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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. -
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. -
Dividend Valuation Models Prepared by Pamela Peterson Drake, Ph.D., CFA
Dividend valuation models Prepared by Pamela Peterson Drake, Ph.D., CFA Contents 1. Overview ..................................................................................................................................... 1 2. The basic model .......................................................................................................................... 1 3. Non-constant growth in dividends ................................................................................................. 5 A. Two-stage dividend growth ...................................................................................................... 5 B. Three-stage dividend growth .................................................................................................... 5 C. The H-model ........................................................................................................................... 7 4. The uses of the dividend valuation models .................................................................................... 8 5. Stock valuation and market efficiency ......................................................................................... 10 6. Summary .................................................................................................................................. 10 7. Index ........................................................................................................................................ 11 8. Further readings ....................................................................................................................... -
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. -
Earnings, Cash Flow, Dividend Payout and Growth Influences on the Price of Common Stocks
Louisiana State University LSU Digital Commons LSU Historical Dissertations and Theses Graduate School 1968 Earnings, Cash Flow, Dividend Payout and Growth Influences on the Price of Common Stocks. William Frank Tolbert Louisiana State University and Agricultural & Mechanical College Follow this and additional works at: https://digitalcommons.lsu.edu/gradschool_disstheses Recommended Citation Tolbert, William Frank, "Earnings, Cash Flow, Dividend Payout and Growth Influences on the Price of Common Stocks." (1968). LSU Historical Dissertations and Theses. 1522. https://digitalcommons.lsu.edu/gradschool_disstheses/1522 This Dissertation is brought to you for free and open access by the Graduate School at LSU Digital Commons. It has been accepted for inclusion in LSU Historical Dissertations and Theses by an authorized administrator of LSU Digital Commons. For more information, please contact [email protected]. This dissertation has been microfilmed exactly as received 69-4505 TOLBERT, William Frank, 1918- EARNINGS, CASH FLOW, DIVIDEND PAYOUT AND GROWTH INFLUENCES ON THE PRICE OF COMMON STOCKS. Louisiana State University and Agricultural and Mechanical College, Ph.D., 1968 Economics, finance University Microfilms, Inc., Ann Arbor, Michigan William Frank Tolbert 1969 © _____________________________ ALL RIGHTS RESERVED EARNINGS, CASH FLOW, DIVIDEND PAYOUT AND GROWTH INFLUENCES ON THE PRICE OF COMMON STOCKS A Dissertation Submitted to the Graduate Faculty of the Louisiana State University and Agricultural and Mechanical College in partial fulfillment of the requirements for the degree of Doctor of Philosophy in The Department of Business Finance and Statistics b y . William F.' Tolbert B.S., University of Oklahoma, 1949 M.B.A., University of Oklahoma, 1950 August, 1968 ACKNOWLEDGEMENT The writer wishes to express his sincere apprecia tion to Dr. -
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. -
In-Sample and Out-Of-Sample Sharpe Ratios of Multi-Factor Asset Pricing Models
In-sample and Out-of-sample Sharpe Ratios of Multi-factor Asset Pricing Models RAYMOND KAN, XIAOLU WANG, and XINGHUA ZHENG∗ This version: November 2020 ∗Kan is from the University of Toronto, Wang is from Iowa State University, and Zheng is from Hong Kong University of Science and Technology. We thank Svetlana Bryzgalova, Peter Christoffersen, Victor DeMiguel, Andrew Detzel, Junbo Wang, Guofu Zhou, seminar participants at Chinese University of Hong Kong, London Business School, Louisiana State University, Uni- versity of Toronto, and conference participants at 2019 CFIRM Conference for helpful comments. Corresponding author: Raymond Kan, Joseph L. Rotman School of Management, University of Toronto, 105 St. George Street, Toronto, Ontario, Canada M5S 3E6; Tel: (416) 978-4291; Fax: (416) 978-5433; Email: [email protected]. In-sample and Out-of-sample Sharpe Ratios of Multi-factor Asset Pricing Models Abstract For many multi-factor asset pricing models proposed in the recent literature, their implied tangency portfolios have substantially higher sample Sharpe ratios than that of the value- weighted market portfolio. In contrast, such high sample Sharpe ratio is rarely delivered by professional fund managers. This makes it difficult for us to justify using these asset pricing models for performance evaluation. In this paper, we explore if estimation risk can explain why the high sample Sharpe ratios of asset pricing models are difficult to realize in reality. In particular, we provide finite sample and asymptotic analyses of the joint distribution of in-sample and out-of-sample Sharpe ratios of a multi-factor asset pricing model. For an investor who does not know the mean and covariance matrix of the factors in a model, the out-of-sample Sharpe ratio of an asset pricing model is substantially worse than its in-sample Sharpe ratio. -
How Does the Market Interpret Analysts' Long-Term Growth Forecasts? Steven A. Sharpe
