In practice, it is essential to take an integrated approach to clients' wealth management and investment supervision activities. The integration is based upon expressly recognizing the three major components of this process: wealth planning, investment supervision, and portfolio accounting and reporting. Each component is now examined in turn.
I The Investment Process: Wealth Planning
Although often a convenient starting point for any investment relationship, the planning phase is really a continuous and dynamic process that requires ongoing review and refinement as client needs and objectives change. It is during this phase that investment supervisors assist their clients in a determination of client goals, objectives, and constraints. The importance of this process should not be underestimated. Proper planning develops the inputs upon which all other portfolio management decisions will rely.
Specifically, investment supervisors must be interested in learning about their client's views and preferences regarding the risk to be taken. These include determining the degree of tolerance for portfolio drawdown (peak-to-trough intervals of loss) and conditional value-at-risk (point-estimate maximal loss).
Other metrics of interest often include the degree of aversion to skew (exposure to directional market bias) and kurtosis (exposure to extreme events). The purpose of these inquiries is to closely discern the degree of client risk tolerance (where risk manifests itself in multiple dimensions).
This concentrated focus on the specific articulation of risk tolerance differentiates "best practice" approaches and is a critical input to the portfolio management and supervision process outlined below.
Effective investment supervisors also assess the organization of their client's investment-level entities in order to determine how such goals and objectives are shared across different constituents. Other planning activities, including tax optimization (and related entity allocations), income and expense modeling, and asset and liability matching must also be conducted in order to more fully appreciate the requirements of the investment portfolio.
The initial goal of this process is to help clients formulate a comprehensive investment policy statement, including the articulation of risk tolerance, which will ultimately guide the asset allocation and portfolio selection decisions.
II The Investment Process: Portfolio Management and Supervision
Once an investment policy statement has been articulated, it must be translated into a consistent and actionable portfolio management process. Ultimately, a diversified portfolio of investments in the "traditional" (e.g., cash, fixed income, equities), and "alternative" (e.g., hedge funds, private equity, real estate) asset classes is built through a deep and intensive due diligence process.
Numerous academic and empirical studies confirm the philosophy that the asset allocation decision is one of the primary determinants of portfolio return variance—both across time and across investment managers (For example, Brinson, et. al., 1991 and Ibbotson and Kaplan, 2000). Security selection and market timing, though also influential, are generally secondary considerations that have marginal contributions relative to the overall asset allocation.
Effective asset allocation optimizes the power of diversification and ensures that an investment portfolio maximizes the return generated for a given level of risk. As a result, getting the "top-down" decision correct is of critical importance.
Unfortunately, applications of the technique by many consultants, investment managers, and brokers often fail to account for varying degrees of market efficiency, skew (bias or event risk), and kurtosis (extreme events) often present among different asset classes. Relying solely upon returns and standard deviations can lead to sub-optimal conclusions, especially since neither vector is particularly robust with respect to time. In addition, the popularly used linear mean-variance optimization models tend to produce results that produce inherently unstable and grossly imbalanced portfolios that are highly sensitive to estimation error (Michaud, 1989).
Such narrow reliance among investment consultants and money managers is not uncommon; however, it often leads to an overestimation of expected return or an underestimation of risk and is the root cause of many forms of investor disappointment. It is also a causal factor in many of the very notable fund "blow ups" that have been witnessed in recent times.
An "Efficient Portfolio Management (EPM)" Methodology
The EPM methodology explicitly addresses such shortcomings by taking on the issue of risk directly. The goals of the EPM are to:
Explicitly determine how much risk to take and what forms of such risk are acceptable; and
Ensure that the portfolio is maximally compensated for taking on those risks.
Under the EPM framework, investment exposure (the sources of risks and, correspondingly, returns) comes in two forms, namely: systematic and nonsystematic. The EPM process is a synthesis of strategic asset allocation (for the purposes of determining systematic allocations) and active risk budgeting (for the purposes of determining nonsystematic allocations).
A brief discussion of each follows below.
