Chapter 4 Sharpe Ratio, CAPM, Jensen's Alpha, Treynor Measure
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Documento Che Attesta La Proprietà Di Una Quota Del Cap- Itale Sociale È Il Titolo Azionario E Garantisce Una Serie Di Diritti Al Titolare
Università degli Studi di Padova Facoltà di Scienze Statistiche Corso di Laurea Specialistica in Scienze Statistiche, Economiche, Finanziarie e Aziendali Tesi di Laurea : PORTFOLIO MANAGEMENT : PERFORMANCE MEASUREMENT AND FEATURE-BASED CLUSTRERING IN ASSET ALLOCATION Laureando: Nono Simplice Aimé Relatore: Prof. Caporin Massimiliano Anno accademico 2009-2010 1 A Luise Geouego e a tutta la mia famiglia. 2 Abstract This thesis analyses the possible effects of feature-based clustering (using information extracted from asset time series) in asset allocation. In particu- lar, at first, it considers the creation of asset clusters using a matrix of input data which contains some performance measure. Some of these are choosen between the classical measures, while others between the most sofisticated ones. Secondly, it statistically compares the asset allocation results obtained from data-driven groups (obtained by clustering) and a-priori classifications based on assets industrial sector. It also controls how these results can change over time. Sommario Questa tesi si propone di esaminare l’eventuale effetto di una classificazione dei titoli nei portafogli basata su informazioni contenute nelle loro serie storiche In particolare, si tratta di produrre inizialmente una suddivisione dei titoli in gruppi attraverso una cluster analysis, avendo come matrice di input alcune misure di performance selezionate fra quelle classiche e quelle più sofisticate e in un secondo momento, di confrontare i risultati con quelli ottenuti operando una diversificazione dei titoli in macrosettori industriali; infine di analizzare come i risultati ottenuti variano nel tempo. Indice 1 Asset Allocation 7 1.1 Introduzione . 7 1.2 Introduzione alle azioni . 8 1.3 Criterio Rischio-Rendimento . -
Fact Sheet 2021
Q2 2021 GCI Select Equity TM Globescan Capital was Returns (Average Annual) Morningstar Rating (as of 3/31/21) © 2021 Morningstar founded on the principle Return Return that investing in GCI Select S&P +/- Percentile Quartile Overall Funds in high-quality companies at Equity 500TR Rank Rank Rating Category attractive prices is the best strategy to achieve long-run Year to Date 18.12 15.25 2.87 Q1 2021 Top 30% 2nd 582 risk-adjusted performance. 1-year 43.88 40.79 3.08 1 year Top 19% 1st 582 As such, our portfolio is 3-year 22.94 18.67 4.27 3 year Top 3% 1st 582 concentrated and focused solely on the long-term, Since Inception 20.94 17.82 3.12 moat-protected future free (01/01/17) cash flows of the companies we invest in. TOP 10 HOLDINGS PORTFOLIO CHARACTERISTICS Morningstar Performance MPT (6/30/2021) (6/30/2021) © 2021 Morningstar Core Principles Facebook Inc A 6.76% Number of Holdings 22 Return 3 yr 19.49 Microsoft Corp 6.10% Total Net Assets $44.22M Standard Deviation 3 yr 18.57 American Tower Corp 5.68% Total Firm Assets $119.32M Alpha 3 yr 3.63 EV/EBITDA (ex fincls/reits) 17.06x Upside Capture 3yr 105.46 Crown Castle International Corp 5.56% P/E FY1 (ex fincls/reits) 29.0x Downside Capture 3 yr 91.53 Charles Schwab Corp 5.53% Invest in businesses, EPS Growth (ex fincls/reits) 25.4% Sharpe Ratio 3 yr 1.04 don't trade stocks United Parcel Service Inc Class B 5.44% ROIC (ex fincls/reits) 14.1% Air Products & Chemicals Inc 5.34% Standard Deviation (3-year) 18.9% Booking Holding Inc 5.04% % of assets in top 5 holdings 29.6% Mastercard Inc A 4.74% % of assets in top 10 holdings 54.7% First American Financial Corp 4.50% Dividend Yield 0.70% Think long term, don't try to time markets Performance vs S&P 500 (Average Annual Returns) Be concentrated, 43.88 GCI Select Equity don't overdiversify 40.79 S&P 500 TR 22.94 20.94 18.12 18.67 17.82 15.25 Use the market, don't rely on it YTD 1 YR 3 YR Inception (01/01/2017) Disclosures Globescan Capital Inc., d/b/a GCI-Investors, is an investment advisor registered with the SEC. -
The Value-Added of Investable Hedge Fund Indices
