PORTFOLIO ANALYSIS: UTILIZING PORTFOLIO MODLEING …

PORTFOLIO ANALYSIS: UTILIZING PORTFOLIO MODLEING AND SOFTWARE

By: Brad Coker

Practicum Advisor: Roger Staiger

A practicum thesis submitted to Johns Hopkins University in conformity with the requirements for the degree of Master of Science in Real Estate

Washington, DC May, 2012

? 2012 Brad Coker All Rights Reserved

Johns Hopkins University MSRE Spring 2012

TABLE OF CONTENTS

EXECUTIVE SUMMARY

METHODOLOGY OF PORTFOLIO ANALYTICS

SUMMARY OF PORTFOLIO METRICS ASSUMPTIONS WITHIN MODEL ANALYSIS OPT QUEST/STOCHASTIC MODELING

OPTIMIZATION STRATEGY

RECOMMENDATION FOR PORTFOLIO

DISPOSITION OF INDIVIDUAL ASSESTS OPTIMAL CRITERIA FOR FUTURE ACQUISTIONS

PORTFOLIO SUMMARY

PORTFOLIO HISTORY

PORTFOLIO OWNERSHIP STRUCTURE

PORTFOLIO DESCRIPTION

TREES AT FLATLANDS HAMPSHIRE'S GLEN ASPENS HOLLOW TIGERS GLADE

MARKET SUMMARY

SUBMARKETS OVERVIEW SUBURBAN VIRGINIA SUBURBAN MARYLAND BALTIMORE

APPENDIX & SUPPORTING SCHEDULES

4/26/2012

2 4 4-6 6-9 10-12 13

13-15 15-19

20 20 21 22 22-24 24-26 27-29 29-30 31 31 31-33 33-35 35-37 38

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EXECUTIVE SUMMARY

4/26/2012

For consideration by the partners in the Joint Venture owning the attached portfolio of four assets, following is an analysis of the existing portfolio and recommendation for future action to increase the efficiency of the portfolio as a whole rather than on an asset by asset approach.

The current portfolio has underperformed dramatically and required substantially more capital to fund for everything from capital improvements of the defensive nature to ongoing yearly debt service shortfalls or operating deficits. At the end of 2011 the portfolio return to date stood at (1.64%) forecasting forward using the 2012 approved budgets for each property the return is only estimated to grow to (.85%). For the purposes of this analysis return will be measured as yearly cash on cash return as it is measured from the end of each calendar year including the partial years in which acquisition took place. This provides a more true view of what this portfolio is worth and is more comparable to the measured returns of the capital markets. The Probability of Loss for the portfolio as measured for the Sponsor in this Joint Venture at the end of 2011 is 58.24% decreasing to 54.54% by the end of 2012 if no changes are made to the portfolio.

This analysis has demonstrated that to maximize the efficiency and ultimately the probability that 100% of the invested capital of this portfolio is returned; there are a number of possible steps to be taken. Efficiency being defined as the lowest product of Risk (mathematically Standard Deviation) divided by Return (weighted average return over the Period), and Probability of Loss mathematically is the Z score derived from the Coefficient of Variation assuming a Norma Distribution. Should the partnership choose to continue the dissolution of the Venture's assets the first step would be to sell the Tigers Glade project as it creates the lowest Probability of Loss and increase the both the return and efficiency at the Sponsors level.

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Further analysis has been done to measure and derive the optimal set of metrics that a new

acquisition should meet to best increase the likelihood of capital return for both the Joint Venture

and the Sponsor in particular. Three objectives were run through the software; first, to maximize

the average Return of the portfolio, second, to minimize the Risk (standard deviation) of the

portfolio, and third to maximize the likelihood of 100% return of invested capital or put another

way to minimize the Probability of Loss percentage. The minimization of Probability of Loss is

the most inherent metric in Real Estate these days; it is with that in mind that the recommendation

to this committee for future acquisitions be derived from this objective's analysis. Using four key

variables OptQuest was able to determine and common sense will back up the following criteria

for a future acquisition that will best enhance the current portfolio;

1. 150 Units

2. $90,000 per Unit purchase price

a. Equating to a purchase price of $13,500,000

3. $2,000 per Unit per Month average rent

4. 10% Capital participation on the Equity requirement by Sponsor

The recommendation being made by this investigative body is to have the Joint Venture sell the Tigers Glade asset and proceed to take advantage of the current market conditions and acquire at least one new community to replace it. Regardless of the Sponsor's and Joint Ventures' decision to sell Tigers Glade the criterion established through Crystal Ball software and the OptQuest add on for a new acquisition should be followed to guide this portfolio into the near future as it

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continues to evolve, and with proper handling become a valuable portfolio to this Sponsor and the

Joint Venture as a whole.

METHODOLOGY OF PORTFOLIO ANALYTICS

SUMMARY OF PORTFOLIO METRICS This analysis focuses on the four metrics that are most commonly evaluated and used in Portfolio analytics. The first two are Risk and Return, these are the most basic and widely used in Real Estate. Risk is quantified by Standard Deviation of the given year over year returns of the individual assets weighted by the correlation of that asset when compared to the portfolio's other positions.

Standard Deviation Graph

Mean

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Return, can be quantified a number of different ways and as stated already, this analysis has

chosen to evaluate the year over year cash on cash return for each asset. Therefore Return is the

average yearly cash on cash return for the individual assets and the Portfolio Return is the Sum of

those individual returns multiplied by the exposure that individual assets are to the whole Portfolio.

Efficiency is the third metric and largely the most important to a portfolio, the maximization of

Return of the minimization of Risk are goals, but being inversely related for the most part means

that taking either to the extreme will be at the detriment of the other. This analysis has used the

Coefficient of Variation to quantify efficiency, which simply put is the maximum level of Return

for a given level of Risk. This can best be seen using the Efficient Frontier concept that

graphically shows the maximization of Return at any given level of Risk.

Efficient Frontier Graph

This graphic depiction of the effiecnt frontier is from the Joint Venture's portfolio with a newly acquired asset in tow. Notice that it shows you a point of each level of Risk (Standard Deviation) and what the Probability of Loss is for that given level of Risk. This shows that in order to

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increase the likelihood that the Joint Venture gets 100% of its invested capital back they will need

to increase their Risk threshold to between 7.5 and 8.

Probability of Loss uses the three prior metrics to derive the likelihood that 100% of invested

capital will be returned. Graphically it can be seen as the portion of the graph to the left of the

axis.

Probability of Loss Graph

Probability of Loss of 100% of Invested Capital

Return -5%

0%

5%

10%

ASSUMPTIONS WITHIN MODEL ANALYSIS The four Metrics that were used in this analysis all have different impacts on the two major metrics, Portfolio Return and Portfolio Risk. Following are the graphic depictions of how these variables affect both major metrics.

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Rent per month using a triangular distribution with High, Low, Mean of $2,000, $1,500, and

$1,750 respectively.

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