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Machine Learning Conferences

Machine Learning Conferences

New York City: Machine Learning & AI in Quantitative Finance Conference, February 28th, March 1st & 2nd 2018.

SPECIAL OFFER: 25% Super Early Bird Discount Until Friday 2nd February 2018. When 2 colleagues attend the 3rd goes free!

London: Machine Learning & AI in Quantitative Finance Conference, 14th, 15th & 16th March 2018.

SPECIAL OFFERS: 25% Super Early Bird Discount Until Friday, January 26th 2018. When 2 colleagues attend the 3rd goes free!

Workshops:

New York City Wednesday February 28th: Machine Learning in Finance: A Practical View by Miquel Noguer Alonso: Columbia University

London: Wednesday 14th March: Machine Learning in Finance: A Practical View by Miquel Noguer Alonso: Columbia University

Conference Topics:

Predictive Power vs. Expressiveness of Machine Learning Models
Challenges with opaque ML models
Machine Learning in Quantitative Finance
Changing role of quants – from derivatives modellers to data scientists
Machine learning in finance - Practice
Black-box Machine Learning: Improving Transparency
Learning Curve Dynamics with Artificial Neural Networks
Machine Learning, High-Frequency Trading and Kdb+/q for Quants and Data Scientists
The 7 Reasons Most Machine Learning Funds Fail
Machine Learning for Trading
Big Data and AI Strategies: Machine Learning and Alternative Data Approach to Investing
Text Mining and Market Sentiment
Machine learning - Deep learning
What are the modelling applications which benefit from deep neural networks?
Financial Singularity -- Paths, Dangers, Strategies
Unsupervised Anomaly Detection in Finance
Financial Time-Series Regime Detection
What new insights can Machine Learning offer into the analysis of financial time series?
Machine Learning at Central Banks
Machine Learning & Event Detection for Trading Energy and Metal Futures
Extracting embedded alpha in Stocks and Commodity underlyings using statistical arbitrage/ML techniques from News/Social data

Conference Speakers

Machine Learning & AI in Quantitative Finance Conferences: New York City & London 2018

Pre-Conference Workshop Day: New York City: Wednesday February 28th 2018 & London: Wednesday 14th March 2018.

Machine Learning in Finance: A Practical View by Miquel Noguer Alonso: Adjunct Assistant Professor, Columbia University 

Outline:

    • Using machine learning in the new financial markets big data landscape
    • Big Data in Finance Landscape
    • Infrastructure and technologyData sources
    • Modern data analysis – Structured and Unstructured Data & New Models
    • Classical and advanced models
    • Machine Learning models in practice
    • Machine learning robust modeling
    • The future of machine learning in finance

08.30 Registration and Morning Welcome Coffee

Workshop Timings: 9.00 – 15.30


Big Data in Finance Landscape

  • Big data in finance landscape: Financial modeling, data governance, integration, NoSQL, batch and real-time computing and storage
  • Infrastructure and technology
  • New data sources
  • Modern data analysis: Structured / Unstructured data and new models

Machine Learning Models

  • Supervised learning
  • Unsupervised learning
  • Reinforcement learning
  • Deep learning
  • Advanced machine learning models

Machine learning in finance – Practice

  • Momentum and Mean Reversion
  • Sentiment Analysis
  • Asymmetric Trading Strategies
  • Non Linear Multi-Factor Models
  • High Frequency Trading
  • Advanced Machine Learning

Machine learning in finance – Opportunities and challenges

  • Algo-Grading 101
  • Interpretation
  • Data mining biases: overfitting, survivorship and data-snooping
  • Robust trading strategies
  • The future of machine learning in finance

Course Tutor:


Miquel Noguer Alonso, Adjunct Assistant Professor, COLUMBIA UNIVERSITY.

Miquel Noguer i Alonso is a financial markets practitioner with more than 20 years of experience in asset management, he is currently working for UBS AG (Switzerland). He worked as a CFO and CIO for a European bank from 2000 to 2006. He started his career at KPMG.

