Bloomberg Exercises for Investments
R. Stafford Johnson
Bloomberg Missionary
Department of Finance
Xavier University
Bloomberg Exercises for Investments
• Essay/Bloomberg projects covering subjects related to:
Portfolio Ranking
Markowitz Portfolio Analysis
CAPM and APT
Applied Fundamental Analysis
Technical Analysis
Efficient Markets
Equity Style Investment
Portfolio Insurance
ETF Construction
2
Expected Return and Risk
• Essay: Explain how the following parameters are
used for analyzing a stock or portfolio:
– Coefficient of determination
– Beta
– Convexity: Beta+ and Beta−
– Alpha
• Bloomberg Part: Use Bloomberg’s Beta and PC
screens to evaluate a stock in terms of these
parameters. 3
4
GE Regression
• GE has a beta 1.172,
alpha of –.028, σ(ε) of
1.644 (V(ε) = 2.7027),
t-statistic = β/ σ(β) =
40.436, and R2 of
0.752:
7027.2)()172.1()(
)(ˆ)(ˆ)(
)(172.1028.0)(
)(ˆˆ)(
2
2
M
M
M
M
RVrV
VRVrV
RErE
RErE
5
Alpha
• The exhibit shows a
comparison of the alphas
for GE and related
companies in its industry
taken from Bloomberg’s
PC screen.
• GE is one of five in the
peer group with a
negative alpha (for
regression with S&P 500)
Bloomberg PC Screem
Portfolio Ranking and Borrowing-Lending Line
• Essay: Explain intuitively and with an example the borrowing and lending line. Explain how the borrowing and lending line is a good objective measure for ranking portfolios. Explain the other measures for ranking portfolios.
• Bloomberg Part 1: Use EQS to find stocks making up the S&P 500 or the Russell 3000 with a market cap greater than $50 billion and then import your stocks into PRTU to form a portfolio. Use PORT to evaluate your portfolio.
• Bloomberg Part 2: The performances of funds by type can be found on the Bloomberg Fund Heat Map Screen, FMAP. Use the screen to identify several equity funds: FMAP <Enter>, click “Objective” in “View By” dropdown and United States in “Region” dropdown, and then click “Equity” and type (e.g. Index). Select one of the funds and study it (the fund’s ticker can be found on the description page) using the functions on the fund’s menus screen (Fund Ticker <Equity> <Enter>). Functions to include: DES, historical fund analysis (HFA), and price graph (GP). Evaluate the fund using the Holdings, Performance, and Characteristics tabs on the fund’s PORT screen.
• Bloomberg Part 3: The FSCO screen scores and rank funds belonging to the same peer group based on a combination of weighted indicators. Select a fund style Using FSCO select a fund style and category (e.g., open-end, growth, large Cap fund domiciled in the U.S.), and then score and them in terms of indexes (e.g., Sharpe, Treynor, and Jensen indexes.
6
Basket Index Menu: .Name <Index>
• To access the menu screen for a basket created in CIXB, type basket name and hit enter:
• XSIF Fund: .XSIF13 <Index> <Enter>
• HRA Screen
7
Efficiency Frontier
• Essay: Explain the steps for generating an efficiency frontier.
• Bloomberg Part 1: Using some of the stocks from the Dow, generate
an efficiency frontier using Bloomberg’s Asset Allocation Optimizer
Template. To download the program you may want to use DAPI: DAPI
<Enter> and click “Excel Template Library,” “Equity,” “Portfolios,” and
“Asset Allocation Optimizer.” For the DJA stocks, select no more than
fifteen stocks identified using the Markowitz Excel Program, set each
stock’s minimum weight to zero, and maximum weight to 99%, and use
the average risk-free rate for the period.
• Bloomberg Part 2: Use the Markowitz Excel portfolio to determine the
best efficient portfolio for a portfolio you have constructed.
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Asset Allocation Optimizer TemplateThis application requires Excel's Solver Add-in to be installed. Go to Help tab for directions. You may also contact Bloomberg Help Desk.Asset Allocation Optimizer uses either historical returns or user-customized forecasted returns to generate optimal portfolios. Follow directions on the left side of the screen to start using the application. You may customize start and end dates for historical return, standard deviation, and correlation matrix data.
