Bibliografie tematiche / Markowitz

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Letteratura scientifica selezionata sul tema "Markowitz"

Autore: Grafiati
Pubblicato: 4 giugno 2021
Ultima modifica: 25 aprile 2022

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Articoli di riviste sul tema "Markowitz"

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Bhullar, Pritpal Singh, e Pradeep K. Gupta. "Expected and Realized Stock Returns: Evidence from India". Asian Journal of Empirical Research 6, n. 11 (16 febbraio 2017): 270–78. http://dx.doi.org/10.18488/journal.1007/2016.6.11/1007.11.270.278.

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Markowitz Portfolio theory is based on the expected return and risk but investors are more interested in realized return. The considerations, expected return as realized return and variance as investment risk, of Markowitz’s mean – variance model enable the researchers or scholars to further explore on the validity of Markowitz theory. The present study makes an attempt to unfold a new idea in investment scenario where Markowitz theory is empirically tested on realized return and risk as well as on realized return and expected return in the context of India. The findings show that a large variation in Expected Return is explained by the risk (Market Beta) alone and this risk and Expected return are significantly negatively related. However, the risk (Market Beta) and Realized return are insignificantly related. Further, a very low variation in the Realized (Actual) Return is explained by the Expected Return and the Expected Return and the Realised Return are insignificantly positively related. Thus, it is considered that the Markowitz model is not possible to implement in the real world even though the relationship holds good. This study acts as one of the guiding tools for investors in transforming their new age investment philosophy.
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Chhabra, Ashvin B. "Beyond Markowitz". Journal of Wealth Management 7, n. 4 (31 gennaio 2005): 8–34. http://dx.doi.org/10.3905/jwm.2005.470606.

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Goldberg, Lisa. "Harry Markowitz: Selected Works, edited by Harry M. Markowitz". Quantitative Finance 11, n. 10 (ottobre 2011): 1455–56. http://dx.doi.org/10.1080/14697688.2011.616215.

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Iliev, Valentin. "On Markowitz Geometry". Fundamental Journal of Mathematics and Applications 1, n. 2 (25 dicembre 2018): 175–83. http://dx.doi.org/10.33401/fujma.453591.

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Baule, Rainer, Olaf Korn e Laura-Chloé Kuntz. "Markowitz with regret". Journal of Economic Dynamics and Control 103 (giugno 2019): 1–24. http://dx.doi.org/10.1016/j.jedc.2018.09.012.

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Poma, A. "The Markowitz Wobble". International Astronomical Union Colloquium 178 (2000): 351–54. http://dx.doi.org/10.1017/s0252921100061480.

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AbstractSeveral decades ago Markowitz was the first to report the existence of fluctuations in the motion of the Earth’s axis with a period of about twenty-four years. This empirical term was often considered not real but only an artifact due to local effects. In this paper long-term variations and the relationship between the 30-yr Markowitz wobble and changes in the Earth’s rotational speed are briefly discussed.
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Jia-an, Yan, e Zhou Xunyu. "Markowitz strategies revised". Acta Mathematica Scientia 29, n. 4 (luglio 2009): 817–28. http://dx.doi.org/10.1016/s0252-9602(09)60072-2.

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Powers, Dennis L. "Jacob Markowitz Award". Journal of Investigative Surgery 10, n. 4 (gennaio 1997): 247. http://dx.doi.org/10.3109/08941939709032160.

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Horvitz, Jeffrey E., e Jarrod W. Wilcox. "Back to Markowitz". Journal of Wealth Management 10, n. 1 (30 aprile 2007): 43–53. http://dx.doi.org/10.3905/jwm.2007.684878.

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Maple, Terry L. "Remembering Hal Markowitz". Zoo Biology 32, n. 3 (7 marzo 2013): 243–45. http://dx.doi.org/10.1002/zoo.21065.

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Tesi sul tema "Markowitz"

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Mertens, Detlef. "Portfolio-Optimierung nach Markowitz /". Frankfurt am Main : Bankakademie-Verlag, 2004. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=012908193&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.

