Harvesting and Cataloging Financial Dragon-King Opportunities
Reference: More Details Posted Below BlogPosts
* The world's first Global Market-Insight Delivery-Feed that Aggregates Streaming Information about Investor Behavior Across 105 Integrated Dimensions of Price and Volume Action -- utilizing the latest innovations in Quantum Behavioral Game Theory.
* The Analytic Process Reverse Engineers Market Perception Metrics of Future Price and Volatility Momentum; Enabling Just-in-Time, Early-Warning Recognition and Prioritization of Trend Acceleration and Capital In-Flows & Out-Flows.
* Presenting fresh value-perspectives, time-sensitive news-flow, and pertinent market anomalies, with coverage that targets special / liquid situations across all asset classes.
* Your Financial Supermarket for Insightful Market Research and Time-Critical Behavioral Analytics for Managing Business Expectations in the G20 Economy.
* Real-Time Tweets of Behavioral Market Insight are Syndicated to many Financial News Sites that TAG Financial Stock Tickers with Time-Sensitive Just-In-Time Commentary.
* Out of the Lab and into the Trading Room --
Financial Dragon Kings are where market-generating opportunities intersect performance
More Details Posted Below BlogPosts
DISCLAIMER: Not a recommendation of any kind, and not an offer to buy or sell any securities of any kind -- strictly for informational and educational purposes only.
BIO:
Mr. Hoffman brings a broad business technology and mathematical physics perspective to Mission-Critical Risk Intelligence, Global-Macro & Sector-Rotation Analysis of Special-Situation Opportunities. He is a recognized inventor of Smart-Data Analysis, and a pioneer of Quantum-Behavioral Trading, with patents that have been cited internationally for use in applications of Environmental Catastrophe Prediction and Quantum Encryption.
One element that has remained constant is his unwavering passion for exploiting the mathematics of nature to better understand how large-scale social networks shift from periods of stability and growth, to unstable regimes of extreme turbulence and decay.
Based in Toronto, the publisher has a deep conviction for writing time-sensisitve commentary, trend-pieces, and investing oppinion-focused posts that challenge conventional thinking and legacy market-analysis, especially when it comes to analyzing emergent trends and Super-Anomalies of the Global Marketplace.
Overview and Strategy Summary
Overview & Strategy Summary:
Clear View Analytics Inc. (CVA) offers the world's first Global Market Management Process that Harvests and Catalogues Financial Dragon-King Opportunities; a new source of Black-Swan and White-Swan Events.
We aggregate streaming Information about Investor behavior across 105 Integrated Dimensions of Price and Volume Action -- utilizing proprietary innovations in Quantum Behavioral Game Theory.
The Analytic Process Reverse Engineers Market Perception Metrics of Future Price and Volatility Momentum; Enabling Just-in-Time, Early-Warning Recognition and Prioritization of Trend Acceleration and Capital In-Flows & Out-Flows.
Real-Time tweets of our Behavioral Market Insight are made available on many primary financial news sites that TAG Financial stock tickers with time-sensitive Just-In-Time Commentary
-- Out of the Lab and into the Trading Room --
Financial Dragon Kings are where
Market-generating opportunities intersect performance
Portfolio Market Intelligence and Portfolio Rationalization (TradeMark), Powered by the Wisdom of Crowd Collaboration Engine -- developed by CVA.
*Methodology Aggregates Price and Volume Exchange-Data at all Periodic Scales of Human Interaction.
*6th Generation Portfolio Analytics Engine -- Supported by Frontier Insights into Behavioral Finance and Quantum Behavioral Game Theory.
Portfolio Coverage:
Sector-Rotation and Special-Situation Behavioral Analysis of: Pricing and Volatility Structures of ETFs;, ETNs; Commodity ETPs; Currencies; Commodity Futures; Primary US Listed Equities, -- ADRs, ADSs; Bonds; and Interest Rates of Domestic and International Economies, is what drives the Data-Mining and Portfolio Discovery Process.
Based in Toronto, Canada, Mr. Hoffman consults as Research Director for the Catastrophe Modeling & Global-Growth Surveillance Observatory at Clear View Analytics Inc (CVA).
