. 2. In this study, we use the length of sample data as the index of separating experiment areas. When the length of sample data is 100, the tracking error is smaller than 200. For this reason, while constructing the index portfolio model, the length of sample data should be adjusted up to time interval. 3. In whatever experiment areas, the index portfolio constructed by Genetic Algorithm index portfolio model contains more stocks than that by Mathematical Planning index portfolio model. However, the tracking error of Mathematical Planning index portfolio model is larger than Genetic Algorithm index portfolio model. 4. There must be more even stocks contained in Genetic Algorithm Model under Even Stock Index Portfolio than those in Mathematical Planning Model under Even Stock Index Portfolio. Keyword：Genetic Algorithm、Mathematical Planning、Index Portfolio、Even Stock
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Chang, Hsiao-Fen, and 張曉芬. "Optimal Portfolio Selection Base on Sharpe Index Selection." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/43543106040133540795.
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碩士中原大學
國際貿易研究所
99
The purpose of investment is to get reward. Generally speaking, investors need to bear higher volatility risks if expected returns of the invested targets are higher, and vice versa. Investors should utilize their money to make good allocation of their assets, and emphasize on the overall returns and risks, rather than just focus on price fluctuations of any specific security. Diversification is also the main consideration in building the optimal investment portfolio. The idea of mutual funds is to use modern investment theory to make optimal portfo lio decision and achieve best performance. To do so, investors can achieve the goal of minimum risk or maximum return. This research is to make use of theories of the modern investment portfolio models. First, we apply the Mean-Variance Criterion Model by H. Markowitz (1952) to get the Efficient Set or Effi-cient Frontier. The concepts of Capital Asset Pricing Model (CAPM) and Sharpe Ratio by William F. Sharpe (1964, 1966) are then used to get the optimal investment portfolio through single index model. Apart from the traditional investment portfolio models and single index model, we also add the Risk Return restriction to this research. We refer to the five Risk Return Levels (RR1, RR2, RR3, RR4, RR5) stipulated by the Bankers Association of the Republic of China according to the risk at-tributes of the invested targets and market risk situation of the invested areas to help investors plan the optimal assets allocation suitable to their investing attributes.
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Chang, Lieh-Tang, and 張烈堂. "Apply Genetic Algorithm to Taiwan Index Option Portfolio." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/15934269660632445025.
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碩士國立中央大學
資訊管理研究所
93
Due to the growth of Taiwan Index Option (TXO) market, it is a new way to investment in Taiwan. This paper uses Combine Encode Genetic Algorithm to set up a portfolio which is composed of TXO options and to solve the fund allocation problem in TXO options portfolio. Compare to other securities, the life cycle of options is very short, depends on the expiration date, it varies from one month to eight month. The history data used before is too few to trust the result of GA. This paper uses three different methods to process option history data. In theory, the option history data can be expended to the first trading day of TXO market. Compare to original history, we can provide more data in GA evolution process. We select the TXO trading data from 2003 to 2004. We compare the portfolio performance between the GA’s strategy and the equally fund allocation strategy. The results show that the GA’s strategy can defect the equally fund allocation strategy, but in some cases, the statistic test result can not support this conclusion. In addition to the statistic test result, we also compare these different option history process methods, the result indicates that the best performance of all is the “ascend sort of the difference between option’s actual and theorical premium” method. It also indicates that the possibility of positive return of an option is high if that option’s value is underestimated.
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Huang, Shu-Hui, and 黃琡惠. "Safety-First Portfolio Selection Problem with Futures Index." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/40791322890952213243.
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碩士中原大學
工業工程研究所
92
Portfolio selection and risk management had been a most important research fields in modern finance recently. Now, the emergence of new financial derivatives such as options and futures, provides more investment opportunities for the investor. Also due to these new instruments, investor has more abilities and opportunities to control risk and obtain the sure profits. In thesis, we consider a safety-first portfolio selection problem in which a future is considered simultaneously. We take a long position on stock portfolio and take the short position on the index future. We set up such problem as a mathematical program model to obtain such portfolio with maximal return under the safety-first criterion considering the allowable downside risk. Moreover, we also measured the performances of the portfolios based on the historical data.
