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25579 – Applied Portfolio Management
创建日期：2024-04-10 16:58:51
所属分类：经济Economics
标签： 25579
Applied Portfolio Management

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25579 – Applied Portfolio Management 

Assignment

The “quality” factor has become one of the strongest and most scalable investment strategies in
equity markets. Your investment firm is thinking of launching a product based on this factor and as
junior member of the newly formed quant research team, you are tasked by your boss to produce a
comprehensive report on this investment strategy.
Deadline: 9.00am Monday 10 May 2021
Score: 40 marks
1. Introduction and background
Around 2013, Cliff Asness, the CEO of AQR published a working paper (later published as Asness
et al., 20191) where he, together with other co-authors, introduced an investment factor called
“Quality”, based on investing in firms with:
• High profitability
• Strong growth
• Low risk and leverage
Frazzini et al. (2018)2 show that this factor largely mimics the investment style of Warren
Buffet.
This investment factor has become very popular and is used by a variety of investment
companies, for example:
• iShares MSCI USA Quality Factor ETF
• Invesco S&P 500® Quality ETF
• AQR Large Cap Multi-Style Fund (where it seems to have replaced “profitability” from
2021).
A number of these products are also available in Australia, here is a comprehensive analysis.

1 Asness, C., Frazzini, A., & Pedersen, L. (2019). Quality minus junk. Review of Accounting Studies, 24(1),
34–112.
2 Frazzini, A., Kabiller, D., & Pedersen, L. (2018). Buffett’s Alpha. Financial Analysts Journal, 74(4), 35–55.
25579 – Applied Portfolio Management 2
Like for other more traditional factors, such as a value and momentum, academics and
practitioners do not have a definitive answer on “why it works”. Bouchaud et al. (2016)3 argue
that a risk-based explanation is unlikely and advance some behavioural explanations similar to
the ones we have analysed for the value and momentum factors.
The CIO (Chief Investment Officer) of your company is exploring the possibility to launch a
product in this space and asks the quant research team to prepare a short analysis of this
investment factor.
Your report will have the following components:
1. Presentation of the fundamental intuition behind this strategy.
2. Statistical analysis (both linear and non-linear) of the predictive power of the quality
factor and its three components (Profitability, Growth and Safety).
3. Detailed backtesting of a long-only strategy based on the quality factor.
4. Detailed backtesting of a long-short strategy based on the quality factor.
There is no formal length requirement for this assignment. My suggestion is to aim at
anywhere between 10-15 pages of “main text” including tables and pictures. You may also add
an appendix if you want to add more tables, etc. Please be sure that all the necessary
information is actually in the main body of the report.

2. Presentation of the Strategy
This should be a presentation of the economic intuition behind the quality factor. After
reading this part the reader should:
• What fundamental economic concepts underpin this strategy.
• Understand what types of companies are the target of this strategy.
• Why should this strategy work? Are quality stock riskier? Is this an “anomaly”?
This part will be mainly descriptive (although, if you want, you may add a table and/or a graph
if you need it to make a point). The intended audience is the Chief Investment Officer of your
firm, so you can assume a high level of sophistication and a good understanding of finance.
As a reference material for this part, you can refer to:
• Asness et al. (2019). Stick to the introduction only, the rest of the paper is interesting
but quite technical.
 The Excess Returns of Quality
Stocks: A Behavioral Anomaly. HEC Paris Research Paper No. FIN-2016-1134.
25579 – Applied Portfolio Management 3
• Bouchaud et al. (2016). Also here do not lose yourself in the details. You are mainly
interested in the economic intuition.
You may also find our sources of information, but please be careful because contrary to other
factors, quality is very loosely defined and different banks use different definitions. For the
sake of this assignment, we will stick with the AQR definition. So, if you look at other sources,
just make sure they are taking about the same thing.
The length of this part should be one page of text plus optional graphs and tables. For this
part only you can take graphs and tables from other sources (with proper citation). Please limit
the number of graphs and tables in this part. It should be mostly about providing the economic
intuition in your own words.

3. Statistical Analysis
In the second part of your assignment, you should present a detailed statistical analysis of the
predictive power of the Quality factor and of its three sub-components (Profitability,
Growth and Safety). The analysis should contain:
• Linear analysis (Regression).
• Non-linear analysis (Information Coefficient and Quantile Analysis).
In doing this analysis you should use all the available data (1980-2020) and you should show
how the predictive power changes in time. After reading this part the reader should
understand:
• How strong is the predictive power of quality, and of its components, over the entire
sample.
• How this predictive power has changed in time over our sample.

