Lending Sociodynamics and Drivers of the Financial Business Cycle

Raymond J. Hawkins; Hengyu Kuang; Raymond J. Hawkins; Hengyu Kuang

doi:10.3934/QFE.2017.3.219

Quantitative Finance and Economics

2017, Volume 1, Issue 3: 219-252. doi: 10.3934/QFE.2017.3.219

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Research article Special Issues

Lending Sociodynamics and Drivers of the Financial Business Cycle

Raymond J. Hawkins ^{1,2
,
,},
Hengyu Kuang ¹

1.
Economics Department, University of California Berkeley, Berkeley, CA 94720, USA
2.
College of Optical Sciences, University of Arizona, Tucson, AZ 85721, USA

Received: 01 May 2017 Accepted: 26 July 2017 Published: 12 October 2017

We extend sociodynamic modeling of the financial business cycle to the Euro Area and Japan. Using an opinion-formation model and machine learning techniques we find stable model estimation of the financial business cycle using central bank lending surveys and a few selected macroeconomic variables. We find that banks have asymmetric response to good and bad economic information, and that banks adapt to their peers' opinions when changing lending policies.
- economic instability,
- Financial Instability hypothesis,
- Sociodynamics,
- opinion formation,
- systemic risk,
- Random Forest,
- Fokker-Planck equation
Citation: Raymond J. Hawkins, Hengyu Kuang. Lending Sociodynamics and Drivers of the Financial Business Cycle[J]. Quantitative Finance and Economics, 2017, 1(3): 219-252. doi: 10.3934/QFE.2017.3.219

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Abstract

We extend sociodynamic modeling of the financial business cycle to the Euro Area and Japan. Using an opinion-formation model and machine learning techniques we find stable model estimation of the financial business cycle using central bank lending surveys and a few selected macroeconomic variables. We find that banks have asymmetric response to good and bad economic information, and that banks adapt to their peers' opinions when changing lending policies.

