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quantech conference - machine learning & ai in quantitative finance conference, london: 16th - 17th november 2017 & blockchain developments in financial markets conference, london: 23rd & 24th november 2017 skip to content toggle navigation quantech conference machine learning & ai in quantitative finance conference, london: 16th - 17th november 2017 & blockchain developments in financial markets conference, london: 23rd & 24th november 2017 speakers about nyc ml conference ml, ai & fintech workshops sponsors book ml nyc contact new york city: machine learning, ai, & fintech in the capital markets new york city: rise of the machines 2018, the next frontier of finance new york city: machine learning & ai in quantitative finance conference header button label:register: machine learning & ai in quantitative finance conference register: machine learning & ai in quantitative finance conference topics: machine learning, ai, & fintech in the capital markets course new york city: may 24th & 25th 2018 financial markets 2018: rise of the machines, the next frontier of finance course new york city: june 7th & 8th 2018 machine learning & ai in quantitative finance conference new york city: june 27th, 28th & 29th 2018 speakers marcelo labre morgan stanley executive director sol steinberg otc partners founding principle miquel noguer alonso columbia university adjunct assistant professor igor halperin nyu tandon school of engineering research professor of financial machine learning gordon ritter gsa capital senior portfolio manager peter decrem citigroup director shengquan zhou bloomberg lp quantitative researcher michael beal data capital management ceo jared broad quantconnect ceo leigh drogen: estimize founder and ceo ksenia shnyra deloitte senior advisor luis cota susquehanna international group, llp (sig) systematic trading & research new york city: machine learning & ai in quantitative finance conference, june 27th, 28th & 29th 2018 special offer: 25% super early bird discount until friday may 18th 2018. when 2 colleagues attend the 3rd goes free! new york city: machine learning & ai in quantitative finance conference workshop day: wednesday june 27th main conference + workshop ($250 discount) machine learning, ai, & fintech in the capital markets by sol steinberg the capital markets have changed forever, the machines are replacing decision making, order flow, risk management, valuation, and much more. explore these changes and be prepared to add value in the transformation of the capital markets. the course: the ai impact on capital markets has never been profound as it is in the present times. ai has certainly taken the finance world, especially banking and investment services by storm. artificial intelligence is a suite that comprises of a set of tools- like machine learning, natural language processing, deep neural networks etc. that are impacting almost every industry, in the most efficient way. at its core, ai is essentially a set of technologies that are meant to augment or perform human tasks, without their intervention. over a few decades, these technologies have evolved to sense, learn, comprehend, and act. such a progression now enable systems and software to acquire, identify, recognize, and an analytical database (both structured and unstructured), derive insights, envision the process, and then put them into the real-time use cases. in context to capital market, ai is enabling the machines to do algorithmic trading, qualitative analysis, automate trade execution, and manage risk. what turns ai set a disruption in almost every industry is its decision making ability, which is based on cognitive learning. in contrast to perpetuating up on the programmed responses, ai overcome the limitations, complexities, and challenges by teaching the system to learn through past experiences. despite being the hot buzzword on wall street these days, machine learning is still fairly misunderstood. it is not artificial intelligence itself, but rather a form of it in which computers fed extremely large data sets are able to learn as changes in that data occur without being explicitly programmed to do so. the data is just one part of the approach, what can be more challenging is making machine learning and data science a core capability among companies so that they instinctively take internal and external data sets and interpret it for patterns, risks, and opportunities. machine learning is shifting your trading counterparty to engineers and quants, it is critical you understand this evolution. location downtown conference center 157 william street new york, ny 10038 usa tel: +1 212 618 6990 www.downtownmeetings.com course modules module 1 modern market structure looking beyond 2020: the rise of alternative technology, marketplaces, and products such as exchange traded derivatives, and crypto currencies. exchanges, clearing houses, and collateral exchange traded & otc derivative landscape big data, ai, and machine learning in trading, finance, and operations module 2 hft, connectivity, & ai in trading- have we hit a wall? how competitors have reached critical mass combating hft? iex launches hft proof exchange, reviewing the offering and why it works and why it doesn’t matter anymore. case study: no more traders? how market leader jpm is automating almost their entire worldwide trading business – eventually case study: hedge fund renaissance & artificial intelligence greatest success story in the markets- how renaissance’s medallion fund became finance’s blackest box module 3 big data in the financial eco-system: financial modelling, 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 module 4 machine learning models: what is your best fit use in your business? supervised learning, unsupervised learning models, reinforcement learning, deep learning machine learning in analysis: momentum and mean reversion, sentiment analysis, asymmetric trading strategies machines at war (trading): non linear multi-factor models, high frequency trading, advanced machine learning module 5 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 how you will benefit: 1. gain a profound understanding of what lies ahead of you in the rapidly changing capital markets driven by machine learning. 2. understand other new technology that is impacting the markets and what fintech offering is next to impact the market. 3. explore relevant risk factors of machine learning that keep market participants up at night. understand how to diagnose these risk factors in a volatile market. 4. participants will be better equipped to understand the unique dynamics of the markets. how various factors push and pull, effecting other areas of the market. how automation, big data, machine learning, regulation, collateral management, and high-frequency trading have an impact on market conditions. 5. participants will address big data, machine learning, automation, fintech solutions, trading workflow, and market structure. delegate challenges/your solutions: challenge #1 : “i don’t understand what is driving machine learning in the market?” participants will come away from this class understanding not only market structure but the factors that are affecting technology in the market and what to expect in the future in terms of machine learning, big data, and a.i. affecting our ecosystem. challenge #2 : “i don’t understand the new technology such as big data, blockchain, hft, or crypto currency.” after attending our course participants will have a deep and profound understanding of the technology behind the crypt

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http://quantechconference.com/
http://quantechconference.com//#machinelearning
http://quantechconference.com//mailto:[email protected]
http://quantechconference.com//#contactinfo
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Domain Name: quantechconference.com
Registrar URL: http://www.godaddy.com
Registrant Name: Neil Fowler
Registrant Organization: BTRM
Name Server: NS1.LIVEDNS.CO.UK
Name Server: NS2.LIVEDNS.CO.UK
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