A Service of Leibniz-Informationszentrum econstor Wirtschaft Leibniz Information Centre Make Your Publications Visible. zbw for Economics Heidorn, Thomas; Kaiser, Dieter G.; Voinea, Andre Working Paper The value-added of investable hedge fund indices Frankfurt School - Working Paper Series, No. 141 Provided in Cooperation with: Frankfurt School of Finance and Management Suggested Citation: Heidorn, Thomas; Kaiser, Dieter G.; Voinea, Andre (2010) : The value- added of investable hedge fund indices, Frankfurt School - Working Paper Series, No. 141, Frankfurt School of Finance & Management, Frankfurt a. M. This Version is available at: http://hdl.handle.net/10419/36695 Standard-Nutzungsbedingungen: Terms of use: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Documents in EconStor may be saved and copied for your Zwecken und zum Privatgebrauch gespeichert und kopiert werden. personal and scholarly purposes. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle You are not to copy documents for public or commercial Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich purposes, to exhibit the documents publicly, to make them machen, vertreiben oder anderweitig nutzen. publicly available on the internet, or to distribute or otherwise use the documents in public. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, If the documents have been made available under an Open gelten abweichend von diesen Nutzungsbedingungen die in der dort Content Licence (especially Creative Commons Licences), you genannten Lizenz gewährten Nutzungsrechte. may exercise further usage rights as specified in the indicated licence. www.econstor.eu Frankfurt School – Working Paper Series No. 141 The Value-Added of Investable Hedge Fund Indices by Thomas Heidorn, Dieter G. -
Post-Modern Portfolio Theory Supports Diversification in an Investment Portfolio to Measure Investment's Performance
A Service of Leibniz-Informationszentrum econstor Wirtschaft Leibniz Information Centre Make Your Publications Visible. zbw for Economics Rasiah, Devinaga Article Post-modern portfolio theory supports diversification in an investment portfolio to measure investment's performance Journal of Finance and Investment Analysis Provided in Cooperation with: Scienpress Ltd, London Suggested Citation: Rasiah, Devinaga (2012) : Post-modern portfolio theory supports diversification in an investment portfolio to measure investment's performance, Journal of Finance and Investment Analysis, ISSN 2241-0996, International Scientific Press, Vol. 1, Iss. 1, pp. 69-91 This Version is available at: http://hdl.handle.net/10419/58003 Standard-Nutzungsbedingungen: Terms of use: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Documents in EconStor may be saved and copied for your Zwecken und zum Privatgebrauch gespeichert und kopiert werden. personal and scholarly purposes. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle You are not to copy documents for public or commercial Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich purposes, to exhibit the documents publicly, to make them machen, vertreiben oder anderweitig nutzen. publicly available on the internet, or to distribute or otherwise use the documents in public. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, If the documents have been made available under an Open gelten abweichend -
Università Degli Studi Di Padova Padua Research Archive
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Archivio istituzionale della ricerca - Università di Padova Università degli Studi di Padova Padua Research Archive - Institutional Repository On the (Ab)use of Omega? Original Citation: Availability: This version is available at: 11577/3255567 since: 2020-01-04T17:03:43Z Publisher: Elsevier B.V. Published version: DOI: 10.1016/j.jempfin.2017.11.007 Terms of use: Open Access This article is made available under terms and conditions applicable to Open Access Guidelines, as described at http://www.unipd.it/download/file/fid/55401 (Italian only) (Article begins on next page) \On the (Ab)Use of Omega?" Massimiliano Caporina,∗, Michele Costolab, Gregory Janninc, Bertrand Mailletd aUniversity of Padova, Department of Statistical Sciences bSAFE, Goethe University Frankfurt cJMC Asset Management LLC dEMLyon Business School and Variances Abstract Several recent finance articles use the Omega measure (Keating and Shadwick, 2002), defined as a ratio of potential gains out of possible losses, for