Psycho-Quantum Finance is an interdisciplinary field drawn from psychology, quantum physics and decentralized finance that studies the structure and behaviour of economic systems using conscience. This postdisciplinary line aims to simulate how probabilistic (aggrieved/angry/happy etc) individual and group mental states produce market actions on the global scale DECENTRALIZED ECONOMIC ECOSYSTEMS. To improve their ability to analyze market states and investor feelings, they are applying the Quantum finance methods to use probabilistic modeling and non-linear dynamics. Quantum-based algorithms expect to grasp economic trends more accurately from the data of decentralized networks, thus making good decisions in the Decentralized Finance (De-Fi) arena. This method also proposes a global approach of the movements in markets and requires the integration of several psychological prejudices and cognitive aspects. It has been concluded from our simulation exercises that integration of psycho-quantum factors does aid content-based predictive models, in making reasonably better predictions on financial time series. This research demonstrates the fundamental opportunities that psycho-quantum finance offers for a reinvention of decentralized economic paradigms with a new perspective on the roles of global consciousness in shaping markets.
Psycho-Quantum Finance is an interdisciplinary field drawn from psychology, quantum physics and decentralized finance that studies the structure and behaviour of economic systems using conscience. This postdisciplinary line aims to simulate how probabilistic (aggrieved/angry/happy etc) individual and group mental states produce market actions on the global scale DECENTRALIZED ECONOMIC ECOSYSTEMS. To improve their ability to analyze market states and investor feelings, they are applying the Quantum finance methods to use probabilistic modeling and non-linear dynamics. Quantum-based algorithms expect to grasp economic trends more accurately from the data of decentralized networks, thus making good decisions in the Decentralized Finance (De-Fi) arena. This method also proposes a global approach of the movements in markets and requires the integration of several psychological prejudices and cognitive aspects. It has been concluded from our simulation exercises that integration of psycho-quantum factors does aid content-based predictive models, in making reasonably better predictions on financial time series. This research demonstrates the fundamental opportunities that psycho-quantum finance offers for a reinvention of decentralized economic paradigms with a new perspective on the roles of global consciousness in shaping markets.
This chapter explores the quantum-like characteristics of human psychology in financial decision-making, revealing how individual cognitive biases create collective market behaviors that exhibit superposition, entanglement, and observer effects. The quantum psychology hypothesis suggests that investor decision-making mirrors quantum mechanics: individuals simultaneously hold multiple conflicting beliefs about market conditions until external events force a resolution into specific positions. The analysis demonstrates how observation changes reality in financial markets through three mechanisms: analyst reports that influence the very companies they analyze; investor sentiment that becomes self-fulfilling through collective action; and measurement effects, where market research alters the behaviors being studied. Three detailed case studies illuminate these principles: the 2020–2022 cryptocurrency boom showing how the fear of missing out (FOMO) created quantum-like feedback loops; the dot-com bubble demonstrating valuation superposition, where companies existed simultaneously as revolutionary and worthless until market forces collapsed these contradictions; and the 2008 housing crisis revealing how cognitive biases maintained conflicting beliefs about property values. The chapter develops frameworks for understanding market sentiment as quantum coherence and decoherence phases in which consensus breaks down, leading to volatility. These insights provide tools for navigating crowd psychology and market dynamics that extend far beyond traditional behavioral economics.
Since the beginning of the 21st century, a new interdisciplinary research movement has started, which aims at developing quantum math-like (or simply quantum-like) models to provide an explanation for a variety of socio-economic processes and human behaviour. By making use of mainly the probabilistic aspects of quantum theory, this research movement has led to many important results in the areas of decision-making and finance. In this article, we introduce a novel and more exhaustive approach, to analyze the socio-economic processes and activities, than the pure quantum math-like modelling approach, by taking into account the physical foundations of quantum theory. We also provide a plausibility argument for its exhaustiveness in terms of what we can expect from such an approach, when it is applied to, for example, a generic socio-economic decision process.