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Gasser, Stephan, Margarethe Rammerstorfer e Karl Weinmayer. "Markowitz Revisited: Social Portfolio Engineering". Elsevier, 2017. http://dx.doi.org/10.1016/j.ejor.2016.10.043.

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In recent years socially responsible investing has become an increasingly more popular subject with both private and institutional investors. At the same time, a number of scientific papers have been published on socially responsible investments (SRIs), covering a broad range of topics, from what actually defines SRIs to the financial performance of SRI funds in contrast to non-SRI funds. In this paper, we revisit Markowitz' Portfolio Selection Theory and propose a modification allowing to incorporate not only asset-specific return and risk but also a social responsibility measure into the investment decision making process. Together with a risk-free asset, this results in a three-dimensional capital allocation plane that allows investors to custom-tailor their asset allocations and incorporate all personal preferences regarding return, risk and social responsibility. We apply the model to a set of over 6,231 international stocks and find that investors opting to maximize the social impact of their investments do indeed face a statistically significant decrease in expected returns. However, the social responsibility/risk-optimal portfolio yields a statistically significant higher social responsibility rating than the return/risk-optimal portfolio.
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Ziemann, Volker. "Allocation d'actifs au-delà de Markowitz". Aix-Marseille 3, 2007. http://www.theses.fr/2007AIX32042.

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Cette th`ese a pour objet de r´ehabiliter la th´eorie de gestion de portefeuille bas´ee sur l’arbitrage entre le gain attendu d’un investissement et le risque associ´e. Selon le mod`ele fondateur de ce domaine de recherche acad´emique, propos´e par Harry Markowitz dans les ann´ees 1950, le gain attendu et le risque sont repr´esent´es par la moyenne et l’´ecart-type empiriques de l’actif. Cette m´ethodologie soul`eve deux probl`emes principaux empˆechant le mod`ele d’ˆetre appliqu´e en pratique: i) dans le cadre de maximisation d’utilit´e la moyenne et l’´ecart-type ne d´eterminent le couple gain-risque que sous des hypoth`eses tr`es fortes et tr`es peu r´ealistes et ii) l’incertitude vis-`a-vis des param`etres et la non-stationnarit´e de ceux-ci. La th`ese s’organise en cinq chapitres, une introduction et quatre articles acad´emiques. Les deux premiers articles discutent l’allocation optimale d’un investisseur lorsque l’on relˆache simultan´ement l’hypoth`ese d’une fonction d’utilit´e quadratique et celle de la normalit´e des rendements d’actif. La fonction objectif d´epend alors des moments d’ordre sup´erieur ce qui fait de l’estimation des param`etres un enjeu consid´erable. Dans ce contexte, nous proposons deux mod`eles statistiques et discutons l’arbitrage qu’il y a entre le risque d’estimation et le risque de sp´ecification en presence des moments d’ordre sup´erieurs. Alors que les deux premiers articles prennent la normalit´e dans les rendements des actifs comme donn´ee, le troisi`eme article ´etudie les b´en´efices d’une allocation lorsque l’individu force la distribution du portefeuille final `a ˆetre asym´etrique en introduisant des produits d´eriv´es dans l’univers d’actifs. Nous montrons ´egalement que l’asym´etrie, et donc un troisi`eme moment non nul, est plus articuli`erement importante en pr´esence d’un passif. Enfin, dans le dernier article, nous tenons compte explicitement de la pr´esence d’un passif et d´erivons des allocation optimales dans un cadre dynamique. Nous montrons ainsi que la dynamique du passif a un impact significatif sur la d´ecision de l’investisseur et sur sa richesse
This thesis intends to reconcile the modern portfolio theory with its original framework based on the arbitrage between risk and expected return. According to the seminal work by Harry Markowitz more than 50 years ago, expected return and risk associated with an asset may be modeled as the average return and the standard deviation of the return respectively. This methodology reveals two major problems that prevent the modeled from being applied in practice: i) in the maximum expected utility framework, it is only under rather stringent assumptions that the mean return and the standard eviation determine the trade-off between expected return and risk and ii) the uncertainty and the non-stationarity related to the involved parameters. The thesis is organized in five chapters. After an introduction the first two papers assess optimal allocation decisions when the hypotheses of gaussian returns and quadratic utility function are relaxed simultaneously. Then, the objective function depends on higher moments and co-moments which increases the challenge of parameter estimation. In this context, we propose two statistical models and discuss the trade-off between estimation and pecification risk. Whereas the first two papers take the deviation from gaussian returns as exogenous, the third chapter assesses the benefits of endogenously introducing asymmetry to the portfolio return distribution. We further assess the implications of such instruments when the investor’s capital structure is enhanced by the presence of liabilities. Finally, the last paper accounts explicitly for the presence of liabilities and derives optimal asset allocation decisions in a dynamic framework. We show that the dynamics of the liabilities drive the investor’s allocation decision and impact her expected utility of terminal wealth
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Whiting, Cameron. "Markowitz and Marriage: Finding the Optimal Risky Spouse". Scholarship @ Claremont, 2015. http://scholarship.claremont.edu/cmc_theses/1019.

