Investment Diagnostics
Portfolio Optimization
ECA uses state-of-the-art computer software to apply statistical,
financial and algorithmic innovations to enhance the investment value and
safety of client portfolios. This process of asset optimization (also known as
modern portfolio theory, capital market theory or mean-variance optimization)
is the scientific combination of various asset classes (fixed income, large cap
stocks, small cap stocks, international, hedge, etc.) to maximize return and
minimize risk. The process also involves rebalancing client portfolios among
asset classes, dealing with alternative investments and meeting cash flow
planning objectives.
Mean-variance optimization is achieved when the expected return of the portfolio
is greater than other similar (but non-optimized) portfolios with the same or
higher level of risk. Reaching this optimization is the efficient frontier –
where returns are maximized for any given level of risk (or, minimizing risk
for any given level of return). This process quantifies the notion that
diversification reduces risk. On the efficient frontier graph, with standard
deviation on the horizontal axis and expected return on the vertical axis, as
the assumed level of risk (standard deviation) increases, the obtainable
expected return increases. In practice, the slope of the efficient frontier
line on the graph is not straight, but rather decreases as risk rises.
Asset / Liability Services
ECA provides customized solutions to identify and meet the unique
investment needs of clients. The Asset/Liability services benefit all types of
investors including defined benefit pension plans, endowments and foundations.
Defined Benefit Pension Plans
Actuarial software is used that applies ERISA and FASB rules.
Simulations are run that incorporate Plan assets and liabilities, as well as
their relationship to each other. Data from the actuarial valuation report is
modeled including:
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Benefit formulas and grandfather clauses.
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The actuarial discount rate and its relationship to economic interest rates.
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Salary scale and its relationship to inflation rates.
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Demographic structure, broken down into active employees, retirees, deferred
vested employees and disabled participants. Each group is further broken down
by age, service, salary and current and accrued benefit payments.
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Decrements including mortality, withdrawal, disability and retirement
rates.
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Market value of assets and the formulas used to determine the actuarial value
of assets.
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Funding methods such as Aggregate Cost, Entry Age Normal and Projected Unit
Credit.
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Methods for distributing benefit payments including annuities and lump sum
payments.
Several efficient frontier portfolios (optimized asset mixes) are modeled along
with the liabilities. Asset values of the pension plan are projected forward
for up to thirty years. A stochastic simulation is performed where the
projection is run 500 to 1,000 times. Within the projections, asset returns are
determined randomly each year consistent with the capital market assumptions.
In addition, interest and inflation rates vary to replicate trends in the
economy. Historical correlations are used to link interest and inflation with
the asset classes. The simulation results display the expected performance of
the pension plan under a complete range of market conditions. All relevant
statistics are displayed at any point in time. These include minimum required
and maximum tax-deductible contributions based on ERISA, funded ratio and
present value of contributions. Also, FASB statistics are calculated including
ABO and PBO.
The statistics are analyzed and the portfolios are compared with regard to their
ability to maintain fiscal security. An appropriate mix is recommended based on
its ability to satisfy the goals of the pension plan sponsor, while not
exposing the Plan to an unmanageable amount of risk.
Endowments and Foundations
When analyzing the best asset allocation strategy for endowments and
foundations, several factors are taken into account, such as spending strategy,
market conditions, financial goals and economic constraints. In analyzing these
factors, ECA uses a stochastic simulation model to analyze various investment
strategies under a wide variety of market conditions. Each portfolio is
analyzed for its ability to grow over the long-term, while protecting it
against downside risk in the short-term.
The two main objectives are to satisfy the spending needs and to maintain a
financially healthy endowment to insure perpetuity. There is often concern
about the spending strategy and equal uncertainty about future contributions.
Fund managers are pressured to spend more in times of a strong market.
Additionally, some spending may be needed for fixed dollar expenses. If the
value of the fund falls due to poor market conditions, larger contributions are
required to cover the shortfall. Therefore, some alterations may be needed in
the spending policy to make sure that the needs are satisfied while avoiding
the possibility of financial stress. The ECA model can test an unlimited number
of spending strategies. This process identifies the best combination of
spending method and investment strategy to accomplish the long-term goals of
the Fund.
Manager Search and Selection System
ECA maintains a significant database of professional asset managers to
assist clients in manager search and selection. The RFP / manager screening
process is very comprehensive, both quantitatively and qualitatively. The
following is a summary of the steps in this process:
Quantitative Database Screening
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Wilshire Associates / Nelsons / Evestment
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Years in Business
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Assets Managed
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Performance History
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Offensive / Defensive Characteristics
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Pertrac Quantitative Analysis
Qualitative Research and Face-to-Face Interviews
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Investment Philosophy
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Quality of People
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Ownership / Business Strategy
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Quality of Historical Performance Results
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Other Business Interests
Continual Monitoring
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Ensures Consistent Performance
First Hand Experience with Each Manager
Institutional Pools or Separate Account Management
Keys to Successful Managers
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Philosophy + Process + People = Performance
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