Summary of Policy Recommendations from Ron Paul and Peter Schiff
Schiff gets it
How is concern for quality different from concern for validity in conventional social science?
Conventional science, and by extension, conventional social science ,are concerned with reproducability, validity and objectivity. As such, principles of rigor and falsifiability are important components of any research, which come from a 3d person point of view, where the researcher remains outside of the system under study. This can be considered an objectivist approach to the ontological question. By this I mean a belief in an objective reality, which is knowable, and in which knowledge is discovered through a rigorous process of proposing hypotheses, testing them under controlled conditions with carefully constructed instruments, which generate reproducable results and from which conclusions may be deduced or inferred with degrees of confidence that come from the quality and form of the data. Sir Karl Popper’s work on falsifiability and the growth of scientific knowledge through trial and error is fundamental here.
A problem with this approach has been the requirement to scope problems so that variables and environments may be controlled, and cause and effect relationships estanlished. Complex problems and especially those involving human social networks present problems of computability, uncertainty, non-falsifiability and irreproduceability that may not be solvable using conventional means. In addition, the value that social science places on neutrality will offend our sensibility concerning what it means to be human.
My sense is that AR intentionally relinquishes the premises of objectivity and value neutrality and a 3d person perspective in the formal sense, and seeks quality instead, based on values of simultaneous 1st, 2d and 3d person engagement, social justice and democracy, and using methods that embrace subjectivity with full acknowledgement of the power as well as the limitations of that approach.
Quality, as a value, implies a set of priorities and value judgments about social conditions, and furthermore posits action as a legitimate end, even when outcomes are not foreseen at the start of a project. The iterative natire of AR and the possibility of reframing goals, purposes, methods and outcomes seems like a natural consequence of this different orientation.
Kuhn’s work on paradigms and the methods of objective science oin The Structure of Scientific Revolution critically examines the sociological phenomenon of the artifact of science. Kuhn’s treatment of the argument is criticized for his fuzzy use of language,and he forthrightly acknowledges legitmate concerns with the shortcomings of language in the postscript to his second edition. nevertheless his main arguments about the limits of scientific inquiry, and the social construction of scientific knowledge remain important and informative of this debate.
It’s not my sense that AR practitioners are arguing for a replacement of Validity with Quality in all areas of science, but rather that with a desire to get on with improving lives and environments they propose a rigorous methodology that seeks to add to the body of practical knowledge in human affairs, informed by and informing more conventioal scientific knowledge.
Kuhn, T. (1970). The structure of scientific revolutions (2d edition). Chicago. The University of Chicago Press.
Popper. K.(1989), Conjectures and refutation: The growth of scientific knowledge (5th ed.) New York. Routledge Press.
The purpose of this article is to review some of the highlights of systems thinking. My focus will be on practical applications and rules of thumb, rather than trying to develop a scholarly article which would only be of interest to … well, scholars! I will make every effort to do you no intellectual harm, and leave you with an appreciation for what systems and systems thinking are all about.
My background in systems management dates to 1991 when I began my graduate studies in the University of Southern California’s Systems management program, which had developed in the 60’s as a way to respond to the difficulties in managing large manufacturing programs which required managers and engineers from many different disciplines to coordinate their efforts to create complex weapons systems like the Polaris class submarine and B-1 bomber. These projects were so complex that no one discipline knew how to go about building one, nor how to many a diverse project team encompassing and managing finance, weapons, propulsion, safety, automation, materials, electronics, and human factors. Computers only seemed to complicate matters. No one knew how to get the projects done on time and under budget, or how to handle the myriad changes and learning moments that inevitably arose in a long complex project.
It also turned out that the senior leader’s background had an undue influence on the outcome of the project, with weapons engineers building big guns with little to no living space for the crew, while an accountant would bring the project in under budget but without the capabilities sought in the original specification.
Tackling this problem, USC and the government developed a program that developed managers with the skills to act as the middlemen between disparate work groups. They developed managers who looked to develop optimal end-products by integrating the efforts of the different disciplines. The program quickly adapted much if the learning about systems that was simultaneously emerging from both the natural sciences, anthropology and physics.
Systems thinking as an approach to problem solving manifests in many different fields these days. Hard systems include mechanical and automation systems that are often modeled in simulations to examine complex interactions and the dynamics of change. Soft systems include complex social organizations and can include many qualitative components that are not easily modeled with cause and effect rules and linear relationships. Evolutionary systems are thought of as complex open systems which have the capacity of learning, adapting and changing over time in response to interactions with and feedback from other systems and the environment.
In general, systems are usually defined as a complex and dynamic whole, which acts as an organized entity for a purpose, and which needs all of its elements to function.