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Huang, Chia-Min, and 黃嘉閔. "Empirical studies of portfolio replication: Baltic dry index." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/f36sjw.
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碩士國立政治大學
國際經營與貿易學系
106
In this paper, I apply the economic tracking portfolio (ETP) approach developed by Lamont (2001) to track Baltic Dry Index (BDI). According to previous studies of ETP, such as Christoffersen (2000), Hayes (2001), Junttila (2004) and Raunig (2007), ETP is tested in closed-economy, using domestic equity as base assets. Junttila (2007) extends this approach to forecast the macroeconomic variables by using international equity returns. Our study also utilizes this concept to forecast BDI, control variables ignored here, and investigates the tracking performance based on different data frequency, forecast horizon, and training period. The results show that, no matter what data frequency is, the performance of recursive window is better than that of rolling window. The returns of diversified mining and iron steel contain more information than other industries about BDI. As a whole, the tracking portfolio can capture the trend of BDI, and also can be used as hedging tool by the practitioners.
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黃柏崴. "Riskiness-minimizing Portfolio Selection Using Single Index Model." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/rxjs3n.
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碩士東吳大學
經濟學系
107
The main purpose of this paper is to determine the optimal portfolio by minimizing Aumann and Serrano (2008)’s Riskiness of the portfolio given an abnormal return or systematic risk of the portfolio, where the returns of assets in the portfolio are estimated by using Sharpe Single Index Model. The Riskiness index employed in our method satisfies various appealing properties such as duality and monotonicity with respect to stochastic dominance (MRSD). More importantly, the riskiness frames the risk as the entire probability distribution. The study provide the solutions of the optimal weights, which can be estimated by method-of-moments. We also provide an empirical example by the Dow Jones Industrial Index to show the applicability of this proposed optimal portfolio model. The empirical results show that the higher abnormal return or systematic risk increases the Riskiness of optimal portfolio.
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Tsai, Yi-Jhang, and 蔡宜璋. "Index Portfolio Construction Based on Fuzzy Goal Programming." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/70838623269197700937.
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碩士國立中興大學
科技管理研究所
99
Mutual fund is one of favorite tools of the investors. Individual investors need no efforts on stock-picking and market-timing because the investing risk can be lowered through the professional management. But the researches indicate that most actively managed mutual fund’ performance is difficult to beat the market, and index investing is more and more popular among the investors. Index investing instruments, such as index funds and ETFs, aim to track the market performance. In practical, an index tracking portfolio has to pay the transaction cost due to following the change of benchmark index and also has to remain certain cash position. This result in the higher tracking error, therefore we want to pursuit both tracking error minimization and excess return maximization to attain the real performance tracking. Both are conflicting objectives. Goal programming is suitable for handling multiple conflicting objectives, but the basic goal programming concept is first to set up the crisp goals. In the real financial environment, the desired/expected level of the decision maker is usually imprecise. Minimizing the tracking error and maximizing the excess return are both represented as “fuzzy goals” in this research. Results show that through certain membership function and tracking model, an index tracking portfolio whose tracking error is lower than 0050 index fund but excess return is similar to 0050 index fund can be constructed.
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白惠琦. "A Tracking Model for Index Fund Portfolio Optimization." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/36104330770811239684.
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碩士國立政治大學
應用數學系
90
Index fund is an investment tool which tracks a stock-market index and thus is associated with market risk only. Its attraction to investors is low investment risk and low administrative expenses. Four different approaches to index fund construction can be classified as full replication, stratification, sampling, and optimizing respectively. In this thesis, we construct an index fund via the goal programming model with the optimizing approach. The model can be formulated as a mixed integer linear programming. The exact optimal solution can not be obtained when the model becomes large. We then develop a valid inequality and use this valid inequality to develop a cutting plane method. We also propose an efficient heuristic by adopting the dual property. Finally, an empirical study applying to the Taiwan Stock Exchange Capitalization Weighted Stock Index is given to show the efficiency of the algorithm.
