Introducing MindShare Indices & Comfort Investing

MindShare Indices
Running Alpha
Capital Markets Inc.
Efrem H. Hoffman
CEO & Founder
647 . 287 . 8439
Toronto, Canada
Introducing
MindShare Indices
Hedge Analytics
Sentiment-Inspired Absolute Return Investment Solutions
Your One-Stop Investment Platform for:
Profiting from Change in a Volatile Planet
and
Converting Market Uncertainty into Hedges that are Paying
You instead of Costing You Money
Presentation for Accredited HNW Investors, Toronto Mar. 28th, 2018

Who is Efrem Hoffman
• Efrem Hoffman is founder of Clear View Analytics Inc. (CVA) and its Director of
Macro-Market Strategy
• CVA is an Independent Alt-Research Firm with International Partners in Toronto,
US, & Eastern Europe
• Offers Institutional Quality Portfolio Solutions & Portable Risk Intel,
• Servicing Currency, Commodity, and Equity Managers
• Research Began in 1996 inspired by Big Data Analytics Solutions
• Vision was to Create a Global Heat Map of Market Volatility – a GPS for Hunting
Down Systemic Crisis Events
• Utilizing State of the Art Visual Decision-Support Tools
• Engineered a Sophisticated Forward-Looking Algorithm Revealing Levels of
Market Risk for All Asset Classes based on Quantum Field Theory
• New Concept called Bottom Down Analytics – for Defining the Architecture of
Time and Human Perceptions of Risk
• Performs Forensic Analysis of Market Micro Structure and Global Trends for Beta-
Neutral Portfolio Diversification & Tail-Risk Hedging Strategies
• Market calls were used to help financial traders successfully prepare for the 2007-
09 market crises with uncanny accuracy -- sees similar crisis on the horizon
© 2018 Running Alpha Inc. • Midtown Toronto 647 . 287 . 8439

Company Profile
Established R&D in 1996 – born out of undergraduate thesis research
study investigating the fundamental nature of catastrophic risk and
uncertainty in social, economic, and financial systems –
2 U.S. Big-Data Analytics patents granted in 2000 and 2001 -- originally
used to extract relevant features for tornado prediction and information
encryption.
Strategic Partnership Approach since 2006 with several leading
visionaries in Investment Analytics – including leading pioneers in
Behavioral Economics & Structural Valuation of Scientific Insolvencies
of Corporations and Sovereign nations, and Dynamic Volatility Hedging
© 2018 Running Alpha Inc. • Midtown Toronto 647 . 287 . 8439 ; 416 . 944 . 1506

About the Founder, Efrem Hoffman
A SHAD Alumni with over 20 years experience commercializing advanced
technologies out of the physics lab and into the trading room, for:
(i) helping professional value managers and angel investors find smarter
investments in the face of volatile market conditions; and
(ii) persistently profit from both this volatility and their mis-pricing -- arising from the
failure of the prevailing best practices to track and quantify the extreme uncertainty of
market variables imparted by our volatile planet,
the founder is passionate about employing this technology for augmenting HUMAN
INTEL on connecting the dots; and bringing together valuable insights about markets,
macro policy and geopolitics, that signal important investable and emerging trends in
world equity, commodity, financial futures and currency markets.
Tapping into this collective wisdom, Efrem is also particularly passionate about
rigorously and routinely stress-testing the research framework in the midst of financial
tornadoes; with a record of successfully warning investors of the demise
of WorldCom, Bear Stearns, Lehman Brothers, GM, among others, before any signs
of trouble emerged in 2008.

On-balance, a review of the much more mixed market settings, scrolling back as far
as 400 years across world capital markets, shows similar predictive intelligence.
With uncanny accuracy and specificity, his market calls were used to help financial
traders successfully prepare ahead of other notable capital market hurricanes,
including“ the Dot.Com Bust, 2005-07 USA Housing Crash, as well as the subsequent
re-acceleration of growth that followed the Great Recession ( particularly from 2013 ),
and that continues to fuel the USA-focused market rally today.
Our current Crisis Surveillance Alert System has recently issued a warning for its
abrupt end, at least in the near to mid term. This market call was recently picked up
by the financial media and put on record in a feature market brief by Benzinga TV |
Pre-Market Prep Radio on June 29th, 2017 ( segment starts after 16:19 minutes of
play ).
Most notable among his Tail-Risk pre-casts of wild sentiment jet-stream behavior,
was the flash crash of May 2006 -- accurately telegraphing in magnitude over
two months in advance, while striking inside the exact hourly timing window of the
anticipated peak tail-risk threat.

With a keen focus on these fronts -- Profiting from Disruptive Uncertainties in
our Volatile Planet (TM), the company's founder, Efrem Hoffman has been
building Social Traction for Running Alpha's intelligence, from:
Feature articles in the March 22nd and June 10th, 2016 editions of DailyFintech ( a
Swiss-based Fintech Conversation and Thought-Leadership Hub ) listing
Running Alpha as:
among 10 Emerging Financial Technology platform leaders and Sentiment
Fintechs in the U.S., respectively; focused "[on] the AI business of “sniffing
out” [signals] in digital wealth management, and changing the value
proposition of financial analysts and asset managers" ; to
Nominations for the 2016 Benzinga (BZ) Fintech Awards,
where RunningAlpha placed as a Finding Alpha Finalist -- at a New York City
Gala held at the Tribeca 360 on May 24th, 2016.