Allocations to Systematic Investment Assets
Systematic investment assets typically relate to broad, well-diversified market exposures (also generically referred to as "beta"). In order to determine the optimal systematic exposure to various asset classes, EPM relies upon the process of strategic asset allocation.
The process begins by identifying the investment universe of candidate assets. These may include, for instance, the following classes (and their related subsets): cash, fixed income, equities, commodities, and real estate. In order to establish the initial (neutral) portfolio weights, EPM draws upon the general findings of the Capital Asset Pricing Model (CAPM), as described by Sharpe (1964) and Lintner (1965).
According to the CAPM equilibrium, the optimal asset class weights are directly related to the relative aggregate market capitalizations of each such asset class. That is, in equilibrium, the portfolio weights for the "market portfolio" in aggregate also become the optimal weights for individual portfolios. EPM refers to these weights as the "Equilibrium Portfolio," and it serves as the initial "center of gravity" for the strategic asset allocation process.
As prescribed by Black and Litterman (1992), EPM next "reverse-optimizes" the Equilibrium Portfolio to ascertain its implied views of asset class risk premiums. Stated differently, if one believes that the Equilibrium Portfolio is in fact the optimal portfolio (as suggested by CAPM), what must the views on relative asset class risk premiums be in order to satisfy mean-variance optimality conditions?
The analysis of such implied views is analogous to the more popular application of using implied volatility to evaluate options pricing. In that approach, it is assumed that the market price represents both known and estimated variables that affect valuation. However, given the difficulty of objectively estimating expected volatility, many investors consequently take the market price as a given and instead determine what it must imply about expected volatility. Then, investors can make individual judgments about whether this implied volatility is in fact reasonable.
Similarly, investment supervisors can compare the implied views of the Equilibrium Portfolio with their own views of relative asset class premiums. Importantly, under this approach, it is not necessary for investment supervisors to make forecasts of the absolute returns of every asset class; they need only make relative risk premium assessments.
Where differences emerge between investment supervisor (or client) views and the market-implied views, EPM combines them through a conditional, Bayesian-weighted adjustment in order to capture the corresponding degree-of-confidence in each view. The adjustment may also affect other asset classes, as the process attempts to maintain the consistency of the covariance relationships among such classes. The resulting portfolio weights form a "passive risk portfolio." This approach tends to minimize the forecast errors and unrealistic portfolio tilts that often plague standard mean-variance optimization.
Since the passive risk portfolio primarily addresses broad market, systematic (beta) exposure, its implementation is best conducted through low-cost, tax-efficient passive investment instruments. Such composition for broad market systematic exposure is consistent not only with CAPM, but also with the general findings of Fama (1970) and Brinson, et. al. (1991).
Allocations to Nonsystematic Investment Assets
Nonsystematic investment assets generally relate to idiosyncratic exposures (also referred to as "alpha") that are not correlated to the systematic universe. In equilibrium, and relying upon the principles of diversification, such idiosyncratic exposure should not be expected to produce excess return. Therefore, expected alpha return in equilibrium is equal to zero.
In reality, however, the markets are often not in a state of CAPM equilibrium, especially in the short to medium term. As a result, it is not unusual to find tactical sources of alpha that do in fact exhibit positive expected excess returns.
Active investment management is the process of identifying and capturing this positive alpha. In order to determine the optimal exposure to these activities from a portfolio management perspective, EPM relies upon a disciplined methodology of budgeting for such "active risks." This risk budgeting process operates on the principle that active risks should be assumed only where the marginal contributions to portfolio return from such activities exceed the marginal contributions to portfolio risk.
Once again, the process begins by identifying the investment universe (in this case, of nonsystematic assets). This universe typically includes certain hedge funds, private equity, and real estate investments. However, it should not be construed that the nonsystematic universe consists solely of such "alternative investments." It can also include actively managed assets in the more traditional classes (equities, fixed income, and others).