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Huang, Chien-Hsun, and 黃建勳. "Using Backward-type Portfolio Selection Methods to Construct Optimal Portfolio Evaluated Index and Model." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/74797563727817301130.
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碩士國立清華大學
工業工程與工程管理學系
92
Portfolio selection methods are developed in many fields. Many techniques and mathematical models are used to settle related problems based on mean-variance model developed in the stock markets. Many researches focus on evaluating items and formulate portfolio from good items and the methods belong to forward-type. On the contrary, this study aims to use “backward-type” portfolio selection method. In the perspective of backward-type selection, this thesis identifies the portfolio attributes into three categories such as independent, interrelated and synergistic portfolio attributes. Other than the mean-variance model considers the risk as the selected criteria. The thesis used the performance (i.e. future return) what the investor emphasized as the target. By the statistic of partial R squares from stepwise-regression method toward performance, the investors’ attitude (i.e. relative importance) of each attribute is obtained periodically and the evaluation index is constructed. Based on the index, the study then constructed multi-criteria mixed-integer quadratic programming model and quadratic programming by different definition of synergistic attributes to obtain invested position of stocks in the portfolio. Finally, This study will have illustrations in Taiwan Stock market and find that the backward-type selection methods, company profitability and synergistic attribute including in the model will have good performance.
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Hsu, Jia-Rong, and 許家榮. "Minimum Variance Portfolio Holding Period Performance: Constructing Buy-and-Hold Portfolio Using Consumer Confidence Index." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/43843270171924292177.
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碩士亞洲大學
財務金融學系碩士班
99
Among the investors in Taiwan’s stock market, over 80% are individual investors. Their main concern is to reduce the transaction costs and to pursue the maximum profit. Using samples of the Taiwan Stock Exchange Corporation (TSEC) listed companies from January 2001 to June 2010 and constructing Markowitz’s minimum variance portfolios for individual investors, this research investigates whether individual investors can simply use a buy-and-hold strategy to get higher yields than the overall stock market. Different from the literatures, this research considers the consumer confidence index under the stock selection strategies. As this index measures how consumers view prospects for the economy and their own finances, individual investors may use it to guide their investments. The results show that the returns of stock portfolio are consistently superior to TSEC Taiwan Weighted Index throughout the test periods, whether or not the consumer confidence index is adopted. In other words, for individual investors to make excess return in Taiwan Stock market, using Markowitz’s minimum variance portfolios with a buy-and-hold strategy can achieve their goal.
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Bian, Jyh-Shang, and 卞志祥. "An Genetic-Algorithm Model for Taiwan Stock Index Portfolio." Thesis, 1996. http://ndltd.ncl.edu.tw/handle/82315334057535445505.
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碩士國立交通大學
資訊管理研究所
84
The purpose of this study is to use the powerful searching ability ofgenetic algorithm to construct a stock selection model for Taiwan stockindex portfolio. The genetic model will be compared with the Capitalization-Weighted-Nonstrtified Model and Capitalization-Weighted-Stratified Model,which are purposed by Meade and Salkin. From the data analysis, it was discovered that GA stock selection model is stable when its fitness fuction return value reaches a asymptotic limit.It shows that the GA stock selection model is reliable. In the results of comparism amount these models, the portfolio constructed from GA stock selection model is better than the other two to track the Taiwan stock index.In addition, the GA stock selection model has a great characteristic, thestability, no matter how many stocks the portfolio contents. The more stocksthe portfolio contents, the better tracking results are. All of the threemodel exhibit that it is exactly match the portfolio theorem. After the dataanalysis of GA stock selection model effective period and forecasting powerare considered, it shows that 288 days is the information cycle of Taiwan stock market. However, when the stock elements increase, the longer leaningdata-area is better. In summary, the powerful space-aearching ability of genetic algorithm is a really feasible manner to develop a constructing model in portfolio kingdom.
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Bian, Zhi Xiang, and 卞志祥. "A genetic model to construct Taiwan stock index portfolio." Thesis, 1996. http://ndltd.ncl.edu.tw/handle/94770371395408360516.