1) Enter Tickers ----> Tickers: Adm Equity AFL Equity CVS Equity Dis Equity Duk Equity JNJ Equity KR Equity MSFT Equity PG Equity XOM Equity
2) Enter Asset Class ----> Asset Class: ADM AFL CVS Dis Duke J&J Kroger Microsoft PG Exxon
ARCHER-
DANIELS-AFLAC INC
CVS
CAREMARK
WALT DISNEY
CO/THE
DUKE ENERGY
CORP
JOHNSON &
JOHNSONKROGER CO
MICROSOFT
CORP
PROCTER &
GAMBLE
EXXON MOBIL
CORP
3) Choose Return Type Returns * 0.61% 13.61% 16.91% 19.78% 7.57% 9.07% 15.77% 7.01% 6.99% 5.18%
Type 1: Standard Dev 32.5% 43.3% 24.7% 27.6% 18.5% 15.9% 24.2% 27.1% 17.3% 22.1%
* For demonstration only; these are not recommendations; please review your inputs carefully.
ARCHER-
DANIELS-AFLAC INC
CVS
CAREMARK
WALT DISNEY
CO/THE
DUKE ENERGY
CORP
JOHNSON &
JOHNSONKROGER CO
MICROSOFT
CORP
PROCTER &
GAMBLE
EXXON MOBIL
CORP
ARCHER-
DANIELS-1.000
AFLAC INC 0.366 1.000
CVS CAREMARK
CORP0.231 0.300 1.000
WALT DISNEY
CO/THE0.471 0.615 0.389 1.000
DUKE ENERGY
CORP0.347 0.438 0.357 0.481 1.000
4) Enter Dates Below JOHNSON &
JOHNSON0.431 0.458 0.254 0.560 0.589 1.000
Start Date: 8/5/2006 KROGER CO 0.314 0.279 0.290 0.350 0.369 0.444 1.000
End Date: 8/8/2013 MICROSOFT
CORP0.233 0.400 0.311 0.477 0.401 0.433 0.298 1.000
PROCTER &
GAMBLE 0.350 0.414 0.263 0.555 0.496 0.585 0.381 0.365 1.000
EXXON MOBIL
CORP0.564 0.444 0.374 0.604 0.506 0.542 0.395 0.478 0.498 1.000
5) Review Constraints ----> Min Weight 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
Constraints Kept Max Weight 99.0% 99.0% 99.0% 99.0% 99.0% 99.0% 99.0% 99.0% 99.0% 99.0%
6) Press Button - Optimize Objective 1: Portfolio that minimizes risk Risk Free Return: 1.50% Return: 9.80% Standard Dev: 13.8%
Weights 0.0% 0.0% 14.6% 0.0% 13.9% 38.6% 5.4% 0.2% 27.3% 0.0%
Objective 2: Portfolio that maximizes return Risk Free Return: 1.50% Return: 19.75% Standard Dev: 27.4%
Weights 0.0% 0.0% 1.0% 99.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
Objective 3: Portfolio that maximizes Sharpe Ratio Risk Free Return: 1.50% Return: 17.47% Standard Dev: 19.1%
Weights 0.0% 0.0% 33.9% 33.1% 0.0% 0.3% 32.7% 0.0% 0.0% 0.0%
Objective 4: Portfolio that maximizes return (*given a volatility) Risk Free Return: 2.50% Return: 15.53% Standard Dev: 17.0%
Weights 0.0% 0.0% 31.1% 21.4% 0.0% 21.6% 26.0% 0.0% 0.0% 0.0%
Objective 5: Portfolio that minimizes risk (*given a return) Risk Free Return: 2.50% Return: 15.50% Standard Dev: 17.0%
Weights 0.0% 0.0% 30.7% 21.4% 0.0% 22.0% 25.9% 0.0% 0.0% 0.0%
Type 2:
You have chosen forecasted
rates. Please go to the
Forecasted Rates Tab to
review your return
assumptions.
