Chapter 5 FinTechs, BigTechs and structural changes in capital markets

This chapter aims at exploring some theoretical issues associated with the impact of technology companies on the market structure in the financial industry with the special focus on capital markets. Based on the industrial organization theory, as well as on an extensive literature review, research to date, and industry reports, the attempt was made to identify main structural changes resulting from FinTech's activity in this market segment. It was found that, in contrast to the banking sector, BigTechs are not interested in entering into capital markets. This can be explained by complexity of investment services and weak synergies between them and non-financial services offered by technology giants. As a result, digitalization in capital markets is driven rather from inside and supported by FinTechs. In the stock market, the development of high-frequency trading resulted in the increasing centralization of trade that neither facilitated market access nor eliminated the market asymmetry. Nonetheless, FinTech solutions allowed reductions in transaction costs and increase in short-term market efficiency. In the asset management and mutual funds industry digital platforms, developed mostly by incumbents, by lowering transaction costs and reducing communication frictions made investing easier and cheaper for individuals, however their decisions became more speculative

Personal data protection in terms of provisions of the Polish state and the authority of the General for Personal Data Protection

The article describing and expand issue personal data and their contemporary protection. Present apparatus the Inspector General for Personal Data Protection and show example results of their work. For the article was conducted survey consisting in examining the small Group of people in order to confirm the rightness activity of the institutions

ŚWIATŁOWODOWE SKOŚNE SIATKI BRAGGA JAKO CZUJNIKI W POMIARACH WSPÓŁCZYNNIKA ZAŁAMANIA CIECZY

This publication presents the basic assumptions about the light guiding mechanisms in tilted fiber Bragg gratings, transmission spectra of the fiber with such structures and their sensor properties related to the occurrence of the so-called cladding modes. The light in the form of modes coupled to the optical fiber cladding causes their spectral properties to depend on the difference in the refractive indices of the surrounding medium and the fiber cladding. With the introduction of a small inclination angle of the diffraction fringes forming the Bragg grating, the cladding modes show sensitivity to changes in the refractive index of the environment of aqueous solutions, which makes the spectrum of their applications broad. This publication presents changes in the spectra of selected modes measured for solutions with a specific refractive index, shift sensitivity, and changes in the mode transmission coefficient and processing characteristics at a selected concentration range of solutions. Experimental results show that high order cladding modes respond both by shifting the central wavelength as well as by changing the transmission minimum. In selected ranges, these parameters show a linear characteristic as a function of changes in the concentration of the cane sugar aqueous solution. In the case of TFBG with a tilt angle of 8 °, the sensitivity of wavelength changes is 0.012nm / RIU for solutions with concentrations ranging from 0% to 10% by weight.Niniejsza publikacja prezentuje podstawowe założenia dotyczące mechanizmów prowadzenia światła w światłowodowych skośnych siatkach Bragga (ang. tilted fiber Bragg grating), widma transmisyjne światłowodu z wytworzonymi takimi strukturami oraz ich właściwości czujnikowe związane z występowaniem tzw. modów płaszczowych. Prowadzenie światła w postaci modów sprzęganych do płaszcza światłowodu sprawia, że ich właściwości spektralne zależne są od różnicy współczynników załamania ośrodka otaczającego oraz płaszcza włókna. Przy wprowadzeniu niewielkiego kąta pochylenia prążków dyfrakcyjnych tworzących siatkę Bragga, mody płaszczowe wykazują wrażliwość na zmiany współczynnika załamania otoczenia roztworów wodnych, przez co spektrum ich zastosowań jest szerokie. W niniejszej publikacji przedstawiono zmiany widm wybranych modów mierzonych dla roztworów o określonym współczynniku załamania, czułości przesunięcia oraz zmiany współczynnika transmisji modu oraz charakterystyki przetwarzania przy wybranym zakresie stężenia roztworów. Wyniki eksperymentalne wskazują, że mody płaszczowe wysokich rzędów reagują zarówno przesunięciem centralnej długości fali jak również zmianą minimum transmisji. Parametry te w wybranych zakresach wykazują charakterystykę liniową w funkcji zmian stężenia roztworu wodnego cukru trzcinowego. W przypadku TFBG o kącie pochylenia 8°, czułość zmian długości fali wynosi 0,012nm/RIU dla roztworów o stężeniach od 0% do 10% stężenia wagowego