He brings a broad business technology and strategic investment vision to the companies he counsels. While consulting for and collaborating with industry experts on financial trading, order execution, electronic trading room design, real-time data management, and extreme event modeling; he has gained over 14 years experience researching and developing intelligent analytic and multi-dimensional visualization solutions for the next-generation of financial wealth management platforms.
Most notably, Mr. Hoffman brings a mathematical physics perspective to Portfolio Management, Mission-Critical Risk Intelligence, Global-Macro & Sector-Rotation Analysis of Liquid-Situation Opportunities. He is a recognized inventor of Smart-Data Analysis Architecture, and a pioneer of Quantum-Behavioral Trading Strategies; with information technology patents that have been cited internationally on over 40 instances on patents granted to Fortune 500 Companies, preeminent governmental agencies, scientific think-tanks, including leading practitioners at ivy-league academic institutions.
Mr. Hoffman deploys in-house applications for Dynamic Portfolio Construction, Financial and Economic Forecasting, Risk Intelligence, and Early-Warning Identification of Systemic Financial Hazards. Previous applications have been successfully used internally for Quantum Encryption of Sensitive Information, Efficient Storage of Digital Media, and Voice Recognition; as well as by governmental think-tanks for enhancing the efficacy of Environmental Catastrophe Prediction.
One instrumental element that is manifested in the investment strategy is Mr. Hoffman's unwavering passion for exploiting the mathematics and knowledge of nature to better understand how large-scale, complex social networks -- of many interacting financial agents -- shift from periods of stability and growth to unstable regimes of extreme turbulence and decay.
For further insight on the underlying mechanisms of our flagship strategy analytics , you are welcome to peruse the attached white-paper, produced by CVA.
Mr. Hoffman also has a deep conviction for writing time-sensitive commentary, trend-pieces, and investing opinion-focused posts that challenge conventional thinking and legacy market-analysis, especially when it comes to analyzing emergent trends and Super-Anomalies of the marketplace.
Mr. Hoffman is now recently an editor of several Financial Blogs that will serve as a Financial Supermarket for Insightful Market Research and Time-Critical Behavioral Analytics for Managing Business Expectations in a G20 Economy.
With dedicated consultants at our investment research facility in Mid-Town Toronto, CVA focuses on providing customized and proprietary institutional-level research for Alternative Fund and Risk Managers in Canada, the US, and abroad.
We cover foreign exchange pairs, commodities, and global inter-market analysis in support of managing risk/cash budgeting and early-identification of long/short global investment allocations, especially applicable during times of crisis and elevated market uncertainty.
The concepts and mathematical logic underlying this quantitatively-driven research strategy are inspired by frontier insights in Behavioral finance and the Wisdom of Crowds; and supported by strategic decision-making under extreme uncertainty, through applying time-tested strategies and rational-choice logic stemming from Quantum Game Theory.
Many local and international clients who have explored opportunities for this technology have been inspired by the way we can process information and exploit it ahead of the crowd, in a truly contrarian way.
Below are a few factoids regarding our strategic experiences.
*International Delegates of the 23rd Annual IFTA conference in Berlin on October 9th, 2010 recently attended a finance conference, including topics on New innovations in Behavioral Finance : A senior delegate and leading Behavioral Finance Faculty Head near Silicon Valley referenced our seminal Risk and Portfolio Analysis Content Engine as a uniquely viable alternative investment process.
*The model has also been used successfully to help High Net-Worth Investors shelter their portfolio's prior to the onset of the 2007 and 2008/2009 banking crisis with great precision.
*On a road-show presentation to algorithmic trading firms in New York and Toronto in very early September 2008, we showed how the model was forecasting the sub-prime crisis and the current commodity bull market -- not only did it get the timing correct to within hours, but also the duration and the specific equities that would suffer the greatest damage and high-impact collateral benefits.
*Furthermore, senior equity traders at Bear Stearns were regularly communicating with us, regarding our predictions of the market, several months before it was obvious that there would be a severe crisis of confidence at Bear Stearns --
* We suggested with conviction to Bear Stearns, on the many telephone calls they posted to me daily, that Bear Stearns stock would be the greatest victim of the crisis; all while its stock price was still above $100/share; The model correctly forecasted the precise trajectory of Bear Stearns collapse, as well as the Lehman Collapse -- over one year in advance, and with great clarity and fidelity at least 6 months in advance.
