Harvesting Risk Premia

Harvesting Risk Premia

This article is part of a series derived from our most recent Algo Boot Camp, in which we developed a strategy for harvesting risk premia. We have allocated proprietary capital to the strategy, and many of our members are trading it too. In our Boot Camps we develop trading strategies in collaboration with the Robot […]

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The Law of Large Numbers – Part 2

This is Part 2 in our Practical Statistics for Algo Traders blog series—don’t forget to check out Part 1 if you haven’t already.   Even if you’ve never heard of it, the Law of Large Numbers is something that you understand intuitively, and probably employ in one form or another on an almost daily basis. […]

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Practical Statistics for Algo Traders

How do you feel when you see the word “statistics”?  Maybe you sense that it’s something you should be really good at, but aren’t.  Maybe the word gives you a sense of dread, since you’ve started exploring its murky depths, but thrown your hands up in despair and given up – perhaps more than once. […]

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Simulating Variable FX Swaps in Zorro and Python

One of the ongoing research projects inside the Robot Wealth community involves an FX strategy with some multi-week hold periods. Such a strategy can be significantly impacted by the swap, or the cost of financing the position. These costs change over time, and we decided that for the sake of more accurate simulations, we would […]

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Fun with the Cryptocompare API

Cryptocompare is a platform providing data and insights on pretty much everything in the crypto-sphere, from market data for cryptocurrencies to comparisons of the various crytpo-exchanges, to recommendations for where to spend your crypto assets. The user-experience is quite pleasant, as you can see from the screenshot of their real-time coin comparison table: As nice […]

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ETF Rotation Strategies in Zorro

At Robot Wealth we get more questions than even the most sleep-deprived trader can handle. So whilst we develop the algo equivalent of Siri and brag about how we managed to get 6 hours downtime last night, we thought we’d start a new format of blog posts — answering your most burning questions. Lately our […]

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Deep Learning for Trading Part 4: Fighting Overfitting with Dropout and Regularization

This is the fourth in a multi-part series in which we explore and compare various deep learning tools and techniques for market forecasting using Keras and TensorFlow. In Part 1, we introduced Keras and discussed some of the major obstacles to using deep learning techniques in trading systems, including a warning about attempting to extract meaningful signals […]

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Deep Learning for Trading Part 3: Feed Forward Networks

This is the third in a multi-part series in which we explore and compare various deep learning tools and techniques for market forecasting using Keras and TensorFlow. In Part 1, we introduced Keras and discussed some of the major obstacles to using deep learning techniques in trading systems, including a warning about attempting to extract meaningful signals […]

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Deep Learning for Trading Part 2: Configuring TensorFlow and Keras to run on GPU

This is the second in a multi-part series in which we explore and compare various deep learning tools and techniques for market forecasting using Keras and TensorFlow. In Part 1, we introduced Keras and discussed some of the major obstacles to using deep learning techniques in trading systems, including a warning about attempting to extract meaningful […]

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Deep Learning for Trading Part 1: Can it Work?

This is the first in a multi-part series  in which we explore and compare various deep learning tools and techniques for market forecasting using Keras and TensorFlow. In this post, we introduce Keras and discuss some of the major obstacles to using deep learning techniques in trading systems, including a warning about attempting to extract meaningful […]

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