A simple note on Herd Behaviour

In his "Simple model of herd behaviour", Banerjee (1992) shows that - in a sequential game - if the first two players have chosen the same action, player 3 and all subsequent players will ignore his/her own information and start a herd, an irreversible one. In this paper we analyse the role played by the tie-breaking assumptions in reaching the equilibrium. We showed that: players' strategies are parameter dependent; an incorrect herd could be reversed; a correct herd is irreversible.Herd behaviour; Run

Microscopic models of financial markets

This review deals with several microscopic models of financial markets which have been studied by economists and physicists over the last decade: Kim-Markowitz, Levy-Levy-Solomon, Cont-Bouchaud, Solomon-Weisbuch, Lux-Marchesi, Donangelo-Sneppen and Solomon-Levy-Huang. After an overview of simulation approaches in financial economics, we first give a summary of the Donangelo-Sneppen model of monetary exchange and compare it with related models in economics literature. Our selective review then outlines the main ingredients of some influential early models of multi-agent dynamics in financial markets (Kim-Markowitz, Levy-Levy-Solomon). As will be seen, these contributions draw their inspiration from the complex appearance of investors' interactions in real-life markets. Their main aim is to reproduce (and, thereby, provide possible explanations) for the spectacular bubbles and crashes seen in certain historical episodes, but they lack (like almost all the work before 1998 or so) a perspective in terms of the universal statistical features of financial time series. In fact, awareness of a set of such regularities (power-law tails of the distribution of returns, temporal scaling of volatility) only gradually appeared over the nineties. With the more precise description of the formerly relatively vague characteristics (e.g. moving from the notion of fat tails to the more concrete one of a power-law with index around three), it became clear that financial markets dynamics give rise to some kind of universal scaling laws. Showing similarities with scaling laws for other systems with many interacting subunits, an exploration of financial markets as multi-agent systems appeared to be a natural consequence. This topic was pursued by quite a number of contributions appearing in both the physics and economics literature since the late nineties. From the wealth of different flavors of multi-agent models that have appeared by now, we discuss the Cont-Bouchaud, Solomon-Levy-Huang and Lux-Marchesi models. Open research questions are discussed in our concluding section. --

Fabric phase sorptive extraction: A paradigm shift approach in analytical and bioanalytical sample preparation

Fabric phase sorptive extraction (FPSE) is an evolutionary sample preparation approach which was introduced in 2014, meeting all green analytical chemistry (GAC) requirements by implementing a natural or synthetic permeable and flexible fabric substrate to host a chemically coated sol–gel organic–inorganic hybrid sorbent in the form of an ultra-thin coating. This construction results in a versatile, fast, and sensitive micro-extraction device. The user-friendly FPSE membrane allows direct extraction of analytes with no sample modification, thus eliminating/minimizing the sample pre-treatment steps, which are not only time consuming, but are also considered the primary source of major analyte loss. Sol–gel sorbent-coated FPSE membranes possess high chemical, solvent, and thermal stability due to the strong covalent bonding between the fabric substrate and the sol–gel sorbent coating. Subsequent to the extraction on FPSE membrane, a wide range of organic solvents can be used in a small volume to exhaustively back-extract the analytes after FPSE process, leading to a high preconcentration factor. In most cases, no solvent evaporation and sample reconstitution are necessary. In addition to the extensive simplification of the sample preparation workflow, FPSE has also innovatively combined the extraction principle of two major, yet competing sample preparation techniques: Solid phase extraction (SPE) with its characteristic exhaustive extraction, and solid phase microextraction (SPME) with its characteristic equilibrium driven extraction mechanism. Furthermore, FPSE has offered the most comprehensive cache of sorbent chemistry by successfully combining almost all of the sorbents traditionally used exclusively in either SPE or in SPME. FPSE is the first sample preparation technique to exploit the substrate surface chemistry that complements the overall selectivity and the extraction efficiency of the device. As such, FPSE indeed represents a paradigm shift approach in analytical/bioanalytical sample preparation. Furthermore, an FPSE membrane can be used as an SPME fiber or as an SPE disk for sample preparation, owing to its special geometric advantage. So far, FPSE has overwhelmingly attracted the interest of the separation scientist community, and many analytical scientists have been developing new methodologies by implementing this cutting-edge technique for the extraction and determination of many analytes at their trace and ultra-trace level concentrations in environmental samples as well as in food, pharmaceutical, and biological samples. FPSE offers a total sample preparation solution by providing neutral, cation exchanger, anion exchanger, mixed mode cation exchanger, mixed mode anion exchanger, zwitterionic, and mixed mode zwitterionic sorbents to deal with any analyte regardless of its polarity, ionic state, or the sample matrix where it resides. Herein we present the theoretical background, synthesis, mechanisms of extraction and desorption, the types of sorbents, and the main applications of FPSE so far according to different sample categories, and to briefly show the progress, advantages, and the main principles of the proposed technique