On the worst scenario method: a modified convergence theorem and its application to an uncertain differential equation

summary:We propose a theoretical framework for solving a class of worst scenario problems. The existence of the worst scenario is proved through the convergence of a sequence of approximate worst scenarios. The main convergence theorem modifies and corrects the relevant results already published in literature. The theoretical framework is applied to a particular problem with an uncertain boundary value problem for a nonlinear ordinary differential equation with an uncertain coefficient

Chapter 5 FinTechs, BigTechs and structural changes in capital markets

This chapter aims at exploring some theoretical issues associated with the impact of technology companies on the market structure in the financial industry with the special focus on capital markets. Based on the industrial organization theory, as well as on an extensive literature review, research to date, and industry reports, the attempt was made to identify main structural changes resulting from FinTech's activity in this market segment. It was found that, in contrast to the banking sector, BigTechs are not interested in entering into capital markets. This can be explained by complexity of investment services and weak synergies between them and non-financial services offered by technology giants. As a result, digitalization in capital markets is driven rather from inside and supported by FinTechs. In the stock market, the development of high-frequency trading resulted in the increasing centralization of trade that neither facilitated market access nor eliminated the market asymmetry. Nonetheless, FinTech solutions allowed reductions in transaction costs and increase in short-term market efficiency. In the asset management and mutual funds industry digital platforms, developed mostly by incumbents, by lowering transaction costs and reducing communication frictions made investing easier and cheaper for individuals, however their decisions became more speculative

Grammar induction for mildly context sensitive languages using variational Bayesian inference

The following technical report presents a formal approach to probabilistic minimalist grammar induction. We describe a formalization of a minimalist grammar. Based on this grammar, we define a generative model for minimalist derivations. We then present a generalized algorithm for the application of variational Bayesian inference to lexicalized mildly context sensitive language grammars which in this paper is applied to the previously defined minimalist grammar

Payment Features and Incentives as Drivers for Non-Cash Payments Usage – the Evidence from Poland

Theoretical background: There is evidence that sustainable economic growth is strictly connected with non-cash payments development. Nevertheless, in many countries, cash still remains the dominant means of payment. Cash can be treated as a store of value and a means of payment. The paper focuses on its transactional function and addresses the need to recognise drivers that can shift consumers away from cash.Purpose of the article: The paper aims to analyse what features of payment instruments and what kind of incentives could convince consumers to switch from cash to non-cash payments.Research methods: The data analysed were collected during the first survey on this topic conducted in 2018 on a representative sample of Polish consumers. The selected statistical methods were applied to analyse research data. Among them are correlation analysis and Thurstone’s method of paired comparisons to analyse preferences and association (co-occurrence) for exploring consumers’ preferences related to their payment choices.Main findings: The results show that in Poland consumers’ payment choices are driven rather by the cost than other payment instrument features such as speed, convenience or security. These results are consistent with the greater sensitivity of Polish consumers to financial incentives than material bonuses or tax benefits. The analysis has also shown a statistically significant correlation between the kind of incentive and the consumer’s characteristics

Verifications of primal energy identities for variational problems with obstacles

We discuss error identities for two classes of free boundary problems generated by obstacles. The identities suggest true forms of the respective error measures which consist of two parts: standard energy norm and a certain nonlinear measure. The latter measure controls (in a weak sense) approximation of free boundaries. Numerical tests confirm sharpness of error identities and show that in different examples one or another part of the error measure may be dominant.Comment: 8 pages, 2 figures, conference paper: LSSC (Large-Scale scientific computing), Sozopol, Bulgaria, 2017. The final version will be published at Springe

Predicting Music Hierarchies with a Graph-Based Neural Decoder

This paper describes a data-driven framework to parse musical sequences into dependency trees, which are hierarchical structures used in music cognition research and music analysis. The parsing involves two steps. First, the input sequence is passed through a transformer encoder to enrich it with contextual information. Then, a classifier filters the graph of all possible dependency arcs to produce the dependency tree. One major benefit of this system is that it can be easily integrated into modern deep-learning pipelines. Moreover, since it does not rely on any particular symbolic grammar, it can consider multiple musical features simultaneously, make use of sequential context information, and produce partial results for noisy inputs. We test our approach on two datasets of musical trees -- time-span trees of monophonic note sequences and harmonic trees of jazz chord sequences -- and show that our approach outperforms previous methods.Comment: To be published in the Proceedings of the International Society for Music Information Retrieval Conference (ISMIR