effectiveness of Value signals within economic sectors.
effectiveness of Value signals within economic sectors.
• Form groups of 2 or 3 students. Answer questions 1 t 3 below, and 3 additional questions among questions 4 to 9.
• To make sure you get full credit for your homework:
o All your answers must demonstrate sufficient effort.
o Include all your answers in one Excel file or one Word file.
o Show your work. Numerical answers without accompanying calculations will not be considered.
o Make sure your Excel/Word file is well organized, so the grader can clearly read all your answers.
• You can access the Value Combo ranking system of Lecture 4 by copy-pasting the following web address: http://www.portfolio123.com/app/ranking-system/250832
1) The purpose of this exercise is to study the effectiveness of Value signals within economic sectors.
We know that, on average, valuation ratios forecast relative stock returns. This does not necessarily imply, however, that valuation ratios forecast returns within
sectors. It is possible that Value signals work because they work across sectors, even though they do not work within sectors. That is, it could be that value signals
identify sectors that are relatively cheap and sectors that are relatively expensive, although it cannot discriminate cheap vs. expensive stocks within each sector.
Knowing whether Value signals work within sectors is useful. If it does work, one can create sector-neutral value investing strategies. In these strategies, each
sector receives the same weight as in the benchmark index. However, stock weights within each sector differ from benchmark weights: stocks with low valuation ratios
are overweighted and stocks with high valuation ratios are underweighted.
In Portfolio123, create the Value Combo ranking system of Lecture 4 (see Slides). Check the performance of such ranking in the PRussell 3000 (NEW) Universe using the
following parameters: MAX time period, rebalancing every 4 weeks, 5 buckets, minimum price=3, Slippage = 0.0, Long, and the Russell 3000 with dividends as a benchmark.
a) Use Sector=ALL. Copy-paste the graph of average annualized returns across buckets.
b) Instead of Sector=ALL as in item a), use each of the 10 USA S&P GICS sectors at a time (Consumer Discretionary, Consumer Staples, Energy, Financials, Health
Care, Industrials, Information Technology, Materials, Telecommunication Services, Utilities). Copy-paste the graph of average annualized returns across buckets for
each of the 10 sectors.
c) Do Value signals work within sectors? Discuss.
Note 1: The way the Sector=????? Restriction works in the Rank->Performance engine is as follows. Portfolio123 first ranks all stocks in the Universe into buckets, and
only then applies sectoral restrictions to the buckets. As a result, the number of stocks within each bucket is not necessarily the same across buckets. A perhaps
superior (but more time consuming) alternative is to first create Custom Universes for each of the 10 USA S&P GICS sectors, and then apply the ranking system to each
of the Custom Universes at a time. This equalizes the number of stocks in each bucket. To create a Custom Universe for each of the sectors use the rule GICS
(FINANCIAL), for example. For the other 9 mnemonics, within Add Free Form Rule click on Classification->Sector and then Full Description.
Note 2: IF you want to find out how many Russell 3000 stocks are there in each of the 10 USA S&P GICS sectors at each point in time, do: Screen->New->Stock Screen->Add
Free Form Rule->Classification. Add two rules at a time: Universe(Prussell3000) and Sector=FINANCIAL, for example. Then hit Run Screen to see the results.
2) The purpose of this exercise is to further study the Value Combo system using Portfolio123’s Screen Engine. Backtest the performance of an equally-weighted
portfolio containing the top 100 stocks in the Russell 3000 according to the Value Combo system. The portfolio will be rebalanced every three months.
To do that, first click on Click on Screen-> New Stock Screen. Then click on Main Settings and choose the following:
Universe=PRussell3000 (NEW) Benchmark=Russell3000 w/div Method = Long
Ranking = Ranking System -> Choose the Value Combo system from Lecture 4 (same from Question 1) Max No. Stocks =100
Then click on Backtest and choose: Price=Next Open
Rank Tolerance = 0 Max Pos = 0 Carry Cost=0 Slippage = 0 Long Weight =100
Start Date – End Date= MAX Rebalance Frequency = 3 months
Save this screen as Value Combo Top 100, for example.
a) Click on Run Backtest to obtain the results of the backtest. Copy-paste the resulting graphs and answer:
i) What is the annualized return of the Top 100 portfolio and of the Russell 3000?
ii) What is the average 3-month return of the Top 100 and of the Russell 3000 portfolio in up markets? And in down markets?
iii) How many (consecutive, non-overlapping) 3-month periods are there from Jan 1999 to now? What is the 3-month Hit Rate of the Top 100 portfolio? That is, in how
many 3-month periods does the Top100 beat the Russell 3000 Index (positive Excess% column)?