In the DailyFintech article ( March 22nd edition ), references are
made to alternative solutions that “can warn you before the market undergoes a
nasty selloff.” Although these platforms use real-time data from exchanges —
“[ looking for patterns and searching for clusters of traders who are bailing out
of an investment and providing clear visual signals when sellers are gaining
strength before a broad slide kicks in”] —
The Running Alpha methodology goes beyond analyzing visible data, which
can be gamed and trolled by your market adversaries.*
The founder was Interviewed by Accern ( Multi Asset-Class Predictive News
Analytics Platform tracking 1 Billion On-line Media Channels ) on November
16th, 2016, and more recently on Benzinga News for an Exclusive NASDAQ.com
Feature Article on this technology, which was released on May 10th, 2017.
Mr. Hoffman also served/serves as an invited keynote speaker / debate panelist
at live Bloomberg, Terrapin Quant World Canada 2017 and Trading Show Chicago
2017, TradersWorld Expo, and Toronto Hedge Fund Hotel Event(s); and

Efrem's thought-leadership and insights have been numerously quoted in the
international press -- i.e. CFA Magazine, NASDAQ news, Huffington Post, Vanity
Fair / Hive Magazine, Hamburg News, BloombergView, Thompson Reuters /
WSJ, CNBC breaking article relating to Trump Market Factor, and
other digital media sources, from an exclusive feature article in a Best-
Selling Amazon Book, authored by the owner of TradersWorld Magazine,
highlighting the best practices of among top traders and trading analysts, to
upcoming feature articles in e-books of leading digital media companies -- set
to hit the wire this fall, 2018.
The NASDAQ articles showcases how Running Alpha, a Toronto-Based FinTech
firm, is redefining the meaning of information and unlocking new insights
into asymmetric sentiment-biases, for
building smart portfolios that can hedge-for-a-profit instead of a cost against
global market uncertainty and tail-risk events.

Continuously pushing the envelope for building and maintaining the Running
Alpha investment strategy infrastructure and data pipelines,
Efrem is actively connected to a global network of industry-leading research
scientists, economists, quants, professional on and off-the-floor traders,
institutional investors, and FinTech industry veterans that are Data Science
powerhouses.
As a demonstration of his active interest in these areas, Efrem was recently an
invited special guest speaker during a semi-annual address ( held on October
27th, 2017) to 100 plus undergraduate and graduate students, faculty, and
industry at the University of Toronto.
The topic was "How Running Alpha is Advancing Emerging FinTech -- AI-
Powered Big Data Science, Quantum Computing Principles, and Alternative
Data from IoT Sensor Technology, Geo-Spatial Satellite and Radar Imagery" –
for revolutionizing financial decision-making and disrupting the digital wealth
and risk management industry;

arming the activist investor with both a new class of alpha and
capital markets transparency for assessing the Sentiment Impact of both News
Events and the Fundamental Drivers of Economic and Corporate Risk;
optimizing the allocation of capital and
shrinking the cost of doing business and most importantly the imbalances
between individual investor returns and fund manager pay outs.
The invitation was extended by the senior lab director's assistant in
collaboration with the Financial Mathematics Risk Lab -- University of Toronto
satellite lab
His research insights have been sought out by major alternative data vendors
and AI-powered alpha quant firms. Here is why:
Most trading on our planet is performed by machines; so Running Alpha's CEO
& Founder, Efrem Hoffman, goes beyond analyzing how people behave to –

discovering anomalies that exploit weak links in the networking & reflexivity
feedback effects arising from the interaction of machine perception biases and
social mood.
With strong international ties to the professional trading and investment community
Efrem actively shares his insights on Strategy Development and the Future States of
Markets, which include special media features:
(i) frequent trend-pieces, published to his 19186+ direct LinkedIn Connections ( &
18993 active followers ) -- accessible to over 20+Million globally connectable
network links of Industry Professionals;
(ii) invited appearances on: (a) TradingPub webinars; (b) panel discussions at
Toronto’s Hedge Fund Hotel, and Toronto Charts Day — a live Bloomberg Event
moderated by David Scanlan, Bloomberg’s Managing News Bureau Editor of Canada;
(c) Dow Jones Newswires article on Portfolio Stress-Testing by WSJ-Dow Jones
Reporter & Columnist, Evelyn Juan; and

(d) authored several feature articles in TradersWorld Magazine & On-Line
Presentations at TradersWorld Expo
With exclusive invitation, Efrem also serves as:
Research Member to The Barydyne Traders Group Project; a breakthrough global
think-tank that is reinventing the future of trading in a live trading lab. The mission
here is to contribute valuable insights for promoting the science of prediction to
trading. As a member of this group, I participate in group decisions to select buy, sell,
entry and exit strategies; and was instrumental in advising members of the emerging
megatrend in semiconductors and high-performance computing, just-in-time to initiate
investment before any trend existed.
Industry Survey Alliance Partner, to ChangeWave Research, a division of 451
Research -- providing time-relevant Insights on current consumer and business
Trends impacting the financial community, with a focus on IT and Networking
Technology; and

Corporate Research Member to Tactical Rabbit Inc, an elite closed intelligence
network offering break-through military intelligence gathering methodologies to
ascertain the relevant information so that the right mission-critical business,
economic, and social decisions can be made under conditions of extreme and
apparent uncertainty.