In those cases where an asset has elements of both systematic and nonsystematic exposure (as is sometimes the case for assets in the traditional classes), the alpha and beta components must be separated. This decomposition can be accomplished by evaluating the distribution of the investment's variance from its systematic benchmark. In this context, the investment's alpha is found by computing the mean of the distribution, while the "tracking error" is found by computing the standard deviation.
The active risk budgeting process now determines the most appropriate portfolio of active risks that, when combined with the passive risk portfolio, meets the client's overall macro goals and objectives—as expressly defined in the earlier wealth planning activity.
The methodology begins with a series of simulation and optimization studies to determine categories of active allocations (conditional upon an allocation to the passive risk portfolio) that can most efficiently meet the client's objectives. The optimization program explicitly recognizes each client's individualized level of risk aversion by first satisfying client constraints related to portfolio variance, acceptable drawdown, and event risk and then determining which remaining combinations of assets maximize return.
This approach is unique in that it contains an explicit focus on the various degrees of each component of risk that can affect the total portfolio, including the higher order moments of the expected distribution. Careful consideration of such risks can provide far greater clarity into the investment process, help optimize the returns achieved in exchange for the risks knowingly taken, inform a strategy mix that might most capably protect from a variety of systematic shocks, and ultimately lead to results that should more closely reflect the original intent and objectives of the client.
For practical purposes, EPM classifies assets into seven "active risk portfolios." Each portfolio consists of managers and strategies that share specific active risk signatures and exhibit stable covariance properties. These portfolios are categorized as follows: "Long Equities," "Long Fixed Income," "Long-Short," "Tactical Trading," "Event Driven," "Relative Value," and "Private Equity."
In determining which assets are eligible for inclusion into EPM's active risk portfolios, investment supervisors engage in a deep and intensive process of manager and investment diligence. In this evaluation, two considerations typically emerge. First, the key evaluation criteria are both quantitative and qualitative. Second, building a portfolio of active assets involves more than simply finding the managers and investments that produce the best returns in isolation. It also requires understanding how they might behave in different economic environments and how they might correlate with one another—and with the passive risk portfolio—particularly during periods of high market volatility. Such analyses are critical, as correlation map surfaces can change dramatically as volatility, liquidity, and other "market stress" factors materialize.
The resulting active risk portfolios are then evaluated in terms of their marginal contribution to the risk (volatility, skew, and kurtosis [VSK]) of the passive risk portfolio. As stated before, the object of this analysis is to determine which combinations of the passive risk portfolio and the individual active risk portfolios produce the risk signature that best satisfies the client's original risk constraints and investment objectives.
Once such a combination has been identified, investment supervisors once again utilize reverse optimization to determine what the implied views (on the expected excess returns of the active risk portfolios) must be in order to satisfy mean-variance skew-kurtosis (M-VSK) optimality conditions.
Investment supervisors again compare their proprietary views of expected excess returns in one or multiple active risk portfolios to the implied views from M-VSK. Any variance is treated in similar fashion to the Black-Litterman approach utilized in the construction of the passive risk portfolio. The resulting portfolio becomes the client's global investment portfolio.
A Dynamic Process
Once the global investment portfolio is established, continuous monitoring and supervision of the portfolio must be conducted on an ongoing basis to confirm the variance, covariance, and other risk characteristics of the underlying investments. Such supervision includes performance attribution (relative to absolute and style benchmarks as well as relevant peer groups), risk control and monitoring (tests of manager adherence to active investment mandates, style drift compliance, short and long-term volatility) and ongoing personal reviews with investment managers (including regular communications, verification of manager commitment to client goals and objectives, and custody and reporting).
Critical to the process, however, is the periodic validation of the original risk constraints and investment objectives set forth in the wealth planning activity as well as the continuous supervision of the portfolio to ensure that its portfolio-level risk signature does not materially deviate from such specifications. Under the EPM approach, there is no distinction between the investment supervision process and the risk management process; they are one and the same by design.
Over time, changes to the investment portfolio can arise from three different sources:
Changes in views:
Investment supervisor proprietary and market-implied views can and do change. Obviously, the results of the strategic asset allocation will change as its inputs change.