He is Adjunct Assistant Professor at Columbia University teaching Asset Allocation, Big Data in Finance, Fintech and Hedge Fund Professor at ESADE. He received an MBA and a Degree in business administration and economics in ESADE in 1993. In 2010 he earned a PhD in quantitative finance with a Summa Cum Laude distinction (UNED – Madrid Spain). He also holds the Certified European Financial Analyst diploma ( 2000 ).

His research interests range from asset allocation, big data to algorithmic trading and fintech. His academic collaborations include a visiting scholarship in Columbia University in 2013 in the Finance and Economics Department, in Fribourg University in 2010 in the mathematics department, and presentations in Indiana University, ESADE, London Business School, CAIA Association, AFI and several industry seminars.


BOOK NEW YORK              BOOK LONDON

London: 15th & 16th March 2018, Machine Learning & AI in Quantitative Finance Conference

Day 1: Thursday 15th March 2018

08:30: Registration and Morning Welcome Coffee

BOOK LONDON


09.00 – 09.45:  Keynote Speech

O. Ediz Ozkaya: (Machine Learning)

Presenter: O. Ediz Ozkaya: Executive Director, Machine Learning Labs, Securities, Goldman Sachs

Overcoming the Trade-off: Predictive Power vs. Expressiveness of Machine Learning Models

  • Challenges with opaque ML models
  • Controlling model behaviour in relation to tail risk
  • Expressive regularising models, native prediction confidence
  • Improving model expressiveness
  • Readiness for increasing model complexity

09.45 – 10.30Machine Learning: History and Implications for Quantitative Finance WILLIAM MCGHEE

  • Historical overview of Machine Learning – from MENACE to Alpha Go Zero
  • Implications for Quantitative Analytics
    • Changing role of Quants
    • Building a Machine Learning framework
    • Model Governance

Presenter: William McGhee: Global Head of Quantitative Analytics, NatWest Markets


10.30 – 11.00: Morning Break and Networking Opportunities


11.00 – 11.45: Reliable Machine Learning 

  • Robustness
  • Awareness
  • Adaptation
  • Value learning
  • Monitoring

Presenter: Lawrence Edwards: Executive Director, Morgan Stanley (to be confirmed)


11.45 – 12.30: “Black-box Machine Learning: Improving Transparency”.Abdel Lantere

“Many of the state of the art machine learning applications are based on black-box models which are difficult to interpret and explain. With more ML-based models being integrated into live decision-making systems, new challenges will be faced by various functions within banks as well as by the regulators. This talk disucsses the challenges faced and presents techniques to help provide more transparency and better understanding of the results of a given ML black-box model.” 

Presenter: Abdel Lantere: Data Scientist, Quantitative Consultant, HSBC 


12.30- 13.30: Lunch


13.30 – 14.15: Machine Learning Models Dr. Miquel Noguer Alonso

  • Supervised learning
  • Unsupervised learning
  • Reinforcement learning
  • Deep learning
  • Advanced machine learning models 

Presenter: Miquel Noguer Alonso: Adjunct Assistant Professor, Columbia University


14.15 – 15.00: Fast MVA Optimisation using Chebyshev Interpolants 

  • MoCaX Smart grids based on Chebyshev spectral decomposition
  • Machine Learning accelerated with MoCaX fast pricing
  • Application: MVA optimisation in real time. With the massive acceleration to compute Greeks with MoCaX, it is possible to evaluate a Monte Carlo simulation of SIMM in fractions of seconds. This in turn makes it possible to revalue an MVA objective function as frequently as required by the optimisation algorithms.

