You are a US long-only quantitative portfolio manager. In Portfolio123, create a ranking system based on the followingcombination of signals: i) 40% Value, using: i.1) 60% EV/EBITDA: EV/Eval(EBIT

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You are a US long-only quantitative portfolio manager. In Portfolio123, create a ranking system based on the followingcombination of signals:

i) 40%


, using:      i.1) 60% EV/EBITDA: EV/Eval(EBITDATTM>0,EBITDATTM,NA)     i.2) 20%: Earnings Yield from Earnings Forecasts: 0.5*(1/ ProjPECurFY)+0.5*(1/ ProjPENextFY)      i.3) 20%: Price to Sales: Pr2SalesTTM

ii) 30% Quality, using:      ii.1) 50% in Gross Profitability: GrossProfitTTM/AstTotQ     ii.2) 50% in Piotroski Score: PiotFScore

iii) 30% Price Trends, using:      iii.1) 50% Industry Momentum 3-months: Pr13W%ChgInd      iii.2) 50% Industry Momentum 6-months: Pr26W%ChgInd

You should know which way the arrows point. Use

Percentile NAs Negative

(Portfolio123’s default option).

a) Backtest the performance of the ranking system above using:      Universe:




Rebalancing Frequency:

every 4 weeks

Number of buckets=


Slippage=0, minimum price = 3, Sector=All, Long

Copy-paste the bar chart with annualized returns over


time period.

b) Explain in as much detail as you can the calculations Portfolio123 does to generate the bar charts in item a).

c) Find the vector E[α] as of

February 21 2015

using the ranking system above. Use a standard deviation of 2% per year. The spreadsheet Week3_Quiz_Q2 has useful data to answer this question.

d) IF you had a covariance matrix


for all stocks in the S&P 1500 Universe, describe how you would use Excel to find the long-only (i.e., no shorting allowed) portfolio that invests in the top 200 stocks according to your rankingsystem and hits a target Active Risk of 4% per year.

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