Paradigm Shift OLDNEW
• See risk on a single dimension – a linear relationship; we see it on many
inter-related axes of change that are dynamically influenced by
momentum perceptions of each trader group – spectrum from short to
long-range.
• Data is King Context is King  Why context is king matters  We
interact with data and its context ; it’s all about how we interpret the
data.
• The risk we perceive and feel goes beyond current events – headline
driven with short attention span – in fact in our new frame, the
collection of our perceptions has been on the assembly line before your
existence – for over 100 years; since the dawn of the financial enterprise
• How we diversify? By allocating across diverse risk windows – Risk
Allocation 2.0 – a bottom-down approach; not generalized bucketing
based on return distributions – but based on volatility of returns and
variance of volatility -- non-correlated across time and securities

Launching the Revolution
• Innovative Research Framework that simplifies 100 Years of Research
(see Slides 37-77 – A New Category of Actionable Intelligence for details )
• Combines various Research areas (Behavioral Finance, Statistics,
Mathematics, Quantum Physics and Supply/Demand Economics)
• Solution Versus Products Oriented – focuses on keeping portfolio costs low
• Our solution serves as a hybrid asset class with a Goldilocks Scenario;
combines the risk reducer benefits of an absolute return fund (having a
performance-seeking hedge), with the benefits of a Return Enhancer, that is
devoid of being subject to high volatility.
• The idea is Original, Global, Scalable, Versatile, and Portable
• Disruptive technology reframes risk in terms of perceived uncertainty,
offering a forensic investigation into architecture of time & market uncertainty
– from this framework, We build Portfolio’s with the World’s Thinnest Risk Boxes.

Out of The Lab And
Into Your Decision Room
• Benefit from a New Alpha Source with Big Data
Self-Generative Decision Networks
• Hunting Down Crisis Events with Location Positioning
of Future Risk Events – Time & Price Coordinates
• Know when to re-enter market with precision after
prolonged risk events
• Enhancing Your Visibility of Key Decision Nodes
Impacting Your Liquidity; &
• Converting Huge Echo-Chambers of Volatility across
Non-Correlated Risk Factors into Scalable Arb Ideas

Disruptive Investment Philosophy
• Investment philosophy founded on a new financial calculus and network
math, called: Relational Perception Calculus TM;
• derived from the Austrian economic science of human action and
mathematical physics principles of logical congruence and least action.
• In plain English, it is rooted in the founder's belief that:
• "The observing investor audience -- be it fundamental or behavioral-
driven trading participants -- those actors perceiving market structures of
the past do not only have different sets of viewing perspectives than the
decision-makers who first created them, but an exponentially wider-range
of vantage points to choose from for partitioning the past and calibrating
their lines of sight for tracking changing events around them."
• Therefore, in the spirit of Albert Einstein, we cannot simultaneously
comprehend and learn from history by trying to view the world through
the same array of lenses as our ancestors.

Disruptive Investment Solution
• To see beyond our mistakes and potential
vulnerabilities, while at the same time keeping the
solution computationally tractable,
• our algorithms utilize quantum computing principles
for super-exponentially speeding up the search for
optimal solutions – through chunking large volumes of
massively interacting perceptions.
• Powered by 360 degree decision-making, the search
algorithm adds context to history by augmenting views
from future versions of both today's decision-makers
and those spanning back to the ancient past.

22
Strategy Differentiators
Risk and Uncertainty are
Quantified in Absolute terms:
MindShare Weighted
High-Performance
Efficient
Portfolio Indices
(EPI)
Dynamic
Volatility
Management
Valuation
Positioning
++
Hedging For a Profit
inside the
World’s Thinnest Risk Windows™
+ Dynamic
Cash Management

Sentiment Jet-Stream

© 2012 Hoffman & Associates • Midtown Toronto • 647 287 8439 • 416 944 1506© 2018 Running Alpha Inc. • Midtown Toronto 647 . 287 . 8439
Running Alpha Framework Captures & Exploits S&P 500 Outlier Events

Running Alpha Framework Captures & Exploits S&P 500 Intraday Tail-Risk Events

Running Alpha Framework Captures March 27th, 2018 Tail-Risk Event

Running Alpha Framework Captures 1987 Crash

Running Alpha Framework Issues 2018 Black Swan Crisis Warning

MindShare Index Performance*

Return Composition

Individual Return Samples

Beyond Predictive Analytics
We monetize scenarios
• These are proprietary Tools
• Which tell the institutional user when and how to hedge for a profit.
• The tools also customize the solution for the user risk and profile.
• The tool is an application we built in-house to service our own needs
• Offers a decision support system with an institutional quality
advisory solution

Who do we compete with?
• Since hedging has a cost and we have a solution for hedging for a
profit.
• The competition could come from me-too solutions after visibility.
• But, the market is using the risk management instruments like
passive indices and other financial instruments in the same 150 year
old approach with high popularity.
• Our Investment Research Framework offers an innovation to not
only use the old risk management instruments in an original way, but
also create a new renaissance in engineering low-cost risk
management solutions for Active High-Performance Enhancement.