For some additional insights of the strategy approach, you are welcome to peruse the introductory material below.
Our strategy and research-driven approach can be summarized in the following manner.
(1) Collect historical price and other data of different asset classes, and determine which is relevant for today's markets and what is not;
(2) Examine behavioral patterns to see how people actually react (in large, small, fragmented, and tightly coupled market environments) to different price levels rather than as per their mathematical models used by economists;
(3) Examine valuation standards participants use;
(4) Measure participants' sensitivities to different price levels of different assets classes and securities;
(5) Model participant's reactions to the price level to see vis-a-vis their valuation standards;
(6) Employ quantum game theory and rational choice theory to model how each part of the financial system reacts to each other parts' movements and reactions;
(7) The model is not based on probability (CAPM) or Fractals (Mandelbrot) but on looking at when symmetries in existing market relationships become unstable and breakdown. For this reason, we are highly critical of probability and fractal models, for reasons that are revealed below and in the attached PDF document.
Please review below to get a better handle on how we process data:
We model market behavior at the level of Perceptions and beliefs. Perceptions for the most part are shaped by [changes in] what investors observe [as change]. There are only so many ways to measure changes in price trend -- namely through measuring deviations [changes] in price momentum. Every market participant [investor group] is free to choose among a specific set of look-back periods, but there is no assurance that he/she [it] will be focusing on the correct aggregate view of the market, at all times.
What we have engineered is a process that gives us a panoramic full-screen view of those periods, where, no matter where future price passes through time, the measurement devices will consistently register values at each [successive] investment scale that would serve to reinforce the aggregate market's perception [view] of relative price direction and momentum trend [ invariant to scale].
This way we can better prepare for those situations where upcoming market releases and economic reports or even small endogenous price changes will tend to have a greater influence on market action; thereby allowing us to spot upcoming anomalies and abrupt changes in volatility [on any scale from the transaction level to multi-year periods], which could become the seeds of the next uptrend or downtrend.
By knowing where such phenomena [events] can take form, we can better position ourselves on the correct side of the trade, or reduce exposure, when it is likely that upcoming volatility conditions are going to increase.
We have identified the precise geometric form – represented through the relative orientation of future values registered on these measurement devices, that give rise to trend formation. We are not looking at patterns of price movement, but rather the structural organization -- divergence or convergence -- of future price levels that are calibrated, for each time-resolution, to forward-looking levels of zero momentum (Balance Point), as well as the extreme limits of price variability on either side of these Balance Points.
Lets divert our attention to an analogy first. For example, when defining what a circle is, one can learn how to recognize a circle by being shown examples of objects that resemble a circle. Because these objects in the real-world will always have different levels of imperfections, then no matter how many samples one looks at or statistical regularities one looks for, the true form of a circle and the underlying process that creates them, will remain concealed from view.
Through applying principles of mathematical physics, one can learn to do better than this – that is, we can define the perfect form of a circle by framing it as a min-max problem, namely by asking one to maximize the area of an enclosed structure by using the least amount of material. In financial markets, this would equate with identifying the precise form --orientation] -- of registered future values of market measurement devices that would maximize the forward generation of price trends [reinforced at different scales], by requiring the least amount of market information [current price change] to sustain the endogenous reinforcement of trend persistence on different time-scales – not just from lower time scales to higher ones, but also accounting for their recurrent interaction in both directions.
What distinguishes CVA and Mr. Hoffman's approach from other models is that we focus on defining the underlying process that creates the imperfect outputs and variability most statistical measurement devices observe in the real-world; be it a geometric object or patterns of price. Often, by the time these output patterns are clear to the observer, the process that created it ceases existence. This time lag interferes with the perception of current conditions. We can not only remove this lag, but provide a strong lead.
We evaluate the number of time units [windows length] it takes for this information [price changes] to be absorbed by or emitted into another time window. Sometimes information [price changes] passes through a region of space [price levels], where it does not interact (is not absorbed or emitted in the way ordinary matter does), but rather creates an echo of background radiation in the future, that at some point will, on a certain scale, interact with new information (price changes) -- be it the result of short term or long-range trade commitments, creating boundary conditions [constraints], whereby future price movement is more likely to be either restricted or free flowing. The recognition of these two very different [types of] market states are what the model uses to define range-bound and trend-driven markets.