Regardless of the domain however, there seem to be general considerations and implications from systems thinking with broad applicability. Here are a few:
1. Systems are more than the sum of their parts, and include the relationships and interactions that are possible and which can combine in many unforeseen ways to produce surprising results.
2. Complex behaviors and outcomes will often emerge from the interactions of a few simple elements and processes in ways that were not predictable.
3. Systems thinking almost always incorporates the building of a model or a description of the system under study, during which opportunities for learning and insight and communication emerges to the amazement of participants who come from different points of view. In fact, this learning moment can be the paradigm shift that enables breakthrough thinking with lasting consequences.
4. The best modeling efforts seem to be iterative, interactive, and integrative. The group spirals around the issue or the system in multiple loops, coming back to add details and insights that emerged in the group’s travels around the systems boundaries and through its depths. There is learning and feedback between participants and the model and that we learn as we go. Finally, points of view are incorporated
5. A useful model for systems building treats the system as a collection of inputs-processes-outputs that co-exist for a purpose and in an environment that has both direct and indirect effects on the system and which will provide feedback in different ways to the systems actions.
6. A systems can be seen as sub-system of a larger system, and is itself composed of smaller systems. For this reason, it is usually important to specify scope and time constraints as boundaries lest the effort never get out of the definition phase!
7. Feedback loops and mechanisms turn out to be crucial to understanding processes of adaption and growth and for understanding the phenomenon of 2d and 3d order effects.
8. Friction, timelags, resistance and non-linear relationships are generally found in all complex systems which helps to explain and understand situations where simple cause and effect rules don’t seem to work well.
In practical terms, in my roles as a trader, an educator, a manager and leader of large organizations, or as a member of a work team, I have seen the systems thinking approach provide a way to get started with the process of understanding, visualizing, describing and directing efforts to achieve our goals in complex, uncertain environments. It is an effective way to engage with complexity, when simple rational analysis proves to be inadequate for the job at hand. But beware! As my professor Dr Jones (lead engineer in the B-1 bomber program) often said: “Once you start down the path of systems thinking, you will never be satisfied with simple answers again.”
With these thoughts in mind, what can a trader do with systems thinking? Where would one begin? Here are 5 things to consider:
1. Start with a systems map of your own trading process. Identify those Inputs-Processes-Outputs that are directly involved in your strategy. Then identify those environmental elements beyond your control that have the greatest impact on your performance. This formal systems definition process is sure to help you focus on those areas you can control or change directly and those that you must endure, and is a great basecamp in your journey of self mastery and trading excellence.
2. Engage with a master mind group to help you examine the assumptions and implications of your beliefs and procedures. Adding new perspectives and points of view will reveal blind spots and insights that you might never find on your own.
3. Look for the feedback loops from the trades you take and the trades you pass on in order to examine what is being learned and what else might be learned through self examination.
4. Look for dynamic relationships in your trading that may not have direct causal effects, but rather look for connections that bring your actions home to roost. Try to imagine ow 2d and 3d order effects can arise from chain of events triggered by your trading decisions.
5. Look for ways that your system can learn and evolve and grow in your chosen environment. Seek for ways you can adapt your systems to new environments.
When you find yourself in conditions of chaos, you discover that your robust systems are beginning to break down. They no longer perform as designed, simply because the volatility is greater than the system boundaries and feedback mechanisms can account for or moderate.
Slack, buffers, filters and boundaries all work to dampen waves of change. When volatiltiy gets to extremes then these mechanisms fail and further, begin to degrade. They lose the ability to modulate the waves of change. The outrigger on a Polynesian canoe acts as a drag and provides stability at the cost of friction. This allows the boat to navigate the waves successfully. When waves get too large for the outrigger, the boat founders and capsizes. The system didn’t change, but you crossed the environmental boundary of the system.
Trading systems are like that. You have to have a sense of what the range of acceptable environments are for the system to perform as designed. As a rule of thumb you could treat a moving average of equity as a bottom line inicator of favorable environment.
When facing periods of chaos (here defined as moments of extreme volatility) you have to change your time horizon in one of 2 directions to continue to trade with some degree of confidence. You either shorten your time period and look for tradeable patterns that you can manage or you lengthen your time period. The second strategy is a belief that after a period of chaos, the previous conditions of normal will reassert themselves and your previous set of systems will still perform to standard.
The only problem with that idea is that its an act of faith that cannot be relied upon. If you make that decision, make sure you take responsibility for your faith. I am unwilling to do that since I am currently finding tradable patterns in the shorter time frames. You can always stand aside too until such time as your paper trading systems have an equity curve that is returning to normal. That’s not a bad idea.
