On the Perils of Security Pricing by Financial Intermediaries: The Case of Open-End Mutual Funds

There are many instances where financial claims trade at prices set by intermediaries. Pricing by an intermediary introduces the potential for economic distortions from innumerable sources. As one example, we show that nonsynchronous-trading generates predictable, readily exploitable, changes in mutual fund-share prices (NAV). The exploitation of predictable changes in mutual fund NAVs involved a wealth transfer from buy-and-hold fund investors to active fund traders and is costly to all fund investors. A simple modification to the mutual fund pricing algorithm eliminates much of this predictability, but nonsynchronous trading is just one of the issues intermediaries face when setting prices.

Spin and lattice excitations of a BiFeO3 thin film and ceramics

We present a comprehensive study of polar and magnetic excitations in BiFeO3 ceramics and a thin film epitaxially grown on an orthorhombic (110) TbScO3 substrate. Infrared reflectivity spectroscopy was performed at temperatures from 5 to 900 K for the ceramics and below room temperature for the thin film. All 13 polar phonons allowed by the factor-group analysis were observed in theceramic samples. The thin-film spectra revealed 12 phonon modes only and an additional weak excitation, probably of spin origin. On heating towards the ferroelectric phase transition near 1100 K, some phonons soften, leading to an increase in the static permittivity. In the ceramics, terahertz transmission spectra show five low-energy magnetic excitations including two which were not previously known to be infrared active; at 5 K, their frequencies are 53 and 56 cm-1. Heating induces softening of all magnetic modes. At a temperature of 5 K, applying an external magnetic field of up to 7 T irreversibly alters the intensities of some of these modes. The frequencies of the observed spin excitations provide support for the recently developed complex model of magnetic interactions in BiFeO3 (R.S. Fishman, Phys. Rev. B 87, 224419 (2013)). The simultaneous infrared and Raman activity of the spin excitations is consistent with their assignment to electromagnons

From Sensor Readings to Predictions: On the Process of Developing Practical Soft Sensors.

Automatic data acquisition systems provide large amounts of streaming data generated by physical sensors. This data forms an input to computational models (soft sensors) routinely used for monitoring and control of industrial processes, traffic patterns, environment and natural hazards, and many more. The majority of these models assume that the data comes in a cleaned and pre-processed form, ready to be fed directly into a predictive model. In practice, to ensure appropriate data quality, most of the modelling efforts concentrate on preparing data from raw sensor readings to be used as model inputs. This study analyzes the process of data preparation for predictive models with streaming sensor data. We present the challenges of data preparation as a four-step process, identify the key challenges in each step, and provide recommendations for handling these issues. The discussion is focused on the approaches that are less commonly used, while, based on our experience, may contribute particularly well to solving practical soft sensor tasks. Our arguments are illustrated with a case study in the chemical production industry

THE INFLUENCE OF SILAGE ADDITIVES FOR QUALITATIVE PARAMETERS OF CLOVER-GRASS SILAGES

We observed the infl uence of silage additives for choice qualitative parameters at 109 samples of clovergrass silages in working conditions. We evaluated total classifi cation and categorization to quality classes according to fermentation process. It has been found out positive effect of the silage additives for fermentation class and for total silage quality of silages. This positive effec t has been more considerable at classifi cation to the fermentation classes at clover-grass silages. The high content of crude fi bre decreased fermentation results and total silage quality at test clover-grass silages. The greatest (deterioration) infl uence for clasifi cation to total quality class has crude fi bre content. It is see from correlation coefi cient at clover-grass silages – r = 0,75 (P < 0,05). The weak dependence r = 0,37 (P < 0,05) was detected between fermentation class and acetic acid content. It was detected large dependence between fermentation class and butyric acid content r = 0,73 (P < 0,05)

VLIV ADITIV NA VYBRANÉ KVALITATIVNÍ UKAZATELE JETELOTRAVNÍCH SILÁŽÍ

We observed the infl uence of silage additives for choice qualitative parameters at 109 samples of clovergrass silages in working conditions. We evaluated total classifi cation and categorization to quality classes according to fermentation process. It has been found out positive effect of the silage additives for fermentation class and for total silage quality of silages. This positive effec t has been more considerable at classifi cation to the fermentation classes at clover-grass silages. The high content of crude fi bre decreased fermentation results and total silage quality at test clover-grass silages. The greatest (deterioration) infl uence for clasifi cation to total quality class has crude fi bre content. It is see from correlation coefi cient at clover-grass silages – r = 0,75 (P < 0,05). The weak dependence r = 0,37 (P < 0,05) was detected between fermentation class and acetic acid content. It was detected large dependence between fermentation class and butyric acid content r = 0,73 (P < 0,05).U 109 vzorků jetelotravních siláží byl v provozních podmínkách sledován vliv silážních aditiv na kvalitativní ukazatele. Posuzováno bylo jednak celkové zatřídění a zařazení do tříd jakosti podle fermentačního procesu. U silážovaných krmiv bylo potvrzeno, že aditiva mají pozitivní vliv na fermentační proces a tím i na celkovou kvalitu siláží. Tento pozitivní vliv byl ještě více patrný na zatřídění do třídy fermentace. Vysoký obsah vlákniny u sledovaných silážovaných krmiv zhoršoval fermentační výsledky i celkovou jakost siláží. Z korelačních koefi cientů hodnotící jetelotravní siláže je patrné, že největší (zhoršující) vliv na zařazení do celkové třídy jakosti má množství vlákniny r 0,75 (P < 0,05). Mírná závislost r 0,37 (P < 0,05) byla zjištěna mezi třídou fermentace a obsahem kyseliny octové. Mezi třídou fermentace a obsahem kyseliny máselné byla zjištěna velká závislost r 0,73 (P < 0,05)