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Economics, Financial Engineering and Business
Economics is the study of how people use resources efficiently and how they are produced, distributed, and consumed, and the purpose of economics will be to find the optimal creation and distribution of value in response to the scarcity of resources and lack of people’s needs.
The main fields of economics are macroeconomics and microeconomics, each of which studies the criteria by which individuals, firms, and nations make decisions about production, distribution, and consumption, as well as the functioning of markets and the international economy.
Financial engineering is the branch of economics that deals specifically with finance. Financial engineering is the study of the pricing, risk assessment, and portfolio management of financial markets and financial instruments using mathematical models and statistical methods, with the main objective of developing strategies and methods for financial institutions and companies to minimize risk and maximize profits.
In this economic and financial context, the activities of organizations and individuals that profit from providing goods and services are referred to as business. The purpose of business is for companies and sole proprietors to contribute to society and earn profits by providing goods and services. Important concepts in business include marketing, financial management, human resource management, and strategic decision making.
Relation to Artificial Intelligence Technology
The application of artificial intelligence technology to these problems has attracted particular attention in recent years. The following are examples of such applications.
The first example is economic forecasting using artificial intelligence technology. Specifically, the use of artificial intelligence in financial market forecasting can be used to predict trends in stock prices and foreign exchange rates.
The next example is big data analysis using artificial intelligence technology, which enables companies to analyze customer behavior and preferences to forecast product demand and understand customer needs, and to find the best way to provide products and services.
Furthermore, artificial intelligence technology can also help optimize labor and resources. This would be production planning and inventory management using artificial intelligence, which in turn are expected to improve productivity and reduce costs for firms.
Various topics related to this economics, financial engineering, and business are discussed here.
Various topics in economics and financial engineering and business
The economy is the system and state of production, distribution and consumption of goods and services, and how people, companies and governments produce, distribute and consume goods using limited resources, making economics a discipline that seeks to understand and elucidate the workings of the economy. This section describes market design and algorithms, one of the applications of economics.
The Stable Marriage Problem (SMP) algorithm is a type of problem and solution method for achieving ‘stable matching’ between two groups. The most famous solution to this problem is the Gale-Shapley Algorithm (Gale-Shapley Algorithm), which can efficiently find stable combinations, and this algorithm has been used in particular for matching medical students and hospitals, job applicants and companies, and It will be applied to many real-world matching problems, in particular matching medical students with hospitals and job seekers with companies.
- Machine learning and algorithms used for surge pricing and examples of implementation
Surge pricing (dynamic pricing based on demand) will be one in which prices fluctuate under certain conditions and the optimum price is set in real time according to consumer demand and supply conditions. To achieve this, various machine learning and algorithms are utilised, with demand forecasting and market analysis techniques playing a particularly important role.
- Overview, implementation examples and applications of optimisation algorithms that take into account the Kelly criterion and equity
The Kelly criterion and equity-aware optimisation algorithms are methods used for various capital allocations. The Kelly criterion is a method for optimally allocating capital in gambling and investment, which calculates how much money should be invested when the expected value of an investment or bet is positive.
Behavioral economics will be the field of economics concerning when human behavior deviates from the assumptions of economic theory. While traditional economics assumes that people make rational decisions and seek to maximize their own self-interest, in reality, people behave in more complex and unpredictable ways. Behavioral economics aims to improve the design of markets and policies and enhance social welfare by understanding how people behave.
Behavioral economics is an interdisciplinary field that combines the disciplines of psychology, sociology, behavioral science, and economics. Typical areas of research include prospect theory, framing effects, loss aversion tendencies, temporal preferences, choice abundance, and the influence of social norms.
Behavioural economics, described in “The economy is driven by ’emotions'”, is one of the current trends in modern psychology, which focuses on irrational thoughts and behaviours and tries to reveal the common laws of irrationality, in contrast to conventional economics based on rational human activities. Two systems are envisaged in our minds, one being a quick, automatic, unintentional and unconscious system, such as intuitive judgement, and the other being a deliberate and conscious system, such as logical judgement, which is time-consuming but controllable. AI technology, which is also described in this blog, aims to take the rational decision-making of System 2 to the extreme instead of humans, and IA, which is also described in “Overview of Intelligence Augmentation (IA) and its application examples”, is an approach to how to connect the useful parts of System 1 and System 2. The IA described in “Overview of IA (Intelligence Augmentation) and its application examples” can be said to be an approach to how to connect the useful parts of System 1 with System 2.
Priming is also an interesting concept in the field of AI, and there is active research into using the concept of priming to improve human-AI interactions. For example, in AI-based experience (UX) design, when a user performs a specific task, an AI assistant can more accurately understand the user’s intentions and present relevant information and context in advance, so that subsequent operations can proceed smoothly, such as Priming can be considered.
Philosophy is an approach to deep contemplation and theoretical reflection on a variety of questions. Philosophy has played an important role in transforming society by fostering logical thinking, problem-solving skills, and ethical judgment. Hiroki Azuma, a contemporary Japanese philosopher, has stated that one such movement by philosophy may be the evolution of modern IT.
Heuristics refers to expedient or heuristic methods used when there is a need to solve a problem or make a decision on an uncertain matter, but there are no clear clues to do so. Contrasted with heuristics are algorithms, which are methods that can be rigorously followed to obtain times.
Economic mathematics is the study of mathematical methods of analysis in economics. It refers to the application of mathematical methods to economics, the study of resource allocation and decision-making by society and individuals, in order to model and analyze mathematically in order to gain deeper insights.
Economic mathematics is used to model theories of supply and demand or by applying mathematical approaches to a variety of other economic problems, such as pricing, cost reduction, production optimization, investment, portfolio theory, and financial market theory.
Financial engineering (FE) is the discipline that applies mathematical and statistical methods and econometric tools to the theoretical analysis, design, valuation, and risk management of financial instruments and financial markets, with the main objective of modeling the prices and risks of financial instruments and developing efficient investment and risk management strategies.
The Black-Scholes model is a valuation model of option prices in financial engineering. This model was published by Fisher Black and Merton Scholes in 1973 and is used to calculate the prices of equity options and other derivative financial instruments. The model has been used to calculate prices of equity options and other financial derivatives, and has also been applied to pricing derivatives and predicting volatility.
- Fast & Slow How is your will determined?
- Predictably Inconvenient
- Zero to One What can you create from nothing?
Applications
- Overview and Various Implementations of Bayesian Estimation
- Overview of Reinforcement Learning Techniques and Various Implementations
- Overview of Game Theory and Examples of Integration and Implementation with AI Technology
- Overview of Intelligence Augmentation (IA) and its application examples
- Overview of Causal Inference and Causal Search
- Overview of Support Vector Machines, examples of application, and various implementations
- Time Series Analysis with Prophet
- Time Series Data Analysis
- Application of State Space Model to Marketing
- Various Applications and Implementation Examples of Knowledge Graphs
- Overview of change detection techniques and implementation examples
- Overview of twitter recommendation algorithms
- Simulation, Data Science and Artificial Intelligence
- Sparse Modeling and Multivariate Analysis (8) Sparsity of Time Transitions
- About the various methods and implementations of Explainable Machine Learning
- Overview of Bayesian Structural Time Series Models and Examples of Applications and Implementations
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