Presenter: Mariano Zeron: Head of R&D, MoCaX Intelligence & Andrés Hernández: Manager, Financial Services Risk Consulting, PwC


15.00 – 15.30: Afternoon Break and Networking Opportunities


15.30 – 16.15: Machine Learning – Recent Trends and Applicability to Risk and Related Areas  

  • Supervised, unsupervised, Reinforcement
  • Deep learning, feature Learning, incremental learning
  • Predictive power and robustness 

 Presenter: Presenter to be confirmed


16.15 – 17.15: Machine Learning & Ai in Quantitative Finance Panel

Moderator:

  • To be confirmed

Panelists:

  • To be confirmed

Topics: 

  • What is the current state of utilisation of machine learning in finance?
  • What are the distinct features of machine learning problems in finance compared to other industries?
  • What are the best practices to overcome these difficulties?
  • What’s the evolution of a team using machine learning in terms of day to day operations?
  • What is a typical front office ‘Quant’ skillset going to look like in three to five years time?
  • How do we deal with model risk in machine learning case?
  • How is machine learning expected to be regulated?
  • What applications can you list among its successes?
  • How much value is it adding over and above the “classical” techniques such as linear regression, convex optimisation, etc.?
  • Do you see high-performance computing (HPC) as a major enabler of machine learning?
  • What advances in HPC have caused the most progress?
  • What do you see as the most important machine learning techniques for the future?
  • What are the main pitfalls of using Machine Learning currently in trading strategies?
  • What new insights can Machine Learning offer into the analysis of financial time series?
  • Discuss the potential of Deep Learning in algorithmic trading?
  • Do you think machine learning and HPC will transform finance 5-10 years from now?
  • If so, how do you envisage this transformation?
  • Can you anticipate any pitfalls that we should watch out for

Day 2: Friday 16th March 2018

08:30: Registration and Morning Welcome Coffee


09.00 – 09.45: Machine Learning, High-Frequency Trading and Kdb+/q for Quants and Data Scientists 

Paul Bilokon, PhD

Abstract: Kdb+/q is a de-facto standard technology among the high-frequency trading firms and market makers. The underlying programming language, q, is based on Ken Iverson’s idea of efficient notation, which enables one to deal with financial data extremely efficiently and with minimum effort. We present excerpts from our forthcoming book and show how big financial data and machine learning can be handled efficiently in q and give several examples – from neural nets, to classifiers, and feature extraction for alpha generation.

Presenter: Paul Bilokon: Founder, CEO,Thalesians, Senior Quantitative Consultant, BNP Paribas & Visiting Lecturer, Imperial College


09.45 – 10.30Practical Aspects of Applying Deep Learning for Market Making 

Presenter: Oded Luria: Data Scientist, Citi (To be confirmed)  


10.30 – 11.00: Morning Break and Networking Opportunities


11.00 – 11.45: Unsupervised Anomaly Detection in Finance 

Claudi Ruiz Camps

‘ABN AMRO Clearing Bank works with considerably large amounts of data every day and we design and implement Deep Learning models to approach  some of our business cases. One example is, how to find real time anomalies (strange behaviors) in our data by using Unsupervised Anomaly Detection with TensorFlow and Spark. The output is being visualized with Tableau in order to express the anomalies and to make data-driven business decisions.’ 

Presenter: Claudi Ruiz Camps: Machine Learning, Deep Learning Specialist, & Marleen Meier: Quantitative Risk Analyst, Data Visualization, ABN AMRO Clearing Bank N.V. (to be confirmed) 


11.45 – 12.30: Machine Learning at Central Banks

Presenter: T
o be confirmed


12.30- 13.30: Lunch


13.30 – 13.50: Co-creating Machine Learning solutions within a global Corporate & Investment BankDaniel Drummer, CFA, LL.M.

  • The Challenge – Why banks and data science startups can often benefit from cooperating with each other.
  • The Opportunity – How JP Morgan is co-creating ML  solutions with startups via the In-Residence program
  • Case study – Experiences and lessons learned from day-to-day cooperation with machine learning startups

Daniel Drummer: Vice President, Corporate & Investment Bank FinTech, J.P. Morgan (to be confirmed)


13.50 – 14.50:  Big Data and AI Strategies: Machine Learning and Alternative Data Approach to Investing

Presenter: To be confirmed


14.50 – 15.00: Quick Afternoon Break


15.00 – 15.45: Machine Learning Techniques for Trading

Presenter: To be confirmed


15.45 – 16.15: Machine Learning & Event Detection for Trading Energy and Metal Futures 

Abstract: The emergence of big data in finance has had a major impact on equities trading. However, other asset classes have seen less of an impact, since fewer alternative data sets are available to support them. In recent years this has changed with the proliferation of various social media sources and with the development of more advanced knowledge graphs that supports global macro themes. During this talk, Peter Hafez will show how to use machine learning and systematic event detection techniques to trade energy and metal futures.