The overall proposition is to predict market movements before they occur to give institutional investors, and other large fund allocators, time to react to opportunities; and contagion breakdowns in risk-management metrics.
NOTE: The statement below is only making a comment about how often the model outputs of price momentum at each time scale are calibrated with future price levels. In no way does the model use probability theory to pre-process or generate the outputs or forecasts. There is a difference between using statistics to describe the average behavior of a model factor versus using a statistical variable that indicates how reliable a model variable (generated non-probabilistically) represents the actual outcome.
[The mathematical process does not require that we know where price will be at a future point; it only demands that we know what their price momentum gauges are likely to register on a relative basis, if indeed such changes in price are actualized in the future. The most robust element of this technique is that the margin of error in the measurement of these registered values have been mathematically demonstrated on over 250,000 instances -- spanning several generations of multi-geographic market records, and over five years of real-life observation -- to be within a confidence level exceeding 99.5%.]
Invitation for Exploring Financial Market Applications:
We invite you to join an engaging group of global macro and special situation market observers on our soon to be launched Live Internet Radio Broadcast -- offering Just-in-Time, Early-Warning Recognition and Prioritization of Trend Acceleration and Global Capital In-Flows & Out-Flows of Leading Equities, Commodities, Currencies, and Bond Markets.
Our Daily Market Commentary and Round-Table Discussion Group gives a sneak preview of tomorrow's high-impact headlines -- with specific near and intermediate term outlooks supported by Global and Behaviorally driven themes.
We trust that we will continue to see a steady stream of real-life trading samples to demonstrate how the model's performance can help you provide added value to your organization.
Nature of the research:
We are great a defining buying/shorting/turnaround plays that have great leadership potential and persistence price appreciation (or depreciation for short plays). We define the period of expected trade duration -- which can be customized to any time horizon of preference (from a few minutes to a few weeks or several months/years+). The model factors were also designed to define position holding periods even while legacy indicators might prematurely suggest that a transformational trend (i.e. current technology and commodity trend) is exhausted.
Our proprietary multi-level entry, exit, and non-linear stop levels ("Line-in the Sand") are known for the entire duration of the trade candidate (before entering the trade). This way, we can better compare the relative merits of alternative opportunities, not just at a single time point, but optimizing cash management and allocation over the entire investment horizon - on the basis of reward to risk. Because the Line-in-the-Sand is also finely tuned and calibrated to the specific price levels where buying interest is expected to increase at the same time that offers for selling actually dry up (opposite for short selling), we are better able to scale into trades -- reducing execution costs and slippage. Also, the model incorporates evolving price action during the interval of the trade to identify tighter price and time stops.
Our Model Focus List of bullish and bearish plays include from 150 to 200 long-term equity components on both sides of the market annually. We then hone in on 3 to 4 periods per year, where subsets of these opportunities (typically 30 to 40 great ideas spread among 5 to 10 market themes) are expected to be most active. We also review currency, bond, and commodity forecasts, in support of these themes.
We are about customization, We do not believe in a one format meets all, especially given the versatility and breadth of the modeling approach.
Our breadth of market research and strategic analytics content engine are not just about portfolio defense in times of crisis, but most importantly optimizing portfolio allocation (based on first principles of rational choice and Behavioral Finance -- true geometric form [not probability] -- (see description in first section) , and finding high-performance liquid-situations that yield favorable characteristics over all preferred time horizons.
Respectfully submitted,
Efrem Hoffman; Financial Model Architect,
Director of Institutional Research
efrem.hoffman@gmail.com
http://dragonkinginvestor.blogspot.com
http://global-macro.chime.in/
High-Impact Real-Time tweets of our Behavioral Market Insight are also made available on many primary financial news sites that TAG Financial stock tickers with time-sensitive Just-In-Time Commentary
DISCLAIMER: The information contained herein is intended for informational, educational and/or research purposes only. None of the information herein is intended to be, nor should it be construed or used as, financial, legal, tax or investment advice, or a representation as to the appropriateness or suitability of an investment and/or business contract. Furthermore, we assume no liability or endorsement for information from any third party links or posts.