Efficient Portfolio Indices Expand the
Efficient Frontier -- Producing Higher
Return Per Unit of Risk
© 2012 Hoffman & Associates • Midtown Toronto • 647 287 8439 • 416 944 1506
Annual Signal Universe: frequency constant at to 25 to 50 significant opportunities
to select from – over 200 candidates from security list of 12,000 symbols meet
these criteria
System performance persists even during tranquil markets – as relative
performance cycles of weakest and strongest assets always exist
Early Warning of Crisis Events with High Conviction and Specificity
Precise recognition of safe periods to re-enter market after prolonged risk event
Diversification benchmarked to risk and uncertainty levels for each asset
component – leads to Diversification without redundancy
Strong book generates alpha – not diluted by mediocre performance

Strength of Research Framework
© 2012 Hoffman & Associates • Midtown Toronto • 647 287 8439 • 416 944 1506
Generated market calls during 2007-2008 market crisis that were significantly
more accurate, bold and timely in both initiation and exit – compared to
performance ratings of over 3000 equity analysts at 432 leading firms, followed
by Bloomberg Magazine, Aug 2008 ; also outperformed security selection of
banks that were listed Bloomberg’s 2011 Risk Report.
Successfully assisted a Merchant Banking Firm and several High Net-Worth
Individuals from assuming Market Risk prior to the Research Framework’s
accurate call of the 2007 & 2008 crisis; warned Bear Stearns of looming crisis.
Research Framework originally generated advance alerts of threatening
volatility storm with specificity more than 3.5 years ahead of event, & to within 3
days of the specific markets melting down – with over 3 months lead time –
correctly called 2010 Flash Crash & Recovery; sees another large magnitude
crisis on the horizon today for Yen – extending its 82 year walk-forward history.

What Makes the Running Alpha Portfolio a New
Category of Actionable Investment Intelligence?
• In today’s computer-driven world it’s virtually impossible for the average
investor to get ahead of trends without the aid of a computer algorithm
that detects early and lasting trend changes.
• There are simply too many variables to track for discovering which
companies are seeing unusual institutional money flows, which is what
creates sustainable and fast rising stock prices.
• Up until now, programming computer algos with inside knowledge and
experience into how institutions think, allocate money, and make trading
decisions were among the most effective methods for gleaning real-time
insight into trend development; now there is a better way --

• Running Alpha is Recasting Systematic Human-Machine biases as a
networking math problem for:
• Exploiting inefficiencies surrounding games of play in financial decision-
making and their corresponding capital flows in world financial markets
• Going back to basics — Research shows that we frequently make
reference to market sentiment and changes in market character, much as
we would speak of another person.
• Running Alpha’s Time Maps of the Forward Sentiment Jet-Stream behavior
is all about enhancing your Social Trading IQ and

• leveraging investor skills at reading and responding to actions and
emotions from the eyes of their competitors; and knowing how to
combine this mash-up of market insight for shining a light on
the best ideas from among the background noise of what individuals and
players around the table think: what they fear, want, value and are willing
to bet on. “What results is a truth greater than one man’s opinion.”
• Unlike traditional crowd-sourcing and collaborative intelligent systems
that focus on interacting with others to harness the collective wisdom of
the crowd for generating new and better trading ideas, we apply a
counter-intuitive version of crowd-sourcing Swarms of Informed Market
Participants.
• How? © 2018 Running Alpha Inc. • Midtown Toronto 647 . 287 . 8439

• How?
• By peering into the mind-space and perception fields of decision makers,
we can unlock the sum non-linear biases and mis-perceptions of the
crowd:
• Exploiting measurement errors of the total decision-making audience —
not just those in the market today, but spanning the decision-making
strategy variants that are accessible based on the myriad of ways trends
can be observed and measured in the forward versions of today’s
marketplace reality.

Whereas traditional Crowd-Sourcing and Swarm Prediction Markets need
non-gamed information, acquired from locally informed sources, to aggregate
as a prerequisite for predicting accurately, Crowd Physics 2.0 is not off-limits
to seeing how the web of communication among market players, with limited
insights into future events, would respond in the marketplace from the
vantage points of their aggregate perception biases.
• This feature alone is enabling traders and investors to exploit market
uncertainty for elevating their game at organically Hedging-for-a-Profit
instead of hedging-for-a-cost in all market environments.