Presenter: To be confirmed

New York City: March 1st & 2nd 2018, Machine Learning & AI in Quantitative Finance Conference

SPECIAL OFFERS: 25% Super Early Bird Discount Until Friday, January 26th 2018. When 2 colleagues attend the 3rd goes free!

Day 1: Thursday March 1st 2018

08:30: Registration and Morning Welcome Coffee

BOOK NEW YORK


09.00 – 09.45:  Keynote Speech

O. Ediz Ozkaya: (Machine Learning)

Presenter: O. Ediz Ozkaya: Executive Director, Machine Learning Labs, Securities, Goldman Sachs

Overcoming the Trade-off: Predictive Power vs. Expressiveness of Machine Learning Models

  • Challenges with opaque ML models
  • Controlling model behaviour in relation to tail risk
  • Expressive regularising models, native prediction confidence
  • Improving model expressiveness
  • Readiness for increasing model complexity

09.45 – 10.30: “Black-box Machine Learning: Improving Transparency”.Abdel Lantere

“Many of the state of the art machine learning applications are based on black-box models which are difficult to interpret and explain. With more ML-based models being integrated into live decision-making systems, new challenges will be faced by various functions within banks as well as by the regulators. This talk disucsses the challenges faced and presents techniques to help provide more transparency and better understanding of the results of a given ML black-box model.”

Presenter: Abdel Lantere: Data Scientist, Quantitative Consultant, HSBC


10.30 – 11.00: Morning Break and Networking Opportunities


11.00 – 11.45: Machine Learning Models Dr. Miquel Noguer Alonso

  • Supervised learning
  • Unsupervised learning
  • Reinforcement learning
  • Deep learning
  • Advanced machine learning models

Presenter: Miquel Noguer Alonso: Adjunct Assistant Professor, Columbia University


11.45 – 12.30: A look at Latest Hardware Developments in Machine & Deep Learning 

Presenter: To be confirmed  


12.30- 13.30: Lunch


13.30 – 14.15: Machine Learning – Recent Trends and Applicability to Risk and Related Areas (To be confirmed) 

  • Supervised, unsupervised, Reinforcement
  • Deep learning, feature Learning, incremental learning
  • Predictive power and robustness

Presenter: Suhail Shergill: Head of R&D and Innovation Lead, Scotiabank (To be confirmed) 


14.15 – 15.00: Fast MVA Optimisation using Chebyshev Interpolants 

  • MoCaX Smart grids based on Chebyshev spectral decomposition
  • Machine Learning accelerated with MoCaX fast pricing
  • Application: MVA optimisation in real time. With the massive acceleration to compute Greeks with MoCaX, it is possible to evaluate a Monte Carlo simulation of SIMM in fractions of seconds. This in turn makes it possible to revalue an MVA objective function as frequently as required by the optimisation algorithms.

