Made available in DSpace on 2014-06-11T19:29:12Z (GMT). No. of bitstreams: 0 Previous issue date: 2009-06-26Bitstream added on 2014-06-13T19:26:46Z : No. of bitstreams: 1 maschtakow_psl_me_sjc.pdf: 1384895 bytes, checksum: 70a332cbbeccc2b9eb6120989f5de1c6 (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / A síndrome da apnéia e hipopnéia obstrutiva do sono (SAHOS) caracteriza-se pela obstrução completa ou parcial das vias aéreas superiores durante o sono sendo comum em indivíduos portadores de Síndrome de Down (SD). O objetivo neste estudo é comparar, por meio da análise em radiografias cefalométricas, em norma lateral, características anatômicas craniofaciais associadas às vias aéreas superiores entre indivíduos portadores de SD, indivíduos portadores de SAHOS e indivíduos não sindrômicos e sem alterações craniofaciais. Além disso, verificar a existência de dimorfismo sexual em relação a essas características nos grupos estudados. Foram realizadas análises computadorizadas em 43 radiografias cefalométricas laterais de indivíduos portadores de SD com idades entre 18 e 34 anos, 26 de indivíduos portadores da SAHOS com idades entre 20 e 70 anos e 29 radiografias cefalométricas de indivíduos não portadores de SD e sem características clínicas de SAHOS com idades entre 18 e 35 anos. Foram avaliadas 14 medidas lineares por meio do software Radiocef Studio 2. Os dados obtidos foram comparados e submetidos à análise de variância (ANOVA) e teste post-hoc de Tukey. Concluimos que existem alterações craniofaciais significantes entre indivíduos portadores de SAHOS e indivíduos não sindrômicos tais como: menor comprimento maxilar e mandibular, naso, oro e hipofaringe com dimensões reduzidas, maior comprimento do palato mole, espaço retropalatal estreitado e osso hióide posicionado mais inferior e anteriormentemente. Dentre as alterações relacionadas à SAHOS, foram encontrados nos indivíduos portadores de SD, menor comprimento da base do crânio, menor comprimento maxilar e mandibular, naso e hipofaringe reduzidas, palato mole aumentado, espaço retropalatal reduzido e osso hióide posicionado mais inferior e anteriormentemente... / Obstructive sleep apnea syndrome is characterized by complete or partial obstruction of the upper airway during sleep, being common in individuals with Down syndrome. The aim of this study is to compare, through analysis of cephalometric radiographs in lateral norm, craniofacial morphology associated with upper airway between individuals with Down syndrome, individuals with obstructive sleep apnea syndrome and non syndromic individuals. Moreover, verify if there is sexual dimorphism in relation to changes in these groups. Computer analysis were performed in 43 lateral cephalometric radiographs of individuals with Down syndrome aged between 18 and 34 years, 26 patients of obstructive sleep apnea syndrome with ages between 20 and 70 years and 29 cephalometric radiographs of non syndromic individuals aged 18 and 35 years old. The analyses were performed using the software Radiocef Studio 2. The data were compared and submitted to analysis of variance (ANOVA) and post-hoc test of Tukey. It was concluded that there are significant craniofacial changes between individuals with and without obstructive sleep apnea syndrome on the lower maxillar and mandibular length, naso, oro and hypopharynx with reduced dimensions, increased length of the soft palate, post-palatal region closer, inferiorly and anteriorly positioned hyoid bone. Among the changes related to obstructive sleep apnea syndrome, that were found in individuals with Down syndrome, the lower length of the base of the skull, lower jaw and mandibular length, reduced nasal and hypo pharynx, longer soft palate, post-palatal region reduced and inferiorly and anteriorly positioned hyoid bone. There is also sexual dimorphism in some factors analyzed: larger anterior skull base, greater length of the maxilla and mandible were found in males in all groups.

In this paper, I examine the top ten historical upward and downward daily shocks in the Dow Jones Industrial Average, and test whether industry specific abnormal returns can be explained by industry specific leverage ratios on those days. I use modified versions of the Capital Asset Pricing Model and the Fama French 3 Factor regression to examine within-industry abnormal returns. I then proceed to rank the industry abnormal returns and industry leverage ratios, from high to low, on days corresponding to these large shocks. Finally, I examine the correlation between these ranks on the days corresponding to the large moves. The results show that on upward moving days, there is no relationship between industry abnormal returns and industry leverage. However, on downward moving days, there is moderate negative correlation between industry abnormal returns and leverage, suggesting that higher leverage leads to lower abnormal returns. This paper explains these results in further detail, and discusses the implications to the greater field of financial economics.

