Low-resistivity Pd nanopatterns created by a direct electron beam irradiation process free of post-treatment steps

The ability to create metallic patterned nanostructures with excellent control of size, shape and spatial orientation is of utmost importance in the construction of next-generation electronic and optical devices as well as in other applications such as (bio)sensors, reactive surfaces for catalysis, etc. Moreover, development of simple, rapid and low-cost fabrication processes of metallic patterned nanostructures is a challenging issue for the incorporation of such devices in real market applications. In this contribution, a direct-write method that results in highly conducting palladium-based nanopatterned structures without the need of applying subsequent curing processes is presented. Spin-coated films of palladium acetate were irradiated with an electron beam to produce palladium nanodeposits (PdNDs) with controlled size, shape and height. The use of different electron doses was investigated and its influence on the PdNDs features determined, namely: (1) thickness of the deposits, (2) atomic percentage of palladium content, (3) oxidation state of palladium in the deposit, (4) morphology of the sample and grain size of the Pd nanocrystals and (5) resistivity. It has been probed that the use of high electron doses, 30000 μC·cm-2 results in the lowest resistivity reported to date for PdNDs, namely 145.1 μΩ·cm, which is only one order of magnitude higher than metallic palladium. This result paves the way for development of simplified lithography processes of nanostructured deposits avoiding subsequent post-treatment steps.

Methodological approaches to the development of investment activities of a professional sports organization

The article discusses ways to improve the investment regulation of professional sports organizations. The approaches of scientists and researchers in the world economic thought to the problem under study are considered. The effectiveness of professional sports as a type of economic activity in the structure of the national economy of the Republic of Belarus is noted. Based on the assessment of the economic efficiency of the functioning of professional sports organizations in the Republic of Belarus, the analysis of normative legal acts and effective foreign experience, a method of effective regulation of investments in the development of a professional sports organization is proposed, which includes a model of investment regulation and methodological recommendations for maximizing income. In contrast to the existing practice, a holistic system has lined that takes into account the management, marketing, export, information technology, innovation and investment potentials of a professional sports organization. The carried out tested developed methodology for optimize the investment regulation of a professional sports organization on the subject for compliance with real market conditions on the example of the football club of the highest League of the Republic of Belarus Shakhtyor (Soligorsk), the results showed a positive economic effect of organization and revealed directions for the development of its supporting segments.

The Efficiency Analysis of Large Banks Using the Bootstrap and Fuzzy DEA: A Case of an Emerging Market

In this study, banks’ business performance efficiency was analysed using data envelopment analysis (DEA), with expense categories as inputs and income categories as outputs. By incorporating a bootstrap method and a fuzzy data approach into a DEA model, additional insights and sensitivity analysis of the results were obtained. This study shows how fuzzy and bootstrap DEA can be used for investigating real market problems with uncertain data in an uncertain sample. The empirical analysis was based on the period of 2009–2018 for a sample of seven of Croatia’s largest private banks. The aim of the study was also to interpret the DEA results with regards to the specific market, legal, and macroeconomic conditions, caused by the changes introduced in the last decade. The results, and the changes in the inputs and outputs over time, revealed that the market processes occurring in the observed period had a significant impact on banks’ business performance, but led to a more efficient banking system. Two banks were found to be dominant over the others regardless of the changes in the sample and data fuzziness. DEA results were additionally compared to the most important financial indicators and accounting ratios, as an alternative or additional measure of banks’ efficiency and profitability.

The End of Western Economic Growth Theory

Economics is a science that studies how the economy grows, so the theory of economic growth is the most important theory of economics. In the real market economy society, people achieve the goal of economic growth through two kinds of economic activities: production and transaction. Then a correct economic growth theory must be one that can explain both production and transaction economic activities. Just like Newton’s law of universal gravitation in physics, it can explain the motion law of all objects. For a long time, we have been dominated by the western economic growth theory of western mainstream economics. It is not difficult to find that it has a fatal defect, which can only explain production economic activities but not transaction economic activities. So it can’t explain the Chinese economy, and it can’t explain the western economy. The new economic growth theory proposed in this paper makes up for the defects of western economic growth theory, and it is the terminator of western economic growth theory. This is a revolution of new economics to traditional western economics.

Deep Learning for seasonality modelling in Inflation-Indexed Swap pricing

An Inflation-Indexed Swap (IIS) is a derivative in which, at every payment date, the counterparties swap an inflation rate with a fixed rate. For the calculation of the Inflation Leg cash flows it is necessary to build a mathematical model suitable for the Consumer Price Index (CPI) projection. For this purpose, quants typically start by using market quotes for the Zero-Coupon swaps in order to derive the future trend of the inflation index, together with a seasonality model for capturing the typical periodical effects. In this study, we propose a forecasting model for inflation seasonality based on a Long Short Term Memory (LSTM) network: a deep learning methodology particularly useful for forecasting purposes. The CPI predictions are conducted using a FinTech paradigm, but in respect of the traditional quantitative finance theory developed in this research field. The paper is structured according to the following sections: the first two parts illustrate the pricing methodologies for the most popular IIS: the Zero Coupon Inflation-Indexed Swap (ZCIIS) and the Year-on-Year Inflation-Indexed Swap (YYIIS); section 3 deals with the traditional standard method for the forecast of CPI values (trend + seasonality), while section 4 describes the LSTM architecture, and section 5 focuses on CPI projections, also called inflation bootstrap. Then section 6 describes a robust check, implementing a traditional SARIMA model in order to improve the interpretation of the LSTM outputs; finally, section 7 concludes with a real market case, where the two methodologies are used for computing the fair-value for a YYIIS and the model risk is quantified.

