Trading volume and the number of trades: a comparative study using high frequency data

Trading volume and the number of trades are both used as proxies for market activity, with disagreement as to which is the better proxy for market activity. This paper investigates this issue using high frequency data for Cisco and Intel in 1997. A number of econometric methods are used, including GARCH augmented with lagged trading volume and number of trades, tests based on moment restrictions, regression analysis of volatility on volume and trades, normality of returns when standardized by volume and number of trades, and Correlation analysis using volatility generated from GARCH and realized volatility. Our results show that the number of trades is the better proxy for market activity.

Bootstrapping long memory tests: some Monte Carlo results

We investigate the bootstrapped size and power properties of five long memory tests, including the modified R/S, KPSS and GPH tests. In small samples, the moving block bootstrap controls the empirical size of the tests. However, for these sample sizes, the power of bootstrapped tests against fractionally integrated alternatives is often a good deal less than that of asymptotic tests. In larger samples, the power of the five tests is good against common fractionally integrated alternatives - the FI case and the FI with a stochastic volatility error case.

On forecasting daily stock volatility: the role of intraday information and market conditions

Several recent studies advocate the use of nonparametric estimators of daily price vari- ability that exploit intraday information. This paper compares four such estimators, realised volatility, realised range, realised power variation and realised bipower variation, by examining their in-sample distributional properties and out-of-sample forecast ranking when the object of interest is the conventional conditional variance. The analysis is based on a 7-year sample of transaction prices for 14 NYSE stocks. The forecast race is conducted in a GARCH framework and relies on several loss functions. The realized range fares relatively well in the in-sample .t analysis, for instance, regarding the extent to which it brings normality in returns. However, overall the realised power variation provides the most accurate 1-day-ahead forecasts. Fore- cast combination of all four intraday measures produces the smallest forecast errors in about half of the sampled stocks. A market conditions analysis reveals that the additional use of intraday data on day t .. 1 to forecast volatility on day t is most advantageous when day t is a low volume or an up-market day. The results have implications for value-at-risk analysis.

A novel MIMIC-style model of European bank technical efficiency and productivity growth

Using Bayesian Monte Carlo methods, we augment a stochastic distance function measure of bank efficiency and productivity growth with indicators of capitalization, return and risk. Our novel Multiple Indicator-Multiple Cause (MIMIC) style model generates more precise estimates of policy relevant parameters such as returns to scale, technical inefficiency, and productivity growth. We find considerable variation in the performance of EU-15 banks over the period 2008-2015. For the vast majority of banks, productivity growth – the sum of efficiency and technical changes - is negative, implying that the industry would benefit from innovation. We show that greater technical efficiency is associated with higher profitability, higher capital, a lower probability of default and lower return volatility

The Effect of Irrigation Frequency and Farm Yard Manure on Salt Leaching Under Saline – Sodic Soil

Abstract: Northern state, Sudan is extremely affected by desertification and Salinization processes, there for this study aimed to investigate an effective method to improve the salt affected soil. Two field experiments were carried out in two successive seasons ( July 2005 – June 2006 ) at Dongola University farm, in the North State to investigate the effect of irrigation frequency ( 7 and 14 days ) and farm yard manure (M0 , M1 , M2 , andM3 ) on salt leaching undersaline – sodic soil . The experiment was designed in spilt – plot design , where irrigation frequency was assigned in the main plots ( 6x28m) and farm yard manure were the sub – plots ( 6x7m) .The total cultivated area was 1342m2 for each experiment. The quantity of water applied was estimated according to Jensen andHaise (1963 ) . The total water quantity was the same by the end of the season. In general , the result indicated that irrigation frequency of 7 days enhanced salt leaching from the root zone. Generally , the reduction in electrical conductivity ( ECe ) and sodium adsorption ratio ( SAR ) due to irrigation frequency was more effective in 7 day irrigation interval as compared with 14 – day irrigation interval . the data obtained indicated that the addition of FYM 10 ton/feddan, significantly degreased the (ECe) and the (SAR) and leached them below the root zone. So, we can conclude that the efficiency of salt leaching is markedly affected by irrigation frequency and yard manure

Shunt Hybrid Active Power Filter Based on Two Compensation Strategies with PI and Fuzzy Logic Controllers

Industrial designs have tremendously changed within the last decade, with its time and nonlinear variation loads in power frameworks spectrum expanding widely. This revolution has resulted in increased quality control problems such as current unbalance, current and voltage harmonics, flicker and poor power factor in control frameworks. The aim of this paper is to address this problem through the development of Synchronous Reference Frame and Reactive Power (SRF and P-Q) control methods. The DC voltage was regulated to its set reference for providing the current reference using proportional-Integral (PI) and fuzzy logic controllers. From the results, Fuzzy logic control was shown to achieve an adequate DC capacitor energy storage optimization, the sinusoidal type of the current and the change of the power factor. A low Total Harmonic Distortion (THD) that met the suggestions of IEEE- 519 standard on symphonious levels was achieved with the proposed method

Oceanic-like axial crustal high in the central Red Sea

Highlights • Deep seismic data reveal oceanic-like axial ridge beneath central Red Sea. • Axial high is similar to those of hotspot-affected spreading centres. • Bouguer anomalies predict low average density beneath axis. • This low density implies thickened crust and/or low mantle density. • Normal thickness predicted from Na8.0 implies recent transition from thinner crust. Abstract The Red Sea is an important example of a rifted continental shield proceeding to seafloor spreading. However, whether the crust in the central Red Sea is continental or oceanic has been controversial. Contributing to this debate, we assess the basement geometry using seismic reflection and potential field data. We find that the basement topography from seismically derived structure corrected for evaporite and other sediment loading has an axial high with a width of 70–100 km and a height of 0.8–1.6 km. Basement axial highs are commonly found at mid-ocean ridges affected by hotspots, where enhanced mantle melting results in thickened crust. We therefore interpret this axial high as oceanic-like, potentially produced by recently enhanced melting associated with the broader Afar mantle anomaly. We also find the Bouguer gravity anomalies are strongly correlated with basement reflection depths. The apparent density contrast necessary to explain the Bouguer anomaly varies from 220 kg m−3 to 580 kg m−3 with no trend with latitude. These values are too small to be caused primarily by the density contrast between evaporites and mantle across a crust of uniform thickness and density structure, further supporting a thickened crustal origin for the axial high. Complicating interpretation, only a normal to modestly thickened axial crust is predicted from fractionation-corrected sodium contents (Na8.0), and the basement reflection is rugged, more typical of ultra-slow spreading ridges that are not close to hotspots. We try to reconcile these observations with recent results from seismic tomography, which show modest mantle S-wave velocity anomalies under this part of the Red Sea

The impact of the soft errors in convolutional neural network on GPUS: Alexnet as case study

Convolutional Neural Networks (CNNs) have been increasingly deployed in many applications, including safety critical system such as healthcare and autonomous vehicles. Meanwhile, the vulnerability of CNN model to soft errors (e.g., caused by radiation mduced) rapidly increases, thus reliability is crucial especially in real-tmie system. There are many traditional techniques for miprove the reliability of the system, e.g.. Triple Modular Redundancy, but these techniques incur high overheads, which makes them hard to deploy. In tins paper, we experimentally evaluate the vulnerable parts of Alexnet mode (e.g., fault mjector). Results show that FADD and LD are the top vulnerable mstructions against soft errors for Alexnet model, both mstruetions generate at least 84% of injected faults as SDC errors. Thus, these the only parts of the Alexnet model that need to be hardened mstead of usmg fully duplication solutions