3.1 Predictive power and the economic environment
We know that factors tend to react differently to the economic environment. At page 6 of this
document MSCI analyses the performance of the quality factor in four different economic
environments based on the Composite Leading Indicator.
Using the data provided replicate this analysis showing how the predictive power of the
Quality factor, and of its three components, varies across these economic regimes. You should
do this only for one measure of predictive power (Regression coefficient, Information
Coefficient or Return of Top quantile minus return of the Bottom quantile).
25579 – Applied Portfolio Management 4
Do not worry if your result for the profitability factor is different from the MSCI one. Their
definition of quality is different and they use a different time horizon.
ATTENTION
From the graph at the top of page 6 you will notice that the way MSCI defines the 4 economic
regimes is not based on the value of the leading indicator but based on the change of the
indicator over the previous 3 months. So from the data provided (the value of the leading
indicator for the US economy) you need first to calculate the difference with respect to three
months before (the .shift() method may come useful here) and then you divide these
differences in 4 groups based on the value of the change. Do not worry if your groups are not
exactly the same as MSCI.
For the length of the statistical analysis, you should aim at around 3 pages maximum. If you
feel the need to add many more tables and graphs, consider the possibility to relegate some of
them to the appendix, leaving only your “main narrative” in the body of the report.

4. Backtesting of a long-only strategy
The third part of your report will be a detailed report of the performance of a long-only
strategy that invest in stocks that rank well according to the Quality factor (you should NOT
repeat the analysis for the three sub-components). Your strategy should:
• Invest in the top x% of stocks according to your factor (quantile strategy).
• Be market weighted (and not equally weighted).
• Rebalance monthly.
• Assume 0.1% roundtrip transaction costs.
• Be tested over the entire period at our disposal.
You should optimize your strategy in terms of the key parameter (the x% above) by trying few
different values (from 3 to 5). At the end of this section the reader should:
• Know how the strategy performs over the entire period and if the performance has
changed over time (for example showing the yearly performance or the performance
over periods of 3-5 years…).
• Know how sensible the performance is to the parametrization of the strategy (how the
choice of the parameter affects the overall performance).
• Know how the optimal parameter changes in time over our sample.
In terms of length, for this part you should aim at 2-4 pages based on the number of graphs and
tables that you want to include in the main body of the report.

25579 – Applied Portfolio Management 5
ATTENTION
To optimize your strategy, you have two option:
Option 1 – Sub-period analysis
1. You backtest your strategy over the entire period using each of your parameter values and
find out which is the optimal parameter.
2. You repeat the backtesting over non-overlapping subperiods of 5 years and find which
would be the optimal parameter over each sub-period.
Option 2 – Walk-forward
You build a walk-forward mechanism where you use 5 years of historical data to find the
optimal parameter and then use that parameter to invest in the following month. Then you
advance your data by one month and repeat the analysis. At the end you will have both the time
series of the (optimized) strategy performance and the time series of the optimal parameter.

5. Backtesting of a long-short strategy
The last part of your report will be a detailed report of the performance of a long-short
strategy that overweights stocks that rank well according to the Quality factor and
underweights stocks that rank poorly. Your strategy should:
• be built with a 1XX/XX approach where you overinvest (underinvest) in the top
(bottom) x% of stocks.
• Use an active weight of ±30% (it should be a 130/30 strategy).
• Rebalance monthly.
• Assume 0.1% roundtrip transaction costs.
• Be tested over the entire period at our disposal.
You should optimize your strategy in terms of the key parameter (the x% above) using the
same approach described in the previous section. At the end of this section the reader should:
• Know how the strategy performs over the entire period and if the performance has
changed over time (for example showing the yearly performance or the performance
over periods of 3-5 years…). In presenting the results special relevance should be given
to the tracking error and its time dynamic.
• Know how sensible the performance is to the parametrization of the strategy (how the
choice of the parameter affects the overall performance).
• Know how the optimal parameter changes in time over our sample.
In terms of length, for this part you should aim at 2-4 pages based on the number of graphs and
tables that you want to include in the main body of the report.
25579 – Applied Portfolio Management 6
6. Data
Together with the assignment you will find the following data files:
• QUALITY.zip contains the monthly data of the quality factor for a sample of US stocks.
• PROFIT.zip, GROWTH.zip and SAFETY.zip contain monthly data of the three sub-
components of quality factor (Profitability, Growth and Safety) for a sample of US stocks.
All the factor are already normalized and winsorized.
• LEAD.zip contains monthly data on the leading economic indicator for the US Economy.
• Returns.zip contains the monthly (log-)returns for the US stocks.
• Market_cap.zip contains the monthly market capitalization for the US stocks.
• Names.zip contains the names and industry-affiliation of the US stocks
7. Timeline
The content of the assignment is covered in different weeks of the subject. Here is a rough
estimation of when we the material (and code) necessary for each session is covered:
Assignment Part Week Notebooks / Concepts
1. Presentation of the
Strategy
3 and 4
None. Concept of Investment Factor,
Risk Premium and Market Anomaly
2. Statistical Analysis 3 and 4
07 - Linear Regression
08 - Information Coefficient
09 - Quantile Analysis
3. Long-Only Strategy 5, 6
11 – Backtesting
13 – Walk-Forward Model (optional)
4. Long-Short Strategy 7
14 – 130/30 Portfolios
13 – Walk-Forward Model (optional)