Historical returns,
correlations and standard
deviations will update
according to dates chosen.
Asset Allocation Optimizer
Historical
Forecasted1. Input the stock tickers (for stocks, ticker with the “Equity” moniker, for indexes, ticker with “Index” moniker, etc.).
2. Input average returns or expected returns.
3. Select the time period for calculating the variance-covariance matrix (correlation coefficient matrix shown in exhibit.
4. Select minimum and maximum weight constraints for each stock; here the user can set the minimum weights to zero and the maximum weight at 99% (or another specified constraints).
5. Input the risk-free rate for the optimization programs, the portfolio standard deviation for portfolio maximization optimization, and portfolio return for portfolio variance minimization.
6. Click “Optimize Weights” tab to run the program.
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Asset Allocation Optimizer Template
Risk Return ADM AFL CVS Dis Duke J&J Kroger Microsoft PG Exxon
13.8% 9.8% 0.0% 0.0% 14.6% 0.0% 13.9% 38.6% 5.4% 0.2% 27.3% 0.0%
13.9% 10.5% 0.0% 0.0% 18.3% 0.0% 10.2% 39.5% 9.2% 0.0% 22.8% 0.0%
14.1% 11.2% 0.0% 0.0% 22.2% 0.0% 6.4% 39.5% 13.1% 0.0% 18.8% 0.0%
14.4% 11.9% 0.0% 0.0% 24.4% 2.5% 4.2% 38.4% 15.3% 0.0% 15.1% 0.0%
14.8% 12.6% 0.0% 0.0% 25.6% 5.8% 2.1% 37.6% 17.5% 0.0% 11.4% 0.0%
15.3% 13.4% 0.0% 0.0% 27.4% 9.7% 0.0% 35.8% 19.5% 0.0% 7.7% 0.0%
15.8% 14.1% 0.0% 0.0% 28.3% 13.2% 0.0% 33.8% 21.8% 0.0% 2.9% 0.0%
16.3% 14.8% 0.0% 0.0% 29.7% 17.2% 0.0% 29.8% 23.2% 0.0% 0.0% 0.0%
17.0% 15.5% 0.0% 0.0% 30.7% 21.4% 0.0% 22.0% 25.9% 0.0% 0.0% 0.0%
17.7% 16.2% 0.0% 0.0% 31.9% 25.6% 0.0% 14.3% 28.2% 0.0% 0.0% 0.0%
18.5% 16.9% 0.0% 0.0% 33.1% 29.8% 0.0% 6.6% 30.4% 0.0% 0.0% 0.0%
19.3% 17.6% 0.0% 0.0% 33.4% 36.1% 0.0% 0.0% 30.4% 0.0% 0.0% 0.0%
20.9% 18.3% 0.0% 0.0% 28.3% 55.3% 0.0% 0.0% 16.4% 0.0% 0.0% 0.0%
23.5% 19.0% 0.0% 0.0% 23.2% 74.2% 0.0% 0.0% 2.6% 0.0% 0.0% 0.0%
27.4% 19.8% 0.0% 0.0% 1.0% 99.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
• The exhibit shows the optimum solutions for the ten stocks making up the Blue Rock Fund.
• The variance-covariance matrix is calculated for the time period from 8/5/2006 to 8/8/2013 (weekly prices are used), the expected stock returns are based on averages over a more recent time period, the specified portfolio return is 15.5%, and the specified annualized portfolio standard deviation is 17%.
• The optimum portfolio weights for the variance minimization are 30.7% in CVS, 21.4% in Disney, 22% in Johnsons & Johnson, and
25.9% in Kroger.
The annualized variance is equal to period variance (e.g., weekly) times the number of periods of
that length (week) in a year (52). The annualized standard deviation is equal to the square root of
the annualized variance .
CAPM and Wells Fargo Stock Selection Application
• Essay: Explain the CAPM. In your explanation include the following: proposition, equilibrium relation, SML equation and graph, explanation of why beta is the only factor, and explanation of the nature and general findings of empirical tests of CAPM.