Presenter: Mariano Zeron: Head of R&D, MoCaX Intelligence 


15.00 – 15.30: Afternoon Break and Networking Opportunities


15.30 – 16.00: Practical Aspects of Applying Deep Learning for Market Making

Presenter: To be confirmed


16.00 – 16.30: What are the Limitations of Machine Learning

Presenter: To be confirmed


16.30 – 17.15: Machine Learning & Ai in Quantitative Finance Panel

Moderator:

  • Paul Bilokon: Founder, CEO,Thalesians, Senior Quantitative Consultant, BNP Paribas & Visiting Lecturer, Imperial College

Panelists:

  • O. Ediz Ozkaya: Executive Director, Machine Learning Labs, Securities, Goldman Sachs
  • Miquel Noguer Alonso: Executive Director, UBS & Adjunct Assistant Professor, Columbia University
  • Rajesh T. Krishnamachari: Vice President, Quantitative and Derivatives Strategy, J.P. Morgan (to be confirmed)
  • Abdel Lantere: Data Scientist, Quantitative Consultant,HSBC
  • Ignacio Ruiz: Founder & CEO, MoCaX Intelligence

Topics: 

  • What is the current state of utilisation of machine learning in finance?
  • What are the distinct features of machine learning problems in finance compared to other industries?
  • What are the best practices to overcome these difficulties?
  • What’s the evolution of a team using machine learning in terms of day to day operations?
  • What is a typical front office ‘Quant’ skillset going to look like in three to five years time?
  • How do we deal with model risk in machine learning case?
  • How is machine learning expected to be regulated?
  • What applications can you list among its successes?
  • How much value is it adding over and above the “classical” techniques such as linear regression, convex optimisation, etc.?
  • Do you see high-performance computing (HPC) as a major enabler of machine learning?
  • What advances in HPC have caused the most progress?
  • What do you see as the most important machine learning techniques for the future?
  • What are the main pitfalls of using Machine Learning currently in trading strategies?
  • What new insights can Machine Learning offer into the analysis of financial time series?
  • Discuss the potential of Deep Learning in algorithmic trading?
  • Do you think machine learning and HPC will transform finance 5-10 years from now?
  • If so, how do you envisage this transformation?
  • Can you anticipate any pitfalls that we should watch out for

Blockchain Developments in Financial Markets Conference

Full Conference Fee: £545 + VAT, Attend Conference Day 1 or 2 Only: £295 + VAT

Day 1 – Regulatory & Compliance Developments, Smart Contracts, Digital Identity & ICOs

Thursday 23rd November

BROCHURE

Location: Kingsway Hall Hotel, London

08:30: Registration and Morning Welcome Coffee


09:00 – 10:00 Keynote Speech: Taking Finance to Blockchain Massimo Morini (Blockchain)

Derivative Products on the Public Blockchain

  • A new market design to minimize risk by technology
  • What stays onchain, what goes offchain
  • Providing the services the market needs. What ICOs are offering.

Redesigning Clearing and CCPs on Private Blockchains

  • Transparency and Auditability by Smart Contracts
  • How to design central clearing without centralization
  • The need for digital versions of fiat currencies

Presenter: Massimo Morini: ‎Head of Interest Rate and Credit Models, Gruppo Intesa Sanpaolo


10.00 – 10.45: Image result for Adedayo Banwo: Senior Counsel, Deutsche BankOff the Chain: Regulatory Challenges Facing Fintech Companies and Banks

This presentation will focus on recent regulatory developments impacting financial technology (Fintech) including initial coin offerings and distributed ledger technology with a focus on Europe and the United States, and legal issues that Fintech firms should consider in the current regulatory environment.

Presenter: Adedayo Banwo: Senior Counsel, Deutsche Bank


10.45 – 11.15: Morning Break and Networking Opportunities


11.15 – 12.00: How to Begin the Transition to Blockchain Image result for Michele Curtoni

  • Taking first steps on the road to Blockchain
  • How should companies go about making the transition?
  • Key considerations and potential challenges

Presenter: Michele Curtoni: Emerging Technology Strategy, London Stock Exchange Group  


12.00 – 12.45: “Designing Standards for Smart Contracts” Panel

Moderator:Lee Braine (Blockchain)

  • Lee Braine: Investment Bank CTO Office, Barclays

 

Panelists:

  • Massimo Morini: Head of Interest Rate and Credit Models, Gruppo Intesa Massimo Morini (Blockchain)Sanpaolo

 

 

  • Yiseul Cho: Partner, Blockchain Partners Korea
    Yiseul Cho (Blockchain)

