This is an expanded version of the lecture given at the AMS Short Course on Mean Field Games, on January 13, 2020 in Denver CO. The assignment was to discuss applications of Mean Field Games in finance and economics. I need to admit upfront that several of the examples reviewed in this chapter were already discussed in book form. Still, they are here accompanied with discussions of, and references to, works which appeared over the last three years. Moreover, several completely new sections are added to show how recent developments in financial engineering and economics can benefit from being viewed through the lens of the Mean Field Game paradigm. The new financial engineering applications deal with bitcoin mining and the energy markets, while the new economic applications concern models offering a smooth transition between macro-economics and finance, and contract theory.
This paper examines the impact of financial risks on economic growth in the first 15 Member States of the European Union, considering 1995-2014 period and aims to lay down a new explanatory model of economic growth, based mainly on the behavioral reactivity of the financial disruptions mentioned above. The model was estimated through the panel estimated generalized least squares method and included additional control variables in order to strengthen the research conducted. Our goal consists in the examination of the financial risks in the European Union and in the estimation of their impact on…
In this paper, we study the financial and economic implications of a zombie epidemic on a major industrialized nation. We begin with a consideration of the epidemiological modeling of the zombie contagion. The emphasis of this work is on the computation of direct and indirect financial consequences of this contagion of the walking dead. A moderate zombie outbreak leaving 1 million people dead in a major industrialized nation could result in GDP losses of 23.44% over the subsequent year and a drop in financial market of 29.30%. We conclude by recommending policy actions necessary to prevent thi…
The paper proposes a method of financial time series forecasting taking into account the semantics of news. For the semantic analysis of financial news the sampling of negative and positive words in economic sense was formed based on Loughran McDonald Master Dictionary. The sampling included the words with high frequency of occurrence in the news of financial markets. For single-root words it has been left only common part that allows covering few words for one request. Neural networks were chosen for modeling and forecasting. To automate the process of extracting information from the economic…
Hierarchical analysis is considered and a multilevel model is presented in order to explore causality, chance and complexity in financial economics. A coupled system of models is used to describe multilevel interactions, consistent with market data: the lowest level is occupied by agents generating the prices of individual traded assets; the next level entails aggregation of stocks into markets; the third level combines shared risk factors with information variables and bottom-up, agent-generated structure, consistent with conditions for no-arbitrage pricing theory; the fourth level describes …
When studying social, economic and biological systems, one has often access to only limited information about the structure of the underlying networks. An example of paramount importance is provided by financial systems: information on the interconnections between financial institutions is privacy-protected, dramatically reducing the possibility of correctly estimating crucial systemic properties such as the resilience to the propagation of shocks. The need to compensate for the scarcity of data, while optimally employing the available information, has led to the birth of a research field know…
The financial framework of the sustainability of health universal coverage in Italy. A quantitative financial model for the assessment of the italian stability and reform program of public health financing
A statistical analysis of financial, economic, and demographic indicators performed by the authors demonstrates (1) that the main countries of East Africa (Uganda, Kenya, and Tanzania) have not escaped the Malthusian Trap yet; (2) that this countries are not likely to follow the "North African path" and to achieve this escape before they achieve serious successes in their fertility transition; (3) that East Africa is unlikely to achieve this escape if it does not follow the "Bangladeshi path" and does not achieve really substantial fertility declines in the foreseeable future, which would impl…
In the current era of worldwide stock market interdependencies, the global financial village has become increasingly vulnerable to systemic collapse. The recent global financial crisis has highlighted the necessity of understanding and quantifying interdependencies among the world's economies, developing new effective approaches to risk evaluation, and providing mitigating solutions. We present a methodological framework for quantifying interdependencies in the global market and for evaluating risk levels in the world-wide financial network. The resulting information will enable policy and dec…
The informational context is regularly questioned in a transitional economic regime like the one implemented in China or Vietnam. This article investigates this issue and the predictive power of fundamental analysis in such context and more precisely in a Chinese context with an analysis of 3 different industries (media, power, and steel). Through 3 different kinds of correlation, we examine 25 financial determinants for 60 Chinese listed companies between 2011 and 2015. Our results show that fundamental analysis can effectively be used as an investment tool in transitional economic context. C…
We demonstrate the existence of an empirical linkage between the nominal financial networks and the underlying economic fundamentals across countries. We construct the nominal return correlation networks from daily data to encapsulate sector-level dynamics and figure the relative importance of the sectors in the nominal network through a measure of centrality and clustering algorithms. The eigenvector centrality robustly identifies the backbone of the minimum spanning tree defined on the return networks as well as the primary cluster in the multidimensional scaling map. We show that the sector…
Conventional economic analysis of stringent climate change mitigation policy generally concludes various levels of economic slowdown as a result of substantial spending on low carbon technology. Equilibrium economics however could not explain or predict the current economic crisis, which is of financial nature. Meanwhile the economic impacts of climate policy find their source through investments for the diffusion of environmental innovations, in parts a financial problem. Here, we expose how results of economic analysis of climate change mitigation policy depend entirely on assumptions and th…
Node centrality is one of the most important and widely used concepts in the study of complex networks. Here, we extend the paradigm of node centrality in financial and economic networks to consider the changes of node "importance" produced not only by the variation of the topology of the system but also as a consequence of the external levels of risk to which the network as a whole is submitted. Starting from the "Susceptible-Infected" (SI) model of epidemics and its relation to the communicability functions of networks we develop a series of risk-dependent centralities for nodes in (financia…
Disagreement is an essential element of science and life in general. The language of probabilities and statistics is often used to describe disagreements quantitatively. In practice, however, we want much more than that. We want disagreements to be resolved. This leaves us with a substantial knowledge gap which is often perceived as a lack of practical intuition regarding probabilistic and statistical concepts. Take for instance the Rényi divergence which is a well-known statistical quantity specifically designed as a measure of disagreement between probabilistic models. Despite its widespread…
It is well-known that disciplines such as mechanical engineering, electrical engineering, civil engineering, aerospace engineering, chemical engineering and software engineering witnessed successful applications of reliability engineering concepts. However, the concept of reliability in its strict sense is missing in financial services. Therefore, in order to fill this gap, in a first-of-its-kind-study, we define the reliability of a bank/firm in terms of the financial ratios connoting the financial health of the bank to withstand the likelihood of insolvency or bankruptcy. For the purpose of …
This paper discusses serious drawbacks of existing knowledge in macroeconomics and finance in explaining and predicting economic and financial phenomena. Complexity science is proposed as an alternative approach to be used in order to better understand how economy and financial market work. This paper argues that understanding characteristics of complex system could greatly benefit financial analysts, financial regulators, as well as macroeconomic policy makers.
European Commission (DG Joint Research Centre)（欧盟委员会（联合研究中心））；Economics and Econometrics Research Institute (EERI)（经济与计量经济学研究所）；Catholic University of Leuven (LICOS)（鲁汶天主教大学）；Slovak University of Agriculture in Nitra (SUA)（尼特拉斯洛伐克农业大学）
Econophysics has developed as a research field that applies the formalism of Statistical Mechanics and Quantum Mechanics to address Economics and Finance problems. The branch of Econophysics that applies of Quantum Theory to Economics and Finance is called Quantum Econophysics. In Finance, Quantum Econophysics' contributions have ranged from option pricing to market dynamics modeling, behavioral finance and applications of Game Theory, integrating the empirical finding, from human decision analysis, that shows that nonlinear update rules in probabilities, leading to non-additive decision weigh…