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Liu, Kuan-Ting, and 劉冠廷. "Portfolio Construction with Cluster Analysis: Evidence from Index Funds." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/9gakk9.
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Lin, Cian-Yu, and 林芊妤. "PERFORMANCE COMPARISON BETWEEN STOCK PORTFOLIO AND INDEX FUTURE INVESTMENT." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/20104111838686847230.
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碩士銘傳大學
經濟學系碩士班
96
Based on an identical investment strategy, concerning particularly the part of identifying the turning point of market movement, it is interesting to compare different performance from stock portfolio and index future investments. Furthermore, the reasoning behind the difference, if any, can also be analyzed as a consequence. Basically, there are certain unique features to deviate index futures from stock portfolios such as simplicity, leverage effect and so on. Therefore, with the existence of information and knowledge asymmetry, there might still have a significant difference between the investment performance from stock portfolio and index future, respectively. Empirical work from this study can include the followings. First, solving the problem of optional data size, this job can be easily completed by extending 陳芸慧 (2007) study. Second, establishing the analytical approach of switching investment positions, as this can be managed by creating two trends representing the WINDEX deviation, taken from both long and short – side market portfolios, and its first difference. Last, settling the doubt of eliminating any hedge tool accompanying both kinds of market portfolios, and this point can be supported after conducting event studies with respect to those highly volatile trading days within the sample period. Major outcomes of this empirical study can be summarized as: (1) Stock portfolio is superior to index future investment with respect to “Taiwan 50”, the reason may lie behind the autonomous hedging function existing within the frontier; (2) The optional date size to be used is 25 and 51 for the long and short – side market portfolio, respectively, revealing the fact that both momentum are quite different in the stock market; (3) It is not necessary to use any hedging position aside the stock market portfolio, as the latter already can exhibit certain degrees of autonomous hedging features based on its essence of picking up the best concurrent stock group in the stock market and sufficient degrees of risk diversification.
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Chang, Chin Cheng, and 章錦正. "Construction of Stock Index Simulation Portfolio Using Genetic Algorithm." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/52527544558928777605.
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碩士國立臺北大學
企業管理學系
91
Investors face systematic risks and non-systematic risks while choosing their investing objects in stock market. Index funds provide a good way for risk averters to invest their money because they will face only systematic risks because of the effect of risk-diversification. We use genetic algorithm to construct a index simulating portfolio and use correlation coefficient as the evaluation function. We find out that using correlation coefficient as the evaluation function in the evaluating process is much more effective and efficient than other studies before. And while comparing to the performance of the Taiwan-50 index, our portfolios out-performed.
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LIU, YAO-SHENG, and 劉耀升. "Dynamic adjustment of portfolio insurance applications Taiwan Stock Index Futures." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/07774371386301355674.
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碩士東吳大學
財務工程與精算數學系
98
In this study, the value of shares of the Taiwan 50 Index right to construct a leading indicator, the Taiwan Futures Exchange Taiwan Index futures for the study. Coupled with improved portfolio insurance, including Constant Proportion Portfolio Insurance, Time-varying Proportion Portfolio Insurance Strategy, and propose a modified dynamic changes in the multiplier model, the traditional portfolio insurance strategy to change the multiplier by a fixed percentage change in the way to see if can get the excess return. The results show that the study establishes a leading trading index and percentage change in the multiplier model can really get paid from the transaction, operating performance of buy and hold strategy during the same period.
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Liu, Tzuchiang, and 劉自強. "Explore The Efficiency Of The Portfolio To The Sharpe Index." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/89964007373582893102.
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碩士義守大學
財務金融學系碩士在職專班
100
In this paper, the net income after-tax EPS to investigate the stock returns and financial indicators such as after-tax EPS, net income, to elect the stocks, the observation of this study in Taiwan from 2005 to 2010, surplus declaration and tax per share for the eight companiesstronger earnings growth for the portfolio in order to observe changes in investment practice performance model, the Sharp indicators most widely used by Sharpe in the 1966 article mentioned, the Sharp index taking into account the risks and rewardsrate is called the ratio of return volatility (reward, to Variability ratio), calculated the Sharpe maximum combination of Sharpe prevail, compared with 0050 (Taiwan 50), the empirical results show that the surplus declaration refer to the information content of sexual. And can increase the rate of return. Really good to burst.