gauging the performance of funds or active strategies, in substitution of the traditional Sharpe ratio, with the arguments that return distributions are not Gaussian and volatility is not always the rel- evant risk metric. Other authors also use Omega for optimizing (non-linear) portfolios with important downside risk. However, we question in this article the relevance of such approaches. First, we show through a basic illustration that the Omega ratio is incon- sistent with the Second-order Stochastic Dominance criterion. Furthermore, we observe that the trade-off between return and risk corresponding to the Omega measure, may be essentially influenced by the mean return. -
307439 Ferdig Master Thesis
Master's Thesis Using Derivatives And Structured Products To Enhance Investment Performance In A Low-Yielding Environment - COPENHAGEN BUSINESS SCHOOL - MSc Finance And Investments Maria Gjelsvik Berg P˚al-AndreasIversen Supervisor: Søren Plesner Date Of Submission: 28.04.2017 Characters (Ink. Space): 189.349 Pages: 114 ABSTRACT This paper provides an investigation of retail investors' possibility to enhance their investment performance in a low-yielding environment by using derivatives. The current low-yielding financial market makes safe investments in traditional vehicles, such as money market funds and safe bonds, close to zero- or even negative-yielding. Some retail investors are therefore in need of alternative investment vehicles that can enhance their performance. By conducting Monte Carlo simulations and difference in mean testing, we test for enhancement in performance for investors using option strategies, relative to investors investing in the S&P 500 index. This paper contributes to previous papers by emphasizing the downside risk and asymmetry in return distributions to a larger extent. We find several option strategies to outperform the benchmark, implying that performance enhancement is achievable by trading derivatives. The result is however strongly dependent on the investors' ability to choose the right option strategy, both in terms of correctly anticipated market movements and the net premium received or paid to enter the strategy. 1 Contents Chapter 1 - Introduction4 Problem Statement................................6 Methodology...................................7 Limitations....................................7 Literature Review.................................8 Structure..................................... 12 Chapter 2 - Theory 14 Low-Yielding Environment............................ 14 How Are People Affected By A Low-Yield Environment?........ 16 Low-Yield Environment's Impact On The Stock Market........ -
Securitization & Hedge Funds
SECURITIZATION & HEDGE FUNDS: COLLATERALIZED FUND OBLIGATIONS SECURITIZATION & HEDGE FUNDS: CREATING A MORE EFFICIENT MARKET BY CLARK CHENG, CFA Intangis Funds AUGUST 6, 2002 INTANGIS PAGE 1 SECURITIZATION & HEDGE FUNDS: COLLATERALIZED FUND OBLIGATIONS TABLE OF CONTENTS INTRODUCTION........................................................................................................................................ 3 PROBLEM.................................................................................................................................................... 4 SOLUTION................................................................................................................................................... 5 SECURITIZATION..................................................................................................................................... 5 CASH-FLOW TRANSACTIONS............................................................................................................... 6 MARKET VALUE TRANSACTIONS.......................................................................................................8 ARBITRAGE................................................................................................................................................ 8 FINANCIAL ENGINEERING.................................................................................................................... 8 TRANSPARENCY...................................................................................................................................... -