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This paper examines data for 12,868 individuals from the National Longitudinal Survey of Youth (NLSY79) from 1979 through 2010 to explore certain financial incentives of marriage. In particular, this paper focuses on identifying the combination of occupations that decreases idiosyncratic income volatility to the greatest extent. For the sake of this paper, marriage is defined as the combination of two separate assets into a single portfolio. With such, I derive the efficient frontier for each occupation and gender. In the process, reward-to-volatility and mean-variance utility maximization techniques are introduced. Ultimately, applying modern portfolio theory to the marriage market allows one to examine the economic incentives of marriage in a way that has not previously been done. On the whole, the analysis confirms previous literature on marriage dynamics, while offering a new framework for analysis.
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Cheng, Chao. "Improving the Markowitz Model using the Notion of Entropy". Thesis, Uppsala University, Department of Mathematics, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-121226.

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Momanyi, Erick. "The Mathematical Formulation and Practical Implementation of Markowitz 2.0". Thesis, Mälardalens högskola, Akademin för utbildning, kultur och kommunikation, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-34690.

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Standard Deviation is a commonly used risk measures in risk management and portfolio optimization. Optimal portfolios have normally been computed using standard deviation as the measure of choice for risk. However, ever since the Great Recession, it has come up short in capturing tail risk leading practitioners and investors alike to look for alternative measures such as Value-at-Risk (VaR) and conditional Value-at-Risk (CVaR). Further, given that it is a coherent risk measure and that it allows for a simplification of the portfolio optimization process, CVaR is preferable to VaR. This thesis analyzes the financial model referred to as Markowitz 2.0 which adopts CVaRas the risk measure of choice. Tapping into the extensive literature on portfolio optimization using CVaR and VaR, we give historical context to the model and make a mathematical formulation of the model. Moreover, we present a practical implementation of the model using data drawn from the Dow Jones Industrial Average, generate optimal portfolios and draw the efficient frontier. The results obtained are compared with those obtained through the Mean-Variance optimization framework.
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Matías, Flores Teófilo, Basurco María Elena Huapaya e Ochoa Francisco R. Rasmussen. "Aplicación en el mercado peruano : teoría de portafolio de Markowitz". Universidad Peruana de Ciencias Aplicadas - UPC. Escuela de Postgrado, 2009. http://hdl.handle.net/10757/273630.

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El presente trabajo brinda al inversionista una herramienta adicional para el análisis de su portafolio de inversión a través del estudio de la Teoría de Portafolio de Markowitz, se realizará una aplicación en el mercado peruano habiendo escogido el índice Nacional INCA como portafolio de inversión ya que este nuevo índice nos muestra la cartera de las empresas más líquidas y que a partir del mes de diciembre será lanzado el Certificado de Participación INCATRACK dirigido a aquellos inversionistas con inversiones desde S/1000 y que su negociación será como cualquier otra acción en rueda de bolsa y tiene como objetivo replicar el rendimiento del índice Nacional INCA
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Freml, Josef. "Modelování individuálních investičních rizik". Master's thesis, Vysoké učení technické v Brně. Ústav soudního inženýrství, 2017. http://www.nusl.cz/ntk/nusl-318571.