• Bloomberg Part: Select a number of stocks to analyze using the Wells Fargo Stock Selection Approach. In selecting your stocks, you may want to consider some of the stocks that make up an index or all the stocks that are included in the Dow.
– Use Bloomberg’s DDM model to estimate each of your stock’s return (IRR). You can use Bloomberg’s default assumptions used in their DDM model or change them.
– Use the Bloomberg’s Beta screen for each of your stocks to estimate their betas. Select a time period you think is appropriate and use either the raw beta or adjusted beta.
– Estimate an ex-ante SML relation by running a cross sectional regression of the returns and betas of your stocks.
– Calculate the excess return of each stock to determine which stock you would include in your portfolio.
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12
Applying the Well-Fargo Approach Using Bloomberg’s DDM
Model and Adjusted Betas
• The Bloomberg
DDM slide for
Proctor &
Gamble shows
a market price
of 77.89 with
the Bloomberg
default
assumptions
• P&G’s IRR is
8.614% on
8/30/2013.
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Applying the Well-Fargo Approach Using Bloomberg’s DDM
Model and Adjusted Betas
• The Beta screen
for P&G shows
an adjusted beta
of 0.706 for the
period from
8/30/2006 to
8/30/2013.
If an analyst concurred with the default assumptions underlying
the DDM model and the adjusted beta as the best estimate of
P&G’s true beta, then she could include E(r) = 8.164% and β =
0.706 as one return-beta stock.
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• All stocks with
positive excess
returns would be
included in the
portfolio:
• Excess = IRR −
(7.3755 + 2.6237β)
> 0)
Applying the Well-
Fargo Approach
Using Bloomberg’s
DDM Model and
Adjusted Betas
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Bloomberg RVC Screen: Return-
Beta Space
• The RVC displays scatter data for a security (stock or fund) and its peer group.
• The screen allows you to select from a variety of analysis criteria and peer group types and sizes.
• By selecting return and beta combinations for stocks or funds and their peers you can create an ex post return and beta space for identifying stocks or funds with abnormal returns.
RVC : GE RVC screen with DJIA selected from the “Peers” tab
X-Axis: Beta 2-yearsY-Axis: Total Return 1Yr
APT and Factor Models
• Essay: Explain the APT by comparing it to the CAPM. Describe how factor models like the RAM or the Fama-French models are used for constructing portfolios
• Bloomberg Part: French and Fama argue that firms with high ratios of book-to-market value are likely to be in more financial stress than firms with low ratios. Altman’s Z score is a measure of a company’s likelihood of default. Examine the significance of financial stress in determining equilibrium returns by conducting a second-pass test of stocks returns explained by their betas and Altman’s Z-scores.
• To run your regression, use the Bloomberg Excel Add-in to run the second-pass test in Excel. Consider for your stocks, the stocks comprising the DJIA or the S&P 100 or 500; for rates of return, the internal rates of return calculated from Bloomberg’s DDM model; for betas, the stocks’ adjusted betas; and then use Altman’s Z-score. For an example on using multiple regression analysis is Excel, see the Excel table in the Bloomberg exhibit box, “Bloomberg Excel Add-In: Second-Pass Test for Multi-Factor Models
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Case: Second-Pass Test Using Bloomberg
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A B C D E F G
1 Stocks DDM IRR Adjusted Beta Altman Z-Score
2 AAPL UW Equity 13.3363 0.9657 5.4980
3 ABBV UN Equity 9.0815 1.0720 4.2521
4 ABT UN Equity 9.1800 0.7351 3.5552
5 ACN UN Equity 10.1505 1.0978 6.6480
6 AEP UN Equity 8.1879 0.7068 0.8991
7 AMGN UW Equity 8.5779 0.7446 2.8591
8 AMZN UW Equity 11.7587 1.1792 6.2581
9 APA UN Equity 10.9999 1.4378 1.6732