Changes in active risk attribution:
The constituents of the active risk portfolio may change due to style drift, lack of continuing edge, lack of attractiveness in a portfolio-level context, or other diligence-related reasons.
Changes in client goals and objectives:
Client preferences and constraints related to risk aversion, tax regime, income requirements, time horizon, and other considerations may dictate a change from a planning perspective.
As a result, client portfolio management is a dynamic process that is responsive to both external (market and economic) as well as internal (client) influences.
EPM: The Benefits of Synthesis
The EPM approach is intended to engineer a portfolio that is capable of obtaining the "biggest bang for the buck," by carefully defining the clients' limited tolerance for risk and then allocating that scarce resource to those areas where it can be most efficiently rewarded.
As noted, EPM accomplishes this objective by explicitly segmenting the universe of investment assets by their risk characteristics; in particular, based upon of the level of systematic (beta) or nonsystematic (alpha) exposure each asset exhibits. In making this distinction, the most appropriate techniques drawn from strategic asset allocation and active risk budgeting can be applied to determine what levels of exposure and combinations of assets best produce the desired portfolio characteristics.
EPM is designed to directly address a variety of issues that are often poorly addressed in the typical applications of asset allocation and portfolio management. Consequently, the process actively: considers the relative market efficiency of various asset classes, includes the higher order moments of asset class distributions in evaluating risk, and incorporates non-traditional, "alternative" asset classes.
Portfolios resulting from the EPM process tend to exhibit the following characteristics (versus other more traditional methods):
Greater protection from the risks that clients choose to avoid and greater control over the risks that clients choose to take.
Higher degrees of efficiency in the compensation for risks that are taken
More rigorous standards for the acceptance of active risk
Higher quality diversification across asset classes, managers, and strategies, based upon specific and tangible opportunities for incremental risk-adjusted return
Lower sensitivity to estimation errors in asset class and strategy return forecasts
Taken together, these benefits lead to intelligent portfolio management solutions capable of more tightly meeting each client's individual goals and objectives.
III The Investment Process: Tax Accounting and Portfolio Reporting
Although the accounting and reporting function is often overlooked or treated as an afterthought, the effective utilization of accounting reports can be a powerful tool in assessing and diagnosing portfolio performance.
Reports can come from a variety of sources, including: investment manager statements, reports from prime brokers and custodians, and valuation audits by independent accountants. The investment supervisor's role is to provide an additional level of independence and produce analytic diagnostics that can be used to make effective investment decisions.
In this regard, investment supervisors must maintain an extensive, redundant database of transactions and tax-lot accounting when this information is obtainable from various custodians. The maintenance of an independent database allows us to analyze investments at the overall client family level, entity-level, and other customizable sub-groups of interest. Investment supervisors can also conduct broad tests of concentration and diversification across various managers and custodians, track cash inflows and outflows to ensure proper deployment, and test the veracity of month-end and quarter-end statements produced by the investment managers.
The reporting function is also useful for aggregating data for the purpose of performance measurement. Producing uniform performance and position reports allows fair comparison of different investment managers, regardless of their own internal performance reporting systems, which may vary by manager. Such reports also enables investment supervision analysts to conduct detailed style regression and returns-based attribution analyses, tools that are particularly invaluable in evaluating managers who may not share granular information on their underlying investments.
Finally, tax reports should be analyzed on an ongoing basis to identify and account for realized and unrealized gains/losses (by entity and by account), income and expense accruals (including amortization and accretion schedules), and potential "cross-manager" wash-sale violations, and for the identification of other tax-minimization strategies.
III Concluding Remarks
The finance and investment literature is full of a variety of (sometimes conflicting) approaches to the proper and effective supervision of investment portfolios for clients. All too often, academic treatments of the subject fail to recognize the realities of the investment world. Investment supervisors are in the challenging position of having to apply otherwise "elegant theories" to the typically messy "real world."
In so doing, however, they must properly blend the best ideas from financial economics with the realities and opportunities that present themselves. As such, no single prescription can work all the time and, indeed, any suggestions must continuously evolve to adapt to the constantly changing nature of the capital markets.
