Thursday, 23 March 2017
Last updated 58 min ago
Jun 9 2010 | 1:02pm ET
By Michael D. Billy, Econophy Capital Advisors -- In order to preserve capital and profit from the turbulence generated by the global debt crisis, the application for succeeding has dramatically changed.
Devaluing a currency is an accepted method to countering a country’s debt. The task is daunting under normal economic conditions and the consequences uncertain. But when a myriad of causational factors are wreaking havoc within global markets, how do you adjust your FX or any asset class risk management control(s) to ensure against losses?
In tandem, how do you effectively implement the changeover process in order to avoid creating a counter measure to self-initialized loss?
Given the severity of price movements, the priority is preservation of capital. Even if only a beta achievement is your objective, the revised model has to contain analytics that properly gauge price turbulence. In the current and foreseeable markets, it is a mandatory control, not an option. If system guidance is absent, volatility remains your nemesis.
Old-school applications, such as Statistical Models, Technical Analysis, Time Series, Neural Network, Chaos Theory and High-Frequency Measurements, have limited observance of the price/volatility space. Conventional models aligned to adjusted risks/returns offer skewed predictability outcomes as they are predicated on mean averages and co-variance analysis.
This is a new investment era: remodel and prosper.
The old adage is “What goes around comes around.” We are in an uncharted global environment. Formally adhered to risk-adverse theories no longer embody the refined elements to protect against all of the erosive influences present today. Nor do they contain deterrents for preserving capital when unexpected future events occur.
When countries collaborate to curtail a single country’s debt exposure by infusing $1 trillion, the depth and width of the respective contributor’s debt issues is of such dimensions that individual situations may be incalculable. “Kicking the can down the road,” which is the preferred solution for addressing fiscal irresponsibility, can no longer be the acceptable remedy. Somewhere in global governments, there has to be at least one politico with brass balls? Fat chance!
For decades, governments around the world have doled out unrealistic and unfunded benefits. Today’s crisis, and those that will follow, marks an end to the era of the public sector version of “keeping up with Jones’.” While the wake-up call is current, the damage is perhaps unrecoverable for the longer term.
As any seasoned market participant has learned, uncertainty breeds volatility. Since there is no clarity to account for each country’s debt liabilities, all contributors to Greece’s debt rescue plan may eventually be forced to forthrightly acknowledge the true cost of their unfunded liabilities. These truths may reveal the Greek situation to be the lesser catalyst for more extreme price movements in the future.
Simply stated, volatility is a form of market inefficiency. It is a reaction to incomplete information whereby the trading environment is uncertain.
For decades prior to 2007, excessive volatility was linked to irrational behavior. Underlying factors were a confluence of mass greed, mass fears, and mass disagreement. Ask yourself to what degree do those factors exist in today’s market?
Debt, on a single country basis, has exploded beyond control. On a collective basis, it is beyond masterful containment. Government's greed, and its relative lack of risk mismanagement controls, combined with an inability to foresee economic consequences has reshaped the globe into a chaotic state of economic affairs, whereby individual responsibility has been replaced by an irrational dependency.
As governments ramp-up printing presses to safeguard against greater degrees of implosion, all contributors become suspect to their own devaluation momentum or debasing. No matter the portfolio composite, the trading environment becomes more suspicious as the consequences transition to being more dire and onerous.
Counter measures to uncertainties and negative influences are constructed by applying sophisticated, scientific customization tools and methodologies. The failure of adopting embedded defensive volatility tactics impairs your ability to engage offensive trading mechanisms. While you may benefit from a single-directional trend, restrictions raise the inability to capture parallel movements.
To gain the upper hand, profitable execution requires analytical components that align risk with volatility forecasting mechanisms and supply/demand imbalance analysis. Besides enacting disciplines to rein in the use of leverage, the underlying defensive mechanics, allowing for a more efficient execution, has to address these questions:
Unquestionably, establishing operable risk thresholds is imperative for assessing potential losses and profit potential. By applying customized scientific solution modeling to relationships related to supply and demand imbalances, the optimization of minimizing losses escalates the opportunity for sustainable absolute return outcomes.