Hint: Download to Excel and use the function COUNTIF
iv) What is the average Turnover of the Top 100 portfolio (3-month and annual)?
Note that Portfolio123 only counts stocks entering or exiting the portfolio, and ignores rebalances back to equal weights. Thus, Portfolio123’s turnover calculation
underestimates the true turnover. However, the turnover coming from rebalances back to equal weights is of second order compared to the turnover coming from stocks
entering or exiting the portfolio, so turnover is not underestimated by too much.
b) The results in a) do not incorporate transaction costs. A quick and dirty way to do so is to fix a Slippage parameter in Portfolio123. This incorporates
transaction costs by assuming that stocks purchases and sales are done at worse prices than the historical record: buy at higher price, sell at lower price. Repeat the
backtest choosing Slippage=0.45%, which is the average all-in transaction cost per trade for institutional investors. This is a quick and dirty approach because true
slippage depends on how much money one is actually trading. Bigger trades move prices against you more. And, as mentioned above, Portfolio123’s Slippage only accounts
for stocks entering or exiting the portfolio, and ignores rebalances back to equal weights. Run Backtest again and answer:
What is the annualized return of the Top 100 portfolio incorporating transaction costs?
c) The results in a) assume trades occur at the Next Open price. Now investigate what happens when trading is delayed by a little bit. Set Slippage=0 again and
choose Price=Next Close instead of Next Open.
What is the annualized return of the Top 100 portfolio when trading is delayed?
d) The backtests in a), b), and c) are done under the assumption that one starts sorting stocks and investing on 01/02/1999. This, and the choice of Rebalance
Frequency, determines the dates of all future stock trades.
What if one starts the analysis at some other date? To investigate, do a Rolling Backtest. Set Price=Next Open and Slippage=0 again and click on Rolling Backtest.
Choose frequency=every week, holding period=3 months, and Start Date – End Date=MAX. Then click on Run Rolling Backtest and answer:
i) How many overlapping 3-month periods are you considering now?
ii) What is the 3-month Hit Rate of the Top 100 portfolio? That is, in how many 3-month periods does the Top100 beat the Russell 3000 Index?
iii) What is the average 3-month return of the Top 100 Value Combo portfolio and of the Russell 3000 across these 3 month periods?
3) The purpose of this question is to solidify your understanding of backtest calculations that Portfolio123 does. The spreadsheet HW3_Q3 has a
hypothetical Universe of 10 stocks, labeled from A to J. You are given information on stock returns, EV/EBITDA, and market cap. Consider a ranking system based only on
EV/EBITDA. Backtest the ranking system using the given Universe of stocks, a sample period of one year (two semesters), 6-month rebalancing, 5 buckets, and choose a
Universe cap-weighted Index as a benchmark. Report the outcome as a bar graph with annualized returns just like Portfolio123’s Annualized Returns plot.
4) For this question, assume taxes, depreciation and amortization are always equal to zero. Consider an all-equity firm with market capitalization equal to
$10,000, earnings equal $500 per year, and with zero cash.
a. What are the P/E and EV/EBITDA of the firm?
The firm then decides to change its capital structure. It takes on $5000 of debt and use all debt proceeds to buy back its own stock. The new debt is a perpetuity with
interest rate equal to 4% per year.
b. What are the P/E and EV/EBITDA of the firm after the capital structure change?
c. Based on your answers to a) and b), explain why, compared to P/E ratios, EV/EBITDA is a conceptually superior valuation ratio.
5) If EV/EBITDA is the best valuation ratio in principle, can you see reasons why quantitative investors typically combine EV/EBITDA with other valuation ratios
such as P/E, P/Cashflow, Shareholder Yield, and P/Book?
6) Explain why, ignoring transaction costs, the Russell 3000 Value Index is a “slow rabbit” benchmark (i.e., relatively easy to beat) for quantitative investors
focusing on Value signals?
7) When looking at the stocks that get classified as Value/Glamour according to valuation ratios, certain patterns emerge. What kind of stocks tend to be Value
stocks? What kind of stocks tend to be Glamour stocks?
8) It is not a secret that, on average, valuation ratios forecasted relative stock returns in the past, not only in the US stock market but also in other markets.
Nonetheless, why does it still make sense, going forward, to take into account Value signals when investing?
9) On average over time, valuation ratios are powerful quantitative signals to forecast relative stock returns.
a. Could there be circumstances under which quantitative strategies should not rely on valuation ratios too much?
b. In practice, how would you figure out whether we are currently facing one of such circumstances?
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