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Philip C. Treleaven
University College London
75Publications
16H-index
1,216Citations
Publications 75
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#1Zeynep Engin (UCL: University College London)H-Index: 1
#2Zeynep Engin (UCL: University College London)H-Index: 1
Last.Philip C. Treleaven (UCL: University College London)H-Index: 16
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#1Philip C. 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.
#1Bogdan Batrinca (UCL: University College London)H-Index: 1
#2Christian W. Hesse (UCL: University College London)H-Index: 1
Last.Philip C. Treleaven (UCL: University College London)H-Index: 16
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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...
#1Adriano Soares Koshiyama (UCL: University College London)H-Index: 4
#2Nick Firoozye (UCL: University College London)H-Index: 1
Last.Philip C. Treleaven (UCL: University College London)H-Index: 16
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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...
#1Bogdan Batrinca (UCL: University College London)H-Index: 1
#2Christian W. Hesse (UCL: University College London)H-Index: 1
Last.Philip C. 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...
#1Adriano Soares Koshiyama (UCL: University College London)H-Index: 4
#2Nick Firoozye (UCL: University College London)H-Index: 1
Last.Philip C. Treleaven (UCL: University College London)H-Index: 16
view all 3 authors...
Derivative traders are usually required to scan through hundreds, even thousands of possible trades on a daily-basis; a concrete case is the so-called Mid-Curve Calendar Spread (MCCS). The actual procedure in place is full of pitfalls and a more systematic approach where more information at hand is crossed and aggregated to find good trading picks can be highly useful and undoubtedly increase the trader’s productivity. Therefore, in this work we propose an MCCS Recommendation System based on a s...
#1Bogdan Batrinca (UCL: University College London)H-Index: 1
#2Christian W. Hesse (UCL: University College London)H-Index: 1
Last.Philip C. Treleaven (UCL: University College London)H-Index: 16
view all 3 authors...
This study presents an in†depth exploration of market dynamics and analyses potential drivers of trading volume. The study considers established facts from the literature, such as calendar anomalies, the correlation between volume and price change, and this relation's asymmetry, while proposing a variety of time series models. The results identified some key volume predictors, such as the lagged time series volume data and historical price indicators (e.g. intraday range, intraday return, and ...
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...
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