A Miniscule Survey on Blockchain Scalability

With the rise of cryptocurrency and NFTs in the past decade, blockchain technology has been an area of increasing interest to both industry and academic experts. In this paper, we discuss the feasibility of such systems through the lens of scalability. We also briefly dive into the security issues of such systems, as well as some applications, including healthcare, supply chain, and government applications

The Evolution of Efficiency in the Chinese Stock Market

This dissertation examines the weak-form efficiency of the Chinese stock market and provides evidence on how the market efficiency evolved throughout the last three decades. The Shanghai Composite Index (SSEC) and the Shenzhen Component Index (SZSE) are the primary indicators of the Chinese stock market in this study. Both traditional economics and the complex systems’ methods are employed to evaluate market efficiency, with an additional focus on the effect of two parameter inputs (embedded dimension and noise filter) on entropy methods to improve their ability to detect phase transitions in stock market data. The traditional efficiency tests indicate that the Chinese stock market during the full sample period of 1990-2021 is inefficient, but some of the sub-sample periods indicate the weak-form efficiency, except for the ADF test. Meanwhile, the complex systems’ methods suggest that the level of randomness in returns increases over time. Additionally, I find that the bull periods of the Chinese market are less efficient than the bust periods, which may indicate that investors tend to commit more errors during the bull period. Generally, the study concludes that the complex systems’ methods provide a more comprehensive evaluation of the changes in the market efficiency than traditional methods. The empirical results suggest that the Chinese stock market is not completely efficient based on the traditional efficiency tests but the level of efficiency has improved over time based on the evidence of the complex systems’ analysis

Interpreting Housing Prices with a MultidisciplinaryApproach Based on Nature-Inspired Algorithms and Quantum Computing

Current technology still does not allow the use of quantum computers for broader and individual uses; however, it is possible to simulate some of its potentialities through quantum computing. Quantum computing can be integrated with nature-inspired algorithms to innovatively analyze the dynamics of the real estate market or any other economic phenomenon. With this main aim, this study implements a multidisciplinary approach based on the integration of quantum computing and genetic algorithms to interpret housing prices. Starting from the principles of quantum programming, the work applies genetic algorithms for the marginal price determination of relevant real estate characteristics for a particular segment of Naples’ real estate market. These marginal prices constitute the quantum program inputs to provide, as results, the purchase probabilities corresponding to each real estate characteristic considered. The other main outcomes of this study consist of a comparison of the optimal quantities for each real estate characteristic as determined by the quantum program and the average amounts of the same characteristics but relative to the real estate data sampled, as well as the weights of the same characteristics obtained with the implementation of genetic algorithms. With respect to the current state of the art, this study is among the first regarding the application of quantum computing to interpretation of selling prices in local real estate markets

Artificial Intelligence in Asset Management

Artificial intelligence (AI) has grown in presence in asset management and has revolutionized the sector in many ways

Essays in High Frequency Trading and Market Structure

High Frequency Trading (HFT) is the use of algorithmic trading technology to gain a speed advantage when operating in financial markets. The increasing gap between the fastest and the slowest players in financial markets raises questions around the efficiency of markets, the strategies players must use to trade effectively and the overall fairness of markets which regulators must maintain. This research explores markets affected by HFT activity from three perspectives. Firstly an updated microstructure model is proposed to allow for empirical exploration of current levels of noise in financial markets, this illustrates current noise levels are not disruptive to dominant trading strategies. Second, a ARCH type model is used to de-compose market data into a series of traders working price levels to demonstrate that in cases of suspected market abuse, regulators can assess the impact individual traders make on price even in fast markets. Finally, a review of various HFT control measures are examined in terms of effectiveness and in light of an ordoliberal benchmark of fairness. The work illustrates the extents to which HFT activity is not yet disruptive, but also shows where HFT can be a conduit for market abuse and provides a series of recommendations around use of circuit breakers, algorithmic governance standards and additional considerations where assets are dual listed in different countries

Three Risky Decades: A Time for Econophysics?

Our Special Issue we publish at a turning point, which we have not dealt with since World War II. The interconnected long-term global shocks such as the coronavirus pandemic, the war in Ukraine, and catastrophic climate change have imposed significant humanitary, socio-economic, political, and environmental restrictions on the globalization process and all aspects of economic and social life including the existence of individual people. The planet is trapped—the current situation seems to be the prelude to an apocalypse whose long-term effects we will have for decades. Therefore, it urgently requires a concept of the planet's survival to be built—only on this basis can the conditions for its development be created. The Special Issue gives evidence of the state of econophysics before the current situation. Therefore, it can provide excellent econophysics or an inter-and cross-disciplinary starting point of a rational approach to a new era

Tracking and Nowcasting Directional Changes in the Forex Market

Price changes in financial markets are typically summarized as time series (TS). Directional Change (DC) is an alternative, data-driven way to sample data points. The main objective of this thesis is to find new ways to extract new, useful information from the market. This is broken down into three directions: (1) to summarize price changes with DC, one must first determine the threshold to be used. We ask: could a threshold be too big or too small? If so, how could we determine the range of usable thresholds? (2) Could DC indicators extract volatility information from the market that is not observable under TS? (3) In DC, the start of a new trend is only confirmed in hindsight – to be precise, at the DC Confirmation (DCC) point when the price has reversed by the threshold specified. Could we detect that a new trend has begun before the DCC point? This is known as a nowcasting problem. This thesis has made three contributions. Firstly, we have created a guideline to determine the range of useable thresholds under DC. This supports the research that follows. Secondly, we have demonstrated how DC indicators could complement TS in tracking the market for volatility information. Thirdly, we have introduced new DC indicators; by using these indicators, we have proposed an algorithm and demonstrated how it could help us nowcast whether a new trend has begun in DC

‘Technology as a trusted companion for accountants and business professionals in the business unusual environment’

Abstract: A conceptual model of corporate social responsibility (CSR) and service quality for Islamic bank service users is developed in this paper. The model is expected to bring about a better understanding of customer perceptions relating to issues of social responsibility and its impact on service quality as it pertains to Islamic banking in South Africa. The conceptual model is developed by synthesising relevant literature and theories pertaining to this study. This conceptual model is proposed to be tested in due course of time by using customer perceptions derived from a survey instrument to assess the relationship between aspects of social responsibility and service quality at the Islamic bank. The proposed model has implications towards enhancing the CSR and service quality offered by the Islamic bank according to their customer expectations