• The Running Alpha technology is currently being employed by high-performing
asset managers, boutique alternative investment funds, and private equity
specialists in Canada and the U.S.
• Efrem continues to lead product development at Running Alpha, including
new sentiment indicators that are not only calibrated for telling history from
the perspective of tomorrow’s versions of today’s decision-making audience,
but for shrinking the time-line of converting sentiment data into easy-to-
understand and actionable high-performance outcomes.
• By uncovering subtle tells of investor and trading participants through
rendering visibility into their higher-order non-linear perception biases,
• Running Alpha gives investors never-before-seen insights into the asset price
impact of unfolding sentiment data sources and tail-risk events.
•

• Leveraging this new category of decision-making, our mission is clear; we are:
• (i) unlocking value and extending the shelf-life of conventional and
alternative data sets;
• (ii) accelerating knowledge discovery under conditions of extreme
uncertainty and limited history with self-generative learning systems; and
• (iii) rendering visibility and sensibility into the sentiment perceptions and
networking feedback effects of the billions of complex interacting trading
market agents, powering business and economic decisions in global capital
markets, and U.S. focused financial futures, options, and equities in
particularly;
•

• thereby, helping professional traders, investors and corporate decision-
makers better allocate their human, machine, and capital resources to the
corners of the marketplace that matters for:
• (a) maximizing alpha creation;
• (b) profiting from disruptive change; and
• (c) defending portfolio positions against known and unknown market
threats; and most importantly
• (d) addressing one of today's biggest and most challenging pain points in
the financial industry:

• Exploiting alternative data fields for helping investors build trust and
confidence in the investment / trading process.
• Many investors with great strategies loose money because they do not have
the confidence or trust in repeatedly following the process that led them to
successful outcomes. I say this because virtually every other provider out
there today may offer insights, but they do not do a great job at telling you
how to augment them with your current strategy.
• Running Alpha takes the concept of building trust to a new level by offering
alternative metrics for measuring performance that have a track record of not
only shrinking the time it takes to build trust in the outcomes, but allowing
investors to lower their anxiety when turning the insights into market actions.

• By raising Anxiety-Adjusted Returns, Running Alpha is on a mission for
leading the Fintech industry toward solutions that are organically designed
for shrinking the gap between reported strategy success and actual
investor alpha.
• To address these challenges, Running Alpha is first in the Global Fintech
community employs strategies founded on a smarter class of artificial war-
gaming intelligence that harnesses the way nature exploits quantum
computing principles for compressing the time it takes to perform
combinatorial search-space problems ( i.e. -- looking ahead whole chunks
of the decision optimization space ) from years to seconds – problems
currently intractable with classical computers, no matter how powerful
they become.

• By following large ( > 100 ) or concentrated basket of 15 to 20 securities from our
subset coverage universe of over 7000 equities, you will quickly discover a
significant asymmetry between the number and magnitude of out-sized winners
and losers. So now rather than waiting for a stop to be hit or investment exit to
trigger, to evaluate the success of the outcome, you can now access these
additional sentiment-aware data points while the trade is developing. This way you
can objectively verify if the anticipated feedback behavior of each position is
consistent with the current market reaction to sentiment-moving news events.
• Strategy Offers significant lead time for building large positions;
• telling you exactly when and at what price levels Windows of Investment
Opportunity open ( specific time and/or date ) and close ( specific time and/or
date ) before market transitions from periods of fear and anger to asymmetric
reward-to-risk intervals of persistent high-momentum recoveries, leading to
periods of long-term sustainable growth trajectories — and

• forecasted Windows of Tail-Risk Growth and/or Decay; thereby:
• Significantly Lowering Portfolio Volatility and Generating Sharpe Ratios above 2
and in some cases exceeding double digits.
• One particular feature traders will find quite useful is that if you are planning to
trade around core investment positions, each actionable investment idea
presented has a specific optimal viewing resolution, such that if traders want to
plot changes in market variables on their own charting or visualization platforms,
they can now be confident that they are observing trends on the right scale.
• The Running Alpha suggested time frame ( data sampling interval: note: duration
of window opening and closing time goes beyond dictating suitable sampling
intervals ); is also designed to align with the network structure of decision-makers
perceptions, which can vary over time; and

• Having knowledge of the dynamic time frames that are most suitable to the
current situation and forward market environment, investors will start
experiencing less anxiety and enhanced clarity from reduced levels of market
noise, freeing up their working schedule during off peak periods, and giving more
time to stay focused on the relevant signal content during active market periods.
Telegraphing Financial Vortices: Your Financial Data is Trying to Tell You Something: Is
Your Digital Wealth Management Process Built to Hear it? ( July 17th, 2017
article)
• The Fintech marketplace is in rapid flux; although we have a myriad of platforms
for leveling the playing field between retail and institutional investors, they fall
short at addressing the underlying physics of asset price movement and volatility
behavior.