Microscopic models of financial markets

This review deals with several microscopic models of financial markets which have been studied by economists and physicists over the last decade: Kim-Markowitz, Levy-Levy-Solomon, Cont-Bouchaud, Solomon-Weisbuch, Lux-Marchesi, Donangelo-Sneppen and Solomon-Levy-Huang. After an overview of simulation approaches in financial economics, we first give a summary of the Donangelo-Sneppen model of monetary exchange and compare it with related models in economics literature. Our selective review then outlines the main ingredients of some influential early models of multi-agent dynamics in financial markets (Kim-Markowitz, Levy-Levy-Solomon). As will be seen, these contributions draw their inspiration from the complex appearance of investors' interactions in real-life markets. Their main aim is to reproduce (and, thereby, provide possible explanations) for the spectacular bubbles and crashes seen in certain historical episodes, but they lack (like almost all the work before 1998 or so) a perspective in terms of the universal statistical features of financial time series. In fact, awareness of a set of such regularities (power-law tails of the distribution of returns, temporal scaling of volatility) only gradually appeared over the nineties. With the more precise description of the formerly relatively vague characteristics (e.g. moving from the notion of fat tails to the more concrete one of a power-law with index around three), it became clear that financial markets dynamics give rise to some kind of universal scaling laws. Showing similarities with scaling laws for other systems with many interacting subunits, an exploration of financial markets as multi-agent systems appeared to be a natural consequence. This topic was pursued by quite a number of contributions appearing in both the physics and economics literature since the late nineties. From the wealth of different flavors of multi-agent models that have appeared by now, we discuss the Cont-Bouchaud, Solomon-Levy-Huang and Lux-Marchesi models. Open research questions are discussed in our concluding section

Phytochemical profiles and antioxidant capacity of pigmented and non-pigmented genotypes of rice (Oryza sativa L.)

Pigmented rice (Oryza sativa L.) genotypes become increasingly important in the agroindustry due to their bioavailable compounds that have the ability to inhibit the formation and/or to reduce the effective concentration of reactive cell-damaging free radicals. This study aimed at determining the concentrations of free, and bound phytochemicals and their antioxidant potential (DPPH and ABTS assays) as well as the vitamin E and carotenoids contents of non-pigmented and pigmented rice genotypes. The results confirmed that the content of total phenolics and flavonoids contents, as well as the antioxidant capacity (DPPH and ABTS assays) of pigmented rice was several-fold greater than non-pigmented ones (4, 4, 3 and 5 times, respectively). Compounds in the free fraction of pigmented rice had higher antioxidant capacity relative to those in the bound form, whereas the non-pigmented rice cultivars exhibited the opposite trend. Ferulic acid was the main phenolic acid of all rice genotypes, whereas black rice contained protocatechuic and vanillic acids in higher contents than red rice and non-pigmented rice genotypes. For vitamin E (tocopherols and tocotrienols) and carotenoids (lutein, zeaxanthin and β-carotene) contents, no obvious concentration differences were observed between non-pigmented and pigmented rice, with the black rice exhibiting the highest carotenoid content. Overall, pigmented rice genotypes contain a remarkable amount of bioactive compounds with high antioxidant capacity; therefore, they have great potential as a source of bioactives for developing functional food products with improved health benefits

The distribution of landed property

The distribution of property is established through various mechanisms. In this paper we study the acreage distribution of land plots owned by natural persons in the Zl\'{\i}n Region of the Czech Republic. We show that the data are explained in terms of a simple model in which the inheritance and market behavior are combined.Comment: The distribution of landed propert

Volatility Cluster and Herding

Stock markets can be characterized by fat tails in the volatility distribution, clustering of volatilities and slow decay of their time correlations. For an explanation models with several mechanisms and consequently many parameters as the Lux-Marchesi model have been used. We show that a simple herding model with only four parameters leads to a quantitative description of the data. As a new type of data we describe the volatility cluster by the waiting time distribution, which can be used successfully to distinguish between different models.Comment: 15 pages TeX, 6 figures PostScrip