HW: Financial Ratio Quantile Strategies
1 Introduction
Here you will consider a few financial accounting ratios, as an approxima- tion of “quantamental” models that typically take much more numerous and carefully defined financial accounting into consideration. You will then in- vestigate profit opportunity of a quantile-based long-short scheme.
2 Understand Your Data
Read all documentation webpages for Zacks Fundamentals B. You will see they supply 6 related tables, FC, FR, MT, MKTV, SHRC and HDM 1. The strategy coding for this assignment will be reasonably easy. The data assembly, deliberately, is the difficult part.
3 Define the Universe
Choose at least 200 tickers2 of US equities such that3 they satisfy the follow- ing:
• end-of-day adjusted closing prices are available , over the entire period Jan 2014 through Jan 2021
1It is easiest to download your data through full-table downloads. Use URLs such as https://www.quandl.com/api/v3/datatables/ZACKS/MT?qopts.export=true
2You can find the full list of available tickers online
3We will not concern ourselves with selection bias in this exercise.
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• • •
debt/market cap ratio is greater4 than 0.1 somewhere in the period Jan 2014 through Jan 2021 (preferably more than fleetingly)
not in the automotive, financial or insurance sector , over the entire period Jan 2014 through Jan 20215
has feasible calculation of the ratios specified below , over the en- tire period Jan 2014 through Jan 2021, including for at least one PER END DATE no more than one year old. Debt ratio of zero is OK.
Select Financial Ratios
For this assignment, we will work with the following ratios: • debt to market cap6.
• return on investment7
• price to earnings8
Note that these data items are reported (at best) quarterly. Use annual numbers only when quarterly ones do not exist. As the equity price changes day-to-day, each ratio changes accordingly9, so ultimately the time series you have will be on daily data10. Recall that we did not know any of these numbers until the FC/FILING DATE .
4This is about 1000-2000 companies, including ASH, VTOL, ISUN and VIVO.
5See the Quandl ZFB fields ZACKS SECTOR CODE, ZACKS X IND CODE, and the classifi- cation list
6 FR/TOT DEBT TOT EQUITY in Quandl. In this homework we pretend that it is OK to
treat market capitalization and book equity as equivalent, though they are not the same
thing.
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8 Compute this based on FC/EPS DILUTED NET, BASIC NET EPS, SHRS/SHARES OUT, MKTV/MKT VAL, use the basic version (GAAP) if no diluted number is available. Treat negative earnings per share as 0.001.
9In many cases PER END DATE is not a trading day, so go ahead and forward fill equity price from the previous trading day.
10If you have memory errors when joining data, you are probably mistakenly creating a combinatorial explosion in your merging code.
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Based on FR/RET INVST, MKTV/MKT VAL, FC/NET LTERM DEBT, FC/TOT LTERM DEBT. Investment is defined here as market cap plus long term debt. Use net debt where available, total debt otherwise. Quandl will report debt as NaN if it was 0.0, but be careful about net versus tot debt.
As an example, consider V , return on investment. Say that our entity had successive report dates of March 31 and June 30, V 3−31 and V 6−30 and those numbers were known on filing dates April 4 and July 7. Our equity price series, which we take (also a bit problematically) as adjusted close prices, will be Pt. We have a debt number D for each report date as well.
We can infer the “return” R for a given report date as the unknown
element in
V=R D+M
and we assume it doesn’t change day-to-day. Rather only the market value element M changes daily, and we estimate the corresponding V ̃ values ac- cording to the filing dates. So for example our inferred values look like
V ̃7-6 = R3-31 D3-31 +M7-6
but the next day is the filing date so we have V ̃7-7 = R6-30
where
and
5 Analysis
D6-30 +M7-7 M7-6 = M3-31 P7-6
M
7-7
P 3-31 6-30 P7-7
= M P 6-30 .
Study performance of weekly or monthly quantile trading strategies using each of these single ratios as well as your choice of least one nontrivial com- bination of them11.