• The existing way people think about how stock markets and asset prices
migrate over time, is fundamentally flawed; so the founder, Efrem Hoffman,
built a new class of technology to solve for this; centered on the mission of:
• Helping Investors Generate Alpha and Protect their Assets by strategically
"Investing in Times of Uncertainty" -- Winning despite the unknown.
• The strategy framework is formulated to go one step beyond AQR's sniff test
for sustainable alpha creation on five axes of merit, namely, it:
• (i) produces an analytic record and walk-forward risk-return structure that
indicates that the empirical investment edge is "persistent, pervasive, and
robust across all asset classes and market regimes;“

• (ii) offers an [ "explanation as to why and how the market inefficiency ( creating the
opportunity ) comes into existence in the first place, and why it has not been and
• (iii) continues to not be arbitraged away with evolving market pricing" ];
• and takes a giant leap forward by:
• (iv) requiring that there are no logical inconsistencies in the alpha-signaling logic across
different fractal viewing scales that have overlapping position holding time-lines
• By solving for the Quantum Measurement Uncertainty Enigma in the Financial
Marketplace, Running Alpha goes beyond exploiting a simple risk premium based on a
systematic behavioral bias or intuitive economic rationale, but leverages a long-held
deeply entrenched philosophical model paradigm blind-spot that exploits the inability
of conventional decision-makers ( both human and machine ) from:

• anticipating an Known Unknown -- ambiguity over factoring in and
determining the market impact of our own buying and selling decisions,
especially others reactions over several iterations of asset price formation;
and
• acknowledging an Unknown Known -- market players who naively dismiss
that their actions can adversely work counter to their intentions;
• (v) ["generates market positioning histories at the times of strategic
opportunity ( entry and exit ), that have a well defined group of financial
actors on the other side ( with limited arbitrage flows ) ] of the
contemplated open market transaction.

• Originally patented ( Patent #: 6,278,799 and 6,035,057 ) for Tracking down 3D
Cloud Droplet Rotation Patterns preceding hostile Tornado events, it is now
being successfully applied by the Toronto-Based Fintech Firm, Running Alpha,
for addressing the need for efficiently generating Comfort-Adjusted Returns
TM ( True Alpha -- see NASADAQ Feature Article ) in world capital markets.
• How? – By developing a new financial curve that re-casts and unifies the
meaning of true alpha and beta; it's called GammaRho.
• Avoiding the curse of volatility variance ( winning in low-volatility
environments and loosing in high volatility market conditions ) and making
portfolios "anti-fragile" -- recovering from draw-downs quickly and adapting
their structure for higher levels of resilience and growth,

• this new curve ( GammaRho ) was designed by the founder to quantify
and understand the correlations among market sentiment perceptions at
the tail -- the way people and machines generate perceptions about the
way they feel about the future when under elevated levels of stress and
uncertainty.
• What gives this curve a leg up on the prevailing view of observing market
change, is that it's about embracing the capacity for not only imagining
the future, but for re-framing it and figuring out how to get from here ( a )
to there ( b ) along the paths of logical congruence and least action -- by
shaping the underlying structure of human and machine perceptions that
ultimately create it (the future).

• At first glance, when most people or machines look at a data set, they only
observe how the market responded to the events of the day or history, and do not
see the hidden variables or higher dimensional architecture of the data's arrow of
time –
• -- how the composition and network of market actors and their perception models
of the world around them could have influenced non-local parts of the network to
effect change differently ( along an alternate vector ), given a marginally different
set of circumstances or economic, financial or geo-political stimuli.
• To dive deep into this level of scenario analysis, we engineered the algorithms for
peering into the cross-sectional time-delay uncertainties of the broad-band of
measurement paradigms, that our adversaries may be using for analyzing data
across different time-scales, asset classes, and geographies; and

• mathematically describing ( using network graphs ) how their perspectives are
interlinked and entangled in a unified whole; even in situations where each
market actor ( playing a passive or active role in order-book creation and price
formation ) is making independent judgments and acting outside the crowd.
• Where our competitors mostly live in the past, confined to either old
precedents, extrapolating historic trends, and/or seeking to describe how
things are -- where the current value is and at what fundamental rate of
growth a company is moving, or what technical momentum a stock is
advancing, we play a different game;
• Rather than see price moving through time, we render visibility of why things
occur and how asset prices come into being.

• By exploiting how nature solves problems and finds smart-cuts though quantum
computing, we have found ways to unlock latent value in traditional and alternative
data sets with limited history.
• This is a big deal, because most of the newer data sources and alpha factors emerging
today have a very short history and/or shelf-life.
• By looking at the non-linear relationships among how financial particles ( decision-
making perceptions and market order-flow ) reveal themselves to others ( the implied
sentiment factor ) and the order book ( the explicit market factor ),
• we have discovered new ways for quantifying the half-lives of news events, investor
sentiment ( convictions and social-chatter ), & their asymmetric emotional effects on
the direction & persistence of emergent price, volatility, & variance of volatility trends.

• This matters, because it plays a key role in not only:
• (i) knowing which assets to own -- those offering the best edge in amplifying
positive news and attenuating adverse outcomes, but also in
• (ii ) shrinking the gap between when decisions are made and executed, resulting in
a significant improvement in navigating investments around volatility and illiquid
market environments, with reduced market friction, efficient execution, and
favorable equity to draw-down performance.
• In other words, whereas the traditional game of play has involved tracking the flow
of money to extrapolate the future path of price, to see what others cannot see,

• Proprietary Capital Asset Pricing Framework look at the factors that power the
migration of capital -- namely:
• the perceptions of influential decision-makers;
• who they are ( investment capacity for each time-frame of investor ); and
• where the decision-making audiences' perception spaces are correlated across
price levels and time.
• This is important, because if you know where the people will be showing up,
and which sandboxes they are going to be playing in, you can better identify
and anticipate fund flows, instead of simply recording them in hindsight.