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Zheng, Yong-Sheng, and 鄭詠升. "Stochastic Linear Program for Portfolio Selection Problem with Index Future." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/03249798070351238701.
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碩士中原大學
工業工程研究所
92
Due to the uncertainty of the returns of asset, the portfolio selection problem is an important topic in the field of finance engineering. In recent years, the emergence of new financial derivatives such as options and futures provides more investment opportunities for the investor. Also due to these new instruments, investor has more abilities and opportunities to obtain the sure profits. In this thesis, we consider a portfolio selection problem with dynamically closing the portfolio. Our portfolio would take the long position on the stock portfolio and take the short position in the future index from the date the future is issued and end when the revenue reach a predetermined threshold. We model it as a two-stage stochastic linear program (two-stage SLP) to maximize the revenue. The first stage of this SLP, we obtain a portfolio under the safety-first criterion; the second stage determines the revenue of this given portfolio with the optimal closing time. Empirical results show that the return of our portfolio is steady, profitable and independent of the market.
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Ye, Jia-Hao, and 葉家豪. "Portfolio Strategies and Empirical Studies on Taiwan Stock Index Option." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/dhgc9m.
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碩士國立清華大學
計量財務金融學系
103
The purpose of this paper is to tight the connection between the option pricing theory and practical trading strategies. The gain-loss ratio method of Bernardo and Ledoit (2000) is employed instead of Black-Sholes pricing method to investigate a reasonable price bounds. By imposing the gain-loss ratio, the option price fall out of the boundary is regarded as an irrational or a semi-arbitrage price. The trading strategies are based on the gain-loss bounds, and various bounds can be obtained by adjusting the gain-loss ratio. The empirical result shows that the greater the gain-loss ratio of trading strategies, the wider the gain-loss bound. The probability that the price fall out the boundary is lower but the return of the strategies is approximately higher. The frequency of facing extremely losses is lower. Moreover, the performance of selling put is better than short strangle when taking the tradeoff between return and risk into consideration. Under our specification, holding the position to maturity seems to have the best performance. Changing the volatility every ten minutes doesn’t have big contribution of reducing the risk and extending the sample period of estimating volatility can lower the risk.
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Ke-Wang, Yun-Jie, and 柯王允傑. "The Investment Portfolio Decision System based on Technical Index Optimization." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/v937a7.
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碩士國立高雄應用科技大學
資訊管理研究所碩士班
104
Stock investing strategy often will influence the final profit in the stock investment process. The past stock investing strategies are mostly focused on a fixed market and strategy, and in the rapidly changing stock market, the strategy which could get an excess return in the past may become inapplicable and even will result in loss. It has become the most important issue on how to find the best investing strategy. In this study, an investment portfolio decision making system with optimized technical indicators is established, so that the investors could find out the investment portfolio which is most applicable to the stock market. Our proposed investment portfolio decision making system provides two functionalities, respectively, data management module (a flexible data import and field management) and stock strategy decision module (stock selection, trading strategy and optimization). Through stock strategy decision module, the investors may find out a better investment portfolio which is optimized by technical indexes. Traditionally, it is not convenient to investors to get the investment performance, e.g. return of investment and risk, because the investors have to program and extract the necessary information from financial database. However, our system also provides an easily operated interface, where the investment performances could be tested through various technical index optimization
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Yang, Wen Hui, and 楊文惠. "The Portfolio Strategy Based on Branch Overbuy and Oversell Index." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/zw9vv7.
