Bloomberg Exercises for Investments

R. Stafford Johnson

Bloomberg Missionary

Department of Finance

Xavier University

JohnsonS@xavier.edu

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.

8

9

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.

10

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.

11

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.

13

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.

14

• 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

15

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

16

Case: Second-Pass Test Using Bloomberg

17

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.

18

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.

19

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.

20

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>).

21

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.

22

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.

23

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.

24

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.

25

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.

26

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.

28

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)?

29

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.

30

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.

31

• Insider’s Sentiment ETF: NFO <Equity>

• Total returns compared to S&P 500 from 11/28/2008 to 10/31/13

32

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