Tail Docking Guideline Genetic:
In particular, they need investment strategies to meet their long-term obligations, but current risk communications, behaviors, and measurements can interfere. FCLTGlobal, with its Members, is developing practical tools to address the issue of balancing long- and short-term risks.
Part of the process includes interviews with experts in the area of assessing, managing, and planning for investment risk. Below is the first in a series of discussions, featuring Dr.
Thank you for participating in this discussion. To what extent does the way that an organization measures risk affect its ability to fulfill its purpose and think in the long term? We use this language to imply more knowledge than we actually have.
We really just estimate risk, and the critical thing is figuring out the limits of our knowledge. Since the Enlightenment in the 18th century, The long tail phenomenon have increasingly convinced ourselves that in principle everything is knowable, if only we can get enough data, but that is incorrect in many relevant situations.
Clearly some things in the future can be extrapolated from the past, but many cannot. Do you have the ability to distinguish between the two? Telling the two apart is important because different categories of risk need different management approaches.
One category of risk is extrapolated from the past and can be reasonably estimated based on historic data, the other category not, as that is where the black swans live or fat tails for the more mathematically inclined. Fundamentally this category corresponds to things that elude direct prediction.
It does not mean you cannot manage those risks, but there is a different set of tools for them. Could you explain what these alternate ways of managing risk are? Complex systems, such as for example stock markets, are characterized by so-called fat-tailed distributions, which basically means that there are extreme events that occur only rarely.
These very large events are more relevant in a long-term view, although they could happen at any time. For fat-tailed distributions, investors need to evaluate the resilience of the system as a risk management approach.
In statistical terms, the potential outcomes within these systems are uncertain — their probability is not defined. Managing the resilience of a system does not pretend to anticipate the future.
Another technique is scenario planning, which started developing in the s to help deal with unknowable and unmeasurable risks.
New tools were developed to shape the strategic conversation about uncertainty. For example Shell has sustained this approach for more than half a century, refining and adapting its approach with the times.
What do you wish the trustees of long-term investment organizations knew about the way that risk is estimated for them?
I think it is understanding the difference between those two categories of risk. Some systems have normalized distributions and others not. You need to understand the difference between the two and demand that management treats them accordingly. The triage is not that hard to do.
The bigger danger is trying to force fit the non-normalized risk.
A journalist asked John Browne at the time when he led BP whether the firm was a complex or complicated business. He thought about this and was silent for a while, eventually responding that the oil business is a complicated but not a complex business. The core business is exploration following well-understood risk patterns, managing largely independent assets and selling into a liquid market.
The implication is that it could be managed more or less top-down, considering normal risk distributions. The point is that the trustees should be able to ask these kinds of questions and the managers should be able to answer them.
Do investors need to use these different tools simultaneously, or is it possible to know when one applies more than the other? My recommendation is to use them in parallel.
To be very practical, if you are scheduling your risk management meeting, have one hour on normalized risks and one hour on non-normalized risks. The bigger danger is trying to force fit one into the other. A few years ago in collaboration with Swiss Re, I developed and tested such tools with risk managers.
These are available for use.Another expression used to refer to this phenomenon is the “long tail”—derived from the fact that when the sales of a company's many products are plotted along an axis they come to look like. Aug 22, · The Long Tail is a potential market and, as the examples illustrate, the distribution and sales channel opportunities created by the Internet often enable businesses to tap into that market successfully.
The long tail is the name for a long-known feature of some statistical distributions (such as Zipf, power laws, Pareto distributions and general Lévy distributions).In "long-tailed" distributions a high-frequency or high-amplitude population is followed by a low-frequency or low-amplitude population which gradually "tails off" asymptotically.
the literature for the tail phenomenon associated with slowly-decaying scattering potentials – long-range poten- tials that approach zero asymptotically (x→ ∞) slower. The "long tail" is a phenomenon related to the rate of Internet news readership. During the era of objective journalism, the commitment of newspapers to two-sided news reporting.
Jan 22, · Financial models with long-tailed distributions and volatility clustering Financial models with long-tailed distributions and volatility clustering have been introduced to overcome problems with.