Temporal mixture ensemble models for probabilistic forecasting of intraday cryptocurrency volume

We study the problem of the intraday short-term volume forecasting in cryptocurrency multi-markets. The predictions are built by using transaction and order book data from different markets where the exchange takes place. Methodologically, we propose a temporal mixture ensemble, capable of adaptively exploiting, for the forecasting, different sources of data and providing a volume point estimate, as well as its uncertainty. We provide evidence of the clear outperformance of our model with respect to econometric models. Moreover our model performs slightly better than Gradient Boosting Machine while having a much clearer interpretability of the results. Finally, we show that the above results are robust also when restricting the prediction analysis to each volume quartile

Variety and Volatility in Financial Markets

We study the price dynamics of stocks traded in a financial market by considering the statistical properties both of a single time series and of an ensemble of stocks traded simultaneously. We use the $n$ stocks traded in the New York Stock Exchange to form a statistical ensemble of daily stock returns. For each trading day of our database, we study the ensemble return distribution. We find that a typical ensemble return distribution exists in most of the trading days with the exception of crash and rally days and of the days subsequent to these extreme events. We analyze each ensemble return distribution by extracting its first two central moments. We observe that these moments are fluctuating in time and are stochastic processes themselves. We characterize the statistical properties of ensemble return distribution central moments by investigating their probability density functions and temporal correlation properties. In general, time-averaged and portfolio-averaged price returns have different statistical properties. We infer from these differences information about the relative strength of correlation between stocks and between different trading days. Lastly, we compare our empirical results with those predicted by the single-index model and we conclude that this simple model is unable to explain the statistical properties of the second moment of the ensemble return distribution.Comment: 10 pages, 11 figure

Long-term prediction of adherence to continuous positive air pressure therapy for the treatment of moderate/severe obstructive sleep apnea syndrome

BACKGROUND: Continuous positive airway pressure (CPAP) therapy is a highly effective treatment for obstructive sleep apnea syndrome (OSAS). However, poor adherence is a limiting factor, and a significant proportion of patients are unable to tolerate CPAP. The aim of this study was to determine predictors of long-term non-compliance with CPAP. METHODS: CPAP treatment was prescribed to all consecutive patients with moderate or severe OSAS (AHI ≥15 events/h) (n = 295) who underwent a full-night CPAP titration study at home between February 1, 2002 and December 1, 2016. Adherence was defined as CPAP use for at least 4 h per night and five days per week. Subjects had periodical follow-up visits including clinical and biochemical evaluation and assessment of adherence to CPAP. RESULTS: Median follow-up observation was 74.8 (24.2/110.9) months. The percentage of OSAS patients adhering to CPAP was 41.4% (42.3% in males and 37.0% in females), and prevalence was significantly higher in severe OSAS than in moderate (51.8% vs. 22.1%; p < 0.001; respectively). At multivariate analysis, lower severity of OSAS (HR = 0.66; CI 95 0.46-0.94) p < 0.023), cigarette smoking (HR = 1.72; CI 95 1.13-2.61); p = 0.011), and previous cardiovascular events (HR = 1.95; CI 95 1.03-3.70; p = 0.04) were the only independent predictors of long-term non-adherence to CPAP after controlling for age, gender, and metabolic syndrome. CONCLUSIONS: In our cohort of patients with moderate/severe OSAS who were prescribed CPAP therapy, long-term compliance to treatment was present in less than half of the patients. Adherence was positively associated with OSAS severity and negatively associated with cigarette smoking and previous cardiovascular events at baseline

Kepler-91b: a planet at the end of its life. Planet and giant host star properties via light-curve variations

The evolution of planetary systems is intimately linked to the evolution of their host star. Our understanding of the whole planetary evolution process is based on the large planet diversity observed so far. To date, only few tens of planets have been discovered orbiting stars ascending the Red Giant Branch. Although several theories have been proposed, the question of how planets die remains open due to the small number statistics. In this work we study the giant star Kepler-91 (KOI-2133) in order to determine the nature of a transiting companion. This system was detected by the Kepler Space Telescope. However, its planetary confirmation is needed. We confirm the planetary nature of the object transiting the star Kepler-91 by deriving a mass of $M_p=0.88^{+0.17}_{-0.33} ~M_{\rm Jup}$ and a planetary radius of $R_p=1.384^{+0.011}_{-0.054} ~R_{\rm Jup}$. Asteroseismic analysis produces a stellar radius of $R_{\star}=6.30\pm 0.16 ~R_{\odot}$ and a mass of $M_{\star}=1.31\pm 0.10 ~ M_{\odot}$. We find that its eccentric orbit ($e=0.066^{+0.013}_{-0.017}$) is just $1.32^{+0.07}_{-0.22} ~ R_{\star}$ away from the stellar atmosphere at the pericenter. Kepler-91b could be the previous stage of the planet engulfment, recently detected for BD+48 740. Our estimations show that Kepler-91b will be swallowed by its host star in less than 55 Myr. Among the confirmed planets around giant stars, this is the planetary-mass body closest to its host star. At pericenter passage, the star subtends an angle of $48^{\circ}$, covering around 10% of the sky as seen from the planet. The planetary atmosphere seems to be inflated probably due to the high stellar irradiation.Comment: 21 pages, 8 tables and 11 figure