10 APC UN Equity 10.2836 1.3811 1.8056
11 BA UN Equity 10.0843 1.0591 1.9648
12 BAX UN Equity 9.7470 0.9038 3.0687 Regression Statistics
13 BMY UN Equity 7.4564 0.6493 4.1850 Multiple R 0.66456058
14 BRK/B UN Equity 7.5869 0.8904 2.2908 R Square 0.44164077
1 CAT UN Equity 10.7978 1.3055 1.9537 Adjusted R Square0.42802225
5 CL UN Equity 8.0858 0.6904 5.7078 Standard Error 1.08295894
16 CMCSA UW Equity 12.1525 1.0547 2.9530 Observations 85
17 COP UN Equity 9.5583 1.0166 1.6137
18 COST UW Equity 9.7208 0.8072 5.6880 Coefficients t Stat
19 CSCO UW Equity 10.9881 1.0662 3.7920 Intercept 5.81697563 10.615359
20 CVS UN Equity 10.1363 0.7536 7.2248 X Variable 1 3.91311396 8.008853
21 CVX UN Equity 9.5118 1.1157 3.5273 X Variable 2 0.09510728 2.1482794
Multiple Regression: Click "Data"and then "Data Analysis"
In Data Analysis Box: Click "Regression"In Regression Box:
• Enter field for Return in "Input Y Range" box: B2:B86;
• Enter field for explanatory variables in "Input X range" box: C2:D86
• Click OK
Regression Output sent to separate worksheet
Data Pulled from Bloomberg Excell Add-In:• "Import Data"; "Real Time/Historical"; "Real Time Current"
• Bloomberg Data Wizzard Box - Step 1 of 3: Loaded S&P 100 stocks
• Bloomberg Data Wizzard Box - Step 2 of 3, Select Fields: DDM IRR, Override adjusted beta, Altman Z-Score
• Bloomberg Data Wizzard Box - Step 3 of 3: click Finish
Applied Fundamental Analysis
1. Using the BI screen (BI <Enter>) select
an industry and evaluate it using the
following BI Screens: Comp Sheets,
Drivers/Metrics News/Research, Events
Data library. Analysis
2. Select one of the companies of interest
from the industry you analyzed in Exercise
1 and evaluate by customizing the stock’s
FA screen. Some customized screens to
consider: Earnings in terms of sales per
share and profit margins; Multipliers: P/e,
P/S, and P/EBIDA; Business Risk;
Financial risk; leverage ratios; Liquidity
risk.
3. Conduct a relative analysis of the company you selected in Exercise 2 with its peers by customizing the stocks’ RV screen. On the RV select the index for the peers from Comp source dropdown. Some custom screens you may want to consider: Earnings in terms of sales per share and profit margins; Multipliers: P/e, P/S, and P/EBITDA; Business Risk: operating and profit margins; Financial risk: leverage ratios; Liquidity risk; Growth: Sustainable growth, payout ratios, and ROE; DuPont ratios; Valuation: DDM values and market prices
4. Identify the stocks that are underpriced and have positive EVAs as possible buy recommendations.
5. Compare each stock you have identified as buy recommendation with the analysts’ recommendation for that stock found on the stock’s EE and ANR screens.
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Bloomberg RV Screen
• Bloomberg RV Screen for Indexes
• Relative analysis screens, RV, for companies in an index can be found by using the RV screen for one of companies and then importing the index from the Comp source dropdown. The RV screen can also be customized (Custom Tab, “Create Templates”, and click “Save as” tab to save the screen.).
• Bloomberg RV screens can be used to do a relative analysis of companies in in the industry in terms of valuation, ratios, and earnings.
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Customized RV screen for
Macy’s and Department
Store Index, BRUSDEPC.
Margins
Department Store Index North
America
• The annualized total return for the period from 1/04/2013 to 10/18/2013 (based on weekly returns) was10.97% , which was significantly less than the 27.38% total return for the S&P 500.
• The drivers for the industry forecast, however, were for an industry moving toward consolidation, where its growth rates would reflect those of its leaders. The bullish position taken on the industry required selecting the correct stocks that comprise the index, such as Macy’s. Macy’s total return for the period was, in turn, 24.53%, closer to the return of the S&P 500.