Risk and Return Comparison of MBS, REIT and Non-REIT Etfs
International Journal of Business, Humanities and Technology Vol. 7, No. 3, September 2017 Risk and Return Comparison of MBS, REIT and Non-REIT Etfs Hamid Falatoon Ph.D Faculty at School of Business University of Redlands Redlands, CA 92373, USA Mohammad R. Safarzadeh Economics California State PolytechnicUniversity Pomona, CA, USA Abstract MBS has become an investment instrument ofchoice for retiring individuals and the ones who have preference for a secure stream of returns while taking lower risk relative to other vehicles of investment. As well, MBS has lately become a recommended investment strategy by financial advisers and investment bankers for safeguarding the retirement accounts of retirees from wild market fluctuations. The objective of this paper is to compare the risk and return of MBS with REIT and Non-REIT invetment opportunities. The paper uses finance ratios such as Sharpe, Sortino, and Traynor ratios as well as market risk and value at risk (VaR) analysis to compare and contrast the relative risk and return of a number equities in MBS, REIT and Non-REIT. The study extends the analysis to pre-recession of 2007-2009 to analyze the effect of the great recession on the relative risk and return of three diffrerent mediums of investment. Keywords: Risk and Return, MBS, REIT, Sharpe, Sortino, Treynor, VaR, CAPM I. Introduction Mortgage-backed securities (MBS) are debt obligations that represent claims to the cash flows from a pool of commercial and residential mortgage loans. The mortgage loans, purchased from banks, mortgage companies, and other originators are securitized by a governmental, quasi-governmental, or private entity. -
On the Ω‐Ratio
On the Ω‐Ratio Robert J. Frey Applied Mathematics and Statistics Stony Brook University 29 January 2009 15 April 2009 (Rev. 05) Applied Mathematics & Statistics [email protected] On the Ω‐Ratio Robert J. Frey Applied Mathematics and Statistics Stony Brook University 29 January 2009 15 April 2009 (Rev. 05) ABSTRACT Despite the fact that the Ωratio captures the complete shape of the underlying return distribution, selecting a portfolio by maximizing the value of the Ωratio at a given return threshold does not necessarily produce a portfolio that can be considered optimal over a reasonable range of investor preferences. Specifically, this selection criterion tends to select a feasible portfolio that maximizes available leverage (whether explicitly applied by the investor or realized internally by the capital structure of the investment itself) and, therefore, does not trade off risk and reward in a manner that most investors would find acceptable. 2 Table of Contents 1. The ΩRatio.................................................................................................................................... 4 1.1 Background ............................................................................................................................................5 1.2 The Ω Leverage Bias............................................................................................................................7 1.3. A Simple Example of the ΩLB ..........................................................................................................8 -
Lapis Global Top 50 Dividend Yield Index Ratios
Lapis Global Top 50 Dividend Yield Index Ratios MARKET RATIOS 2012 2013 2014 2015 2016 2017 2018 2019 2020 P/E Lapis Global Top 50 DY Index 14,45 16,07 16,71 17,83 21,06 22,51 14,81 16,96 19,08 MSCI ACWI Index (Benchmark) 15,42 16,78 17,22 19,45 20,91 20,48 14,98 19,75 31,97 P/E Estimated Lapis Global Top 50 DY Index 12,75 15,01 16,34 16,29 16,50 17,48 13,18 14,88 14,72 MSCI ACWI Index (Benchmark) 12,19 14,20 14,94 15,16 15,62 16,23 13,01 16,33 19,85 P/B Lapis Global Top 50 DY Index 2,52 2,85 2,76 2,52 2,59 2,92 2,28 2,74 2,43 MSCI ACWI Index (Benchmark) 1,74 2,02 2,08 2,05 2,06 2,35 2,02 2,43 2,80 P/S Lapis Global Top 50 DY Index 1,49 1,70 1,72 1,65 1,71 1,93 1,44 1,65 1,60 MSCI ACWI Index (Benchmark) 1,08 1,31 1,35 1,43 1,49 1,71 1,41 1,72 2,14 EV/EBITDA Lapis Global Top 50 DY Index 9,52 10,45 10,77 11,19 13,07 13,01 9,92 11,82 12,83 MSCI ACWI Index (Benchmark) 8,93 9,80 10,10 11,18 11,84 11,80 9,99 12,22 16,24 FINANCIAL RATIOS 2012 2013 2014 2015 2016 2017 2018 2019 2020 Debt/Equity Lapis Global Top 50 DY Index 89,71 93,46 91,08 95,51 96,68 100,66 97,56 112,24 127,34 MSCI ACWI Index (Benchmark) 155,55 137,23 133,62 131,08 134,68 130,33 125,65 129,79 140,13 PERFORMANCE MEASURES 2012 2013 2014 2015 2016 2017 2018 2019 2020 Sharpe Ratio Lapis Global Top 50 DY Index 1,48 2,26 1,05 -0,11 0,84 3,49 -1,19 2,35 -0,15 MSCI ACWI Index (Benchmark) 1,23 2,22 0,53 -0,15 0,62 3,78 -0,93 2,27 0,56 Jensen Alpha Lapis Global Top 50 DY Index 3,2 % 2,2 % 4,3 % 0,3 % 2,9 % 2,3 % -3,9 % 2,4 % -18,6 % Information Ratio Lapis Global Top 50 DY Index -0,24 -