The most important priority for an investment supervisor is to design and build an investment portfolio that best meets client goals and objectives. In the end whatever methodology best satisfies this priority in a way that optimizes performance, cost, and tax efficiencies—and is rooted in sound financial economics and not arbitrary logic—is bound to be a viable approach.
Professor Sury has been a trusted adviser to some of the nation's wealthiest family groups and private organizations for nearly two decades.� Since having retired as CEO of Chicago Analytic Trading Co. (CATC) and Chicago Analytic Capital Management (CACM), a multi-billion dollar family office investment supervisor, Mr. Sury has been the Dean's Executive Professor of Finance at Santa Clara University and an Adjunct Professor of Economics at the University of California, where he teaches investment theory, corporate finance, and applied portfolio management.� He is also the founding and current Director of the Santa Clara Initiative for Financial Innovation & Risk Management (SCIFIRM); and serves as a Board Member of the University of California's School of Management in Silicon Valley, the Arditti Center for Risk Management in Chicago, and the Santa Cruz Center for International Economics.
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As a recognized expert in the fields of portfolio theory and risk budgeting, Mr. Sury is a frequently invited speaker at various prominent venues, including for the CFA Institute, Financial Research Associates, FinanceIQ, Opal's Wealth Management Summits, Private Banking India (Chair), and the University of Chicago.� His research on the optimal integration of traditional and alternative (hedge fund) investments is featured in the highly anticipated anthology, "Essential Readings in Advanced Financial Economics."
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Under Mr. Sury's leadership, Chicago-based S4 Capital became the #1 ranked US wealth management firm in both 2007 and 2006, according to Wealth Manager Magazine, a "Top 10" Financial Advisory firm in 2006, according to Financial Advisor Magazine, and was the #2 ranked US wealth management firm in 2005, according to the Bloomberg Wealth Manager Survey.� Over the years, S4 Capital's R&D arm, comprised of researchers with Ph.D.'s and other advanced degrees, developed state-of-the-art techniques and strategies for client-optimized portfolio management.
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Prior to the formation of CACM and S4, Mr. Sury was an appointed Vice President at Goldman, Sachs & Co., where he built one of the fastest growing teams in the Midwest and advised a niche group of ultra-wealthy clients representing several billion dollars in investment assets spanning equities, fixed income, and alternative investments.� During his tenure, Mr. Sury also taught several classes of incoming Goldman Sachs Financial Analysts on topics ranging from portfolio analysis to accounting.
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Mr. Sury had previously served in special advisory and enforcement capacities for both Federal/local government agencies and also held highly technical oriented positions with International Business Machines Corp. (IBM), Lockheed Missiles & Space Co. (C3I & SSD), and the MCC R&D Consortium.� For his achievements in these roles, he has been highlighted in the media and awarded a variety of honors, among them the prestigious IBM Austin Excellence Award, Lockheed's Space Systems Division Commendation, and the SCC District Attorney's Letter (for Service in the Economic Crimes Unit).�
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Mr. Sury received his MBA (High Honors) in Finance & Statistics from the University of Chicago, Graduate School of Business.� He received his undergraduate degree in Economics (High Honors and Phi Beta Kappa) from the University of California, where he also held teaching assistantships in Macroeconomic Theory & Statistical Analysis.� In 2003, Mr. Sury was featured in Crain's Chicago Business "40 Under 40: Chicago's Rising Stars," for his professional accomplishments.
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On a personal note, Mr. Sury enjoys giving back to the community, through such efforts as Junior Achievement, Habitat for Humanity, and the Starlight Children's Foundation.� He has also served on the Board of Directors of the MRIC/Children's Memorial Hospital, and the GSB CEO Roundtable.� Based in part on his experience in law enforcement (criminal investigation), he currently serves on the Santa Clara Co. Sheriff's Advisory Board and the Executive Committee of the San Jose Police Officer Association's Charitable Foundation.
Orignal From: "Efficient Portfolio Management": A Guide To Effective Investment Supervision Processes
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