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Bloomberg FA Screen
• Bloomberg FA Screen
for Indexes
• The income statements,
balance sheets,
valuation, and other
information for indexes
be accessed found
Bloomberg’s FA screen.
You can also create
customized screens:
Index Ticker <Index>
<Enter>; FA.
• Note: To compare a
company to the index,
enter the company’s
ticker in the Compare
box (e.g., Macy’s: M
<Equity>).
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Customized FA screen for
Department Store Index,
BRUSDEPC.
Profit margins of index and
Macy’s
Technical Analysis
• Bloomberg Part 1:
• There have been two speculative-type bubbles over the last twenty years: the 1995-2000 Dot-Com bubble and the 2008 financial crisis. Using the GP graph, analyze the price trends of the Dow or S&P 500 around these periods.
– On the GP screen, select moving averages and identify points where the price lines cross the moving average lines.
– On the GP graph, select volume (drop down box in right corner) and identify the volume at different breakout points.
– On the GP graph, select Put – Call volume (drop down box in right corner) and identify the volume at different breakout points.
– Create an auto regression bands for the flat trends, downtrends, and uptrends. Click the “Annotate” button on the grey toolbar at the top of the price chart to bring up annotations palette. On the palette, select regression from the pointer box (top right corner of the palette), span the Regression pointer over the time period of interest and then click to create the regression band
– Select primary reversal points on your graph and study the important news at those times. To find news, click the News button on the grey toolbar to bring up an orange vertical bar. Move the bar to a date of interest and then click to bring up a news box.
– Save your graph to the G screen from the “Save as” tab.
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Breadth of the Market
• The exhibit shows the price graph and cumulative advance-declines graph for S&P 500 for the period from 11/6/2006 to 11/4/2013.
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Technical Analysis
• Bloomberg Part 2:
• Moving average bands are used to identify resistance and support
levels, and confirm a price reversal. Using Bloomberg’s moving average
envelope screen for a stock or index of interest, create a moving
average band or envelope for a time period of interest and identify any
break outs from the band. To bring up the screen for a loaded stock or
index, type GPO MAENV. Once created, looks for trends and reversals.
You may want to save your graph to the G screen; to do so, click the
“Save as” tab.
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Moving Average Bands
• Examining the moving average band, Macy’s crossed its moving average support line from above on the August 14th and continued its downtrend to August 28th.
• The stock hit a low for this period on October 15.
• It then started an upward trend, crossing it 30-day moving average on the 17th and its resistance level on October 28th.
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Note that if the moving average bands had been set at
2% instead of 3%, then it would have crossed the
upper band on the 24th.
Efficient Market Analysis
• Essay: Explain the Efficient Market Theory in terms of its propositions and implications, hypotheses, and some of the empirical studies. Explain how some investment funds (or styles) could be constructed based on the efficient market theory (e.g., size, earnings announcements, P/e, etc.).
• Bloomberg Part 1: Filter rule tests are designed to test technical rules of buying and selling when stocks break their support and resistance levels. Bloomberg’s back testing screen (BTST) can be used to back test the profitability of various technical trading rules, including when stocks hit their resistance and support line. Use the BTST screen to back test a moving average envelope for the S&P 500 or a stock or other index of interest. For your test, take a long position when the closing price cuts its lower band and a short positive when it cuts its upper band. Do a back test of just long position.
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Bloomberg’s Other Technical Index Slides
Back Testing, BTST: BTST <Enter>:
• On BTST, click the pencil icon to bring up a box for setting the conditions of the test. For example, click the Simple Moving Average icon
• In the condition box, set the conditions to be long when the closing pricing crosses the moving average line from below and short when it crosses the line from above.
27
Filter Rule: Back Test
• The exhibit shows a back tests of a moving average envelope (15-day moving average with a 3% band) for the S&P 500, in which a long position is taken when the closing price cuts its lower band and a short positive when it cuts its upper band.
• The back test covered the period from 11/9/2008 to 11/8/2013. The percentage return for the moving-average envelope strategy was 49%.