References

[1]	Altavilla C, Darracq Paries M, Nicoletti G, et al. (2015) Loan supply, credit markets and the euro area financial crisis. ECB Working Paper 1861, European Central Bank.
[2]	Bouwman CH, Malmendier U (2015) Does a bank's history affect its risk-taking? Am Econ Rev 105: 321-325. doi: 10.1257/aer.p20151093
[3]	Breiman L (2001) Random forests. Mach Learn 45: 5-32. doi: 10.1023/A:1010933404324
[4]	Caruana R, Niculescu-Mizil A (2006) An empirical comparison of supervised learning algorithms. In Proceedings of the 23rd international conference on Machine learning, ACM, 161-168.
[5]	Favara G, Gilchrist S, Lewis K, Zakrajsek E (2016) Recession risk and the excess bond premium. FEDS Notes, Board of Governors of the Federal Reserve System.
[6]	Ghonghadze J, Lux T (2012) Modelling the dynamics of EU economic sentiment indicators: an interaction-based approach. Appl Econ 44: 3065-3088. doi: 10.1080/00036846.2011.570716
[7]	Ghonghadze J, Lux T (2016) Variation of lending standards and the financial instability hypothesis. FinMaP Working Paper, Kiel University.
[8]	Gilchrist S, Zakraj (2012) Credit spreads and business cycle fluctuations. Am Econ Rev 102: 1692-1720. doi: 10.1257/aer.102.4.1692
[9]	Granovetter M (2005) The impact of social structure on economic outcomes. J Econ Perspect 19: 33-50.
[10]	Hawkins RJ (2011) Lending sociodynamics and economic instability. Phys A: Stat Mech its Appl 390: 4355-4369. doi: 10.1016/j.physa.2011.07.003
[11]	Helbing D (2010) Quantitative Sociodynamics: Stochastic Methods and Models of Social Interaction Processes, Berlin: Springer.
[12]	Holmes A (1969) Operational constraints on the stabilization of money supply growth. Controlling Monetary Aggregates, (Boston MA: Federal Reserve Bank of Boston) 65-77.
[13]	Kane MJ, Price N, Scotch M, Rabinowitz P (2014) Comparison of ARIMA and Random Forest time series models for prediction of avian influenza H5N1 outbreaks. BMC Bioinf 15: 276. doi: 10.1186/1471-2105-15-276
[14]	Kawashima T, Nakabayashi M (June, 2014) Non-performing loan reduction with regulatory transition: A Japanese experience, 1998--2013. FSA Institute Discussion Paper Series DP2014-2, Financial Research Center (FSA Institute) Financial Services Agency.
[15]	Keynes JM (1931) The consequences to the banks of the collapse in money values (Aug. 1931). In Essays in Persuasion, New York: W. W. Norton \& Company, book published in 1963, 168-180.
[16]	Keynes JM (1937) The general theory of employment. Q J Econ 51: 209-223. doi: 10.2307/1882087
[17]	Khaidem L, Saha S, Dey SR (2016) Predicting the direction of stock market prices using random forest. arXiv preprint arXiv:1605.00003.
[18]	Kindleberger CP, O'Keefe R (2011) Manias, Panics, and Crashes, Springer.
[19]	Köhler-Ulbrich P, Hempell HS, Scopel S (2016) The euro area bank lending survey: Role, development and use in monetary policy preparation. Occasional Paper 179, European Central Bank.
[20]	Kursa MB, Rudnicki WR (2010) Feature selection with the Boruta package. J Stat Software 36: 1-13.
[21]	Lempérière Y, Deremble C, Seager P, Potters M, Bouchaud JP (2014) Two centuries of trend following. arXiv preprint arXiv:1404.3274.
[22]	Lux T (1997) Time variation of second moments from a noise trader/infection model. J Econ Dyn Control 22: 1-38. doi: 10.1016/S0165-1889(97)00061-4
[23]	Lux T (2009a) Applications of statistical physics in finance and economics. In Jr., J. B. R. and Jr., K. L. C., editors, Handbook of Research on Complexity, chapter 9. Edward Elgar, Cheltenham, UK.
[24]	Lux T (2009b) Rational forecast or social opinion dynamics? Identification of interaction effects in a business climate survey. J Econ Behav Organ 72: 638-655.
[25]	McLeay M, Radia A, Thomas R (2014) Money in the modern economy: an introduction. Bank of England Quarterly Bulletin Q1.
[26]	Menkhoff L, Sarno L, Schmeling M, Schrimpf A (2012) Currency momentum strategies. J Financ Econ 106: 660-684. doi: 10.1016/j.jfineco.2012.06.009
[27]	Minsky, H. P. (1977) The financial instability hypothesis: An interpretation of Keynes and an alternative to "standard" theory. Nebraska J Econ Bus 16: 5-16.
[28]	Minsky HP (2008) Stabilizing an Unstable Economy. McGraw-Hill, New York, NY. A reissue of 1986 publication.
[29]	Moore MJ (2009) Morgan Stanley's Mack welcomes regulation by Fed (update 2). Bloomberg.
[30]	Osborn DR (1995) Moving average detrending and the analysis of business cycles. Oxford Bulletin of Economics and Statistics 57: 547-558. doi: 10.1111/j.1468-0084.1995.tb00039.x
[31]	Towers G (1939) Minutes of proceedings and evidence respecting the Bank of Canada. Committee on Banking and Commerce, Ottawa: Government Printing Bureau.
[32]	Weidlich W (1972) The use of statistical models in sociology. Collective Phenomena 1: 51-59.
[33]	Weidlich W (2000) Sociodynamics: A Systematic Approach to Mathematical Modeling in the Social Sciences. Dover, Mineola, NY.
[34]	Weidlich W, Haag G (1983) Concepts and Models of a Quantitative Sociology: The Dynamics of Interacting Populations, volume 14 of Springer Series in Synergetics. Springer-Verlag, Berlin.
[35]	Werner RA (2014) Can banks individually create money out of nothing? -- The theories and the empirical evidence. Int Rev Financ Anal 36: 1-19.
[36]	Werner RA (2016) A lost century in economics: Three theories of banking and the conclusive evidence. Int Rev Financ Anal 46: 361-379. doi: 10.1016/j.irfa.2015.08.014

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