 

 

 

  • Adedayo Banwo: Senior Counsel, Deutsche BankAdedayo Banwo (Blockchain)

 

 

  • Ashley Patricks: Lead Software Engineer, Lloyds Banking Group Innovation Labs 

 

 

Topics:

  • Smart Contracts: how should law react to self-executing agreements?
  • What it takes for a Smart Contract to be also a legal Contract?
  • Tokens and Smart Contract. How should ICO be designed to be considered Legal?
  • Smart Contracts and Dapps on the Public Blockchains: anyhting good in the recent hype?
  • Smart Contracts on the Private Blockchains: do we have three Champions that will rule the world?
  • What is the current state of play with architecture standards for smart contracts?
  • Why are business process standards necessary for smart contracts?
  • Why types of data standards are required for smart contracts?
  • Do you foresee trade associations (such as ISDA, FIA, BAFT, etc) supporting smart contracts standards?

12.45 – 13.45: Lunch 


13.45 – 14.30: Are ICO’s the Answer to the Funding Gap for SME’s and Technology Businesses?

Martin Bartlam (Blockchain)

  • What is an “ICO”?
  • Jurisdictions and structures being used
  • Utility tokens and regulated assets in the form of digital rights
  • Types of business using ICOs
  • What to look for and what to be concerned about
  • ICO Funds
  • Where is the market now and where is it likely to go?

Presenter: Martin Bartlam: Head of International Finance, DLA Piper 


14.30 – 15.15: Good Governance on ICOs

  • ICOs changing the way startups raise money.
  • How not to do an ICO
  • The proper way to do an ICO

Presenter: Adam Leonard: CEO, BlockEx 


15.15 – 15.30: Afternoon Break and Networking Opportunities


15.30 – 16.15: The Crypto Finance Scene Yiseul Cho (Blockchain)

  • Blockchain data project
  • Global trends
  • Building a quantitative tool to assess the risks around ICOs 

Presenter: Yiseul Cho: Partner, Blockchain Partners Korea


16.15 – 17.00: How the NAGA Coin will make Financial and Virtual Goods Trading Accessible for Everyone 

Presenter: Yasin Sebastian Qureshi, Founder & Executive Director, NAGA Group

 

Day 2 – DLT (From PoC to Large Scale Implementation), Clearing and Settlements & Pricing for Cryptocurrencies

Friday 24th November

BROCHURE

Location: Kingsway Hall Hotel, London

08:30: Registration and Morning Welcome Coffee


09.00 – 09.45: Keynote Speech: Distributed Ledger Technology: Clearing and SettlementImage result for Keith Bear ibm

  • Blockchain in Financial Markets: Bridging the Divide
  • Use Case Analysis
  • Governance and Consortium: the challenges
  • Turning PoC’s into Industrialised distributed networks
  • Lessons learnt from early Financial Markets deployments 
  • Lessons learnt from blockchain implementation in post-trade 

Presenter: Keith Bear: VP, Global Financial Markets, Global Markets, IBM


09:45 – 10:30: Using Blockchain to Set New Standards in Post Trade SettlementsHugh Halford-Thompson (Blockchain)

  • How blockchain streamlines post-trade
  • Deploying blockchain at scale
  • Use cases in energy and finance
  • Blockchain’s advantages in setting industry-wide standards
  • What might adoption of blockchain look like

Presenter: Hugh Halford-Thompson: CIO, BTL Group LTD


10.30 – 11.00: Morning Break and Networking Opportunities


11:00 – 11.45: Panel – Challenges the Industry is Experiencing Taking DLT from PoC to Large Scale Production Implementations.