How Does the Market Interpret Analysts’ Long-term Growth Forecasts? Steven A. Sharpe Division of Research and Statistics Federal Reserve Board Washington, D.C. 20551 (202)452-2875 [email protected] April, 2004 Forthcoming in the Journal of Accounting, Auditing and Finance. The views expressed herein are those of the author and do not necessarily reflect the views of the Board nor the staff of the Federal Reserve System. I am grateful for comments and suggestions from Jason Cummins, Steve Oliner, and an anonymous referee, and members of the Capital Markets Section at the Board. Excellent research assistance was provided by Eric Richards and Dimitri Paliouras. How Does the Market Interpret Analysts’ Long-term Growth Forecasts? Abstract The long-term growth forecasts of equity analysts do not have well-defined horizons, an ambiguity of substantial import for many applications. I propose an empirical valuation model, derived from the Campbell-Shiller dividend-price ratio model, in which the forecast horizon used by the “market” can be deduced from linear regressions. Specifically, in this model, the horizon can be inferred from the elasticity of the price-earnings ratio with respect to the long- term growth forecast. The model is estimated on industry- and sector-level portfolios of S&P 500 firms over 1983-2001. The estimated coefficients on consensus long-term growth forecasts suggest that the market applies these forecasts to an average horizon somewhere in the range of five to ten years. -1- 1. Introduction Long-term earnings growth forecasts by equity analysts have garnered increasing attention over the last several years, both in academic and practitioner circles. -
QUESTIONS 3.1 Profitability Ratios Questions 1 and 2 Are Based on The
140 SU 3: Profitability Analysis and Analytical Issues QUESTIONS 3.1 Profitability Ratios Questions 1 and 2 are based on the following information. The financial statements for Dividendosaurus, Inc., for the current year are as follows: Balance Sheet Statement of Income and Retained Earnings Cash $100 Sales $ 3,000 Accounts receivable 200 Cost of goods sold (1,600) Inventory 50 Gross profit $ 1,400 Net fixed assets 600 Operations expenses (970) Total $950 Operating income $ 430 Interest expense (30) Accounts payable $140 Income before tax $ 400 Long-term debt 300 Income tax (200) Capital stock 260 Net income $ 200 Retained earnings 250 Plus Jan. 1 retained earnings 150 Total $950 Minus dividends (100) Dec. 31 retained earnings $ 250 1. Dividendosaurus has return on assets of Answer (A) is correct. (CIA, adapted) REQUIRED: The return on assets. DISCUSSION: The return on assets is the ratio of net A. 21.1% income to total assets. It equals 21.1% ($200 NI ÷ $950 total B. 39.2% assets). Answer (B) is incorrect. The ratio of net income to common C. 42.1% equity is 39.2%. Answer (C) is incorrect. The ratio of income D. 45.3% before tax to total assets is 42.1%. Answer (D) is incorrect. The ratio of income before interest and tax to total assets is 45.3%. 2. Dividendosaurus has a profit margin of Answer (A) is correct. (CIA, adapted) REQUIRED: The profit margin. DISCUSSION: The profit margin is the ratio of net income to A. 6.67% sales. It equals 6.67% ($200 NI ÷ $3,000 sales). -
Picking the Right Risk-Adjusted Performance Metric
WORKING PAPER: Picking the Right Risk-Adjusted Performance Metric HIGH LEVEL ANALYSIS QUANTIK.org Investors often rely on Risk-adjusted performance measures such as the Sharpe ratio to choose appropriate investments and understand past performances. The purpose of this paper is getting through a selection of indicators (i.e. Calmar ratio, Sortino ratio, Omega ratio, etc.) while stressing out the main weaknesses and strengths of those measures. 1. Introduction ............................................................................................................................................. 1 2. The Volatility-Based Metrics ..................................................................................................................... 2 2.1. Absolute-Risk Adjusted Metrics .................................................................................................................. 2 2.1.1. The Sharpe Ratio ............................................................................................................................................................. 2 2.1. Relative-Risk Adjusted Metrics ................................................................................................................... 2 2.1.1. The Modigliani-Modigliani Measure (“M2”) ........................................................................................................ 2 2.1.2. The Treynor Ratio ......................................................................................................................................................... -
Dividend Discount Models
ch13_p323-350.qxp 12/5/11 2:14 PM Page 323 CHAPTER 13 Dividend Discount Models n the strictest sense, the only cash flow you receive from a firm when you buy I publicly traded stock in it is a dividend. The simplest model for valuing equity is the dividend discount model—the value of a stock is the present value of expected dividends on it. While many analysts have turned away from the dividend discount model and view it as outmoded, much of the intuition that drives discounted cash flow valuation stems from the dividend discount model. In fact, there are compa- nies where the dividend discount model remains a useful tool for estimating value. This chapter explores the general model as well as specific versions of it tailored for different assumptions about future growth. It also examines issues in using the dividend discount model and the results of studies that have looked at its efficacy. THE GENERAL MODEL When an investor buys stock, he or she generally expects to get two types of cash flows—dividends during the period the stock is held and an expected price at the end of the holding period. Since this expected price is itself determined by future dividends, the value of a stock is the present value of dividends through infinity: ∞ t= E(DPS ) Value per share of stock = ∑ t + t t=1 ()1 ke = where DPSt Expected dividends per share = ke Cost of equity The rationale for the model lies in the present value rule—the value of any asset is the present value of expected future cash flows, discounted at a rate appropriate to the riskiness of the cash flows being discounted.