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碩士國立高雄科技大學
金融資訊系
107
This research focuses on the investment strategy that is based on the number of buyers and sellers in brokerage firms. Using a sample comprising the Taiwan 50 Index and Taiwan Mid-Cap 100 Index, take the average returns rate on a weekly, monthly, and quarterly basis and segment the results into five categories. Comparing the five categories, prove that where the ratio of negative discrepancy in the number of buyers and sellers is higher, the probability of entering the market spontaneously is higher and so will be the returns. Period of Study: January 2014 - September 2018 for a total of 247 trading weeks. The results show that where the ratio of negative discrepancy in the number of buyers and sellers is higher, the stock performance tends to be not satisfactory. By contrast, where the ratio of negative discrepancy is lower, the average returns rate was higher. This indicates that the primary stimulant could be the stocks were already in hand for a period of time (ratio of negative discrepancy between buyers and sellers is higher), the stock price is increasing, and therefore selling would generate a profit. This led to a negative weekly average rate of return when the stock price decreased. Shifting the focus to a previously overlooked stock (ratio of negative discrepancy between buyers and sellers is lower) and potentially stimulating it with increased buying, resulted in an increased stock price and a positive the weekly average rate of return.
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Jen, Chung-hao, and 任仲豪. "The empirical analysis of Lowest risk portfolio verses stock index." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/19152798159659156418.
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碩士義守大學
財務金融學系碩士班
97
We use historical simulation approach, Variance-covariance approach and the Monte Carlo simulation approach to predict the Value the Risk of stock price in this study. The historical simulation approach estimates probability distribution of future returns of stock by historical data of stock. Variance-covariance approach assumes that asset returns have a normal distribution, We use the TW50 of stock are used to compute the VaR. Finally, this investigation uses the Monte Carlo simulation method to measure the risk of securitization of financial assets. The risk factors are simulated by ten thousand times in order to obtain the optmum value of the portfolio. By the portfolio theories brought up by Markowitz(1952), the portfolio risks and returns of Mean-Variance Portfolio Model is accurately calculated, it increases the flexibilities that the expected returns of investors achieve the maximum or remain the same in fixed investment risks.
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Chen, Tzu-Yu, and 陳姿妤. "Portfolio Selection and Performance Evaluation Based onPEG and PERG Index." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/12808969192087335105.
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碩士國立高雄第一科技大學
財務管理所
94
Abstract This paper uses the methodologies proposed by Estrada (2003) to construct the stock portfolios and compare their investment performance based on several investment strategies, including the P/E, PEG, and PERG index. There are many listed stocks traded on TSE (Taiwan Stock Exchange) are used as research targets. This paper contains the sample periods from 1996 to 2005. For all of the listed stocks, the empirical results indicate that the P/E ratio outperform the buy and hold strategy for 1~3 years investment horizon. In the electronics industry, the empirical results indicate that the P/E ratio and PEG index outperform the buy and hold strategy for 1~3 years investment horizon. The investment combination excluded the electronics industry from the listed stocks, the empirical results indicate that the P/E ratio outperform the buy and hold strategy for one-year investment horizon. This paper suggested that the P/E ratio will be better than PEG and PERG on investment performance.
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Tang, Hsiang-Jui, and 湯祥瑞. "Applications of Index Put to Portfolio Insurance — Example of Index Option in TAIFEX and SGX-DT." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/68891087936100331930.
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碩士銘傳大學
財務金融學系碩士班
91
Like any other form of insurance , portfolio insurance is designed to eliminate downside risk . It is equivalent to a portfolio of securities plus an insurance policy that guarantees the portfolio against a given level of loss over a specified policy period . Because it make Taiwan index option open to public on 24 , Dec. 2001 , this thesis probes into portfolio insurance using protective put option with TAIFEX and SGX-DT , and then compares the return rate and hedging performance of TAIFEX with SGX-DT , to provide a access for investors and fund manager . Firstly , this thesis screens the suitability of put option with the formula of Tian(1996) . Secondly , it compares the return rate of TAIFEX to SGX-DT in portfolio insurance under the formula of Tian(1996) which it is prerequisite for minimal cost . Lastly , analyzing the performance of TAIFEX and SGX-DT with EMG(Extended Mean-Gini)index .The results is : in the case of return rate of portfolio insurance, it is better for portfolio insurance to purchase put option in TAIFEX with fund of lower beta and to purchase put option in SGX-DT with fund of higher beta. In the case of hedging performance, it is better to purchase put option in SGX-DT with any beta and floor.
