27-28 June 2018, Central London
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In this course you’ll learn how to build and apply Machine Models for modelling the behaviour of asset prices and other time series, and to optimize your own strategies.
After this course you:
- will have a good understanding of the field of Machine Learning
- know about the various models and be aware of the dos and don’ts
- will be able to build your own highly advanced models
- Unsupervised Learning models: Finding clusters
- Training a bot to play Blackjack
- Speeding up pricing models with Neural Network function approximation
- Modelling probability densities with Kernel Methods and Gaussian Mixture Models
- Realistic simulation of Open/High/Low/Close volume bars
- Extracting Stochastic Differential Equations from time series data with Neural Network function approximation
- Modeling the dynamics of complex time series that have memory and non-Gaussian returns: How to outperform GARCH with Recurrent Neural Networks
- Tools and techniques to prevent models blowing up
- Non-linear dimension reduction with Autoencoders as a substitute for PCA
- Building multi-factor Monte Carlo simulations that capture non-linear interactions with Variational Autoencoders
- Simple and accurate arbitrage-free Implied Volatility smile modelling with GMM
- Modelling intraday volume and volatility with Recurrent Neural Networks
- Pricing complex contracts with Reinforcement Learning methods
- Optimizing investment strategies, learning the Kelly criterion from real-world data
- Pairs trading, scanning portfolios for investment opportunities
- Filling in missing data with denoising autoencoders
Cost: £1500+VAT (Earlybird price of £995 until 15th May)
Book your place now
Thijs van den Berg is founder of sitmo.com and an Independent Machine Learning and Risk consultant, mainly in the Financial Sector.
In the past Thijs has worked in various roles ranging from being a successful option trader on the exchange floor for four years, to being head of the modelling and research department at a large European energy trading firm, supervising PhDs and managing IT staff. In that role a wide spectrum of innovative modeling needs was addressed: building models for asset valuation for new investments and M&A, asset dispatch optimization, modelling energy and commodity spot/forward curves, weather and load forecasting, pricing exotic derivatives, credit modelling.
For the last 15 years Thijs has been working as a consultant in the Energy and Financial sector, researching, building and validation a wide range of models in pricing, risk management and prediction. Notable clients are Dutch government, ING Bank, Rabo Bank, SNS bank, Cardano, Shell, Vattenfall, Nidera, Enel, Cardano AEGON, PGGM, Boskalis.
Thijs ranked in the top 0.5% at Kaggle, a platform where AI coders compete on projects, often with financial rewards. He’s also a contributor to the highly acclaimed open-source Boost C++ libraries.
Paul Wilmott is a researcher, author, consultant, lecturer and expert witness working in risk management, derivatives and most things quantitative in finance. He has written over 100 research papers in mathematics and finance, and several best-selling, and some would say ground-breaking, text books including: Paul Wilmott On Quantitative Finance, Paul Wilmott Introduces Quantitative Finance and Frequently Asked Questions in Quantitative Finance. He founded the website you are now reading, the eponymous quant magazine, a successful volatility arbitrage hedge fund and the world’s largest, high-level quant education program, the Certificate in Quantitative Finance. Paul is one of the authors of the Financial Modelers’ Manifesto.
Paul Wilmott has been called “cult derivatives lecturer” (Financial Times), “the smartest of the quants, he may be the only smart quant” (Portfolio magazine), “the finance industry’s Mozart” (Sunday Business), “financial mathematics guru” (BBC), “arguably the most influential quant today” (Newsweek) and “egocentric” (some bloke called Taleb). He can often be found in the pages of books by this same Taleb as an illustration of extreme behaviour.