• By shining light on previously dark regions of data ( Dark Data -- the
perception biases of the trader ecology ), Relational Perception
Calculus (TM) is recasting the content of our existing data-store;
• permitting us to resurrect data elements from the dust-bins of history,
and see how they are behaving more like radioactive material, with a
half-life that persists on into the future;
• allowing "ancient" data to come alive and continue interacting with the
changing market sentiment in new ways, much like relativity theory
introduces reflexivity between gravity fields and mass.

• So, it is not the prices that have memory, but the decision-makers ( people and robots )
that both re-enact and evolve their perceptions of what is happening and has happened
in the past.
• We keep track of these Decisions ( driven by previous perceptions ) that are yet to be
implemented, based on prevailing liquidity conditions and the network feedback effects
of both market-player perceptions and their reactions to changes in Perceived Value,
Price and Volatility;
• because without this new source of knowledge, we would be blind-sighted to abrupt
regime transitions in market behavior; those "symmetry-smashing“ events punctuated
by asymmetric periods of:
• positive feedback that amplify future perception biases; and
• negative reflexivity conditions that yield extreme reversion events.

• We make it our business to profit from both sides of this divide.
• Laboratory results and real-life experiences, explains why the frequency and
impact of unexpected ( surprise ) events are generally underestimated using
previous model infrastructures
and
• ontologies ( "sets of concepts and categories in a subject area or domain that
shows their properties and the relations between them" )
• -- i.e. we are living in an age where 100 year floods are arriving every election
cycle, or perhaps sometime soon, every earnings season.

• We're different because we don't see information the way others do;
• When we look at a data set, we see a living breathing organism that expels
energy in the form of information to the environment ( sentiment context of
marketplace);
• rendering data more uncertain over time; thereby decreasing the value of
insights that may have been learned and gleaned from previous trend
recognition algorithms.
• To get around this trap and impart meaning back into the less ordered (
entropy increasing ) data states, we add context by leveraging the increasing
self-ordered structure of sentiment and perceptions biases driving them.

• By measuring the pulse of where decisions are being made with bias, across a
wide spectrum of market player viewing perspectives, instead of naively
tracking outputs from the order-book in the form of previous transactions,
• we can better identify and profit from discontinuities in market behavior that
are not visible in the unfolding market data or fundamental information fields,
that most all our competitors rely on as the only game in town –
• -- i.e. sudden jumps and wild swings in value, such as opening market price
gaps, that cannot be reliably anticipated with even today's most sophisticated
negative lag or leading indicators; since they all fall victim to quantum
measurement uncertainty, as will be seen in the upcoming section)

• By doing something others do not, we can better aim at extracting
absolute alpha ( excess returns well above the market benchmark, without
the use of any leverage) in all market environments ( Bull or Bear, High
Volatility, Stressed, or directionless ), and economic and geo-political
cycles.
• Imagine a technology advancement so powerful that it can transform the
way financial markets and economies work;
• disrupting the way investors and entrepreneurs think about risk and
uncertainty for better managing future expectations with the least
amount of discomfort.

• After 20 years in the making, and several million dollars of R&D investment, the
solution now exists, and its called Relational Perception Calculus ( RPC TM ).
• Money is only one of the possible applications. But we started here, as it offers the
longest and most reliable record of data on the digital assembly line for monetizing
its insights.
• To offer this new experience of wealth-building, we exploit a subtle, overlooked
feature of quantum computing systems;
• a secret sauce that helps us explain why records are made to be broken and
diverge from past discourse, especially as they apply to profiting from and averting
the episodic fits of panic, mania, greed, fear, and despondency –

• -- belonging to the rare 1% event class, which history repeatedly shows giving rise to
the 99% of market pressures -- information energy fields we, as investors, are otherwise
collaterally exposed to each and every trading day
• As will be described in the proceeding section, this inconspicuous feature solves the
problem of efficiently processing complex data and weighting and blending the factors (
unique technical / fundamental data fields ) of its many billions of interacting parts --
human and machine based decisions.
• To give you a sense of why this task has been a "wicked" challenge for the investment
community, one must first understand its greater fundamental significance in the field
of physics, namely:
• Chaos Theory, and Quantum Uncertainty -- expressed by the "Heisenberg Uncertainty
Relation" in scientific circles.