8. Submission
You will submit:
1. A pdf file with your report (APM_XXXXX.pdf)
2. A Jupyter Notebook with all your code (APM_XXXXX.ipynb).
Where XXXXX is your UTS student ID number. Files with wrong names or wrong extension will
attract 1-point penalty.
25579 – Applied Portfolio Management 7
Your pdf report should contain a professionally-looking cover page (no specific format
required) with your name and Student ID.
Tables in the report should be edited and not simply cut and paste images from the Notebook.
The graphs coming from the notebooks should be exported as image files and then inserted in
the report and not “screenshotted and pasted”.
The files will be submitted electronically using the electronic drobox in Canvas.
8.1 Structure of the Jupyter Notebook
1. You can use the empty skeleton file (APM_XXXXX.ipynb) provided adding all the cells that
you need while respecting the general structure.
2. Your python notebook should contain your name and student ID at the top.
3. The first code cell should contain all the import statements.
4. The second code cell should contain all the user-generated functions.
5. The notebook can import any of the libraries used in the subject including the
apmodule_vx libraries. If you want to import a library that we have not used in class, please
check with me beforehand.
6. The file can only load and use the datafiles provided with the assignment or other
datafiles used in the subject. No external data can be used.
7. Your code should be well commented using either markdown cells or # comments in the
code cells.
8. You should use markdown cells to help the reader navigate the file, basically explaining
what you are doing in any code cell (or at least the most relevant ones).
9. You should choose which results to present in the notebook in order to help the reader
without overwhelming. For example, if you simply modify a column in a DataFrame it may
not be necessary to show the result on screen.
10. I need to be able to run your notebook in one go from top to bottom, so before submitting
make sure that all your code runs properly. Do not worry about the running time of your
notebook. You do not need to optimize for speed.
11. You can copy portions of the notebooks created in class, but please do not follow their
structure. The notebooks used in class were designed for teaching purposes and do not
reflect the sequence of objectives of your notebook. Not everything we have done in class
fits with this research project…
You should consider the notebook as the natural complement to the pdf report. imagine that
your reader will go through the report and then, from time to time have a look at the
corresponding section of the Notebook to understand some technical aspect of your model.
25579 – Applied Portfolio Management 8
9. Marking Guide

Component Value
Below Expectations
<50% (Fail)
Meets Expectations
50% - 74% (Pass-Credit)
Exceeds Expectations
≥ 75% (Distinction-HD)
Presentation
of the Strategy
10%
• The presentation of the quality factor betrays
lack of understanding of its economic
fundamentals.
• The analysis of the determinants of the factor ins
confused or insufficient.
• The presentation of the factor is complete and
based on coherent financial and economic
reasoning.
• The presentation is rich and engaging.
• The language is professional and proficient.
• The presentation conveys a deep understanding
of the quality factor and its determinants.
Statistical
Analysis
20%
• There are serious methodological errors in the
analysis.
• The analysis is incomplete.
• The results are not well commented.
• There are no serious methodological errors, and
the analysis is complete.
• The presentation of the results is sufficient.
• The results are presented in a professional
manner providing enough information without
overwhelming the reader.
Macro
Analysis
5%
• The analysis is missing or insufficient.
• There are methodological errors in the analysis.
• The analysis provides some economic intuition.
• The analysis is technically correct.
• The results of the analysis are very well explained
and presented.
Log-Only
Strategy
22.5%
• There are errors in the backtesting process.
• The backtesting process is incomplete.
• The optimization process is incomplete.
• The process is not explained clearly enough.
• The presentation of the results is missing or
insufficient and does not convey sufficient
information.
• There are no errors in the backtesting /
optimization process.
• The process is complete.
• The explanation is sufficiently clear.
• The presentation of the results is sufficient.
• The description of the process is clear, complete
and of professional quality.
• The results are presented in a professional
manner providing enough information without
overwhelming the reader.


