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EE590 Project Proposal
创建日期：2024-04-15 17:07:14
所属分类：经济Economics
标签： EE590
Project Proposal

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EE590 Project Proposal

SAMPLE PROPOSAL
2
Proposed Work
1. Problem Statement
For federal employees, retirement planning and investment strategies differ slightly from those working in
the private sector. In the private sector, employers offer a 401(k)-retirement account. In the public sector,
employers offer a Thrift Savings Plan (TSP). While different in name, both have employer defined
investment funds with varying levels of risk and reward associated with them.
With the TSP, there are five funds that a portfolio can be diversified between (G, F, C, S, and I). There is
also an option to for an employee to utilize the Lifecycle Fund (L Fund). A comparison matrix of the
funds, as published on the TSP website, can be seen in Table 1 [1]. The lifecycle fund utilizes a
professional service that determines the fund allocation based on target date and risk allocation. With this
fund, individual risk preferences are not considered. All individuals that elect to allocate their investment
in this fund are grouped based on time horizon and individuals in the group all have the same investment
strategy.
Table 1: TSP Published Fund Comparison Matrix [1]
G Fund F Fund* C Fund* S Fund* I Fund* L Funds**
Description of
Investments
Government
securities
(specially
issued to the
TPS)
Government,
corporate,
and
mortgage-
backed bonds
Stocks of
large and
medium-
sized U.S.
companies
Stocks of
small to
medium-
sized U.S.
companies
(not included
in the C
fund)
International
stocks of
more than 20
developed
countries
Invested in the
G, F, C, S, and
I Funds
Objective of
Fund
Interest
income
without risk
and loss of
principal
To match the
performance
of the
Bloomberg
Barclays U.S.
Aggregate
Bond Index
To match the
performance
of the
Standard &
Poor’s 500
(S&P 500)
Index
To match the
performance
of the Dow
Jones U.S.
Completion
TSM Index
To match
performance
of the MSCI
EAFE
(Europe,
Australasia,
Far East)
Index
To provide
professionally
diversified
portfolios
based on
various time
horizons, using
the G, F, C, S,
and I Funds
Volatility Low Low to
moderate
Moderate Moderate to
high –
historically
more volatile
than C Fund
Moderate to
high –
historically
more volatile
than C Fund
Asset
allocation
shifts as time
horizon
approaches to
reduce
volatility
*The F, C, S, and I Funds are also have earnings from securities lending income and from temporary
investments in G Fund securities. These amounts represent a very small portion of total earnings.
**Each of the L Funds is invested in the individual TSP funds (G, F, C, S, and I).
3
This study focuses on optimizing the retirement plan of a federal employee utilizing personal investment
preferences. Individuals have different risk tolerances, diversification preferences, and opinions on
manager/fund performance. With the Lifecycle fund, these preferences are not considered. Using
historical data for the TSP funds and the Benchmark Indices, an interactive model will be developed
where a user can define their personal investment preferences and receive an investment strategy that
maximizes portfolio return per unit of risk.
This is an important study because it considers personal risk preferences for federal retirement investment
strategies. Currently, there are limited resources and funds available for TSP holders. Developing a tool
that not only provides an investment strategy, but also allows an individual to adjust their investment
preferences as they age encourages one to better optimize their portfolio.
2. Approach
For each of the TSP funds, the daily stock price is available from 2005 to 2020. In order to capture an
entire economic cycle in the analysis, historical data from Jan 1, 2005 to Dec 31, 2014 (10-year
timeframe) will be used for analysis and model creation. Historical data from Jan 1, 2015 to Dec 31, 2017
(3-year timeframe) will be used to validate the model.
There are two main components to the approach to this problem: analysis of manager/fund performance,
and portfolio optimization. The model will be developed in Excel.
Manager/Fund Performance:
There are five funds that will be analyzed in this study (G, F, C, S, and I). Each fund in the TSP is
modelled to match the performance of a market style/index. To determine the manager performance of the
TSP funds, each fund will be compared to its respective benchmark. Table 1 identifies each TSP’s
benchmark index under the “Objective Fund” row of the table.
To examine portfolio performance compared to the benchmark, beta and alpha, two metrics commonly
used to examine fund performance need to be calculated.
Beta Calculation:
To determine fund volatility, beta (β), will be calculated for each TSP fund.
=
( , )
( )
Beta will indicate how much the fund deviates from the overall market, where the overall market has a
beta equal to 1.0 [2]. If beta is greater than 1, the fund tends to have a higher risk and a higher reward; a
beta less than 1 equates to less risk and a lower reward [2]. By determining the beta for each fund, the
systematic risk for the fund will be determined and one can then calculate the alpha for each fund.
Alpha Calculation:
Alpha, α, is a metric used to evaluate fund performance compared to its benchmark. Derived from the
CAPM model, the formula for alpha is listed below [3]:
= ? ? ( ? )
4

