The document discusses the evolving landscape of risk management in investing, emphasizing the shift from traditional transparent and straightforward models to more complex, opaque systems. It critiques the 'endowment model' adopted in the 2000s for its failure during market crises, asserting that simplicity, transparency, and proper liquidity are key to effective risk control. Ultimately, it advocates for a return to basic principles of risk management that prioritize understanding portfolio behaviors over reliance on complex quantitative models.

1. Managing risk in e
a complex world
Introduction
The best risk control lies in being able to see an entire portfolio easily and being able to
spot deviations from the expected without difficulty. Transparency should therefore be the
primary method of risk control in most portfolios.
Over the last few decades, fundamental changes in the investment model have lost sight
of this. It has almost become an accepted truth that to be a “sophisticated” institutional
investor in a complex, interactive, tightly coupled and adaptive world, one has to
adopt a complex, interactive, tightly coupled and opportunistic investment model (and
organization). This new approach, which emphasizes non-transparent and illiquid vehicles,
relies on quantitative, detailed models of portfolio characteristics as their primary risk
control devices.
However, a complex investment world does not require a complex response, either in the
nature of the investment organization or the particular investment strategies chosen.
The cockroach lives in a highly complex environment with one of the best long-term success
rates of any creature. Yet it has only one defense mechanism – running in the opposite
direction from a puff of air. The equivalent for the investment world is, at the core, a
very simple structure founded upon public market diversification with one basic defense
mechanism: see a volatile movement, react in the opposite direction (i.e. rebalance into it).
A simple structure and strategy, if adhered to, has one of the best chances of surviving for
many decades.
Club
Views expressed here are those of the
author, who is solely responsible for any
errors and omissions.
Content:
Introduction 1
1. How risk management
changed 2
2. The test of time 3
3. Conclusion 7
Bob Maynard
Chief Investment Officer at
The Public Retirement System of Idaho (PERSI)

2. 2 | The 300 Club | Managing risk in a complex world | October 2014
1. How risk management changed
Investment life in the early 1990s was easy. The guiding conventional investment
philosophy was to have a portfolio that was simple, transparent, and focused: simple, in
relying primarily on the public markets over time and maintaining a consistent presence in
those markets; transparent, in being relatively easy to understand and explain; and focused,
in concentrating extra efforts on a relatively small number of special strategies that would
have material impacts on the portfolio.
The resulting portfolio’s risk control relied primarily on the transparency of the portfolio
as a whole, and the clear nature of the relationship and behavior to its parts, and only
secondarily on extensive quantitative risk models and systems. It avoided investment
approaches that used significant leverage or non-transparent structures.
As a result, passive indexing of a diversified asset type was the basic investment vehicle.
Portfolios could be constructed using mean-variance models under the assumptions of
proportionate return to risk relationships for major asset types and normal randomness.
Linear models (with the concepts of “alpha,” “beta,” and a number of related risk ratios)
could approximate market and portfolio behavior both for purposes of monitoring risk and
as tools to generally predict portfolio behavior.
Because the style or portfolio is very clear and transparent, with daily and independently
priced securities, activity can easily be monitored contemporaneously. Unexpected behavior,
if it occurs, is instantly clear, and explanations for unexpected behavior can be quickly
determined.
This conventional approach came under severe attack in the late 1990s and 2000s because
of the growing disparity between the long-term views of the capital markets and the shorter-term
behavior of those markets.
In the past decade, the conventional approach moved from being in the mainstream of
multi-billion-dollar investment portfolios to an outlier. The investment world moved on
to a new model of investing, often described as the “endowment model.” This places much
less reliance on major public market exposures and, instead, emphasizes intense active
management, illiquid instruments and vehicles, often embraces leverage, and uses many
detailed and often opportunistic investment strategies.
It tears apart the traditional asset-class categories of equity and fixed income in favor of
supposedly underlying factors, such as “real” returns (commodities, Treasury Inflation-
Protected Securities [TIPS], timberland, real estate), inflation/deflation investments,
credit-based returns (high-yield, equity), quality differentiations, and similar categories
to reorganize the investments in the portfolio. It requires that risk be managed actively
through extensive quantitative models and risk-control systems.