• First off, Chaos Theory ( "Deterministic Chaos" in scientific parlance ) simply means
that extraordinary precision would be needed in measurements, in order to know
what is going to happen in the long run -- i.e. "Butterfly Effect" -- something as
appearing innocuous as a flap of a butterfly's wings in the Canadian Rockies can
cause global weather patterns to yield economic peril across the Atlantic.
• In other words, sensitive dependence on initial conditions translates into widening
divergences as time marches on, so much so, that what first starts out as an
independent path in price, time, and value, quickly starts crossing others (
alternate paths of equally independent agents of market change ) in the future;
• causing interactions at the crossroads to deem the initial extrapolation of past
trends inaccurate across all fractal scales of human and machine observation.

• Relational Perception Calculus renders high-definition visibility of these
interactions ( in perception space ) before they show up in the macroscopic
behavior of price, sentiment or fundamental economic or financial indicators.
• Chaos Theory is the least of what should be keeping quants up at night;
• Quantum Uncertainty is the Mammoth-Sized "Elephant in the Room." It
simply means that precise values for both position and momentum --
velocity*mass ( transaction volume ) of a particle ( price or value ) are, in
principle, unknowable.
• In a sense these numbers don't even exist until they are measured, because
before they are observed they exist in more than one state at the same time;

• until the final moments of decision-making, when the observer probes the
region where the particles reside, and disturbs the configuration, tipping the
system into a state that is radically different from what was intended to be
measured.
• Since all measurement devices, no matter how small interact with the
environment; it renders conventional observation tool-sets ineffective at
quantifying instantaneous change without introducing uncertainty;
• and when combined with deterministic chaos, can profoundly influence even
macroscopic ( i.e. macro-economic ) behavior in unintended ways. As will be
seen later, our algorithms not only corrects for these episodes of collateral
damage ( or beauty ), but leverages them against less informed traders for
competitive positioning.

• This type of ambiguous measurement goes on all the time in the financial
and economic marketplace, and is known as "probing the markets."
Market players do this to get inside the head-space of their adversaries,
and acquire access to their intentions;
• it involves placing phantom orders ( orders of magnitude more devious
and inconspicuous than spy shoppers in the brick and mortar economy ) --
orders lacking deliberate execution.
• This type of "spoofing" was prominently displayed during the flash crash
of 2010 by market predators, to game the system for short term reward
and long-term strategic advantage.

• Our system flagged this nefarious behavior to within a three hour orb ( window )
over one month before its onset, and continues to actively monitor such activities
to circumvent future portfolio landmines.
• To this end, today's robo-traders, no matter how sophisticated, relying for the
most part on Artificial Intelligent (AI ) machines, that learn from experience ( real-
world measurements ), are doomed to fall prey to this uncertainty and ever-
increasing disorder ( High Entropy market condition ).
• While the laws of physics may inherently prevent us from observing the physical
universe without ambiguity, we have created a RPC (TM) tool-set that allows our
in-house traders and venture partners for the first time to gain insight into their
competitors perception space without the need for probing or measuring price
and momentum in real-time.

• Our proprietary quantum decision-making metrics allow us to calibrate
fields of forward price ( yet to be actualized in the future -- we call this
Gamma ) with the specific values of zero momentum balance points ( we
call this Rho ), spanning across all investable time scales, telescoping
upwards from the sub-millisecond interval of high frequency traders to the
time-lines of multi-generational investors.
• This GammaRho curve enables our investment algorithms to not only
provide a layer of transparency that our peers consistently lack, but allows
us to overcome the cost of: being human; or running algos, whose most
subtle measurements impart collateral uncertainty into the observed
market outcomes.

• The prevailing problem is "not whether buy and hold works in theory; it does not
work on average in practice," because people who make investment decisions, and
the people who use machines relying on ground-based risk intelligence, do not
have the fortitude to resist media chatter and market noise ( i.e. data exhaust --
redundant data and statistical information mirages ), during periods of elevated
uncertainty.
• What investors really need is to raise their "Emotional Alpha" IQ --
• -- the best returns they can achieve for the level of stress per unit of risk ( and
unintended uncertainty ) they're going to have to take on for the lifetime of their
investment.
• Our algo factors in how much discomfort each investor type is likely to endure
from not knowing the future state with certainty.

• Investor pain often attacks at two key points –
• (i) when investors panic out of positions after a sudden market setback;
• or
• (ii) during times of heightened uncertainty surrounding economic
conditions, when people or machines either:
• (a) freeze like deer just before the onset of a large informed market order -
- that precipitates a cascading sequence of orders that unwind the
excesses of a crowded trade in the form of a market crash; or

• (b) investor’s make the all too frequent mistake of exiting positions too
early, just before a large market advance -- compressed over a relatively
short time interval -- accounts for the majority of the long term gains.
• Running Alpha solves for both of these pain-points, building portfolios
with high levels of Comfort-Adjusted Returns (TM).
• Armed with this new class of intelligence, we trust that decision-makers
will be better prepared for making bold decisions with confidence — every
investors dream —

• Informing the institutional user when and how to hedge for a profit.
• The platform customizes the solution for the user risk and profile.
• Built in-house to service our own needs, we are now offering this
strategy for:
• Delivering actionable decision support & portfolio construction
services to Ultra-High Networth Individuals & Single Family Offices,
with an institutional quality managed account solution — for
maximum transparency.

Introducing MindShare Indices & Comfort Investing

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