Achievable through innovation, success comes when portfolios harness volatility to their benefit. When properly structured and managed, an alpha-type ROI will perpetuate itself.
What are the next generation, quantitatively-based scientific applications, for achieving this level of outcome?
Before answering, it is necessary to acknowledge two counterproductive analyses and/or executions.
Traditionally, risk management techniques are based on analyzing price-volatility interactions among a select group of financial instruments. By assessing co-variance matrices that try to explain these interactions, strategists erroneously use those behaviors as forecasting tools for price movements and quantifying risk.
Secondly, historical price movements, along with historical volatilities, do not possess the necessary information to produce accurate forecasts, especially given the fact that markets trade with unprecedented movements.
Showcased in Econophy’s asset management methodology is Dr. Gregory Chernizer’s adaptation of Financial Markets Universal Dynamics (FMUD) risk control disciplines, a more efficient monitoring comes from the interaction between supply/demand imbalances and instantaneous volatility, as opposed to usage of conventional theory. These applications model the relationship between supply and demand, thereby optimizing position placement tied to execution frequency. The outcome is a higher level of ROI expectation.
The Supply/Demand Relationship
Independently developed in 1997, FMUD risk management theory is predicated on quantifying the current supply and demand relationship vs. a future expected change in the relationship for any anticipated price level.
Within what we term as the Causational Economic Space (CES), the method quantifies the current volume excess (VE) of supply and demand, and the volume excess expectation (VEE) of supply and demand in the future. Where VE = Volume-bid ( Vb ) minus Volume-ask ( Va ) at the price point level VEE is computed by utilizing a physics principle, called the Least Common Action Principle, to obtain equations of motion for the supply and demand relationship.
Our risk controls utilize collaborative tools to derive differential equations in order to obtain an estimate of VEE for any time horizon. When Vb = Va, the price of a financial instrument doesn’t move, regardless of the total volume of trading activity. Hence, movements in price are not determined by total volume, historical prices, or even historical volatility, but from changes in the supply and demand relationship.
By quantifying VE and VEE, one can envision a highly-informative picture of direction and the pivotal price points. This clarity allows for a truer assessment of the underlying risk associated with any open position.
For calculating instantaneous price volatility through observation and a forecasting mode for a volume excess expectation (VEE), the interaction between the two components to display a similar property is akin to an adiabatic invariant.
An adiabatic invariant is a property of a physical system that stays constant when continuous changes are made. Developed within our systematic style, the interaction between VEE and instantaneous volatility is a crucial contributor.
Simply stated, a particular price level and the VEE computed for that price level determines the risk thresholds for an open position. If we assume that (VEE) * equals a constant, the observation is that as volatility rises, VEE diminishes.
As this diminishing value approaches threshold risk levels, an open position with these expected VEE levels must be closed to prevent losses. Therefore, for any price level and volatility, the system produces local extreme positive and negative levels of VEE.
Setting Risk Thresholds
These upper and lower ranges set up the role of traditional resistance and support levels. They act as the reverse execution when quantifying risk associated with any position. As prices move, the threshold levels move in tandem, which creates a trailing stop level for the open position. This allows our trader to not only lock in any potential profit, but also maintain a preset risk threshold.
In quantifying the supply and demand relationship, the parallel exam is the interaction of this relationship with instantaneous price volatility.
Historically, these methods have only been applied to liquid markets, i.e. FX managed futures, equity indices, spot currency, etc. The question remains, “how effective has our model been during varying degrees of volatility?
Historical performances include:
While previously constructed risk management models and tools have served their purposes over the past decades, the onslaught of economic turmoil has created a new trading environment whereby volatility dominates the landscape.
Get used to it; adjust or completely revamp. The “good ol’ days” on how to combat volatility are gone!
Michael D. Billy, Managing Partner and Founder of Econophy Capital Advisors LLC, can be reached at email@example.com.