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Introduction to Global Markets SignalHubTM + Applications
A discussion document
NOTICE: Proprietary and Confidential
This material is proprietary to Opera Solutions. It contains trade secrets and confidential information which is sole property of Opera Solutions. This material is solely for the Client’s
internal use. This material shall not be used, reproduced, copied, disclosed, transmitted, in whole or in part, without the express written consent of Opera Solutions.
© 2012 Opera Solutions, LLC. All rights reserved.
2. Overview: Opera Solutions
• 700+ people – 220+ data scientists and machine learning experts
• Offices in North America, Europe, Asia
• Blue chip, global customer list
Scientists Solutions
Delivered As A
+ Service
Domain Experts VERTICAL
Big Data
+ Platform to
automate and
SignalHubs™
Dynamic collections
Applications for defined
industry/functional
problems
Management scale the of powerful Signals
+
Software
development and
delivery of Big
and advanced
models for specific
ENTERPRISE
Transformative capabilities
Developers industries and
Data analytics to fuel productivity, profit,
+
functional areas and performance for
Global 250
Deployment and
Ongoing Delivery
© 2012 Opera Solutions, LLC. All rights reserved. 2
3. The Asset Manager’s Challenge
Participants in the markets face a new environment with issues manifested at an unprecedented
scale and complexity; conventional approaches fail to address these challenges
CURRENT ENVIRONMENT THE CHALLENGE
Underutilized
Enterprise Data
Improve the speed
Fragmented and consistency of
Systems & Processes key risk and portfolio
management decisions
Market
Volatility
© 2012 Opera Solutions, LLC. All rights reserved. 3
4. Our Approach to Solving the Challenge – Man + Machine
LESSONS FROM CHESS
“An intelligent machine can almost always beat an
MACHINE INTELLIGENCE intelligent human… but the combination of even an
HUMAN INSIGHTS
+ average player with an intelligent machine can always
beat an intelligent machine or an intelligent human.”
Garry Kasparov, ex-world chess champion,
who played IBM’s Deep Blue in 1997
“Machine intelligence has become
DECISION MAKING more critical in my decisions and
points to many new and
EXCELLENCE
unusual ideas.”
Vishy Anand, current world chess champion
© 2012 Opera Solutions, LLC. All rights reserved. 4
5. Global Markets SignalHubTM and Applications
We convert ‘Big Data’ into a continuous flow of signals manifested as applications
Data
Best-in-class capabilities
in integrating internal
and external data
sources:
Intra-Enterprise
• Portfolio Info
• Transactions DNA SignalHubTM Applications
Inter-Enterprise
• Research Proprietary techniques Advanced algorithms Serving up Signals
• Trade ideas used to deconstruct data producing 9000+ daily through intuitive
into defining Signals for interfaces to convert
• Products/Strategies
characteristics sales, research, and insights into actions
Extra-Enterprise trading
• News/Transcripts
• Events
• Social Media
• Blogs
• Market Data
• Macro Economic data
© 2012 Opera Solutions, LLC. All rights reserved. 5
6. SignalHubTM for Global Markets - Topography
Opera’s advanced algorithms generate over 9000+ signals on a daily basis with reason codes and
rationale across asset classes
All signal types have certain qualities that describe how quickly signals can be generated
Signal Attributes (frequency), how often they signals vary (rate of change), whether they are forward looking
(quality), and how responsive they are to stimulus (sensitivity)
Frequency Rate of Change Quality Sensitivity
High or Low Slow or Fast Predictive or Descriptive Sensitive or Insensitive
Event/Alert/
Sentiment Behavior Clusters Correlation
Anomaly
Expressed as These signals identify A discrete signal Signals based on an Measures the
positive, neutral, or persistent trends or generated when entity’s cohort correlation of entities
negative, the prevailing patterns in behavior certain threshold characteristics: against their
attitude towards an over time. Examples conditions are met prescribed attributes
entity. Can apply to: include: such as: • Ultra high net worth over time:
clients with similar
• Security, e.g. AAPL, IBM • Market direction, • Withdrawal exceeds 3x high frequency • Stock prices within a
magnitude daily average transactions are sector
• Asset Class. e.g. corporate invested in PCY.
bond • Propensity to transact • Rating downgrade • Unemployment rate
(buy or sell) • Financial advisors impact on bonds of
• Market, e.g. US, BRIC • Increased trading with a focus on ETFs similar duration and
• Aggregate money flow activity that deviates and a minimum 5 rating
• Research Interest, e.g. from stated risk year are buying
Greek debt crisis tolerance level corporate bonds.