Image result for Keith Bear ibm

Moderator:

  • Keith Bear: VP, Global Financial Markets, Global Markets, IBM

Panelists:

  • Anthony Woolley: MD, UK CIO, Societe Generale

 

 

  • Richard Crook: Head of Innovation Engineering, RBSRichard Crook (Blockchain)

 

 

  • Adriano Bertini: Vice President – Electronic Trading Technology, Bank of America Merrill LynchAdriano Bertini (Blockchain)

 

 

 

 

  • Hugh Halford-Thompson: CIO, BTL Group LTDHugh Halford-Thompson (Blockchain)

 

 

Topics:

  • Technological issues
  • Centralized vs. Decentralized Blockchain
  • Commercial structures of consortia and associated operations
  • Legal and regulatory considerations
  • The byzantine general problem solution and the impact to systems of trust (e.g. Payment system)
  • The importance of distributed consensus to keep network nodes honest
  • The evolution of peer-to-peer systems and the impact to third party service providers
  • The accelerated growth of cryptocurrencies in hyper inflationary markets – proxy or use case?
  • The integration of regulatory applications in distributed consensus payment networks

11.45 – 12.30: Pricing and Risk in a CryptoTech World

  • CryptoTech is about information and coordination, not pricing but pricing and risk are influenced by coordination.
  • XVA and coordination

Presenter: Chris Kenyon: Head of XVA Quant Modelling | FOS-Quant Modelling, MUFG Securities EMEA plc


12.30 – 13.30: Lunch 


13.30 – 14.15: The Future of OTC Derivatives: Using Blockchain for Decentralised Post-Trade Services 

  • Current Challenges with OTC Derivatives with a focus on Structured Notes
  • How DLT could re-model the existing setup
  • The Potential Benefits to Issuers and Clients
  • Approach to implementation with focus on Post Trade Events
  • The challenges to being able to achieve this

Presenter: Sohail Raja: Head of Execution Platforms, Societe Generale Corporate & Investment Banking


14.15 – 15.00: How Blockchain is Changing Traditional Venture Capital and Capital Markets Alexander Shelkovnikov (Blockchain)

  • Technology financing landscape has started to shift significantly over the past couple of years
  • There are some key advantages of blockchain technology which are driving this shift
  • Why decentralised technology and transparency is going to win long term
  • What does it mean for venture capital and the world of capital markets

Presenter: Alexander Shelkovnikov: Founder, Semantic Capital


15.00 – 15.15: Afternoon Break and Networking Opportunities


15.15 – 16.00: Applied Blockchain: Attention Economy in the Age Or Algorithms

Presenter: Andy Mccutcheon, Co-Founder, Synereo

  • Advertising and the Attention Economy that powers the internet
  • Decentralisation, Blockchain and Crypto – know the difference
  • Information control in the age of AR and instant context

Sponsors

There are limited sponsorship opportunities for this event so please contact neil@wbstraining.com
Featured Image

MoCaX Intelligence is a new-to-the-market algorithm that accelerates existing Risk Engines without the need for complex systems development or expensive hardware upgrades. MoCaX removes the pricing step bottle-neck that often uses over 90% of computational effort in existing engines and increases capabilities by several orders of magnitude with no loss of accuracy.

MoCaX builds on the new Algorithmic Pricer Acceleration (APA) and Algorithmic Greeks Acceleration (AGA) methods. APA synthesises your existing pricers and creates an accelerated version of them. Even your very slowest and complex pricer, passed through MoCaX, will return the same results (down to 10-15 precision) ultra-fast (up to a few nanoseconds). For example, this enables highly accurate Monte Carlo within Monte Carlo in an instant.

Please ask for a free version of MoCaX so you can test it for yourself: i.ruiz@iruiztechnologies.com

Featured Image

CompatibL is a software application, analytics and consultancy company specializing in Regulation and market and counterparty risk such as FRTB and all XVAs, for which for which it was the winner of Risk magazine’s 2017 award for Specialist Market Risk Vendor of the Year. Compatibl not only offers turnkey solutions for XVA and regulatory needs, but CompatibL’s consultancy teams additionally offer FRTB and pricing / XVA Model validation and development.
CompatibL is at the forefront of many important industry innovations and trends around the trading and risk space, including Adjoint Algorithmic Differentiation (AAD), a proven technique for delivering massive performance gains for the calculation of sensitivities and capital measures.
With a team of over 200 experienced developers and financial engineers, CompatibL has implemented more than 70 major projects across a client base of over 50 banks, central banks, Supranationals and asset managers in the US, EMEA and Asia, including 4 out of 5 largest derivatives dealers.

