The Hitchhiker's Guide to Risk-Adjusted Returns
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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. -
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 -
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. -
Performance Measurement in Finance : Firms, Funds and Managers
PERFORMANCE MEASUREMENT IN FINANCE Butterworth-Heinemann Finance aims and objectives • books based on the work of financial market practitioners and academics • presenting cutting edge research to the professional/practitioner market • combining intellectual rigour and practical application • covering the interaction between mathematical theory and financial practice • to improve portfolio performance, risk management and trading book performance • covering quantitative techniques market Brokers/Traders; Actuaries; Consultants; Asset Managers; Fund Managers; Regulators; Central Bankers; Treasury Officials; Technical Analysts; and Academics for Masters in Finance and MBA market. series titles Return Distributions in Finance Derivative Instruments: theory, valuation, analysis Managing Downside Risk in Financial Markets: theory, practice and implementation Economics for Financial Markets Global Tactical Asset Allocation: theory and practice Performance Measurement in Finance: firms, funds and managers Real R&D Options series editor Dr Stephen Satchell Dr Satchell is Reader in Financial Econometrics at Trinity College, Cambridge; Visiting Professor at Birkbeck College, City University Business School and University of Technology, Sydney. He also works in a consultative capacity to many firms, and edits the journal Derivatives: use, trading and regulations. PERFORMANCE MEASUREMENT IN FINANCE Firms, Funds and Managers Edited by John Knight Stephen Satchell OXFORD AMSTERDAM BOSTON LONDON NEW YORK PARIS SAN DIEGO SAN FRANCISCO SINGAPORE SYDNEY TOKYO -
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 -
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. -
Sharpe Ratio
StatFACTS Sharpe Ratio StatMAP CAPITAL The most famous return-versus- voLATILITY BENCHMARK TAIL PRESERVATION risk measurement, the Sharpe ratio, RN TU E represents the added value over the R risk-free rate per unit of volatility risk. K S I R FF O - E SHARPE AD R RATIO T How Is it Useful? What Do the Graphs Show Me? The Sharpe ratio simplifies the options facing the The graphs below illustrate the two halves of the investor by separating investments into one of two Sharpe ratio. The upper graph shows the numerator, the choices, the risk-free rate or anything else. Thus, the excess return over the risk-free rate. The blue line is the Sharpe ratio allows investors to compare very different investment. The red line is the risk-free rate on a rolling, investments by the same criteria. Anything that isn’t three-year basis. More often than not, the investment’s the risk-free investment can be compared against any return exceeds that of the risk-free rate, leading to a other investment. The Sharpe ratio allows for apples-to- positive numerator. oranges comparisons. The lower graph shows the risk metric used in the denominator, standard deviation. Standard deviation What Is a Good Number? measures how volatile an investment’s returns have been. Sharpe ratios should be high, with the larger the number, the better. This would imply significant outperformance versus the risk-free rate and/or a low standard deviation. Rolling Three Year Return However, there is no set-in-stone breakpoint above, 40% 30% which is good, and below, which is bad. -
A Sharper Ratio: a General Measure for Correctly Ranking Non-Normal Investment Risks
A Sharper Ratio: A General Measure for Correctly Ranking Non-Normal Investment Risks † Kent Smetters ∗ Xingtan Zhang This Version: February 3, 2014 Abstract While the Sharpe ratio is still the dominant measure for ranking risky investments, much effort has been made over the past three decades to find more robust measures that accommodate non- Normal risks (e.g., “fat tails”). But these measures have failed to map to the actual investor problem except under strong restrictions; numerous ad-hoc measures have arisen to fill the void. We derive a generalized ranking measure that correctly ranks risks relative to the original investor problem for a broad utility-and-probability space. Like the Sharpe ratio, the generalized measure maintains wealth separation for the broad HARA utility class. The generalized measure can also correctly rank risks following different probability distributions, making it a foundation for multi-asset class optimization. This paper also explores the theoretical foundations of risk ranking, including proving a key impossibility theorem: any ranking measure that is valid for non-Normal distributions cannot generically be free from investor preferences. Finally, we show that approximation measures, which have sometimes been used in the past, fail to closely approximate the generalized ratio, even if those approximations are extended to an infinite number of higher moments. Keywords: Sharpe Ratio, portfolio ranking, infinitely divisible distributions, generalized rank- ing measure, Maclaurin expansions JEL Code: G11 ∗Kent Smetters: Professor, The Wharton School at The University of Pennsylvania, Faculty Research Associate at the NBER, and affiliated faculty member of the Penn Graduate Group in Applied Mathematics and Computational Science. -
Generating Potential Income in a Low Interest Rate World
GENERATING POTENTIAL INCOME IN A LOW INTEREST Hypothetical Growth of 10K: 5/1/2013 to 1/31/2017 RATE WORLD $ 12,000.0 Write Income is solely focused on generating yield $ 11,500.0 through dividends and derivatives strategies with a focus on seeking to generate a high single-digit yield. This strategy is comprised of firms that have $ 11,000.0 sustainable business models, attractive balance sheets and strong cash flow generation with a $ 10,500.0 history of sustaining and increasing dividends over time. $ 10,000.0 $ 9,500.0 INVESTMENT OBJECTIVE 1/2014 7/2014 1/2015 7/2015 1/2016 7/2016 1/2017 Investment Horizon: Minimum of 3 Years Write Income (Gross) Write Income (Net) BarCap US Agg Bond Investment Minimum: $200,000 Past performance is not indicative of future results. See additional important disclosures on next page. Benchmark: Barclays US Agg Bond Objective: Growth with Income Write Income Performance (Annualized) Since 1 Mo 3 Mo YTD 1 Yr 3 Yr 5 Yr 10 Yr 5/1/2013 Top Holdings Write Income (Gross) 2.66-0.36-0.36 11.08 4.75 —— 4.16 Portfolio % Write Income (Net) 2.19-0.51-0.51 9.09 2.88 —— 2.30 Target Corp 5.40 BarCap US Agg Bond -2.040.200.20 1.45 2.59 —— 1.67 Cisco Systems Inc 5.38 Exxon Mobil Corp 4.39 Calendar Year Performance Waste Management Inc 4.03 YTD 2016 2015 2013 General Mills Inc 3.87 Write Income (Gross) -0.36 6.53 -2.07 4.10 Invesco Ltd 3.63 Write Income (Net) -0.51 4.63 -3.82 2.85 Eaton Corp PLC 3.62 BarCap US Agg Bond 0.20 2.65 0.55 -2.89 MetLife Inc 3.54 Wal-Mart Stores Inc 3.50 Dow Chemical Co 3.49 Risk Analysis