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Chang, Jui-Fang, and 賴居易. "Using genetic algorithm to support index fund portfolio strategy- A Case on Taiwan Stock Price Index." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/22055476680893928386.
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碩士國立高雄應用科技大學
商務經營研究所
94
Using genetic algorithm (GA),this study propose a index fund portfolio optimization strategy . This strategy is taken by fund managers to scheme when their portfolio can’t be sure about outperforming the market and they can adjust themselves to average performance. Recently, index fund is noticed that the performances of index funds are better than those of many other actively managed fund [Elton, E., Gruber, G., & Blake, C. (1996). Survivorship bias and mutual fund performance.] Index funds are popular investment tools being used in modern portfolio management. In this article,we use genetic algorithm to support our index fund portfolio. And according to Oh et al(2005) propose model, we give some adjust base on industry in Taiwan. The main objective of this article is to report that index fund could improve its performance greatly with the proposed genetic algorithm portfolio strategy , which will be demonstrated for index fund designed to track Taiwan Stock Price Index (TSPI) KEYWORD：genetic algorithm、index fund、portfolio strategy
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Lee, Pei-Ching, and 李佩靜. "Applying DEA Portfolio Efficiency Index to Fund of Funds in Taiwan." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/73008189037380376316.
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碩士長庚大學
企業管理研究所
94
Traditional fund performance indices like Sharpe ratio and Jensen’s alpha ignore transaction cost and have the problem in choosing benchmark model. To overcome the shortcomings, this thesis modifies the DEA (data envelopment analysis) portfolio efficiency index (DPEI) by Murthi et al. (1997) to better appraisal the performance of fund of funds in Taiwan. Specifically, this thesis replaces the standard deviation with value at risk (VaR) to better capture the downside risk in DPEI, and introduces the super-efficiency by Andersen and Petersen (1993) to rank efficient decision making units (DMU). The proposed model is called AP-DEPI, which can effectively measure the performance of fund of funds in Taiwan. Besides, it doesn’t have the problems caused by the traditional indices. Fund of funds does not have long history here in Taiwan and report on their performance is not yet available. For this exploratory study, we choose 8 funds with establishment duration over 1 year and data for empirical study fall between 2004/03/01 and 2005/03/31. Research results are as follows. 1.The proposed AP-DEPI model outperform DEPI since the former can rank efficient DMUs. 2.Performance measurement by AP-DEPI model is consistent with that by traditional indices. 3.Performance of fund of funs is superior to the market index; hence this new financial product can be a good instrument for investors here in Taiwan.
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Li, Kan-Yan, and 李侃諺. "A Comparison on the Portfolio Model Construction for Stock Index Arbitrage." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/87222009324199873588.
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碩士國立臺灣科技大學
資訊管理系
88
The index arbitrage is making, in theory, riskless profits by trading stocks underlying the index and index futures simultaneously when the actual futures price diverges its theoretical price widely. Index arbitrage is a simple concept in financial theory；however, there are some problems needed to be solved in practice. Due to restrictions in short selling and consideration of transactions costs, arbitrageurs usually construct a smaller portfolio which is designed to track the movement of the market index. This study uses four portfolio construction models to construct Taiwan stock index . These Models are “ Capitalization-Weighted-Nonstratified Model ”、 “ Capitalization-Weighted-Stratified Model ”、 “ The Optimization Approach Model ” and “Genetic Algorithm Stock Selection Model ”. A performance measurement index -“Tracking Error” is used to measure four portfolio construction models’ performance. The major empirical results is as the following: The best portfolio construction model to construct Taiwan stock index is “Genetic Algorithm Stock Selection Model ”. Because , it has the smallest Tracking Error. And “ The Optimization Approach Model ” is the second. “ Capitalization-Weighted-Stratified Model ” is the third. “ Capitalization-Weighted-Nonstratified Model ” is the worst.