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1

Semmler, Willi. Asset prices, booms and recessions: Financial economics from a dynamic perspective. 3rd ed. Springer, 2011.

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2

Bhattacharya, Sudipto. Financial intermediation versus stock markets in a dynamic intertemporal model. INSEAD, 1998.

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3

Aït-Sahalia, Yacine. Dynamic equilibrium and volatility in financial asset markets. National Bureau of Economic Research, 1996.

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4

Thorsten, Hens, and Schenk-Hoppe Klaus Reiner, eds. Handbook of financial markets: Dynamics and evolution. North Holland, 2009.

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5

Mishchenko, Aleksandr, and Elena Miheeva. Methods of assessment of efficiency of management of production and financial activity of the enterprise. INFRA-M Academic Publishing LLC., 2019. http://dx.doi.org/10.12737/monography_5d1ae60d82d6d9.87533425.

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The proposed book describes the static and dynamic models of optimization of production and financial activities of the enterprise in the conditions of deterministic source data, and taking into account the uncertainty and risk. In the latter case, when choosing a management decision, not only the amount of expected profit, but also various types of risks, as well as such an indicator as the stability of the selected option of production and economic activity to changes in the market environment, are taken into account.
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6

Knapp, Keith. A dynamic spatial equilibrium model of the California alfalfa market. Giannini Foundation of Agricultural Economics, University of California, 1990.

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7

Mizuta, Takanobu, and Isao Yagi. Financial Market Design by an Agent-Based Model. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-1713-5.

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8

Kauppi, Olli. A model of imperfect dynamic competition in the Nordic power market. Helsinki School of Economics, 2009.

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9

Kauppi, Olli. A model of imperfect dynamic competition in the Nordic power market. Helsinki School of Economics, 2009.

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10

Moore, Tomoe. India's emerging financial market: A flow of funds model. Routledge, 2007.

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11

Hu, Sheng C. Optimal advertising pricing policies in a mature market: A dynamic duopoly model. Institute for Research in the Behavioral, Economic, and Management Sciences, Krannert Graduate School of Management, Purdue University, 1989.

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12

Cave, Jonathan A. K. The interdictor's lot: A dynamic model of the market for drug smuggling services. Rand, 1988.

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13

Eliasson, Gunnar. The firm and financial markets in the Swedish micro-to-macro model: Theory, model, and verification. Industrial Institute for Economic and Social Research, 1985.

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14

Suarez, Javier. Closure rules, market power and risk-taking in a dynamic model of bank behaviour. LondonSchool of Economics Financial Markets Group, 1994.

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15

Graddy, Kathryn Jo. A dynamic model of price discrimination and inventory management at the Fulton fish market. National Bureau of Economic Research, 2009.

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16

Hommel, Ulrich. The strategic CFO: Creating value in a dynamic market environment. Springer, 2012.

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17

Love, Inessa. Financial development and financing constraints: International evidence from the structural investment model. World Bank, Development Research Group, Finance, 2001.

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18

Shih, Tsuen-Hua. Static and dynamic models of financial markets and the evaluation of monetary policy: A theoretical and econometric study. University of Birmingham, 1989.

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19

Caballero, Ricardo J. International and domestic collateral constraints in a model of emerging market crises. National Bureau of Economic Research, 2000.

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20

Kurosawa, Yoshitaka. Capital market and rating agencies in Asia: Structuring a credit risk rating model. Nova Science Publishers, 2011.

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21

Min, Hong G. Dynamic capital mobility, capital market risk, and exchange rate misalignment: Evidence from seven Asian countries. World Bank, 1998.

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22

Baanante, Carlos A. A dynamic model to forecast and evaluate changes and trends in the global market for fertilizers. IFDC, 2010.

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23

Chater, Sean Christopher. The optimal rate of monetary growth in a dynamic macro model with a labour market distortion. typescript, 1995.

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24

Philippon, Thomas. Real options in a dynamic agency model, with applications to financial development, IPOs, and business risk. National Bureau of Economic Research, 2007.

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25

Philippon, Thomas. Real options in a dynamic agency model, with applications to financial development, ipos, and business risk. National Bureau of Economic Research, 2007.

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26

Ferson, Wayne E. Economic, financial, and fundamental global risk in and out of the EMU. National Bureau of Economic Research, 1999.

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27

Zervoyianni, Athina. Product-market openness and dynamic responses to exogenous shocks and policies in a two-country, two-goods model. University of Hull. Department of Economics, 1994.

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28

Santa Fe Institute (Santa Fe, N.M.), ed. Agent-based modeling: The Santa Fe Institute artificial stock market model revisited. Springer, 2008.

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29

Pesando, James E. Discontinuities in pension benefit formulas and the spot model of the labor market: Implications for financial economists. Dept. of Economics, University of Toronto, 1985.

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30

Becker, Torbjörn. Common trends and structural change: A dynamic macro model for the pre- and postrevolution Islamic Republic of Iran. International Monetary Fund, Research Department, 1999.

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31

Chinn, Menzie David. Latin America and East Asia in the context of an insurance model of currency crises. National Bureau of Economic Research, 1999.

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32

Mercurio, Fabio. Modelling interest rates: Advances in derivatives pricing. Risk Books, 2009.

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33

Alekseev, Petr, Vladislav Antropov, Valeriy Barabanov, et al. The multi-currency standard and the global financial market. INFRA-M Academic Publishing LLC., 2022. http://dx.doi.org/10.12737/1871448.