3. The 300 Club | Managing risk in a complex world | October 2014 | 3
2. The test of time
The events of 2008-2009 showed that both theoretically and practically, the endowment
model failed its first stress test miserably. Markets are extremely volatile, but there is no
place to hide. Many of the places where the new model took shelter turned out to be
stunningly worse.
In the shorter-term, capital markets are inefficient, but they are even more unpredictable
than assumed by the standard mathematical investment models, and active management
faces even higher hurdles than previously imagined.
Much of the mathematics of the investment world is based on the idea of “normal”
randomness, where returns and actions are based on identical and independent activities
(like coin tossing). In the near term, however, the world is not “normal” and models
based on standard capital market theory, such as linear-regression and mean variance
based on bell-shaped curves, give a false sense of security and can lead to disaster when
pushed to extremes.
In fact, near term capital market moves are better characterized as being like “earthquakes”
rather than “normal random” phenomena. (Charts 1 and 2)
Chart 1: Example seismogram of an earthquake

4. 4 | The 300 Club | Managing risk in a complex world | October 2014
Chart 2: “Earthquakes” in capital markets
10%
Daily Price Movement
8%
6%
4%
2%
0%
-2%
-4%
-6%
-8%
-10%
Jan-02
Apr-02
Jul-02
Oct-02
Jan-03
Apr-03
Jul-03
Oct-03
Jan-04
Apr-04
Daily SP Price Movements
Jul-04
Oct-04
Jan-05
Apr-05
2002-2010
Jul-05
Oct-05
Jan-06
Apr-06
Jul-06
Oct-06
Jan-07
Apr-07
Jul-07
Oct-07
Jan-08
Apr-08
Jul-08
Oct-08
Jan-09
Apr-09
Jul-09
Jan-10
Apr-10
Jul-10
Oct-09
Non-linear (disproportionate) influences are often the major factor in describing market
activity over near-term periods. Actual market returns have therefore been both wilder and
milder, with more extreme “fat tails” (periods of very high volatility) and longer periods
where returns were mildly positive, than standard theory predicts. (Chart 3)
Chart 3: Markets are wilder and milder than “normal”
Number of Days
Daily Dow Jones Returns vs. Expected
October 1928 – December 2010 (3.5 Standard Deviations)
-0.5%
-0.2%
3,041
1,845
0.0%
0.3%
0.5%
0.8%
1.1%
Daily Return (log)
3500
3000
2500
2000
1500
1000
500
0
151
7
-3.9%
-3.7%
-3.4%
-3.1%
Actual Returns
“Normal” Distrubition
-2.9%
-2.6%
-2.3%
-2.1%
-1.8%
-1.6%
-1.3%
-1.0%
-0.8%
1.3%
1.6%
1.9%
2.1%
2.4%
2.6%
2.9%
3.2%
3.4%
3.7%
4.0%
93
4.2%
3
The impact of turbulent, earthquake-like market behavior fades as time horizons lengthen.
Annualised five-year rolling stock returns show a sharp reduction in the occurrences of wild
and mild periods, and exhibit behaviour much more consistent with the linear assumptions
of normal randomness. (Chart 4) Planning portfolios over five to 10 year periods can
therefore generally use the tools based on standard theory much more effectively.

5. The 300 Club | Managing risk in a complex world | October 2014 | 5
Chart 4: Markets are more linear when considered over longer periods
Frequency
Expected vs Actual Frequency of Annual Returns
5 Year Rolling Returns 1871-2008 (log)
-20% -15% -10% -5% 0% 5% 10% 15% 20% 25% 30% 35% 40%
Annual Return (log)
Expected
Actual
30%
25%
20%
15%
10%
5%
0%
30%
25%
20%
15%
10%
5%
0%
During the financial crisis, the different nature of shorter-term markets turned out to offer
only opportunities for pain, not gain, for the endowment model because it is opaque and
non-transparent, relying instead on quantitative risk-control systems and models.
The problem is there are no risk systems that can currently be based on the mathematics of
the non-linear world. Instead, the only usable tools are risk measures that are based on the
assumptions of coin-tossing randomness (such as value at risk, or VaR), linear relationships
(such as regression analysis, factor analysis, and concepts of alpha and beta), and the
successful identification of potential future stresses and strains on the portfolio (scenario
analysis and stress testing). These systems can be badly fooled in a non-linear and turbulent
market structure. Numbers based on daily, monthly, or even quarterly return patterns, and
measurements based on that data (historical or expected), provide little comfort when the
occasional “fat tail” arrives.
And while “fat tails” are relatively rare, they are responsible for a disproportionately large
percentage of a portfolio’s total return. (Chart 5)
Chart 5: “Fat tails” have a disproportionately large impact on returns
9%
8%
7%
6%
5%
4%
3%
2%
1%
0%
5.9%
3.7%
% of Action
Dow Jones Daily Returns 1928-2010
Frequency vs % of Action
Daily Return
3500
3000
2500
2000
1500
1000
500
0
-3.92%
-3.66%
-3.40%
-3.13%
-2.87%
-2.61%
-2.35%
-2.08%
-1.82%
-1.56%
-1.29%
-1.03%
-0.77%
-0.51%
-0.24%
0.02%
0.28%
0.54%
0.81%
1.07%
1.33%
1.59%
1.86%
2.12%
2.38%
2.65%
2.91%
3.17%
3.43%
3.70%
3.96%
4.22%
Frequency
% of Action

