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Leveraging Financial News for Stock Trend Prediction with Attention-Based Recurrent Neural Network. (arXiv:1811.06173v1 [q-fin.CP])

November 15, 2018 by Quantitative Finance at arXiv   Comments (0)

Stock market prediction is one of the most attractive research topic since
the successful prediction on the market's future movement leads to significant
profit. Traditional short term stock market predictions are usually based on
the analysis of historical market data, such as stock prices, moving averages
or daily returns. However, financial news also contains useful information on
public companies and the market. Existing methods in finance literature exploit
sentiment signal features, which...

The effects of non-tariff measures on agri-food trade: a review and meta-analysis of empirical evidence. (arXiv:1811.06323v1 [econ.GN])

November 15, 2018 by Quantitative Finance at arXiv   Comments (0)

The increasing policy interests and the vivid academic debate on non-tariff
measures (NTMs) has stimulated a growing literature on how NTMs affect agrifood
trade. The empirical literature provides contrasting and heterogeneous
evidence, with some studies supporting the standards as catalysts view, and
others favouring the standards as barriers explanation. To the extent that NTMs
can influence trade, understanding the prevailing effect, and the motivations
behind one effect or the other, is a...

On approximations of Value at Risk and Expected Shortfall involving kurtosis. (arXiv:1811.06361v1 [q-fin.RM])

November 15, 2018 by Quantitative Finance at arXiv   Comments (0)

We derive new approximations for the Value at Risk and the Expected Shortfall
at high levels of loss distributions with positive skewness and excess
kurtosis, and we describe their precisions for notable ones such as for
exponential, Pareto type I, lognormal and compound (Poisson) distributions. Our
approximations are motivated by extensions of the so-called Normal Power
Approximation, used for approximating the cumulative distribution function of a
random variable, incorporating not only the...

Clips From Today’s Halftime Report

November 15, 2018 by The Reformed Broker   Comments (0)

David Tepper no longer long Apple from CNBC. Morgan Stanley says Apple a buying opportunity from CNBC. Final Trades: Walmart, Royal Dutch Shell & JPMorgan from CNBC....

Charting the Next Pandemic

November 15, 2018 by Complexity Digest   Comments (0)

This book provides an introduction to the computational and complex systems modeling of the global spreading of infectious diseases. The latest developments in the area of contagion processes modeling are discussed, and readers are exposed to real world examples of data-model integration impacting the decision-making process. Recent advances in computational science and the increasing availability of real-world data are making it possible to develop realistic scenarios and real-time forecasts...

Information | Special Issue : Computational Social Science

November 15, 2018 by Complexity Digest   Comments (0)

The last centuries have seen a great surge in our understanding and control of ‘simple’ physical, chemical, and biological processes through data analysis and the mathematical modelling of their underlying dynamics. Encouraged by its success, researchers have recently embarked on extending such approaches to gain qualitative and quantitative understanding of social and economic systems and the dynamics in and of them. This has become possible due to the massive amounts of data generated by...

Cross-Sectional Variation of Intraday Liquidity, Cross-Impact, and their Effect on Portfolio Execution. (arXiv:1811.05524v1 [q-fin.TR])

November 14, 2018 by Quantitative Finance at arXiv   Comments (0)

The composition of natural liquidity has been changing over time. An analysis
of intraday volumes for the S&P500 constituent stocks illustrates that (i)
volume surprises, i.e., deviations from their respective forecasts, are
correlated across stocks, and (ii) this correlation increases during the last
few hours of the trading session. These observations could be attributed, in
part, to the prevalence of portfolio trading activity that is implicit in the
growth of ETF, passive and systematic...

Stochastic Algorithmic Differentiation of (Expectations of) Discontinuous Functions (Indicator Functions). (arXiv:1811.05741v1 [q-fin.CP])

November 14, 2018 by Quantitative Finance at arXiv   Comments (0)

In this paper we present a method for the accurate estimation of the
derivative (aka.~sensitivity) of expectations of functions involving an
indicator function by combining a stochastic algorithmic differentiation and a
regression.

The method is an improvement of the approach presented in Risk, April 2018.

The algorithmic differentiation is a path-wise method and the path-wise
differentiation of discontinuous payoffs is problematic. A natural approach is
to replace the path-wise automatic...