This thesis examines the theoretical underpinnings and practical construction of select economic and financial indexes. Such indexes are used for a variety of purposes, including the measurement of inflation, portfolio return performance, and firm productivity. Chapter 1 motivates interest in economic and financial indexes and introduces the principal ideas in the thesis. Chapter 2 focuses on one potential source of bias in the Canadian consumer price index (CPI) that arises from the emergence of large discount/warehouse stores—the so-called outlet substitution bias. Such outlets have gained market share in Canada in recent years, but current CPI procedures fail to capture the declines in average prices that consumers enjoy when they switch to such outlets. Unrepresentative sampling, and the fact that discount stores often deliver lower rates of price increase can further bias the CPI. Bias estimates for some elementary indexes are computed using data from Statistics Canada's CPI production files for the province of Ontario. It is shown that the effect on the Canadian CPI of inappropriately accounting for such discount outlets can be substantial. Another area in which indexes are frequently used is the stock market. Several stock market indexes exist, including those produced by Dow Jones and Company, Standard and Poor's Corporation, Frank Russell and Company, among others. These indexes differ in two fundamental respects: their composition and their method of computation—with important implications for their usage and interpretation. Chapter 3 introduces the concept of a stock index by asking what, in fact a stock market index is—this is tantamount to considering the purpose for which the index is intended, since stock indexes should be constructed according to their usage. Because stock indexes are most commonly used as measures of returns on portfolios, the main considerations in constructing such return indexes are examined. Chapter 4 uses the Dow Jones Industrial Average (DJIA) as a case study to examine its properties as a return index. It is shown that the DJIA is not the return on a market portfolio consisting of its thirty component stocks: in fact the DJIA measures the return performance on a very particular (and unusual) investment strategy, a fact that is not well understood by institutional investors. An examination of some other popular stock indexes shows that they all differ in their computational formula and that each is consistent with a particular investment strategy. Numerical calculations reveal that the return performance of the DJIA can vary considerably with the choice of basic index number formula, particularly over shorter time horizons. Given the numerous ways of constructing stock market return indexes, the user is left to determine which is 'best' in some sense. The choice of an appropriate (or 'best') formula for a stock market index is formally addressed in chapter 5. The test or axiomatic approach to standard bilateral index number theory as in Eichhorn & Voeller (1983), Diewert (1993a), and Balk (1995) is adapted here. A number of a priori desirable properties (or axioms) are proposed for a stock index whose purpose is to measure the gross return on a portfolio of stocks. It is shown that satisfaction of a certain subset of axioms implies a definite functional form for a stock market return index. Chapter 6 evaluates the various stock indexes is use today in terms of their usefulness as measures of gross returns on portfolios. To this end the axioms developed in chapter 5 are used to provide a common evaluative framework, in the sense that some of the indexes satisfy certain axioms while others do not. It is shown that the shortcomings of the DJIA as a measure of return arise from its failure to satisfy a number of the basic axioms proposed. Notwithstanding this, each index corresponds to a different investment strategy. Thus, when choosing an index for benchmarking purposes an investor should select one which closely matches his/her investment strategy—a choice that cannot be made by appealing to axioms alone. / Arts, Faculty of / Vancouver School of Economics / Graduate

In today's society most swedish people are saving money on saving accounts that give nointerest return. So, in this study we have examined two investment strategies GrahamScreener and Dogs of the dow. We wanted to see how the two strategies perform on theswedish stock markets and even see which one of them performs the best and gives back thehighest interest rate. After we have tested the two strategies on the two different markets overa 14-years period we got the resultat that Graham Screener is a way better strategy than Dogsof the dow. This gave us the conclusion that the theory that the efficient market hypothesisgives us that you can't overperform the market could be questioned with the data and theresultat this study gave us