? =
= ?
=
= , ?
For each of the TSP funds, alpha will be calculated. A positive alpha indicates the portfolio outperforms
the benchmark. A negative alpha indicates the portfolio underperformed the benchmark. Further, the
value of alpha is the percentage of over/underperformance compared to the benchmark [3]. The value of
alpha will be used when developing the portfolio optimization model.
Portfolio Optimization:
This study has identified multiple metrics to evaluate portfolio risk and compare fund performance to its
respective benchmark. Using the above metrics, along with conducting a mean variance analysis and
calculating the Sharpe ratio for the optimal portfolios, an informed decision regarding the investment
strategy for the TSP fund can be developed.
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关键词一 关键词二 关键词三 关键词四 关键词五 和法规和的发更好的风格和 ECON 615 FINC 612 CSC148 COMP 639 ACCT 203 ACCT 211 PSYC 101 MTH2009 COMP52315 PSYCO 432 statistics MATH4063 11 xxx 1 MA1MSP MAST30028 MATH3888 CS341 EEE30002 ES2F5 MCD4160 CC0933 ECON 1101 MCHM3001 CHEM3118 COMMGMT 2511 COMP41280 STAT 631 24T1 IRE379 SENG365 ECON433 FIT3139 MATH4602 LING5621M FINS5516 ECON3208 MN2177 L2 SM EEET1415 Finance DS4023 COMP3004 7CCSMRTS K1S5B6 Stat230 CSCI4211 CSI2132 ECON30130 MAS6100 ENVS222 COM2107 INFO1112 STAT 4004 FIT2100 comp2022 COMP4691 Physics 307 Econ 659 probability CSCI316 fir29 CSCI203 COMP3160 COMP6714 INFO1113 Physics 7B Physics Photonics S203031 STAT2005 COMP90015 CSCI 2110 CSCC46 Information CSC477 COMP4650 Statistical COMP 346 COMP1017 ELEC340 MATH1007 Programming function STAT 244 CS 134 Java cse13s Math 108A FW20 ECON3389 CSE 130 Science 331 COMP9020 engineering COSC 445 CSE 5523 GAME2012 visualization MATH 235 Math 370 CSC343 COGS 108 EE524 COMP10200 STAT 416 3FK4 MSCI 311 ECON6113 ACC40700 EMESTER1 MAS8383 ECO 512 STAT 8310 CMN3102 MA577 CMPT 225 COMP0045 Methods Equations MATH 113 Math 3283W ICS-33 EN4302/ENT603 BIA B350F MA318 MTHM506 MECH 5315M ECONOMICS MAS8382 COM 2004 PX3142 XJEL 3662 STAT 231 MGT B399F PX4131 COM2108 30AM MSCI521 ECONM1015 ACFI304 GR5241 MATH10101 ECON 2070 COMS31900 EFIM20011 CSE 250B ACSE-5 STAT4207 SOFT2412 ELEC 331 AY2020 MSIN0209 FIT2094 CS 241L ST404 CS 411 3D CA3 INF4002 COMP3506 SIT718 CS 188 CS 170 MATH 138 CSE 251A CMT118 DATA5207 CMPT307 CMPT459 T1 PGEE11108 COSC 3P32 ME 163 MATH96007 7QQMM203 EE6227 BA 574 STA 4234 ECO206Y1Y ECO2008 MT2300 MATH 11158 CS 527 MACM 316 CSE474 2DI70 ISE 525 COMP3411 EMAT30007 7CCSMBDT MFIN704 MFIN704W21 MfIB ECE 438 CS 436 F36 CS5344 FE 621A FE621 TBA 612 ECM3151 ECMM422 MF1 MSIN0107 ESSMENT CS 5854 MFIT 5008 MIPS R4000 ENG5274 BU52018 ENG2079 BIOA02 STA2570 F0 INF553 STAT 440 STAT3008 COMP9417 COMP6451 6COM1042 BU52006 ST303 HW-1 CISC-235 CS 510 MATH3161 ECN 140 ECE391 Comp 3613 CVEN 9625 PRG455 UESTION 1 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