Correlations, volatilities and expected returns as the monetary tide reverses flow..

I note comments by El-Erian over Central Bank’s inability to suppress volatility as a bigger risk than China and I would agree although I would qualify this in terms of the immediate asset price risk.   Asset focussed money supply growth and asset price relatives (relative to GDP growth and income growth as well as its distribution) are all deeply negative for asset markets when liquidity dynamics, amongst others, change.

Recent commentary by Zero Hedge on the winding up of Nevsky Capital is also worth reading: the Nevsky Capital report suggested that a disciplined structure can no longer be counted on to realistically manage risk and return given the uncertainty of an increasingly skewed distribution of possible outcomes in an environment worryingly distanced from fundamentals/exposed to unconventional monetary policy; liquidity dynamics in the market place also impacted.  

Another interesting piece of data shows the 10 year rolling returns on commodities that I found in a tweet from @zatapatique.

I have written on the issues of excess asset focused money supply and liquidity for some time (relevant posts of mine).

Many portfolio management structures depend on expected return/correlation/standard deviation assumptions that would be very much exposed to a break in the direction of money flows towards assets.  All statistical measures of risk and co variance are drawn from the impact of monetary demand flows for assets.  In an environment where monetary policy is accentuating flows to asset classes as well as expanding the quantity of money and reducing the supply of certain asset classes the natural flow response to risk and return in the environment are muted.  As unconventional monetary policy recedes, additions to the quantity of asset focussed money and interest rate support reverses, the natural flows not only start to reassert but the prior excess flows adjust to the new environment.  We get a break out of trading ranges and covariances.

This is all incredibly risk and uncertain for those dependent on traditional statistical measures of asset price sensitivities and covariances.

My submission to the CSA re Risk Classification disclosure

Re: CSA Notice 81-324 and Request for Comment – Proposed CSA Mutual Fund Risk Classification Methodology for Use in Fund Facts

The part must relate to the whole and the whole to the part and the both must know of it:

The CSA in their consultation paper fail to explain how the risk classification methodology proposed for use in the point of sale documents is to be used by investors to make informed decisions, and how advisors are to use the same to determine suitability.

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What is investment risk?

“What is investment risk” is both simple and complex and in order to assess the information needed to assess risk we first of all need to qualify the world view of risk and return and then the model we are using to manage the risks and their impact. All this is beyond the subject matter expertise of the individual investor and why point of sale documentation can only ever inform about the broad nature of risk and return but never be sufficient to allow the investor to fully own the decision. Ownership of the transaction decision resides with ownership of the process and the significance of risk assumed with respect to risk via structure, assumptions and costs.

At a very basic level, risk is what happens to a price between two points in time and the impact of that movement in price – it can be both positive and negative.  But what gives rise to risk is more important than a mere list of risk factors, or indeed a narrow quantitative measure of risk.

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Standard deviation may not tell the whole story but it does tell a story

In terms of risk, a prior positive demand flow (+ve standard deviation) has more impact on liability risk in an out of equilibrium world, so that arguments that suggest that a statistic that fails to focus only on the downside is meaningless are incorrect.

Way back when the world was more enamoured than today about standard deviation I openly discussed its weakness in terms of managing liability risks.  This was primarily to do with the fact that mean variance optimisers did not incorporate liabilities into the portfolio construction (optimisation process) and ignored relative and absolute valuation issues. 

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