• However, the percentage return from a buy-and-hold strategy for the period was 93%. Most of the losses, however, were from the short positions, giving some credence to the Sweeny study.
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Efficient Market Analysis
• Bloomberg Part 3:
• The Basu study provided empirical support for the time-honored investment strategy of investing in stocks with low P/e ratios. Many value funds and indexes are constructed with stocks with relatively low P/e ratios and many growth funds and indexes are formed with stocks with relatively high P/e’s. Evaluate the performance of portfolios based on P/e ratios by comparing the performances over different time period of the Russell 1000 Value index (RLV <Index>) and the Russell 1000 Growth index (RLG <Index>) using the COMP and HS screens: RLV <Index>; COMP and HS. On the COMP and HS screen enter the growth index in the compare box (RLG <Index). Use the HRA or beta screen to see the regression relation of the indexes with the market (S&P 500): RLV or RLG <Index>; HRA. Vary the time periods for your regression. Do either of the indexes have an abnormal return (positive alpha)?
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Performance of Low P/e Index
• The exhibit shows the total returns based on daily percentage changes in price for the Russell U.S. Low P/e (RU1LPETR) and the S&P 500 from 11/7/2008 to 11/30/2012 when there was a bullish market trend.
• For that period, the low P/e index outperformed the S&P 500 with a total return of 70.64% (annualized return of 14.04%) compared to a 52.12% return (10.87% annualized return) for the S&P 500.
• However, when the market was declining from 10/1/2008 to 3/3/2009, the total return of the low P/e Index was −42.94% compared to −40.03% for the S&P 500.
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11/7/2008-11/30/2012
Total Return:
Low P/e Index = 70.64% (Annualized Return = 14.05%)
S&P = 52.12% (Annualized Return = 10.87%)
Note: Returns are percentage price change; dividends are not included.
10/1/2008-3/3/2009
Total Return:
Low P/e index = −42.94%% (Annualized Return = −73.78% )
S&P 500 = −40.03% (Annualized Return = −70.47%)
Efficient Market Analysis
• Bloomberg 4: Several studies (Chowdhury, Howe, and Lin, Pettit
and Venkatesh, and Jaffe) have found modest abnormal returns
were possible for short periods from trading from inside information.
The Sabrient Insider Sentiment Index (SBRIEN <Index>) consists of
publically-traded companies that reflect a positive sentiment by
insiders closest to the company’s financials. There is also an
Insider’s Sentiment ETF, NFO (NFO <Equity>), that is tied to the
Sabrient index. Study the relative performance of the index or ETF
to the S&P 500 over different time periods using the COMP screen.
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• Insider’s Sentiment ETF: NFO <Equity>
• Total returns compared to S&P 500 from 11/28/2008 to 10/31/13
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Bloomberg Insiders Trade Screens
Efficient Market Analysis
• Bloomberg 6
• The performances of funds by type can be found on the Bloomberg Fund Heat Map Screen, FMAP.
• Use the screen to identify several value style funds and growth style fund:
• FMAP <Enter>, click “Objective” in “View By” dropdown and United States in “Region” dropdown, and then click “Equity” and select type (e.g. Value Broad Market and Growth Broad Market).
• Select one of the funds and study it (the fund’s ticker can be found on the description page) using the functions on the fund’s menus screen (Fund Ticker <Equity> <Enter>). Functions to include: DES, historical fund analysis (HFA), and price graph (GP). Evaluate the fund using the Holdings, Performance, and Characteristics tabs on the fund’s PORT screen. Examine the fund’s total returns for different periods and frequencies relative to the S&P 500, Russell 3000, or Dow using the COMP screen: Fund Ticker <Equity> <Enter> and then click COMP. Using the HRA or Beta screen, determine the fund’s characteristic line with the S&P 500, its systematic risk (R2), and unsystematic risk.
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• The exhibit shows Bloomberg’s total return graph for the Russell 2000 Value Index (RUJ) and the Russell 2000 Growth Index (RUO).