Identification of Silver and Palladium in Irradiated TRISO Coated Particles of the AGR-1 Experiment

Evidence of the release of certain metallic fission products through intact tristructural isotropic (TRISO) particles has been seen for decades around the world, as well as in the recent AGR-1 experiment at the Idaho National Laboratory (INL). However, understanding the basic mechanism of transport is still lacking. This understanding is important because the TRISO coating is part of the high temperature gas-cooled reactor functional containment and critical for the safety strategy for licensing purposes. Our approach to identify fission products in irradiated AGR-1 TRISO fuel using scanning transmission electron microscopy (STEM), Electron Energy-Loss Spectroscopy (EELS) and Energy Filtered TEM (EFTEM), has led to first-of-a-kind data at the nano-scale indicating the presence of silver at triple-points and grain boundaries of the SiC layer in the TRISO particle. Cadmium was also found in the triple junctions. In this initial study, the silver was only identified in SiC grain boundaries and triple points on the edge of the SiC-IPyC interface up to a depth of approximately 0.5 μm. Palladium was identified as the main constituent of micron-sized precipitates present at the SiC grain boundaries. Additionally spherical nano-sized palladium rich precipitates were found inside the SiC grains. No silver was found in the center of the micron-sized fission product precipitates using these techniques, although silver was found on the outer edge of one of the Pd-U-Si containing precipitates which was facing the IPyC layer. Only Pd-U containing precipitates were identified in the IPyC layer and no silver was identified in the IPyC layer. The identification of silver alongside the SiC grain boundaries and the findings of Pd inside the SiC grains and alongside SiC grain boundaries provide important information needed to understand silver and palladium transport in TRISO fuel, which has been the topic of international research for the past forty years. The findings reported in this paper may support the postulations of recent research that Ag transport may be driven by grain boundary diffusion. However, more work is needed to fully understand the transport mechanisms. Additionally, the usefulness of the advanced electron microscopic techniques for TRISO coated particle research is demonstrated in this paper

Calibration of optimal execution of financial transactions in the presence of transient market impact

Trading large volumes of a financial asset in order driven markets requires the use of algorithmic execution dividing the volume in many transactions in order to minimize costs due to market impact. A proper design of an optimal execution strategy strongly depends on a careful modeling of market impact, i.e. how the price reacts to trades. In this paper we consider a recently introduced market impact model (Bouchaud et al., 2004), which has the property of describing both the volume and the temporal dependence of price change due to trading. We show how this model can be used to describe price impact also in aggregated trade time or in real time. We then solve analytically and calibrate with real data the optimal execution problem both for risk neutral and for risk averse investors and we derive an efficient frontier of optimal execution. When we include spread costs the problem must be solved numerically and we show that the introduction of such costs regularizes the solution.Comment: 31 pages, 8 figure

Algebraic Correlation Function and Anomalous Diffusion in the HMF model

In the quasi-stationary states of the Hamiltonian Mean-Field model, we numerically compute correlation functions of momenta and diffusion of angles with homogeneous initial conditions. This is an example, in a N-body Hamiltonian system, of anomalous transport properties characterized by non exponential relaxations and long-range temporal correlations. Kinetic theory predicts a striking transition between weak anomalous diffusion and strong anomalous diffusion. The numerical results are in excellent agreement with the quantitative predictions of the anomalous transport exponents. Noteworthy, also at statistical equilibrium, the system exhibits long-range temporal correlations: the correlation function is inversely proportional to time with a logarithmic correction instead of the usually expected exponential decay, leading to weak anomalous transport properties

Similarity solutions of Fokker-Planck equation with time-dependent coefficients

In this work, we consider the solvability of the Fokker-Planck equation with both time-dependent drift and diffusion coefficients by means of the similarity method. By the introduction of the similarity variable, the Fokker-Planck equation is reduced to an ordinary differential equation. Adopting the natural requirement that the probability current density vanishes at the boundary, the resulted ordinary differential equation turns out to be integrable, and the probability density function can be given in closed form. New examples of exactly solvable Fokker-Planck equations are presented, and their properties analyzed.Comment: 13 pages, 8 figures. Version to appear in Ann. Phys. Presentation improved. Discussions and figures of easy examples remove

Emergence of long memory in stock volatility from a modified Mike-Farmer model

The Mike-Farmer (MF) model was constructed empirically based on the continuous double auction mechanism in an order-driven market, which can successfully reproduce the cubic law of returns and the diffusive behavior of stock prices at the transaction level. However, the volatility (defined by absolute return) in the MF model does not show sound long memory. We propose a modified version of the MF model by including a new ingredient, that is, long memory in the aggressiveness (quantified by the relative prices) of incoming orders, which is an important stylized fact identified by analyzing the order flows of 23 liquid Chinese stocks. Long memory emerges in the volatility synthesized from the modified MF model with the DFA scaling exponent close to 0.76, and the cubic law of returns and the diffusive behavior of prices are also produced at the same time. We also find that the long memory of order signs has no impact on the long memory property of volatility, and the memory effect of order aggressiveness has little impact on the diffusiveness of stock prices.Comment: 6 pages, 6 figures and 1 tabl