ABSTRACT MAJID MEMARI, for the Masters of Science degree in Computer Science, presented on November 3rd, 2017 at Southern Illinois University, Carbondale, IL. Title: PREDICTING THE STOCK MARKET USING NEWS SENTIMENT ANALYSIS Major Professor: Dr. Norman Carver Big data is a term for data sets that are so large or complex that traditional data processing application software is inadequate to deal with them. GDELT is the largest, most comprehensive, and highest resolution open database ever created. It is a platform that monitors the world's news media from nearly every corner of every country in print, broadcast, and web formats, in over 100 languages, every moment of every day that stretches all the way back to January 1st, 1979, and updates daily [1]. Stock market prediction is the act of trying to determine the future value of a company stock or other financial instrument traded on an exchange. The successful prediction of a stock's future price could yield significant profit. The efficient-market hypothesis suggests that stock prices reflect all currently available information and any price changes that are not based on newly revealed information thus are inherently unpredictable [2]. On the other hand, other studies show that it is predictable. The stock market prediction has been a long-time attractive topic and is extensively studied by researchers in different fields with numerous studies of the correlation between stock market fluctuations and different data sources derived from the historical data of world major stock indices or external information from social media and news [6]. The main objective of this research is to investigate the accuracy of predicting the unseen prices of the Dow Jones Industrial Average using information derived from GDELT database. Dow Jones Industrial Average (DJIA) is a stock market index, and one of several indices created by Wall Street Journal editor and Dow Jones & Company co-founder Charles Dow. This research is based on data sets of events from GDELT database and daily prices of the DJI from Yahoo Finance, all from March 2015 to October 2017. First, multiple different classification machine learning models are applied to the generated datasets and then also applied to multiple different Ensemble methods. In statistics and machine learning, Ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from any of the constituent learning algorithms alone. Afterwards, performances are evaluated for each model using the optimized parameters. Finally, experimental results show that using Ensemble methods has a significant (positive) impact on improving the prediction accuracy. Keywords: Big Data, GDELT, Stock Market, Prediction, Dow Jones Index, Machine Learning, Ensemble Methods

Problemformulering: Går det att uppnå en signifikant återkommande överavkastning samt riskjusterad överavkastning i förhållande till den svenska aktiemarknaden genom systematiskt följande av investeringsstrategin “Dogs of the Dow”? Syfte: Syftet är att undersöka huruvida teorin ”Dogs of the Dow” är applicerbar på den svenska aktiemarknaden i sökandet efter en signifikant återkommande överavkastning i förhållande till marknaden. Med detta hoppas det finnas en positiv differens av den riskjusterade överavkastningen gentemot index. Metod: Studien samlar in primärdata för empirin via SIX Trust, SIX Edge samt från Riksbankens hemsida. Sekundärdata härstammar från vetenskapliga artiklar uthämtade från främst JStor och EBSCO Host. Även studentlitteratur, tidigare studier utgör sekundärdata. Studien tillämpar befintliga teorier för att via modeller studera studiens syfte. Resultat: Resultatet anses av författarna vara imponerande. Portföljerna sammansatta i enlighet med investeringsstrategin ”Dogs of the Dow” presterar till de skådade faktorerna i genomsnitt över lag bättre än jämförelseindexen SIXRX och SIX30RX. Resultaten kan dock inte fastställas statistiskt men författarna önskar skilja på statistisk och praktisk signifikans då en möjlig kumulativ effekt genererar enorm förmögenhetsutveckling. / Problem: Is it possible to receive a reoccurring significant abnormal return as well as risk adjusted abnormal return against the Swedish stock market through systematic appliance of the investment strategy ”Dogs of the Dow”? Objective: The objective is to study whether the theory ”Dogs of the Dow” is applicable on the Swedish stock market in the search of a significant reoccurring abnormal return against the market. The hopes are to find a positive difference between the risk adjusted abnormal return and index. Method: The study collects the primary empirical data through SIX Trust, SIX Edge as well as from the Swedish central bank. The secondary data is derived from scientific articles, student literature, and previous studies. Models are used to study the objective. Results: The authors find the results to be impressive. The portfolios structured through the investment strategy “Dogs of the Dow” outperform the comparison indices SIXRX and SIX30RX in general on all the observed accounts. The results can although not be stated as statistically significant within any reasonable confidence levels, but the authors would like to emphasize the difference between the terms statistically and practically significant. This since cumulative gains could contribute to a massive gain of wealth which could be practically significant for the long-term investor.