Monte Carlo As a Hedge Fund Risk Forecasting Tool
F eat UR E Monte Carlo as a Hedge Fund Risk Forecasting Tool By Kenneth S. Phillips edge funds have gained The notion of uncorrelated, absolute popularity over the past “retur ns encompassing a broad range of asset Hseveral years, especially among institutional investors. Assets allocated classes and distinct strategies has enjoyed to alternative investment strategies, distinct from private equity or venture great acceptance among conservative inves- capital, have grown by several hundred tors seeking more predictable and consistent percent since the dot-com bubble burst in 2000 and now top US$2.5 trillion. retur ns with less volatility. The notion of uncorrelated, absolute returns encompassing a broad range ” of asset classes and distinct strategies has enjoyed great acceptance among conservative investors seeking more level of qualitative due diligence, may management objectives resulted in the predictable and consistent returns with or may not have provided warnings evaporation of nearly US$6.5 billion of less volatility. As a result, the industry and/or given investors adequate time to investor equity, virtually overnight. has begun to mature and investors now redeem their capital. Although the ar- Global Equity Market Neutral range from risk-averse fiduciaries to ag- ticle implicitly considers different forms (GEMN). Since 2003, GEMN had gressive high-net-worth individuals. of investment risk such as leverage managed a globally diversified, equity As the number of hedge funds and and derivatives, it focuses primarily on market neutral hedge fund. Employ- complex strategies has grown, so too quantitative return-based data that was ing various amounts of leverage while have the frequency and severity of publicly available rather than strategy- attracting several billion dollars of negative events—what statisticians refer or security-specific risk. -
Arbitrage Pricing Theory: Theory and Applications to Financial Data Analysis Basic Investment Equation
Risk and Portfolio Management Spring 2010 Arbitrage Pricing Theory: Theory and Applications To Financial Data Analysis Basic investment equation = Et equity in a trading account at time t (liquidation value) = + Δ Rit return on stock i from time t to time t t (includes dividend income) = Qit dollars invested in stock i at time t r = interest rate N N = + Δ + − ⎛ ⎞ Δ ()+ Δ Et+Δt Et Et r t ∑Qit Rit ⎜∑Qit ⎟r t before rebalancing, at time t t i=1 ⎝ i=1 ⎠ N N N = + Δ + − ⎛ ⎞ Δ + ε ()+ Δ Et+Δt Et Et r t ∑Qit Rit ⎜∑Qit ⎟r t ∑| Qi(t+Δt) - Qit | after rebalancing, at time t t i=1 ⎝ i=1 ⎠ i=1 ε = transaction cost (as percentage of stock price) Leverage N N = + Δ + − ⎛ ⎞ Δ Et+Δt Et Et r t ∑Qit Rit ⎜∑Qit ⎟r t i=1 ⎝ i=1 ⎠ N ∑ Qit Ratio of (gross) investments i=1 Leverage = to equity Et ≥ Qit 0 ``Long - only position'' N ≥ = = Qit 0, ∑Qit Et Leverage 1, long only position i=1 Reg - T : Leverage ≤ 2 ()margin accounts for retail investors Day traders : Leverage ≤ 4 Professionals & institutions : Risk - based leverage Portfolio Theory Introduce dimensionless quantities and view returns as random variables Q N θ = i Leverage = θ Dimensionless ``portfolio i ∑ i weights’’ Ei i=1 ΔΠ E − E − E rΔt ΔE = t+Δt t t = − rΔt Π Et E ~ All investments financed = − Δ Ri Ri r t (at known IR) ΔΠ N ~ = θ Ri Π ∑ i i=1 ΔΠ N ~ ΔΠ N ~ ~ N ⎛ ⎞ ⎛ ⎞ 2 ⎛ ⎞ ⎛ ⎞ E = θ E Ri ; σ = θ θ Cov Ri , R j = θ θ σ σ ρ ⎜ Π ⎟ ∑ i ⎜ ⎟ ⎜ Π ⎟ ∑ i j ⎜ ⎟ ∑ i j i j ij ⎝ ⎠ i=1 ⎝ ⎠ ⎝ ⎠ ij=1 ⎝ ⎠ ij=1 Sharpe Ratio ⎛ ΔΠ ⎞ N ⎛ ~ ⎞ E θ E R ⎜ Π ⎟ ∑ i ⎜ i ⎟ s = s()θ ,...,θ = ⎝ ⎠ = i=1 ⎝ ⎠ 1 N ⎛ ΔΠ ⎞ N σ ⎜ ⎟ θ θ σ σ ρ Π ∑ i j i j ij ⎝ ⎠ i=1 Sharpe ratio is homogeneous of degree zero in the portfolio weights.