Markets react daily to news, but most of the news, in truth, is already baked into the pie.
Daily data points can easily move in ways that are at odds with the overall direction of underlying fundamentals, and, of course, everyone interprets that information differently. Many minds have differing agendas and it is quite often the agenda that defines a data point’s interpretation. Much of risk is therefore driven by irrationality and agenda, and even rationale exploitation of irrational acts.
Reacting daily to new data as if it is independent and random, is much easier than interpreting the data within the overall construct and the construct’s dynamics: in other words assuming that it has dependencies and dynamics that stretch into the past and the future. One requires little processing power, the other not only much greater processing power but also much more information and detailed knowledge of the logical constructs underpinning interrelationships.
Appreciating, understanding and modelling the construct, and the changing dynamics of the construct is what risk management should be about for long term asset liability modelling and management. A large boat’s future trajectory is partly determined by the past and the present, at all points in time, and so it is with an economy, and because of this, a market and a market’s prices.
Some feel that they can react, or predict the data points, because if you want to beat the market at all points in time, then you need to predict with reasonable accuracy the variation of the distribution of data points around the fundamental trend direction and the market`s reaction to those data points.
Assessing the fundamental risks to return and the fundamental direction of return is a much more constrained process, and not one which you can trade around, but it is one which I feel asset/liability portfolio managers need to be focussed on. The past and the present (the structure and their reverberating dynamics) weigh heavily on the future, and especially so on the near future. The greater the imbalances, the further out the near future and the more dependent the near future outcome on the past and present dynamics.
And so, while we need to analyse data, we need to analyse it within a context that relates it to the past and the present dynamics as well as perceptible marginal developing dynamics (change and the future). When markets and economies are structurally imbalanced, to extremes, the past and the present more greatly impact the direction of the fundamentals, and hence risks and returns.
Portfolio management, at least on the private client side, is still insufficiently focussed on fundamental risk management, and I am not talking about complex derivatives, expensive options management, or a rigid inflexible product, but a simple yet comprehensive construct that incorporates the fundamental risk/return paradigm into structure, planning and management. I know many may say that the events of the last decade or more were incapable of being forecast, but I would disagree and argue that the asset price and economic risks were clear as they were built up, and this clarity should have been brought into portfolio risk/return modelling, and hence structure and management.
The high fees and costs of portfolio management in a low return, high risk environment represent one aspect of the failure of the financial services industry to manage fundamental risk: these high costs are a) the product in many instances of barriers to competition and innovation, and b) the failure to institute systems and processes that can manage the complexity of constructing, planning and managing the complex interactions of the client needs and assets, risk preferences and market and economic dynamics.
There are many who have covered one element of the equation, through the use of low cost indexed investments, but who a) still charge relatively high service costs that mitigate the benefits of the lower cost asset allocation vehicles and b) have rudimentary and insufficient risk management systems in place to construct plan and manage the relationship between assets and liabilities over time in varying risk/return environments.
We have portfolio constructs that can manage risk and return in a general equilibrium model, where data points are random and independent, but not an accepted construct that can manage out of equilibrium risks and the relationships between these risks, portfolio structure and time.
Risk management needs to be proactive both in terms of structure and in terms of risk and return assumptions that cover the dynamic structural economic and market risks. Change, or what we call uncertainty around the outcome for a given paradigm is what the structure adjusts to over time, positively in the case of a better outcome, and negatively in terms of a worse outcome. But because risk management should be focussed on the downside risks, adjustments to better than expected should be the more probable outcome, in the sense that that risk management should be exposed to positive surprises as opposed to negative surprises.
Much of today’s risk management has come in the form of expensive and complex products, and/or derivatives that can either be expensive (options) or neutral to positive surprises (futures), that are designed to serve the present as opposed to the future without regard a) for the impact of cost on ALM outcome and b) for the simpler and cost effective structural solution.
Structural risk management solutions, those that manage risk by incorporating risk into modelling of risk and return, and by adjusting, at the margin, the allocation of assets given the underlying fundamentals, are cheaper, more robust and long lasting. But this also requires a disproving, dispassionate distance from the daily machinations of the market. Trying to maximise point in time risk and return should not be the objective: focus should be on the structure, and the smoothed longer term outcome predicated on the major and not the marginal risks.
The lack of what I call long term asset liability modelling, that is the analytical process of observing, by modelling, the impact of asset risk and return over time relative to market and economic risks for a given liability profile, is preventing the development of portfolio management within an asset liability context. This dearth of robust risk/return modelling overly focuses risk management on the present data point and on short term product/derivative driven solutions. Too much risk management is based on MPT simplifying assumptions, or rather a certain expected risk, return and correlation, and a certain distribution of all three within uncertainty over the path of the actual risk, return and correlation.
Indeed, part of the financial crisis has been driven by the belief that risks can be hedged and the consequent build up of this risk in the financial sector via the rather lucrative business of selling such such insurance (of course, until a crisis hits). Modern portfolio theory is bunk as far as cost effective risk management, in out of equilibrium situations, over time is concerned.
As I have said before, proper risk management would provide greater stability to asset prices by forcing market participants to more effectively assess the demand/supply dynamics of economic and market relationships. I also think it is difficult to be a rational investor in an out of equilibrium world while believing that prices are random, independent and that market prices not only equate demand and supply but properly price the economic and the market risks. A rational investor would look to manage the risks of an out of equilibrium world, and minimise their dependency on data points and point in time market movements……