"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

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Presented at QuantCon Singapore 2016, Quantopian's quantitative finance and algorithmic trading conference, November 11th. This talk will provide a deconstruction of the algorithm development process for a popular and deep area of the quantitative investment world: systematic cross-sectional equity investing, also known as statistical arbitrage or equity market neutral investing. Dr. Jess Stauth will break this workflow into 6 distinct stages, each of which presents its own challenges and opportunities for differentiation to the algorithm developer. During this talk, she will give you an insider's look at how legions of quants at the biggest hedge funds in the world spend their days. She will also briefly explore how innovations in the fintech space have the potential to reshape this workflow and throw open the doors wide open to a new global pool of talent.

Wirtschaft & Finanzen

"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

"The 6 Stages of a Quant Equity Workflow" by Dr. Jessica Stauth, Vice President of Quant Strategy at Quantopian

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"Deep Q-Learning for Trading" by Dr. Tucker Balch, Professor of Interactive C...

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Maxwell will present the methodologies and results behind the algorithm that has been developed by 1QBit, named Quantum Hierarchical Risk Parity, or QHRP. This is an extension of the work done by Marcos Lopez de Prado on Hierarchical Risk Parity in his paper "Building Diversified Portfolios that Outperform Out-of-Sample." QHRP tackles the problem of minimizing the risk of a portfolio of assets using a quantum-inspired approach. Although the ideas surrounding this go back to Markowitz’s mean-variance portfolio optimization of 1952’s Portfolio Selection, we have applied recent quantum-ready machine learning tools to the problem to demonstrate strong performance in terms of a variety of risk measures and lower susceptibility to inaccuracies in the input data. The quantum-ready approach to portfolio optimization is based on an optimization problem that can be solved using a quantum annealer. The algorithm utilizes a hierarchical clustering tree that is based on the covariance matrix of the asset returns. The results of real market data used to benchmark this approach against other common portfolio optimization methods will be shared in this presentation. View the White Paper: https://bit.ly/2k5xTxW.

"Quantum Hierarchical Risk Parity - A Quantum-Inspired Approach to Portfolio ...

"Quantum Hierarchical Risk Parity - A Quantum-Inspired Approach to Portfolio ...

"Quantum Hierarchical Risk Parity - A Quantum-Inspired Approach to Portfolio ...

BlackRock forecasts smart beta investing oriented toward size, value, quality, momentum, and low volatility to reach $1 trillion by 2020 and $2.4 trillion by 2025. Gary’s talk will show that this growth may not be justified due to these factors' lack of robustness, consistency, persistence, intuitiveness, and investability. Gary will also show that the success attributed to these factors would be better directed toward macro momentum and the short interest ratio.

"Snake Oil, Swamp Land, and Factor-Based Investing" by Gary Antonacci, author...

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Deep Learning continues to build out its dominance over other machine learning approaches on several challenging tasks including image, hand-writing, and speech recognition, image synthesis, as well as playing board and computer games exceeding human expert abilities. This has generated a lot of interest in the quant finance community to try and mirror Deep Learning's success in the domain of algorithmic trading. Unfortunately, algorithmic trading poses a unique set of challenges. Specifically, the risk (i.e. uncertainty) of certain trading decisions as well as the fact that market behavior changes over time (i.e. non-stationarity) is not handled well by deep learning. In this talk, I will show how we can embed Deep Learning in the Probabilistic Programming framework PyMC3 and elegantly solve these issues. Expressing neural networks as a Bayesian model naturally instills uncertainty in its predictions. This talk is focused on practitioners and will be introductory and hands-on with many code examples.

"Bayesian Deep Learning: Dealing with Uncertainty and Non-Stationarity" by Dr...

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We will present the most general model of the type considered by Black and Litterman (1991) after fully clarifying the duality between Black–Litterman optimization and Bayesian regression. Our generalization is itself a special case of a Bayesian network or graphical model. As an example, we will work out in full detail the treatment of views on factor risk premia in the context of APT. We will also consider a more speculative example in which the portfolio manager specifies a view on realized volatility by trading a variance swap.

"On the Bayesian Interpretation of Black–Litterman" by Dr. Gordon Ritter, Sen...

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"Don't Lose Your Shirt Trading Mean-Reversion" by Edith Mandel, Principal at ...

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"Quantum Hierarchical Risk Parity - A Quantum-Inspired Approach to Portfolio ...

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Gurley shaw Theory of Monetary Economics.

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