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This diploma thesis deals with modeling of individual investment risks. The first part is devoted to the approach of the basic concepts in the area of investment risks, assets, portfolio and its components. The basic principles of optimization, stochastic programming including the problems of modern theory of the portfolio are presented. The analysis of the current situation is divided into two parts, where the first part contains analysis of the investor profile. In the second part, the selection and analysis of assets suitable for combination in the portfolio are made. The practical part is focused on the creation of the Markowitz model of optimal portfolio of determined assets. The model works with real data and is programmed through the GAMS mathematical program.
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DeWeese, Jackson Paul. "Markowitz-style Quartic Optimization for the Improvement of Leveraged ETF Trading". Digital WPI, 2013. https://digitalcommons.wpi.edu/etd-theses/305.

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This paper seeks to unconventionally maximize the volatility of a portfolio through a quartic optimization based on Markowitz’s modern portfolio theory, which generally seeks to do exactly the opposite. It shows that through this method, a daily leveraged exchange traded fund (ETF) strategy investigated by Posterro can be significantly improved upon in terms of its Sharpe ratio. The original strategy seeks to use a combination of momentum trading and tracking error in leveraged ETFs to trade during the last half an hour of the trading day, but it suffers in a low volatility market. By maximizing the volatility to take better advantage of tracking error and momentum, this problem is addressed by both increasing the mean daily return and significantly decreasing the variance of the strategy’s daily returns. GARCH forecasting is also implemented to assist in the maximization of the daily portfolios’ variances, though this does not prove to make a statistically significant difference in the strategy’s performance.
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Eismann, Eismann. "Markowitz vs Black--Litterman: A Comparison of Two Portfolio Optimisation Models". Thesis, Mälardalens högskola, Akademin för utbildning, kultur och kommunikation, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-39411.

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Modern portfolio theory first gained its ground among researchers and academics, but has become increasingly popular among practitioners. This paper examines the two popular portfolio optimization models, Markowitz mean-variance model and Black-Litterman formula and compares their results on real data. In second chapter mean-variance model is derived step-by-step using Lagrange multipliers and matrices, whereas in third chapter Black-Litterman formula is proved by two different methods - by Maximum Likelihood method and Theil's model. Two portfolio optimization models are used on real data, monthly data from November 2007 to November 2017. In order to build the two models, Microsoft Excel is used. Swedish 30-day Treasury Bill is taken as risk-free asset and SIXPRX as a benchmark. Detailed results are presented in Chapter 4. In Black-Litterman model two different views are implemented to see if the model outperforms Markowitz mean-variance model. All in all there is a significant difference in the outcomes, Black-Litterman portfolio performs better than mean-variance portfolio.
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Libri sul tema "Markowitz"

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Goodman, Allegra. The family Markowitz. New York, NY: Washington Square Press, a division of Simon & Schuster, Inc., 1997.

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The family Markowitz. New York: Farrar, Straus, and Giroux, 1996.

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Goodman, Allegra. The family Markowitz. New York: Farrar, Straus and Giroux, 2005.

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Markowitz, H. Harry Markowitz: Selected works. Singapore: World Scientific, 2008.

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Markowitz, Susan. My stolen son: The Nick Markowitz story. New York: Berkley Books, 2010.

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Markowitz, Fran. Coming of age in post-Soviet Russia / Fran Markowitz. Urbana: University of Illinois Press, 2000.

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The portfolio theorists: Von Neumann, Savage, Arrow and Markowitz. Houndmills, Basingstoke, Hampshire: Palgrave Macmillan, 2012.

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Read, Colin. The portfolio theorists: Von Neumann, Savage, Arrow and Markowitz. Houndmills, Basingstoke, Hampshire: Palgrave Macmillan, 2012.