Based on our market classification scheme, there are 9 market states derived from 3 price momentum measures combined with 3 volatility measures. There is an important phenomenon related to the Bull-Sideways-Bear market states that can give you both insight into current conditions as well as a decisive market edge in risk management. The edge comes from observing and understanding the correllation in returns from geographical regions of the world with respect to US market returns.
Correllation is a basic statistic that examines the degree to which 2 streams of returns (in this case) move in tandem. At high levels of correllation and with a hypothesis in support, we may begin to look for cause and effect, but for our purposes simple correllation is sufficient for insight into favorable trading conditions.
When the world market is in Bull conditions, and the sun is shining, it is normal to find correllations diminishing, with some regions of the world achieving much higher than normal rates of return. Simply based on the size of the US market it is usual to find different parts of the world leaving the US behind.
As we have seen lately though, when things turn south, correllations quickly converge and the whole world starts going south together. It is normal in these conditions for a flight to quality to occur and money seeks out the relative safety of the mature companies of the US. This sets up perfect conditions for a pair trade that goes long the US markets and short the rest of the worls, which can either be the mature economies of Europe and Asia (represented by ETF symbol EFA) or emerging market (represented by symbol EEM).
This strategy essentially will eliminate market direction and allow you to benefit from the persistent relative strength between regions of the world. This strategy allowed for you to benefit tremendously from the current market volatility, and it repeats itself with surprising regularity over long time periods.
COL John Boyd , USAF was a national treasure. One of the most gifted and effective fighter pilots of all time, he went on to revolutionize the way the armed services thought about command, control and combat effectiveness on the modern chaotic battlefield. He was instrumental in reforming the process by which the Department of Defense designed and procured platforms for all services. The intellectual and visceral contribution he made to the art of war for which he is most often remembered is the “OODA Loop”, and the implications of this theory have reached every corner of our current military doctrine. I believe the insights he developed for fighter combat, and the doctrine of warfighting have an even broader applicability to the world of business and specifically to the art and science of trading. There is already quite a cottage industry that adapts his insights to the business world. I want to briefly examine a few of his ideas and their implications for traders.
Briefly, the OODA Loop is an acronym that stands for “Observe-Orient-Decide-Act”. In his now famous diagram of this iterative feedback process, Boyd describes a “decision cycle”, a process set in motion by the recognition of a meaningful input (observe) that triggers the selection of a mental model or mindset appropriate for processing this input (orientation). The mental model and thought process generate a decision to act that steers you to a more desirable state (decide), and then this decision is put into action (Act). There is nothing particularly novel about this sequence; it is intuitively compelling and natural. Boyd’s genius lays in his examination of the many avenues of feedback between each of these steps, and the implications for improving the cycle time to get from observation into action.
There may not be a combat environment that requires more precision, split- second timing, and effective decision- making than fighter to fighter combat, where the consequences of failure are so catastrophic and the margin for error so slim. This laboratory of human decision making under stress was where Boyd forged the insights that make the OODA loop a powerful combat multiplier in the air. Its applicability to all forms of competitive interaction make his story and insights so compelling. His story is well told in Boyd: The Fighter Pilot Who Changed the Art of War by Robert Coram.
Why do you care? You might find his insights make you a better trader. Here are a few direct applications of his insights for traders.
- Orientation drives the train or “Believing is seeing”: Boyd described orientation as the integrated whole of our personal analysis and synthesis of our experience, culture, new information, and genetic heritage. In other words, it’s our paradigm, or the paradigm we are currently using if we have more than one to choose from. It’s the context you use to frame a problem, which identifies the values you will use to evaluate courses of action, and provides the foundations of your motivation to act and compete. It feeds forward all of these elements into the Decision loop, but perhaps even more importantly it establishes the framework and sensory apparatus to seek the new observations that will trigger a new decision cycle. Your world view, your mental model, and your paradigm act as a filter for you to sense the world and to make sense of the input you can gather. These beliefs operate at the unconscious level to define what is knowable and what is observable. These paradigms have evolved because they are generally a very effective way of organizing a chaotic world into a manageable entity that permits planning, goal setting and achieving. It describes our sense of cause and effect. The pervasiveness of paradigms are such that when we experience things outside of that paradox, it can seem like the world has just come apart and we are stunned by the unexpected, the unforeseen. It’s the experience that makes you say in surprise “Man! I never saw that coming”. This line of reasoning suggests that we are well- served by examining our paradigms, assumptions and beliefs with care and attention, to define environments in which a given paradigm is likely to be effective, and the boundary conditions that define the limits of its utility. Some of Van Tharp’s most powerful teachings are precisely in this area of paradigms and beliefs.