Featured Image

TriOptima provides risk management services for OTC derivatives, reducing costs and eliminating operational and credit risk through a range of services.

triResolve for proactive reconciliation of OTC derivative portfolios, repository validation and dispute resolution

triReduce for multilateral portfolio compression services across OTC product types

triBalance for rebalancing counterparty risk exposure between multiple CCPs and bilateral relationships

triCalculate for the complete spectrum of counterparty credit risk analytics leveraging state-of-the-art massively parallel computing devices

TriOptima maintains offices in London, New York, Singapore, Stockholm, and Tokyo.

Featured Image

At NAGA, we believe that the financial world is about to change. We build and shape companies of the future. We are on a mission to revolutionize the outdated banking sector.

The financial markets are about to change, and we embrace that.

The NAGA GROUP AG operates financial technology ventures with innovative business models. By offering a streamlined company building process we are able to pursue disruptive ideas in an organized and efficient manner. On our mission to revolutionize the outdated banking sector we follow particular values. We stand for disruptive concepts, an experienced team and a strong technology focus. We passionately believe in technology and that there is a solution to every problem. We want to ease banking services and make it accessible to everyone.
Within a short period of time, NAGA developed to a leading German FINTECH Group.

From day one we were focusing on creating value for our customers. NAGA specifically targets the untouched and inefficient financial market. NAGA was founded in October 2015 and since then experienced a rapid growth. We aim to bring the advantages of financial technology to the masses – making financial markets and virtual goods trading accessible to everyone.

Media Partner (Blockchain)

Media Partner (Blockchain)

Distributed:

Distributed produces a print magazine, online news portal, international event series and weekly newsletter covering enterprise-level blockchain technology. Our products provide professionals with the intelligence, support and expertise they need to navigate the distributed ledger industry.

We explore the business cases, technical considerations, regulatory approaches and projects that will shape the future of industry. Our global team combines critical information with authoritative insight, bringing you closer to the people, projects and perspectives behind this digital revolution.

https://distributed.com/

Featured Image

Over the years, financial professionals around the world have looked to Wiley and the Wiley Finance series with its wide array of bestselling books for the knowledge, insights, and techniques that are essential to success in financial markets. As the pace of change in financial markets and instruments quickens, Wiley continues to respond.



Media Partner (Blockchain)

Media Partner (Blockchain)

Brave New Coin (BNC) is a Data & Research company who has built a superior Market-Data Engine for the Blockchain & Digital Equities industry. We collect, process & index live data from over 100 trading platforms in real-time to produce a number useful data tools for Developers, Traders & Enterprise. 



Media Partner (Blockchain)

Media Partner (Blockchain)

CIOReview is a technology magazine that talks about the enterprise solutions that can redefine the business goals of enterprises tomorrow. It is the leading source that shares innovative enterprise solutions developed by established solutions providers, upcoming hot enterprises and is a neutral source for technology decision makers. Published from Fremont, California, CIOReview is an excellent platform for the enterprise to showcase their innovative solutions.

Media Partner (Blockchain)

Media Partner (Blockchain)

Connecting the Financial Services and Commodities Technology Community, Harrington Starr work with both the world's leading brands and the best talent in the sector to help our customers become more productive and successful. Through talent and opportunity identification, network introductions, thought leading content and a series of events we work hard to ensure added value in every point of contact with our clients.

Media Partner (Blockchain)

Media Partner (Blockchain)

Eventcha.in is the tracking platform of blockchain events worldwide.
Our mission is to help to find a conference, summit, forum, ICO event or meetup that is any person is truly interested in and want to take part in it.
Evencha.in is the project of Byzantium ICO agency which provides a full range of services for conducting and promoting the launching projects.