Detection of Mutual Exciting Structure in Stock Price Trend Dynamics

We investigated a comprehensive analysis of the mutual exciting mechanism for the dynamic of stock price trends. A multi-dimensional Hawkes-model-based approach was proposed to capture the mutual exciting activities, which take the form of point processes induced by dual moving average crossovers. We first performed statistical measurements for the crossover event sequence, introducing the distribution of the inter-event times of dual moving average crossovers and the correlations of local variation (LV), which is often used in spike train analysis. It was demonstrated that the crossover dynamics in most stock sectors are generally more regular than a standard Poisson process, and the correlation between variations is ubiquitous. In this sense, the proposed model allowed us to identify some asymmetric cross-excitations, and a mutually exciting structure of stock sectors could be characterized by mutual excitation correlations obtained from the kernel matrix of our model. Using simulations, we were able to substantiate that a burst of the dual moving average crossovers in one sector increases the intensity of burst both in the same sector (self-excitation) as well as in other sectors (cross-excitation), generating episodes of highly clustered burst across the market. Furthermore, based on our finding, an algorithmic pair trading strategy was developed and backtesting results on real market data showed that the mutual excitation mechanism might be profitable for stock trading.

An Analysis of Asymptotic Properties and Error Control under the Exponential Jump-Diffusion Model for American Option Pricing

Our work is aimed at modeling the American option price by combining the dynamic programming and the optimal stopping time under two asset price models. In doing so, we attempt to control the theoretical error and illustrate the asymptotic characteristics of each model; thus, using a numerical illustration of the convergence of the option price to an equilibrium price, we can notice its behavior when the number of paths tends to be a large number; therefore, we construct a simple estimator on each slice of the number of paths according to an upper and lower bound to control our error. Finally, to highlight our approach, we test it on different asset pricing models, in particular, the exponential Lévy model compared to the simple Black and Scholes model, and we will show how the latter outperforms the former in the real market (Microsoft “MSFT” put option as an example).

Trading and Technology: An Information Systems Course Application

Financial markets today are highly computerized -- from software-driven order submission to price determination to straight-through clearing and settlement -- computer technology has displaced manual activities and streamlined functions throughout the trading value chain. The previous chapters examined microeconomic principles that underpin trading and price-setting, and finance theory that provides analytical frameworks for market outcomes. Our analysis introduces real market frictions and examines how transactions costs and heterogeneity among market participants makes market structure and tracing mechanism design crucial determinants of market outcomes and behavior. . In this chapter, we drill down further into the realities of a non-frictionless market in order to focus on how technology can enhance the efficiency of an actual marketplace. Challenging market design issues are encountered when developing and operating an actual trading facility, and as IT professionals know, the devil is in the details. The practical considerations in operating a market system successfully are the next topic this book addresses.

Exponential Income Distribution and Evolution of Unemployment Compensation in the United Kingdom

We show that an exponential income distribution will emerge spontaneously in a peer-to-peer economic network that shares the publicly available technology. Based on this finding, we identify the exponential income distribution as the benchmark structure of the well-functioning market economy. However, a real market economy may deviate from the well-functioning market economy. We show that the deviation is partly reflected as the invalidity of exponential distribution in describing the super-low income class that involves unemployment. In this regard, we find, theoretically, that the lower-bound u of exponential income distribution has a linear relationship with (per capita) unemployment compensation. In this paper, we test this relationship for the United Kingdom from 2001 to 2015. Our empirical investigation confirms that the income structure of low and middle classes (about 90% of populations) in the United Kingdom exactly obeys exponential distribution, in which the lower-bound u is exactly in line with the evolution of unemployment compensation.

The Stock Market Model with Delayed Information Impact from a Socioeconomic View

Finding the critical factor and possible “Newton’s laws” in financial markets has been an important issue. However, with the development of information and communication technologies, financial models are becoming more realistic but complex, contradicting the objective law “Greatest truths are the simplest.” Therefore, this paper presents an evolutionary model independent of micro features and attempts to discover the most critical factor. In the model, information is the only critical factor, and stock price is the emergence of collective behavior. The statistical properties of the model are significantly similar to the real market. It also explains the correlations of stocks within an industry, which provides a new idea for studying critical factors and core structures in the financial markets.