- Construct your dashboard wisely: Using an older simpler and performance- inferior aircraft, Boyd routinely out-flew hot shot fighter jocks piloting the Air Force’s most sophisticated fighters, because he was able to apply the advantage of simplicity. He flew the aircraft as an extension of his own body and will. He had internalized to an instinctive and personal level the capabilities and limitations of his jet, and its simple, barebones dashboard layout supported rapid observation. His opponents struggled consciously to make sense of the complicated instrument panels before them that flooded them with too much information, which made them take their eyes off of Boyd while they tried to figure out what was going on. It was in that moment of sensory overload that they would routinely discover Boyd on their tail in the dominant, decisive position. We should remember the differences between need to know and nice to know, and that newer isn’t better; better is better. As a trader, I must give careful consideration to the amount, the format and timing of my information feeds to ensure they are supporting my decision making and not getting in the way.
- Perfect practice makes perfect: Boyd embodied the warrior spirit and spent his life in pursuit of refining his approach to and his understanding of air-to-air tactics. He invented impossible maneuvers, and refined their execution with physical models, computer models and actual practice. He over-trained his critical skills so that in the moment of decision there would be no hesitation and he could execute maneuvers on a dime. This insight pertains to both orientation (warrior spirit or trading identity) and decision. The payoff was performance to a high standard in the shortest possible time.
- Operate inside your opponents decision cycle: This is often interpreted as simply acting more quickly, but Boyd’s insight was to add in the factor of doing the unexpected. The unexpected is what creates confusion in your opponents mind and causes them to slow down or stop to figure out what is wrong with their paradigm. When you multiply reduced decision cycle time AND doing the unexpected, you get tremendous payoffs. As a trader, you have to recognize that if you do what everyone else does, you will get what everyone else gets. And if your execution time is slow because of equipment limitations you are unnecessarily harming your performance, and if you are waiting to get too much redundant confirmation of your signals, you may be missing the opportunity in your search for certainty. Finally, this insight suggests that by looking at the market in new and different ways, you have the possibility of uncovering unique insights and fresh opportunities to get better than average results.
- Always wear a parachute and know the location of the ejection lever: When you are operating in a risk filled environment, where consequences of failure have serious implications, it’s important to know when to eject, and have the opportunity to live to trade again. Honor your stops and know the limitations as well as the capabilities of your system (which includes you). Know your envelope of performance!
Ison, R. (2008). Systems Thinking and Practice for Action Research. In P. Reason & H. Bradbury (Eds.), The SAGE Handbook of Action Research: Participative Inquiry and Practice (Second ed.). London: Sage Publications., Ltd.
My masters work is in systems management, and Ison’s work struck a chord with me as well. His mind map of the systems thinking domains is basically a road map of my practical intellectual travels since 1991. I have been reading and practicing in many of those domains he outlines, and the relationships and groupings he maps look like the wiring diagram inside my own skull.
As a systems thinker, my value add to the Army for the last 15 years has been as a problem-finding and problem-solving integrator, bringing together different domains on various projects related to Army change management. I have had training and applied it in the mapped areas of human performance engineering, operations research, soft and hard systems, total quality, statistical process control, lean 6 sigma and systems dynamics.
My current research area is educating leaders for uncertainty and complexity, but it’s actually a little more than that. I am attaching a short slide presentation on a model that stretches along the continuum of Simplicity<->Complicated<->Complexity<->Chaos<->Randomness. Each state seems to have distinct conditions, requirements, values, success strategies, and process. The world seems to shift dynamically, but not quite randomly between these states, and the boundary conditions appear to be fuzzy and the states are not mutually exclusive. Each state has a different set of cognitive, emotional, and conciousness related skills, which means our leaders need to be able to sense, adapt and respond mindfully. Rendering these notions into deliverable curriculum is my research area.
Ison’s work is directly related to my inquiry, and I have come across other works of his before and found him to be an excellent resource. He has a terrific blog and website and I will be sending him a note to see if I can get his take on where Complex Adaptive Systems, emergence, chaos might be arrayed on his mindmap. Weick’s ideas on High Reliability Organizations, and the work of Kahneman, Tversky and Gigerenzer on bounded rationality and cognitive heuristics and biases needs to be integrated as well.
I seem to be heading towards blending the content that includes Checkland’s soft systems methodologies (as a synthesis of best practices of dynamic human systems), systems dynamics for leaders, and Schon’s methods of educating reflective practitioners as the basis of developing education strategies for the 21st century. Action research to get stakeholder participation in content selection and educational environment construction seems to be a natural fit.