6. 6 | The 300 Club | Managing risk in a complex world | October 2014
The influence of these unusual events on near-term portfolio risk management simply
means that linear models and risk systems based on “normal” randomness should be
rejected as the primary tools for close-to-shore navigation. The markets are complex
adaptive systems, and at the moment the mathematics of that discipline are at best
descriptive rather than prescriptive. Like predicting earthquakes, reliable systems for
navigating future market risk are still an aspiration, not a usable tool for major actions.
Therefore, the best risk control in a non-linear world still comes from being able to see,
relatively easily, all the investments in the portfolio, their behaviors, and how they fit
together. This emphasizes simplicity, transparency, and maintaining sufficient liquidity
to survive market disruptions of at least three years.
A conventional approach does not rely on extensive quantitative controls or systems as
the primary bastion to defend against risk. Instead, conventional portfolios rely on the
transparency of the portfolio, daily public and independent pricing of public-market
securities (with the attendant liquidity), managers with clear styles or concentrated
portfolios, and a reasonable number of active manager relationships that can be easily
followed and understood, to protect them from unexpected and unforeseen events.

7. The 300 Club | Managing risk in a complex world | October 2014 | 7
3. Conclusion
The best risk control lies in knowing what you have, what it is worth, and how it is
behaving. The more that detailed quantitative models of portfolio characteristics are needed
to describe a portfolio and its behavior, the greater risk it will incur.
A focus on the long-term, as emphasized by the conventional model of investment, also allows
time to erode the impact of wild and mild periods in markets on portfolios, which increases
the applicability and effectiveness of the tools based on standard investment theory.
Quantitative models are better used as supplementary rather than primary risk-control
devices. As the sign in Einstein’s office supposedly stated: “Not everything that counts can
be counted, and not everything that can be counted counts.”

8. The 300 Club
The 300 Club is a group of leading investment professionals from across
the globe who have joined together to respond to an urgent need to raise
uncomfortable and fundamental questions about the very foundations of
the investment industry and investing. The mission of the 300 Club is to
raise awareness about the potential impact of current market thinking and
behaviours, and to call for immediate action.
Current economic and investment trends will change the investing landscape
over the next two decades and we are at a crisis point which presents huge risks
to investors, according to the 300 Club. Moreover, the 300 Club believes that
current financial and investment theory and practice run the risk of failing
investors at their time of greatest need.
www.the300club.org
Contact us
For further information about the 300 Club, contact our Media Team:
Jean Dumas
+44 (0) 20 7680 2152
jean.dumas@the300club.org
The views and opinions contained herein are individual views held by those of the 300 Club.
The information herein is believed to be reliable but the 300 Club does not warrant its completeness
or accuracy. No responsibility can be accepted for errors of fact or opinion. This material is not
intended to provide and should not be relied on for accounting, legal or tax advice, or investment
recommendations. This document is published solely for informational purposes and is not to be
construed as a solicitation or an offer to buy or sell any securities or related financial instruments.
Although the 300 Club believes that its expectations and the information in this document were
based upon reasonable assumptions at the time when they were made, it can give no assurance that
those expectations will be achieved or that the actual results will be as set out in this document.
The 300 Club undertakes no obligation to publicly update or revise any forward-looking
information or statements.
CM15220 T1128
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