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We came through Ellis Island: The immigrant adventures of Emma Markowitz. Washington, D.C: National Geographic Society, 2003.

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Four Jewish families in Philadelphia: The Solotnitsky, Markowitz, Malinger, and Rosenberg families. Baltimore, MD: Gateway Press, 2000.

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Capitoli di libri sul tema "Markowitz"

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Kaplan, Paul D., e Sam Savage. "Markowitz 2.0". In Frontiers of Modern Asset Allocation, 325–49. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2015. http://dx.doi.org/10.1002/9781119205401.ch26.

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Dick, Steven J., e Dennis D. McCarthy. "Markowitz, William". In Biographical Encyclopedia of Astronomers, 1400–1401. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4419-9917-7_904.

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Guerard, John B. "Harry Markowitz". In Profiles in Operations Research, 643–58. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-1-4419-6281-2_35.

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Hall, Graham, Ian Elliott, Mihkel Joeveer, Fabrizio Bònoli, Y. Tzvi Langermann, Josep Casulleras, Ke Ve Sarma et al. "Markowitz, William". In The Biographical Encyclopedia of Astronomers, 738–39. New York, NY: Springer New York, 2007. http://dx.doi.org/10.1007/978-0-387-30400-7_904.

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Brugière, Pierre. "The Markowitz Framework". In Springer Texts in Business and Economics, 27–50. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-37740-3_3.

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Petters, Arlie O., e Xiaoying Dong. "Markowitz Portfolio Theory". In An Introduction to Mathematical Finance with Applications, 83–150. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-3783-7_3.

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De Mol, Christine. "Sparse Markowitz Portfolios". In Financial Signal Processing and Machine Learning, 11–22. Chichester, UK: John Wiley & Sons, Ltd, 2016. http://dx.doi.org/10.1002/9781118745540.ch2.

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Linowski, Dirk, e Sven Hartmann. "Markowitz meets Real Estate". In Die moderne Finanzfunktion, 415–25. Wiesbaden: Gabler Verlag, 2008. http://dx.doi.org/10.1007/978-3-8349-9596-4_17.

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Ang, Clifford S. "Markowitz Mean-Variance Optimization". In Springer Texts in Business and Economics, 209–40. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14075-9_7.

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Ang, Clifford S. "Markowitz Mean–Variance Optimization". In Springer Texts in Business and Economics, 197–223. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-64155-9_7.

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Atti di convegni sul tema "Markowitz"

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Lee, Ingyu. "A robustILUpreconditioner using constraints diagonal Markowitz". In the 48th Annual Southeast Regional Conference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1900008.1900031.

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Ticoh, Janne Deivy, e Cherys Fomy Laloan. "Electric Power Generation Optimization with Markowitz Model". In The 7th Engineering International Conference (EIC), Engineering International Conference on Education, Concept and Application on Green Technology. SCITEPRESS - Science and Technology Publications, 2018. http://dx.doi.org/10.5220/0009009702730279.

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Ticoh, Janne Deivy, e Cherys Fomy Laloan. "Electric Power Generation Optimization with Markowitz Model". In The 7th Engineering International Conference (EIC), Engineering International Conference on Education, Concept and Application on Green Technology. SCITEPRESS - Science and Technology Publications, 2018. http://dx.doi.org/10.5220/0009009702790285.

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Ramli, Suhailywati, e Saiful Hafizah Jaaman. "Markowitz portfolio optimization model employing fuzzy measure". In THE 4TH INTERNATIONAL CONFERENCE ON MATHEMATICAL SCIENCES: Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society. Author(s), 2017. http://dx.doi.org/10.1063/1.4980932.

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Mikulis, Laurynas Mikulis, e Renaldas Vilkancas. "INVESTICINIO PORTFELIO FORMAVIMAS GLOBALIOJE AKCIJŲ RINKOJE REMIANTIS BLACK – LITTERMAN METODU". In 23rd Conference for Young Researchers "Economics and Management". Vilnius Gediminas Technical University, 2020. http://dx.doi.org/10.3846/vvf.2020.032.