[Continues in the next page]

25579 – Applied Portfolio Management 9

Component Value
Below Expectations
<50% (Fail)
Meets Expectations
50% - 74% (Pass-Credit)
Exceeds Expectations
≥ 75% (Distinction-HD)
Long-Short
Strategy
22.5%
• There are errors in the backtesting process.
• The backtesting process is incomplete.
• The optimization process is incomplete.
• The process is not explained clearly enough.
• The presentation of the results is missing or
insufficient and does not convey sufficient
information.
• There are no errors in the backtesting /
optimization process.
• The process is complete.
• The explanation is sufficiently clear.
• The presentation of the results is sufficient.
• The description of the process is clear, complete
and of professional quality.
• The results are presented in a professional
manner providing enough information without
overwhelming the reader.
Quality of the
Presentation
10%
• There are frequent spelling and punctuation
errors.
• The language is often non correct and does not
convey financial concepts in an effective way.
• There is not a common graphic style and colour
palette.
• Graphs and tables are badly formatted.
• There are only minor spelling and punctuation
errors.
• The language is correct, and the financial
terminology properly used.
• There is evidence of editing to make the feel
professional.
• The document has a truly professional tone and
feel.
• The narrative structure s easy to follow.
• The language is very effective, and the key ideas
presented in a succinct but clear way.
• Tables and graphs are effective in
communicating the key results.
Quality of the
Notebook
10%
• The notebook does not run properly.
• The notebook is not commented, or the
comments are insufficient and/or unclear.
• The notebook runs properly
• The comments are sufficiently to allow the
reader to properly follow the process.
• The code is well written and formatted. It makes
good use of functions and packages.
• The variables are properly named and easy to
follow.
• The choice of which intermediate results to
present is effective to help the reader.
• The comments are rich and well-made, allowing
the reader to follow both the financial logic and
the code structure.
• The comments make an effective use of
markdown.
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CIVL2010 ECMT2150 CS 333 CP1406 KIT308 Economics 701 ECON3740 ECE 5759 BFC3340 FINC2012 COMP4500 MATH3871 FIT3080 18-819C Economic ECO202Y5Y PHY100 FINC-780 Econ 100B EC602 IE582 EE450 COMP9517 WRDS 150B ECON 570 LECTURE 2 ECA5101 ECE 4420 ADAD9311 FIT3031 CS 544 MF 703 CS 6140 KIT501 ENGSCI 344 CSC171 IE 332 FINM8007 21S2 COSC 1114 FE545 E471 SIT102 CSC108 MAT301 IAE 101 COP3503 STAT2004 EC 303 CS1026 STAT1203 MATH3171 ISOM5160 IFN657 FIT2014 ACCT2102 DSCI550 STATS 330 ELEC421 COMP3670 QBUS6840 MEES:698B MAST30027 MIET1077 Economics IFT 6758 FIT5122 BUSN5101 CptS 111 HRMT5502 Math2018 PP 312 INFS3200 CZ3005 CSSE1001 SENG 2011 MKTG 553Q BUFN 640 COMP507 ETF5952 DATA 311 ECE4043 BANK3011 finance M3H623544 HW1 INFS 7410 AI6103 STAT3888 INFS3208 ACCT7103 ECOS3013 PSYCH 20B F79MA STAT3006 ENGG952 2X MGSC 7000 ECE4132 MSF 526 MATH 3033 CDS 511 EEEE4120 EEET2465 ECA5103 MATH2070 ELEC3104 BU51019 EEE8147 ENGR20003 COSC 1107 ETF3200 FNCE 435 MSFI 435 ISyE6420 GENG4405 HW ETC5523 IE 7315 MOEC0021 STA 106 ENGG 1300A ENGG 1300 OLET1139 STAT 3503 STAT 206 FEM11149 ELEN 4720 COMP20003 SOLA1070 CS574 C11CS LINB29H3 MAST90083 ECON7200 STAT 610 LINB29 DSM-5 COMP3161 EEEN40010 MATH 4431 K353 STA 3386 IERG4300 COMS W4167 ENG5298 AMME 2302 CS3910 COMPSCI 320 STATS 369 GR5242 COSC 328 CSCI435 MGTS1301 INFS2200 COMP3900 CIS 375 Module AE03 COMP3121 CS260 HAM503 MGMT5050 INT3075 COSC 285 GEOL0029 GEGE2X01 STAT1201 MATH1061 MMF1941H STAT 5060 CS 520 COMP 4320 MSIN0104 000T FINS3648 ECMT2160 ECON4003 Phys 129L CSE 142 CS 3130 MGEB01 EECS 340 Finance (20443/20444) ECMM149 COMP5310 EEEN60180 CSC 111 AT2 CSCI 4430 STAB57 MA/CSC 427 MATH322 D100 CSCI544 CITS3004 CI6227 CSE 565 APCO 1P01 852L1 ELEC S411F COMP3207 STATS330 ECON7530 FIT5149 CSI4104 CMPT 371 COMP201 SEHS4696 FI4003 MATH6182 CG1 WS MATH401 MGT 205 QTM 110 COMP 0137 MACE12201 FIT5210 ECE 544 BISM7206 HUDM 6055 ECON3203 STATS 210 MSCI 570 MATH6173 COMPSCI4039 Accounting COM3503 AOE2024 ECON213 PSYC10004 Control Data 100/200A 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