• For the period from 1/31/1995 to 10/31/2013, the value index had an annualized total return of 13.56% compared to an 11.63% return for the growth index.
• However, during the bear market period from 10/1/2008 to 3/3/2009 the annualized loss on the growth index was 49.49%, where the loss on the value index was 35.09%.
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Performance of Value Index
and Growth Index
Annualized Total Return
Value Index = 13.56%
Growth Index = 11.63%
1/31/1995-10/31/2013
Value = White
Growth = Orange
10/1/2008-3/3/2009
Value = White
Growth = Orange
Annualized Total Return
Value Index = −35.09%
Growth Index = −49.49%
Efficient Market Analysis
• Bloomberg 7: Construct one or more of the following portfolios based on style or characteristics and evaluate it using PORT:
– Low P/e Portfolio (e.g., P/e less than 15 or 10 or between 5 and 15 or a condition based on what you found from Exercise 9)
– Large P/e (e.g. P/e > 25 or a condition based on what you found from Exercise 9)
– Small Cap (e.g., market cap between $5 billion and $10 billion)
– Large Cap (e.g., market cap greater than $100 billion)
– Low P/B (e.g., price-to-book ratio less than 3)
– High P/B (e.g., price-to-book ratio greater than 7)
– Fund consisting of stocks with the potential for consistent earnings and dividend growth without high volatility, or funds consisting of stocks with posted positive earnings surprises in their last outings or those with consensus broker ratings that have also recently been upgraded.
• Steps: Use EQS to search for stocks; create a portfolio of the stocks from your search in PRTU; evaluate your portfolio’s past performance relative to an index (e.g., DJA, INDU) using the PORT screen; evaluate the characteristics
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• Market cap greater than or equal to $2.0B
• P/e less than or equal to 15
• Book value growth greater than or equal to 10%
• ROE greater than or equal to 15%
• Beta less than or equal to 1.25
• 5-year average dividend growth rate greater than or equal to 5%
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Bloomberg EQS Search
Portfolio Evaluation
• Import EQS search into PRTU
• Evaluate portfolio in PORT
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Bloomberg: Portfolio Evaluation in PORT
Portfolio Insurance
• Essay: The economic climate is quite uncertain. Explain how portfolio
insurance and range forward strategies can be used to manage a stock
portfolio.
• Bloomberg Part: Construct a portfolio insurance position for one of your
portfolios using S&P 500 options. Use the Bloomberg OSA screen to import
your portfolio and SPX options. Determine the index put positions you would
need to create a portfolio insurance strategy (consider the horizon period
when you select the maturity of the option). Use OSA to generate a profit
graph and/or market value graph of your hedged portfolio. Import a call (with
higher X) and set up a range forward position for your portfolio. Include
screens in you answer and bullet points on key observations.
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• OSA <Enter>
• From the “Portfolio” dropdown, select a portfolio.
• From red “Positions” tab, click “Add Listed Options” and then enter SPX in upper right amber area box.
• Select options and then click 1<GO>.
• On OSA screen, click portfolio summary box to include all stocks and options.
• Scroll down to options and set the number of puts needed to insure portfolio.
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OSA: Portfolio Insurance
Click “Scenario Chart” tab and input setting:
profit/loss, mkt. value, range (− 20% ,+20%),
and evaluation dates.
• From the “Portfolio” dropdown,
select a portfolio: XSIF Equity
• Note: Market value of the portfolio
is $1,312,161
• From red “Positions” tab, click
“Add Listed Options”
• Input setting: profit/loss, mkt. value, range ( −20%, +20%), and evaluation dates.
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OSA: Portfolio Insurance
ETFs
Essay: Explain how ETFs are constructed.
Bloomberg Part: Construct a simple market indexor sector ETF. Test the correlation of your ETF withthe appropriate index by putting the portfolio in aCIXB basket and then examining its correlation.Use HRA screen to see R2 and Beta. Comment onyour correlation.
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• ETF Features and correlation with index:Regression of Energy ETF against S&P Energy index (9/11/06/9/7/12): R2 = .969, Beta = 1.079; Alpha = .015
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ETFs