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Straipsnyje yra analizuojama Black – Litterman optimalaus portfelio teorija ir jos praktinio pritai-kymo galimybės. Remiantis atlikta mokslinės literatūros analize, apibrėžiamas Black – Litterman modelis, palyginamas su H. Markowitz teorija, išskiriami pagrindiniai BL teorijos pranašumai ir trūkumai. Pasitelkiant analitinį hierarchinį procesą (AHP) nustatomi pasirinktų santykinių finansinių rodiklių svoriai. Atliekant daugiakriterinį vertinimą TOPSIS metodu, iš dešimties didžiausių pagal apyvartą įmonių „OMX Nordic 40“ indekse: „Volvo“, „Assa“, „Sandvik“, „Neste“, „Investor“, „SEB“, „Atlas“, „Novo Nordisk“, „Vestas wind systems“ ir „Nordea“, išrenkamos penkios perspektyviausios įmonių akcijos į kurias bus investuojama. Remiantis gautais rezultatais, suformuojamas optimalus investicinis portfelis pagal Black – Litterman ir H. Markowitz modelius, įvertinami sudarytų portfelių rezultatai ir jie palyginami tarpusavyje.
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Gercekovich, D. A., O. Yu Basharina, I. S. Shilnikova, E. Yu Gorbachevskaya e S. A. Gorsky. "Information and algorithmic support of a multi-level integrated system for the investment strategies formation". In 3rd International Workshop on Information, Computation, and Control Systems for Distributed Environments 2021. Crossref, 2021. http://dx.doi.org/10.47350/iccs-de.2021.06.

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The article summarizes the accumulated practical experience of the authors in the development of algorithms for the formation of investment strategies. For this purpose, the optimization of the studied parameters, information support of investment activities, verification, monitoring and adjustment in the testing mode and the subsequent practical application of the described tools are considered. The system is based on the main provisions of the Markowitz portfolio theory. The analytical block of the Information System Portfolio Investor includes Profitability-Risk model; empirical models of optimal complexity; hybrid predictive model systems; the principle of combining (integrating) both models and forecasts, as well as decision rules; optimization of the training sample length (modified Markowitz model); optimization of the frequency of monitoring and adjusting the composition of the investment portfolio. The principles of design and development of the information block of the system, its replenishment and functioning are described in detail. All the above listed components of the algorithmic content of the investment decision making system are described sequentially. The system modules have been successfully tested on a wide class of financial instruments: ordinary shares, preferred shares, government and corporate bonds, exchange commodities, stock, commodity, industry and bond indices, exchange-traded investment funds and real estate funds. The implemented Markowitz model with a dynamic database of historical data can significantly increase the efficiency of investment decisions, which is facilitated by taking into account the characteristics of both the markets under study and the corresponding financial instruments.
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Chakrabarty, Navoneel, e Sanket Biswas. "Strategic Markowitz Portfolio Optimization (SMPO): A Portfolio Return Booster". In 2019 9th Annual Information Technology, Electromechanical Engineering and Microelectronics Conference (IEMECON). IEEE, 2019. http://dx.doi.org/10.1109/iemeconx.2019.8876969.

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Wei, Jicai, Tingguang Ren, Jiali Jiang, Zhao Wei, Cui Hao e Junmei Li. "System-of-Systems Planning Method based on Markowitz Model". In Applied Simulation and Modelling. Calgary,AB,Canada: ACTAPRESS, 2012. http://dx.doi.org/10.2316/p.2012.776-017.

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Das, Sujit, e Mukul Goyal. "Rebalancing a two-asset Markowitz portfolio: A fundamental analysis". In 2012 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr). IEEE, 2012. http://dx.doi.org/10.1109/cifer.2012.6327804.

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Fei, Cai, e Hu Da-Wei. "Improvement Markowitz investment profolio model based on genetic algorithm". In 2010 2nd International Conference on Future Computer and Communication. IEEE, 2010. http://dx.doi.org/10.1109/icfcc.2010.5497721.

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