The Remarkable Story of Risk

by | Oct 14, 2014 | Reading for Results

Against the Odds: The Remarkable Story of Risk

by Peter L. Bernstein


“Likeness to Truth is not the same as Truth”

I found the historical breadth and depth of this work remarkable as the title suggests. Bernstein takes us on an interesting evolutionary path of theory and attitudes toward risk. From the Dark Ages when it was assumed that accepting a risky fate by whim of the gods was a fact of life; to the modern movement which seeks to master risk by measuring it and weighing its consequences. Bernstein delves into the theoretical intricacies and beyond to focus on the practical: how does history help us to understand risk? How can we make the best choices with what we know today about a future that is unknown? Are the tools we use to measure risk appropriate to the task?

The serious study of risk began with the Renaissance movement in 1654. Forecasting methods were forever changed. The varied perspectives of mathematicians, statisticians, social scientists, gamblers, and investors represents an eclectic mix, and underscores the contrasting views amongst pure theoreticians, ideologues, academics, and the pragmatic all who seek to quantify and measure this thing called risk. Today, two schools have emerged:
1. the Rational school of thought, and
2. the Behavioral school of thought.

Rational thought works fine in the natural science world where data tends to follow a normal distribution curve – which means that it allows for predictability that very rarely deviates by extremes. This rational school of thought was introduced to finance by Harry Markowitz in 1952, and so was born Modern Portfolio Theory (MPT). MPT underpins much of modern finance and is accepted dogma by many academics and finance practitioners. However, a look at the assumptions underlying MPT requires a hearty “suspension of disbelief” from what we know takes place in the market.

MPT Assumptions

• Asset returns are normally distributed random variables
• Investors attempt to maximize economic market returns (not necessarily)
• Investors are rational and avoid risk when possible (mostly)
• Investors all have access to the same sources of information for investment decisions
• Investors share similar views on expected returns
• Taxes and brokerage commissions are not considered
• Investors are not large enough players in the market to influence the price
• Investors have unlimited access to borrow (and lend) money at the risk free rate.

Markowitz’ mean/variance framework, in laymen’s terms, means how much return can I get on average, and what type of variation can I expect in that return. The so-called “efficient frontier” looks for a combination of assets that will generate the best return at the lowest risk. Mean/variance borrows from an engineering concept that seeks maximum output relative to my input. This framework works well in financial engineering, neural networks, genetic algorithms, and gambling, but does not apply so neatly to financial markets. As we have witnessed, human emotions can create self-fulfilling, often irrational prophecies, bubbles or busts.

Extrapolating historic averages to plot a nice, symmetric bell-shaped curve may fit natural science in highly predictable fashion; however, with respect to social science (like markets) the ‘likeness to a bell-curve is not a bell-curve.’ Bernstein and others note that theory ideologues, who simply assume history will repeat the past, are dangerous to your financial health and wealth. Rare events, or outliers, at the extremes can destroy a lifetime of wealth accumulation. Relying on stock market averages does not tell the whole story.

“With your head in the oven, and feet in the freezer – on average you are statistically comfortable.”

The Only Constant is Change

In contrast to the rationalists, Freud and the behaviorists note that social phenomenon and the complexity of human motivation presents inconsistency, myopia, and situational dependent circumstances. Welcome to financial markets, where the orderly and symmetrical bell curve and its normal distribution of outcomes is a fallacy. How can we quantify emotions and herd thinking that impact stock market movements at the extremes? As noted above, these outliers are larger and more frequent than averages, probability, and normal distributions tell us they should be. The ivory tower statistical view from MIT is a lot neater than the real world where “gut rules measurement.” What should be is not what is.

Rationalists hold to the belief that diversification is a free lunch. Diversification does help; that is, if you can find low correlated assets. Research done by Rob Arnott showed that in 2008-09, sixteen asset classes headed south at the same time (when diversification benefits were needed most, they failed). This had never happened before in capital markets. What happens when correlation across asset classes increase as they have for the past 15 years? Is this a mean reversion waiting to ‘return to normal’, or do we have a new average emerging? How and when do we make portfolio adjustments?

Bernstein dissects the flawed assumptions that are used to measure risk in the financial industry. Many adviser and broker presentations portray time series with a numeric certainty that does not exist, and scarcely mention the potential for downside risk. Objectivity and rigorous analysis are not selling points in the business of investing.

Bernstein cuts to the heart of the matter. For rational theory and its Bell Curve to work as intended two things are required:

1) Sample data that is independent, and
2) A large number set

Natural science data are based on independent outcomes where one event is not connected to the other: in rolling the dice, the die has no memory; one roll is not dependent on the other; weather patterns likewise are independent of each other. Human psychology, on the other hand, is not always in sync with rational theory assumptions: different risk appetites, information flow, personal experience and circumstance – have memories and emotions and can create a herd effect in a short time. One panic sale creates another and so on.

Can the two schools co-exist to build a more robust framework to help us manage risk? Bernstein doesn’t deliver a clear answer. That isn’t surprising because there isn’t a ‘free lunch.’ But if you are in the profession of trying to manage uncertainty, or more importantly minimize damage, what is there to do? The Soviets tried to plan uncertainty out of existence, and we know how that turned out. Bernstein offers some last gasps of air: more active management, options, and insurance. All of which are ways that one can reduce downside, but they also add cost and complexity into the equation and the need to assess the cost-benefit tradeoffs: lower return, lower risk, and/or unintended consequences. Sounds like extra activity that carries dubious merit.

MPT provides a structure that is a useful beginning point because it provides a practitioner like me a means to evaluate the needs of a client. Useful, but not precise. Bernstein notes that a multi-dimensional view of risk is needed. Risk management needs to maximize areas where we have some control and minimize the areas where we have no control. This is where the adviser can add value by candidly reviewing the different asset classes and their attendant risks and matching them with your financial state and your future goals. This much we can control. Risk is not a predestined fate but is a series of choices that need to be consistently managed within the framework of your values and your objectives.


Jerry Matecun helps business owners and individuals with key planning and investment considerations vital to build and protect business value and personal assets.  For a no cost, confidential conversation regarding your situation, please call or email Jerry at 949-273-4200, 616-499-2000 or

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