Set initial capital to be 10 times the gross notional of your first month’s set of positions. You may assume zero trading costs, that trading fractional shares and arbitrary positions sizes are possible, that all securities are easy to borrow with a repo rate equal to your funding rate minus 100bp12, and that
11That is to say, at least 4 types of scores. 12This number may sometimes become negative.
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the portfolio capital is equal to the initial capital, adjusted for all realized and unrealized PL to date. Choose either a constant funding rate, or rolling 3-month LIBOR.
Analyze performance of a top-and-bottom decile trading strategy. Now rank based on changes in your ratios rather than the ratios themselves. Play with the effects of sizing positions by rank.
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6 Data Example
Here is recent sample data for Eli Lilly (ticker LLY):
6.0.1 SEC Reports
per end date
filing date
tot revnu
eps diluted net
basic net eps
tot lterm debt
net lterm debt
net curr debt
zacks x ind code
zacks sector code
zacks metrics ind code tot debt tot equity
ret invst
free cash flow per share shares out
pertype
mkt val
6.0.2
2020-06-30 2020-09-30
2020-07-31 2020-10-28 5499.4 5740.6 1.55 1.33
1.55 1.33 15064.4 16334.6 712.3 1786.0 -235.4 -914.3 225.0 225.0
2020-12-31 2021-03-31 2021-06-30
2021-02-17 2021-04-30 2021-08-03 7440.001 6805.6 6740.1 2.31 1.49 1.53
2.32 1.49 1.53 16586.6 16199.6 14736.6 1785.8 NaN NaN -1494.2 -3.7 196.3 225.0 225.0 225.0
2021-09-30
2021-10-27 6772.8 1.22
1.22 15522.4 505.5
Date
2019-10-25 2019-10-28 2019-12-31 2020-01-02 2020-02-19 2020-02-20 2020-03-31 2020-04-01 2020-05-01 2020-05-04 2020-06-30 2020-07-01 2020-07-31 2020-08-03 2020-09-30 2020-10-01 2020-10-28 2020-10-29 2020-12-31 2021-01-04 2021-02-17 2021-02-18 2021-03-31 2021-04-01 2021-04-30 2021-05-03 2021-06-30 2021-07-01 2021-08-03 2021-08-04
73.467766 79.176659 92.631604 93.181347 99.774689 77.868328 76.069679 74.808431 84.245853 92.984654
100.062297 99.525966 91.596800 96.155810 93.581421 91.223235 83.017001 97.662767
125.053966 122.580143 153.559427
86.126239 80.002505 79.325897 78.268161
123.433215 153.043896 154.117443 170.694087 170.439396
Ratios On Key Dates
4.0 4.0 4.0 13.0 13.0 13.0 2.8489 2.2825 2.4784 9.445 5.817 6.4962 5.6018 1.5312 3.066 956.58 959.03 959.03
-1.5 225.0 4.0 13.0 2.148 4.7286 4.4859 956.59
4.0 4.0
13.0 13.0
3.8221 3.3871
7.3023 5.6651
2.5664 4.1159
956.47 956.58 QQQQQQ 157033.3 141593.2 161509.22 179165.14 220115.53 221020.67
(Using MKTV/MKT VAL, FC/NET LTERM DEBT to infer operating income)
Debt To Mkt Cap
5.554480 4.352354 3.720165 3.698217 3.453830 5.225211 5.348760 5.438939 4.829656 4.877282 4.532301 4.556724 4.951182 4.105682 4.218627 4.327682 4.755473 3.782411 2.953930 3.013544 2.405588 2.381655 2.563957 2.585826 2.620772 2.293549 1.849797 1.836912 1.658523 2.167266
Return On Inv
8.048674 7.249701 6.227653 6.191987 5.794008 8.356740 8.549034 8.689238 7.739485 7.671248 7.127691 7.166169 7.787704 7.841469 8.056110 8.263302 9.075546 6.317094 4.948484 5.047243 4.038046 7.910124 8.509632 8.581494 8.696299 5.842814 4.789536 4.758436 4.324818 5.725783
Price To Earnings
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