Diffusion Approximations for Expert Opinions in a Financial Market with Gaussian Drift. (arXiv:1807.00568v3 [q-fin.PM] UPDATED)

This paper investigates a financial market where returns depend on an unobservable Gaussian drift process. While the observation of returns yields information about the underlying drift, we also incorporate discrete-time expert opinions as an external source of information. For estimating the hidden drift it is crucial to consider the conditional distribution of the drift given…

Optimal Incentive Contract with Endogenous Monitoring Technology. (arXiv:1810.11471v5 [econ.TH] UPDATED)

Recent technology advances have enabled firms to flexibly process and analyze sophisticated employee performance data at a reduced and yet significant cost. We develop a theory of optimal incentive contracting where the monitoring technology that governs the above procedure is part of the designer’s strategic planning. In otherwise standard principal-agent models with moral hazard, we…

Can Deep Learning Predict Risky Retail Investors? A Case Study in Financial Risk Behavior Forecasting. (arXiv:1812.06175v3 [q-fin.RM] UPDATED)

The paper examines the potential of deep learning to support decisions in financial risk management. We develop a deep learning model for predicting whether individual spread traders secure profits from future trades. This task embodies typical modeling challenges faced in risk and behavior forecasting. Conventional machine learning requires data that is representative of the feature-target…

The Impact of Renewable Energy Forecasts on Intraday Electricity Prices. (arXiv:1903.09641v2 [econ.GN] UPDATED)

In this paper we study the impact of errors in wind and solar power forecasts on intraday electricity prices. We develop a novel econometric model which is based on day-ahead wholesale auction curves data and errors in wind and solar power forecasts. The model shifts day-ahead supply curves to calculate intraday prices. We apply our…

Enhancing Time Series Momentum Strategies Using Deep Neural Networks. (arXiv:1904.04912v2 [stat.ML] UPDATED)

While time series momentum is a well-studied phenomenon in finance, common strategies require the explicit definition of both a trend estimator and a position sizing rule. In this paper, we introduce Deep Momentum Networks — a hybrid approach which injects deep learning based trading rules into the volatility scaling framework of time series momentum. The…

Renewal reward perspective on linear switching diffusion systems. (arXiv:1911.07746v1 [q-bio.SC])

In many biological systems, the movement of individual agents is commonly characterized as having multiple qualitatively distinct behaviors that arise from various biophysical states. This is true for vesicles in intracellular transport, micro-organisms like bacteria, or animals moving within and responding to their environment. For example, in cells the movement of vesicles, organelles and other…

Biological Value of Centaurea damascena: Minireview. (arXiv:1911.07788v1 [q-bio.QM])

The family Asteraceae include large number of Centaurea species which have been applied in folk medicine. One of the family Asteraceae members is the Centaurea damascena which authentically been tested for its antibacterial activity. The aim of the study was to discuss antibacterial activities of essential oil composition and methanolic extract of the same plant…

Law of the Minimum Paradoxes. (arXiv:0907.1965v4 [q-bio.PE] UPDATED)

The “Law of the Minimum” states that growth is controlled by the scarcest resource (limiting factor). This concept was originally applied to plant or crop growth (Justus von Liebig, 1840) and quantitatively supported by many experiments. Some generalizations based on more complicated “dose-response” curves were proposed. Violations of this law in natural and experimental ecosystems…

Infinite graphs in systematic biology, with an application to the species problem. (arXiv:1201.2869v7 [q-bio.PE] UPDATED)

We argue that C. Darwin and more recently W. Hennig worked at times under the simplifying assumption of an eternal biosphere. So motivated, we explicitly consider the consequences which follow mathematically from this assumption, and the infinite graphs it leads to. This assumption admits certain clusters of organisms which have some ideal theoretical properties of…

Sleep-like slow oscillations improve visual classification through synaptic homeostasis and memory association in a thalamo-cortical model. (arXiv:1810.10498v5 [q-bio.NC] UPDATED)

The occurrence of sleep passed through the evolutionary sieve and is widespread in animal species. Sleep is known to be beneficial to cognitive and mnemonic tasks, while chronic sleep deprivation is detrimental. Despite the importance of the phenomenon, a complete understanding of its functions and underlying mechanisms is still lacking. In this paper, we show…