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The monograph was prepared by a team of authors of the Financial University under the Government of the Russian Federation based on the results of research carried out at the expense of budgetary funds under the state assignment of the Financial University.
 The directions, forms and prospects of creating a multi-currency standard in the process of transformation of the world monetary and financial system are investigated. An integral model for assessing the sectoral development of the global financial market has been developed. The possibilities of adapting the Russian financial market t
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34

Semmler, Willi. Asset Prices, Booms and Recessions: Financial Economics from a Dynamic Perspective. Springer, 2014.

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35

Jia, Daniel Lukui. Dynamic Macroeconomic Models in Emerging Market Economies: DSGE Modelling with Financial and Housing Sectors. Springer Singapore Pte. Limited, 2021.

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36

Jia, Daniel Lukui. Dynamic Macroeconomic Models in Emerging Market Economies: DSGE Modelling with Financial and Housing Sectors. Springer Singapore Pte. Limited, 2020.

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37

Fornari, Fabio, and Antonio Mele. Stochastic Volatility in Financial Markets: Crossing the Bridge to Continuous Time (Dynamic Modeling and Econometrics in Economics and Finance). Springer, 2000.

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38

Westerhoff, Frank, and Reiner Franke. Agent-Based Models for Economic Policy Design. Edited by Shu-Heng Chen, Mak Kaboudan, and Ye-Rong Du. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199844371.013.40.

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With the help of two examples, this chapter illustrates the usefulness of agent-based models as tools for economic policy design. The first example applies a financial market model in which the order flow of speculators, relying on technical and fundamental analysis, generates intricate price dynamics. The second example applies a Keynesian-type goods market model in which the investment behavior of firms, relying on extrapolative and regressive predictors, generates complex business cycles. It adds a central authority to these two setups and explores the impact of simple intervention strategi
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39

Quintana, José Mario, Carlos Carvalho, James Scott, and Thomas Costigliola. Extracting S&P500 and NASDAQ Volatility: The Credit Crisis of 2007–2008. Edited by Anthony O'Hagan and Mike West. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198703174.013.13.

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This article demonstrates the utility of Bayesian modelling and inference in financial market volatility analysis, using the 2007-2008 credit crisis as a case study. It first describes the applied problem and goal of the Bayesian analysis before introducing the sequential estimation models. It then discusses the simulation-based methodology for inference, including Markov chain Monte Carlo (MCMC) and particle filtering methods for filtering and parameter learning. In the study, Bayesian sequential model choice techniques are used to estimate volatility and volatility dynamics for daily data fo
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40

McCauley, Joseph L. Dynamics of Markets: The New Financial Economics. Cambridge University Press, 2009.

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41

McCauley, Joseph L. Dynamics of Markets: The New Financial Economics. Cambridge University Press, 2009.

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42

McCauley, Joseph L. Dynamics of Markets: The New Financial Economics. Cambridge University Press, 2010.

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43

Abu Bakar, Nor'Aznin. Currency crisis in four Asian countries: The insolvency model approach. UUM Press, 2017. http://dx.doi.org/10.32890/9789672064039.

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The book deals with the 1997 Asian currency crisis and analyses the causes and consequences of the crisis.The two hypotheses, fundamental and panic/herd behavior hypotheses, which are often viewed as competing, are also examined. The first hypothesis states that fundamental imbalances triggered the Asian currency and financial crisis in 1997.The crisis occurred because the economies had deteriorating current accounts, a slow down in growth rates and short-term debt approaching a dangerous level; while the second hypothesis states that sudden shifts in market expectations and confidence were th
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44

Erceg, Christopher John. A dynamic general equilibrium model of the housing market. 1993.

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45

Cowhey, Peter F., and Jonathan D. Aronson. National Innovation Systems. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190657932.003.0001.

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Innovation is the key driver of economic prosperity. It is the product of an ecosystem of at least five interlinked building blocks: social networks and dynamic labor markets, shared assets that lower costs for innovative companies, flexible business models, financial models to support innovation, and appropriate government policies. National innovation systems transform periodically and public policy significantly influences their evolution. Since 1945, the United States has had two dominant systems of innovation. The first relied on vertically integrated firms such as AT&T or DuPont. Mor
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46

Fernández-Villaverde, Jesús, Pablo Guerrón-Quintana, and Juan Rubio-Ramírez. Futures markets, Bayesian forecasting and risk modelling. Edited by Anthony O'Hagan and Mike West. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198703174.013.14.

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This article demonstrates the utility of the Bayesian approach in forecasting and risk modelling regarding speculative trading strategies in financial futures markets. It first provides an overview of subjective expectations that are motivated as fair prices of futures contracts before discussing the futures markets and a portfolio mean-variance efficiency generalization. In particular, it considers the critical role of hedging to ensue attractive risk-adjusted performance. It also describes general Bayesian dynamic models and specific Bayesian dynamic linear models for assessing risk models i
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47

Transparency and Fragmentation: Financial Market Regulation in a Dynamic Environment. Palgrave Macmillan, 2002.

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48

Wells, S., J. Board, and C. Sutcliffe. Transparency and Fragmentation: Financial Market Regulation in a Dynamic Environment. Palgrave Macmillan Limited, 2002.

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49

Wells, S., J. Board, and C. Sutcliffe. Transparency and Fragmentation: Financial Market Regulation in a Dynamic Environment. Palgrave Macmillan Limited, 2002.

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50

Board, John, Stephen Wells, and Charles Sutcliffe. Transparency and Fragmentation: Financial Market Regulation in a Dynamic Environment. Palgrave Macmillan, 2002.

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