Made available in DSpace on 2015-05-08T14:45:04Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 1848162 bytes, checksum: 8d8c6d6ea96038f73be05f042425a488 (MD5) Previous issue date: 2010-09-17 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The prices of securities traded on stock exchanges, as well as any other commodity in the financial market fluctuate naturally with the demand for these products. These oscillations, along with the asymmetry of information about the prices of these products generate volatility processes. Charles Dow in the early twentieth century created sector indexes, in which papers met the same area of activity, according to him, several indicators point to the same direction would be a sign that this really would be a tendency to drive the market, thus characterizing the Dow Theory. Ralph Nelson Elliott (1871-1948) studied the average prices of the Dow Jones Industrial and realized repetitions in the market changes, their observations were summarized in what became known as "The Wave Principle." Elliott developed his theory based on so-called Fibonacci sequence, discovered by Leonardo Pizza (Fibonacci) around 1200. In addition to the Dow Theory and the Theory of waves in this work was done using the Theory of Rationality of the agents as a complementary way to explain the decision process of investors, as happens in situations of uncertainty. A rational decision involves selecting the choice which has the largest expected return for a given level of risk. / Os preços dos ativos negociados em bolsas de valores, assim como qualquer outro tipo de commodity do mercado financeiro, oscilam naturalmente com a procura por esses produtos. Essas oscilações, juntamente com a assimetria das informações acerca dos preços desses produtos geram processos de volatilidade. Charles Dow, no início do século XX criou índices setoriais, nos quais reunia papéis da mesma área de atividade, segundo ele, se vários índices apontassem para a mesma direção seria um sinal de que realmente essa seria uma tendência de movimentação do mercado, caracterizando assim a Teoria de Dow. Ralph Nelson Elliott (1871-1948) estudou as cotações médias dos índices Dow Jones Industrial e percebeu repetições nas alterações do mercado, suas observações foram resumidas no que ficou conhecido como O Princípio da Onda . Elliott desenvolveu a sua teoria com base na denominada Sequência de Fibonacci, descoberta por Leonardo de Pizza (Fibonacci) por volta de 1200. Além da Teoria de Dow e da Teoria das Ondas, nesse trabalho, fez-se uso da Teoria da Racionalidade dos agentes como uma forma complementar para se explicar o processo de decisão dos investidores, dado que acontecem em situações de incerteza. Uma decisão racional implica em selecionar a escolha que apresente o maior retorno esperado para um dado nível de risco.

Submitted by Marcio Pintan (mpintan@gmail.com) on 2018-06-25T18:13:19Z No. of bitstreams: 1 financas-pintan-dissertação versao final.pdf: 1855884 bytes, checksum: 0ac7f69afc81d4cea8446f01d309fd99 (MD5) / Approved for entry into archive by Mayara Costa de Sousa (mayara.sousa@fgv.br) on 2018-08-13T16:18:19Z (GMT) No. of bitstreams: 1 financas-pintan-dissertação versao final.pdf: 1855884 bytes, checksum: 0ac7f69afc81d4cea8446f01d309fd99 (MD5) / Approved for entry into archive by Suzane Guimarães (suzane.guimaraes@fgv.br) on 2018-08-13T16:25:32Z (GMT) No. of bitstreams: 1 financas-pintan-dissertação versao final.pdf: 1855884 bytes, checksum: 0ac7f69afc81d4cea8446f01d309fd99 (MD5) / Made available in DSpace on 2018-08-13T16:25:32Z (GMT). No. of bitstreams: 1 financas-pintan-dissertação versao final.pdf: 1855884 bytes, checksum: 0ac7f69afc81d4cea8446f01d309fd99 (MD5) Previous issue date: 2018-05-25 / Esta dissertação trata das operações realizadas na BM&F BOVESPA chamadas comumente de 'Day Trading', ou seja, operações cuja compra (ou venda) e a liquidação são realizadas no mesmo dia. Tal questão é relevante, principalmente para o pequeno investidor, por possibilitar a otimização do resultado da sua carteira de investimento ao longo do tempo. O objetivo de pesquisa deste trabalho é apresentar e testar algumas técnicas utilizadas pelos operadores do mercado financeiro na modalidade 'Day Trading'. Em conjunto com a verificação das teorias de análise gráfica, o trabalho pretende conciliar tais técnicas preditivas com teorias de gestão de risco e de gestão de portfólio, nesse caso mais precisamente a teoria moderna de portfólio de Markowitz, de forma a testar a eficiência da combinação entre essas teorias no mercado de ações brasileiro, e se existe a possibilidade de otimização dos resultados que um investidor pode alcançar ao longo do tempo. Para atingir este objetivo foi realizada uma pesquisa quantitativa utilizando técnicas de análise gráfica baseadas em