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Philip Treleaven
University College London
Machine learningComputer scienceArtificial neural networkMedicineTheoretical computer science
71Publications
16H-index
1,299Citations
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Publications 75
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Last. Philip TreleavenH-Index: 16
view all 5 authors...
In this work we introduce QuantNet: an architecture that is capable of transferring knowledge over systematic trading strategies in several financial markets. By having a system that is able to leverage and share knowledge across them, our aim is two-fold: to circumvent the so-called Backtest Overfitting problem; and to generate higher risk-adjusted returns and fewer drawdowns. To do that, QuantNet exploits a form of modelling called Transfer Learning, where two layers are market-specific and an...
#1Adriano Soares Koshiyama (UCL: University College London)H-Index: 4
#2Nick FiroozyeH-Index: 1
Last. Philip Treleaven (UCL: University College London)H-Index: 16
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This paper reviews Artificial Intelligence (AI), Machine Learning (ML) and associated algorithms in future Capital Markets. New AI algorithms are constantly emerging, with each ‘strain’ mimicking a new form of human learning, reasoning, knowledge, and decision-making. The current main disrupting forms of learning include Deep Learning, Adversarial Learning, Transfer and Meta Learning. Albeit these modes of learning have been in the AI/ML field more than a decade, they now are more applicable due...
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#1Zeynep Engin (UCL: University College London)H-Index: 2
#2Justin van Dijk (UCL: University College London)H-Index: 1
Last. Alan Penn (UCL: University College London)H-Index: 24
view all 7 authors...
Abstract Big data analytics and artificial intelligence, paired with blockchain technology, the Internet of Things, and other emerging technologies, are poised to revolutionise urban management. With massive amounts of data collected from citizens, devices, and traditional sources such as routine and well-established censuses, urban areas across the world have – for the first time in history – the opportunity to monitor and manage their urban infrastructure in real-time. This simultaneously prov...
1 CitationsSource
#1Adriano Soares Koshiyama (UCL: University College London)H-Index: 4
#2Nick Firoozye (UCL: University College London)H-Index: 1
Last. Philip Treleaven (UCL: University College London)H-Index: 16
view all 3 authors...
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#1Philip Treleaven (UCL: University College London)H-Index: 16
#2Jeremy BarnettH-Index: 1
Last. Adriano Soares Koshiyama (UCL: University College London)H-Index: 4
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The legal status of AI and algorithms continues to be debated. Resume-sifting algorithms exhibit unethical, discriminatory, and illegal behavior; crime-sentencing algorithms are unable to justify their decisions; and autonomous vehicles' predictive analytics software will make life and death decisions.
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#1Zeynep Engin (UCL: University College London)H-Index: 2
#2Philip Treleaven (UCL: University College London)H-Index: 16
3 CitationsSource
#1Bogdan Batrinca (UCL: University College London)H-Index: 1
#2Christian W. Hesse (UCL: University College London)H-Index: 1
Last. Philip Treleaven (UCL: University College London)H-Index: 16
view all 3 authors...
This study investigates the effect of periodic events, such as the stock index futures and options expiration days and the Morgan Stanley Capital International (MSCI) quarterly index reviews, on the trading volume in the pan-European equity markets. The motivation of this study stems from anecdotal evidence of increased trading volume in the equity markets during the run-up to the index options and futures expiration days and MSCI rebalances. This study investigates this phenomenon in more detai...
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#1Adriano Soares Koshiyama (UCL: University College London)H-Index: 4
#2Nick Firoozye (UCL: University College London)H-Index: 1
Last. Philip Treleaven (UCL: University College London)H-Index: 16
view all 3 authors...
Systematic trading strategies are algorithmic procedures that allocate assets aiming to optimize a certain performance criterion. To obtain an edge in a highly competitive environment, the analyst needs to proper fine-tune its strategy, or discover how to combine weak signals in novel alpha creating manners. Both aspects, namely fine-tuning and combination, have been extensively researched using several methods, but emerging techniques such as Generative Adversarial Networks can have an impact i...
3 Citations
#2Nick FiroozyeH-Index: 1
Last. Philip TreleavenH-Index: 16
view all 3 authors...
Derivative traders are usually required to scan through hundreds, even thousands of possible trades on a daily basis. Up to now, not a single solution is available to aid in their job. Hence, this work aims to develop a trading recommendation system, and apply this system to the so-called Mid-Curve Calendar Spread (MCCS), an exotic swaption-based derivatives package. In summary, our trading recommendation system follows this pipeline: (i) on a certain trade date, we compute metrics and sensitivi...
#1Bogdan Batrinca (UCL: University College London)H-Index: 1
#2Christian W. Hesse (UCL: University College London)H-Index: 1
Last. Philip Treleaven (UCL: University College London)H-Index: 16
view all 3 authors...
There is anecdotal evidence of reduced trading volume in equity markets when other external markets are not trading. This phenomenon can be called the “cross-market holiday effect,” and this study investigates it in detail, providing evidence for the existence of a strong cross-market holiday effect in the pan-European equity markets. The analysis provides an in-depth examination of other aspects like lagged volumes, market capitalization, or multistep ahead modelling. The trading volumes on dat...
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