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Stacking with Neural network for Cryptocurrency investment. (arXiv:1902.07855v1 [stat.ML])

February 21, 2019 by Quantitative Finance at arXiv   Comments (0)

Predicting the direction of assets have been an active area of study and a
difficult task. Machine learning models have been used to build robust models
to model the above task. Ensemble methods is one of them showing results better
than a single supervised method. In this paper, we have used generative and
discriminative classifiers to create the stack, particularly 3 generative and 9
discriminative classifiers and optimized over one-layer Neural Network to model
the direction of price...

Deep Adaptive Input Normalization for Price Forecasting using Limit Order Book Data. (arXiv:1902.07892v1 [q-fin.CP])

February 21, 2019 by Quantitative Finance at arXiv   Comments (0)

Deep Learning (DL) models can be used to tackle time series analysis tasks
with great success. However, the performance of DL models can degenerate
rapidly if the data are not appropriately normalized. This issue is even more
apparent when DL is used for financial time series forecasting tasks, where the
non-stationary and multimodal nature of the data pose significant challenges
and severely affect the performance of DL models. In this work, a simple, yet
effective, neural layer, that is...

What is the central bank of Wikipedia?. (arXiv:1902.07920v1 [cs.SI])

February 21, 2019 by Quantitative Finance at arXiv   Comments (0)

We analyze the influence and interactions of 60 largest world banks for 195
world countries using the reduced Google matrix algorithm for the English
Wikipedia network with 5 416 537 articles. While the top asset rank positions
are taken by the banks of China, with China Industrial and Commercial Bank of
China at the first place, we show that the network influence is dominated by
USA banks with Goldman Sachs being the central bank. We determine the network
structure of interactions of banks and...

Clips From Today’s Halftime Report

February 21, 2019 by The Reformed Broker   Comments (0)

 How to trade Roku ahead of earnings and the view on Albemarle in #AskHalftime from CNBC. Wells Fargo’s bearish bank call from CNBC. Final Trades: Winnebago, Albemarle, Disney, Solid Bio & Monster Beverage from CNBC....

The evolution and expanding utility of Ray

February 21, 2019 by The Practical Quant   Comments (0)

[A version of this post appears on the O'Reilly Radar.]There are growing numbers of users and contributors to the framework, as well as libraries for reinforcement learning, AutoML, and data science.In a recent post, I listed some of the early use cases described in the first meetup dedicated to Ray—a distributed programming framework from UC Berkeley’s RISE Lab. A second meetup took place a few months later, and both events featured some of the first applications built with Ray. On the...

Divestment may burst the carbon bubble if investors' beliefs tip to anticipating strong future climate policy. (arXiv:1902.07481v1 [q-fin.GN])

February 21, 2019 by Quantitative Finance at arXiv   Comments (0)

To achieve the ambitious aims of the Paris climate agreement, the majority of
fossil-fuel reserves needs to remain underground. As current national
government commitments to mitigate greenhouse gas emissions are insufficient by
far, actors such as institutional and private investors and the social movement
on divestment from fossil fuels could play an important role in putting
pressure on national governments on the road to decarbonization. Using a
stochastic agent-based model of co-evolving...

Market Impact: A Systematic Study of the High Frequency Options Market. (arXiv:1902.05418v3 [q-fin.TR] UPDATED)

February 21, 2019 by Quantitative Finance at arXiv   Comments (0)

This paper deals with a fundamental subject that has seldom been addressed in
recent years, that of market impact in the options market. Our analysis is
based on a proprietary database of metaorders-large orders that are split into
smaller pieces before being sent to the market on one of the main Asian
markets. In line with our previous work on the equity market [Said et al.,
2018], we propose an algorithmic approach to identify metaorders, based on some
implied volatility parameters, the at...

Matching Refugees to Host Country Locations Based on Preferences and Outcomes. (arXiv:1902.07355v1 [econ.GN])

February 21, 2019 by Quantitative Finance at arXiv   Comments (0)

Facilitating the integration of refugees has become a major policy challenge
in many host countries in the context of the global displacement crisis. One of
the first policy decisions host countries make in the resettlement process is
the assignment of refugees to locations within the country. We develop a
mechanism to match refugees to locations in a way that takes into account their
expected integration outcomes and their preferences over where to be settled.
Our proposal is based on a...

Robust Asset Allocation for Robo-Advisors. (arXiv:1902.07449v1 [q-fin.PM])

February 21, 2019 by Quantitative Finance at arXiv   Comments (0)

In the last few years, the financial advisory industry has been impacted by
the emergence of digitalization and robo-advisors. This phenomenon affects
major financial services, including wealth management, employee savings plans,
asset managers, etc. Since the robo-advisory model is in its early stages, we
estimate that robo-advisors will help to manage around $1 trillion of assets in
2020 (OECD, 2017). And this trend is not going to stop with future generations,
who will live in a...

Large teams develop and small teams disrupt science and technology

February 21, 2019 by Complexity Digest   Comments (0)

One of the most universal trends in science and technology today is the growth of large teams in all areas, as solitary researchers and small teams diminish in prevalence1,2,3. Increases in team size have been attributed to the specialization of scientific activities3, improvements in communication technology4,5, or the complexity of modern problems that require interdisciplinary solutions6,7,8. This shift in team size raises the question of whether and how the character of the science and...