teorias amplamente conhecidas no mercado de capitais, como os Princípios de Ondas de Elliott e a Teoria de Dow. A partir dos indicadores de sucesso obtidos por essas técnicas preditivas (através de 'backtests'), o presente trabalho testa a efetividade das questões relativas a eficiência de mercado apresentadas nas Hipótese de Mercados Eficientes de Fama (1970). As principais conclusões desta dissertação sugerem que uma estratégia passiva, de compra e manutenção do Índice Bovespa, domina respectivamente estratégias baseadas na Teoria de Markowitz e estratégias ativas de Day Trading baseadas em análise técnica. Os resultados trazem uma grande contribuição para o pequeno investidor através de uma maior compreensão sobre possibilidades que as operações de curto prazo podem trazer para ao seu portfólio de investimentos e confirma a visão de que o mercado de ações brasileiro é eficiente em sua forma fraca. / This thesis deals with operations carried out on BM&F BOVESPA commonly called 'Day Trading', which are operations whose purchase (or sale) and settlement are carried out on the same day. This issue is relevant, especially for the small investor, because it allows the optimization of the result of their investment portfolio over time. The objective of this research is to present and test some techniques used by financial market traders in the 'Day Trading' modality. In conjunction with the verification of theories of technical analysis, the paper aims to reconcile such predictive techniques with theories of risk management and portfolio management, in this case more precisely the Modern Portfolio Theory of Markowitz, in order to test the efficiency of the combination between these theories in the Brazilian stock market, and whether there is a possibility of optimizing the results that an investor can achieve over time. To achieve this goal a quantitative research is performed using graphical analysis techniques based on theories widely known in the capital market, such as the Elliott Wave Principle and the Dow Theory. From the indicators of success obtained by these predictive techniques (through backtests), the present research explores aspects of market efficiency presented in the Efficient Market Hypothesis of Fama (1970). The main conclusions of this dissertation suggest that a passive buy and hold strategy of the Bovespa Index dominates respectively strategies based on Markowitz Theory and active day trading strategies based on technical analysis. The results make a contribution to the small investor through a better understanding of the possibilities that short-term operations can bring to their investment portfolios and confirms the view that the Brazilian stock market is efficient in its weak form.

Background: The increase in development and welfare that has been achieved in recent decades has led to a deterioration of the planet. Increased awareness on this matter has led to a concern to become more sustainable, both on an individual level and firm level. The concept of sustainable development integrates consideration to economic growth, protection of the environment, and social justice. Firms have sustainability regulations they must follow to be allowed to operate, but when they go beyond their economic interests it is referred to as corporate social responsibility (CSR). Certain indexes select which firms to include based on their CSR performance. In this way, firms can use CSR to build a reputation. Objectives: The purpose of this study is to investigate if inclusion in or exclusion from Dow Jones Sustainability Europe (DJSEUR) index has a significant effect on a firm’s stock price. The sub-purpose of this study is to investigate if different sector characteristics significantly impact the investors’ response to inclusion and exclusion. The study is conducted on firms in the European region. Methods: The event study methodology was used to examine abnormal returns associated with inclusion in and exclusion from a sustainability stock index. Further, a linear regression was developed to distinguish if sector affiliation affects the reactions of investors when firms are included or excluded from the index. This study uses stock data for firms over a period of time from 2014-2019. Results: The results suggest no significant increase in CAAR from being included in the index. However, exclusion from the index significantly affected CAAR negatively on the day of the announcement. Five sectors experienced a significantly different CAAR from the event of exclusion from the index. Only the result from one sector indicated to be significantly affected by the event of inclusion in the index. Conclusions: Our results provide evidence that being removed from the DJSEUR results in a decrease in a firm’s share price, suggesting that the European stock market