© 2012 Opera Solutions, LLC. All rights reserved. 6
7. Converting Signals to Action: Our Applications
Opera’s SignalHubTM supports many applications/products that provide sustainable increase in
business
• Suggest and promote innovative
Institutional Research trade ideas and content
• Match suitable trades for specific
Institutional Insights institutional clients or prospects
Signals combined with advanced
visualization, contextualizing
insights and facilitating action
• Minimize portfolio investment risk
Unintentional Risk
and optimize risk diversification
Portfolio • Provide innovative tools to
Optimization optimize client assets
Fraud • Identify trading anomalies for potential
Detection fraudulent likelihood and market risk
Hedge • Identify unintentional risk and suggest
Identification low basis risk hedges
© 2012 Opera Solutions, LLC. All rights reserved. 7
8. Opera’s Delivery Model for SignalHubTM + Applications
Opera will configure and deliver a fully customized solution and provide ongoing services to
ensure continuity, improvement and wide adoption of the solution
C U S T O M I Z AT I O N DEPLOYMENT ONGOING SERVICE
Define Operationally lean Platform Algorithm
requirements infrastructure maintenance improvement
Interview
stakeholders
Opera
Insights
Assess Bureau
data
Customize Fully secure and Offline Usage
platform compliant analytics monitoring
© 2012 Opera Solutions, LLC. All rights reserved. 8
9. Illustrative Work Plan (1 of 2)
Below is a work plan outline of a SignalHubTM + Apps solution development process; the
definition phase can be kicked off immediately independent of any external constraints
1 Definition 2 Customization
Set up planning workshops to create a 1. Develop execution plan
Project preliminary work plan and to establish a 2. Set up measuring and tracking
Management project structure mechanism
1. Set up technology, analytics and data 1. Clean, link, and organize disparate data
workshops to understand existing data sources
SignalHubTM content, sources of data, data 2. Customize algorithms to extract signals
structure, and systems from data
2. Set up business workshops to articulate
the business problem, to understand
1. Customize visualization components
the business need, and to brainstorm
Applications and assemble the applications
potential SignalHubTM applications
2. Create support documentation
1. Definition of the 1. User Acceptance Testing (UAT) signoff
concept, scope, timelines, and the key 2. Deployment - ready solution
Deliverables deliverables
2. A final client requirements document
© 2012 Opera Solutions, LLC. All rights reserved. 9
10. Illustrative Work Plan (2 of 2)
Below is a work plan outline of a SignalHubTM + Apps solution development process; the
definition phase can be kicked off immediately independent of any external constraints
3 Deployment 4 Ongoing Service
Project Develop production support and Ongoing production support and
Management maintenance plan maintenance
1. Work with client to refine signals and Monitor performance of signals to
SignalHubTM applications and to launch Beta version continuously improve the signals and work
with client to identify new signals
2. Obtain and incorporate feedback for
continual improvement through Beta
version release
Collaborate with client to improve
Applications 3. Go live with SignalHubTM + Apps solution applications and to identify new
applications
Solution in production Incremental releases of the solution
Deliverables
© 2012 Opera Solutions, LLC. All rights reserved. 10
Hinweis der Redaktion 1) Traditional and new sources of ideas conveyed at an increased frequency complicating the harnessing and leveraging of intellectual capital2) Heighted awareness, sensitivity and expectations of service levels and demonstrated added value3) Weak credit markets, reduced deal flow and heighted regulation hindering the ability to align clients with suitable investmentsThe Challenge:Right products for right clients at right time True and transparent performance measurement DG: edit content around the signals (sentiment examples), How you feel: individual/groupExample:1. Positive or negative - Market sentiment2. Advisor research interest – what do advisors read3. Sensitivity of sentiment given current market state4. Transition probability between sentiment states/level ???What you do - Behavior – Time SeriesMarket direction, magnitudePropensity to transactAsset Allocation trendsAdvisors’ relative performanceEvent/Alert/Anomaly- Impulse (DG: change “Anomalies” to this title)Abnormal trading volumeRating change and price target changeMembership/Cluster: who belong to where based on criteria we measureTrading behaviourAsset allocationMarket cap, credit risk cluster, industry clusterMost/least popular productsCorrelation: relationship (DG: add another vertical) Market correlationSecurity correlationAttributes:1. Frequency – High/low – asset allocation trends monthly or daily or every 15 min.2. slow/fast signal given a frequency (if we measure asset allocation every 15 min it will be slow, if we measure monthly, it will be faster)3. Descriptive/PredictiveAlgo: (DG: add this to the sample algo section – these are bucketed)PCA, SVD, Wavelets – transform data in certain way – data compressionK-Means/Hierarchical/ Spatial– ClusteringSVM/NN/Logistical RegressionKalman Filtering/ARIMANLP – Name Entity recognition, Relationship discovery, Bagofkeywords, regression model