Introduction. Modern financial science increasingly faces a paradox: classical models based on deterministic assumptions fail to adequately describe the nonlinearity and uncertainty of public decision-making. In this context, the quantum paradigm of thinking, originally developed in physics, is becoming increasingly relevant as it gradually penetrates the fields of economics and finance. Problem Statement. In contemporary academic discourse, growing attention is being paid to the integration of the principles of quantum logic into socio-economic systems. Traditional financial science rests upon classical macroeconomic determinants that assume linearity, causal determinacy, and parameter stability. However, in the modern world – characterized by high uncertainty, dynamic crises, and global financial fluctuations – such logic proves insufficient. Therefore, there is a pressing need to employ quantum logic as a modern cognitive and analytical paradigm that enables the comprehension of the essence and structure of public finance through the prism of nonlinear, stochastic, and interrelated phenomena and processes. Purpose is to establish a theoretical and methodological foundation for applying quantum principles in the domain of public finance and to identify directions for their practical implementation. Methods. To obtain the scientific results presented in the article, the following methods were employed: methods of quantum logic, synthesis and analysis, deduction and induction, an abstract-logical method of “negation of negations” in financial decision-making, and theoretical generalization to define the nature of quantum finance. Results. The article reveals the potential for interpreting key principles of quantum physics within the system of public finance. A dual-level research framework is proposed, combining methodological analogies between quantum and financial processes with the practical application of quantum models in state financial management. It is demonstrated that the concepts of uncertainty, superposition, and coherence allow for a deeper understanding of the nature of budgetary decisions, tax expectations, debt imbalances, and behavioral effects in the public sphere. Conclusions. Quantum logic crystallizes a methodological framework for modern public finance capable of accounting for the complexity, uncertainty, and interconnectivity of global transformations, hybrid wars, and the contemporary economy. The application of quantum paradigms makes it possible to construct dynamic, probabilistic models of financial policy that significantly surpass the capacities of classical deterministic methods and open new perspectives for scientifically grounded public governance in the field of public finance.
Quantum finance is a new paradigm in financial market operations, based on the principles of quantum computing in solving highly complex problems with efficiency. This chapter covers some basic ideas of quantum finance through its historical context and the role it has played in surmounting the limitations of classical financial models. The chapter commences with the basics, including the need for an introduction to quantum mechanics, qubits, quantum gates, and algorithms that can be applied in financial applications to demonstrate how quantum computing can change finance. We discuss some of those areas where this technology is bound to make an impact: in portfolio optimization, quantum computing considers several combinations of assets at a time; in risk management, improved models will allow for better predictions of market movements; in derivative pricing, the calculations are faster and more accurate; and in fraud detection, it enables one to execute better analysis of transactional data. The advancement of quantum finance is linked to the need to resolve ethical, legal, and technical obstacles while integrating with traditional financial institutions. The financial markets will be a key source of innovation that will drive efficiency, precision, and invention to previously unheard-of heights, given the direction that quantum computing technology is expected to take. Thus, the chapter ends with a call for more study and cooperation to fully grasp quantum finance's transformative potential.
Quantum economics is an interdisciplinary field that combines the principles of quantum mechanics and economic theories. The research examines the main theoretical and practical aspects of quantum economics, starting with its theoretical foundations based on the principles of quantum mechanics, such as superposition, uncertainty and entanglement, and ending with practical applications and perspectives for further research. Special attention was paid to the potential impact of quantum technologies on finance, marketing, supply chain management, as well as on macroeconomic planning and policy. It discusses how quantum algorithms can transform traditional approaches in economic research and practice, providing new methods for analyzing complex data, improving forecasting of economic trends, and optimizing decisions under uncertainty. Quantum economics opens up new perspectives for understanding dynamic and interconnected processes in the global economy, which can fundamentally change our perception of economic laws and strategies. It is emphasized that the quantum economy is at the initial stage of its development, and scientists and practitioners face many challenges and questions that need to be solved. In the future, we can expect the development of new tools for economic analysis and decisionmaking based on quantum computing, which will allow us to cope with current and future economic challenges more effectively. The quantum economy can also offer new approaches to risk management and financial security, especially in light of growing cyber threats and the need to protect economic information. Quantum economics is an exciting and promising direction that can significantly enrich both theoretical and applied aspects of economic science.
The integration of quantum computing into financial systems marks a transformative leap in risk management, security, and market operations. Unlike classical computing, quantum algorithms can process vast datasets and complex models at unprecedented speeds, enabling real-time risk analytics, rapid fraud detection, and optimized trading strategies. This study explores the emerging field of quantum-driven finance, focusing on its potential to enhance predictive accuracy, reduce systemic vulnerabilities, and accelerate decision-making in volatile markets. Applications such as quantum-enhanced Monte Carlo simulations, quantum machine learning for anomaly detection, and optimization in algorithmic trading are examined alongside challenges in scalability, cybersecurity, and regulatory adaptation. By evaluating current advancements and future prospects, this research highlights quantum computing's role in shaping a secure, intelligent, and high-velocity global financial ecosystem.