penalizes firms for not obtaining a sufficiently high level of CSR. But investors do not financially reward firms for inclusion in the DJSEUR index. Implying that investors in the European stock market expect firms to implement CSR but do not reward them financially. Therefore, managers need to satisfy the pressure from various stakeholders, including shareholders, while trying to maximize stock value. / Bakgrund: Ökningen av utveckling och välfärd som uppnåtts under det senaste decenniet har lett till nedbrytning av planeten. Medvetenhet om problemet har lett till ökad angelägenhet för att agera mer hållbart, både på individnivå och företagsnivå. Konceptet av hållbar utveckling integrerar ekonomisk tillväxt, skydd av planeten och sociala rättigheter. Företag måste uppfylla vissa krav inom hållbarhet för att vara verksamma. Om de gör mer än vad som krävs benämns det som företags sociala ansvar, eller corporate social responsibility (CSR) i engelska termer. Det finns speciella index som selekterar företag baserat på deras prestationer inom CSR. På det sättet kan företag använda sig av CSR för att påverka sitt rykte.  Syfte: Syftet med denna studie är att undersöka huruvida inkludering i eller exkludering från Dow Jones Sustainability Europe (DJSEUR) index har en significant påverkan på företags aktiepriser. Det sekundära syftet är att undersöka om olika sektorer, samt karaktärsdrag, har en signifikant påverkan på investerares respons till inkludering och exkludering. Studien inkluderar företag inom Europaregionen. Metod: Metodiken för en eventstudie användes för att beräkna abnormala avkastningar associerade med inkludering i eller exkludering från ett hållbarhetsindex. En linjär regression tillämpades för att skilja på om sektortillhörighet påverkade investerarnas reaktioner på när företag inkluderades i eller exkluderades från indexet. Studien använder aktiedata för företag från tidsperioden 2014-2019.  Resultat: Resultaten tyder på att inkluderingar från indexet inte signifikant ökar CAAR. Exkluderingar från indexet påverkade dock CAAR negativt på dagen för tillkännagivandet. För exkluderingar redovisade resultatet att fem sektorer har en signifikant skillnad i CAAR, men enbart en sektor för inkluderingar.  Slutsatser: Våra resultat visar att exkludering från DJSEUR minskar företagets aktiekurs, vilket tyder på att den europeiska aktiemarknaden straffar företag för att de inte bibehåller en tillräckligt hög nivå av CSR. Men investerare belönar inte företag för att inkluderas i DJSEUR indexet. Vilket innebär att investerare på den europeiska aktiemarknaden förväntar sig att företag implementerar CSR men belönar dem inte finansiellt. Därför tvingas managers tillfredsställa trycket från olika intressenter, inklusive aktieägare, samtidigt som de försöker maximera aktiens värde.

This thesis evaluates the mean-variance analysis framework by comparing the performance of an optimized portfolio consisting of stocks from the Dow Jones Industrial Average to the performance of the Dow Jones Industrial Average index itself. The results show that the optimized portfolio performs better than the corresponding index when evaluated on the period between 2015 and 2019. However, the variance of the returns are high and therefore it is difficult to determine if mean-variance analysis performs better than its corresponding index in the general case. Furthermore, it is shown that individual stocks can still influence the movement of an optimized portfolio significantly, even though the model is supposed to diversify firm-specific risk. Thus, the authors recommend modifying the model by restricting the amount that is allowed to be invested in a single stock, if one wishes to apply mean-variance analysis in reality. To be able to draw further conclusions, more practical research within the subject needs to be done. / Denna uppsats utvärderar ramverket ”mean-variance analysis” genom att jämföra prestandan av en optimerad portfölj bestående av aktier från Dow Jones Industrial Average med prestandan av indexet Dow Jones Industrial Average självt. Resultaten visar att att den optimerade portföljen presterar bättre än motsvarande index när de utvärderas på perioden 2015 till 2019. Dock är variansen av avkastningen hög och det är därför svårt att bedöma om mean-variance analysis generellt sett presterar bättre än sitt motsvarande index. Vidare visas det att individuella aktier fortfarande kan påverka den optimerade portföljens rörelser, fastän modellen antas diversifiera företagsspecifik risk. På grund av detta rekommenderar författarna att modifiera modellen genom att begränsa mängden som kan investeras i en individuell aktie, om man önskar att tillämpa mean-variance analysis i verkligheten. För att kunna dra vidare slutsatser så krävs mer praktisk forskning inom området.