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The Brownian Motion in Finance: An Epistemological Puzzle

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Abstract

While in medicine, comparison of the data supplied by a clinical syndrome with the data supplied by the biological system is used to arrive at the most accurate diagnosis, the same cannot be said of financial economics: the accumulation of statistical results that contradict the Brownian hypothesis used in risk modelling, combined with serious empirical problems in the practical implementation of the Black-Scholes-Merton model, the benchmark theory of mathematical finance founded on the Brownian hypothesis, has failed to change the Brownian representation, which has endured for more than fifty years despite the extent of its invalidation by experience. Without any statistical foundations, one mathematical representation (Brownian motion) has become the established approach, acting in the minds of practitioners as a “prenotion” in the sense the word is used by Durkheim (The rules of sociological method: and selected texts on sociology and its method, Free Press, New York, 1894), i.e. a “schematic, summary representation” which has produced a kind of spontaneous epistemology. The question arises of the persistence of this mathematical (Brownian) representation, which has been the basis for every financial risk modelling approach: how can its long life be explained? How was this spontaneous epistemology formed, and why did it prove to be so persistent? To address this question and offer an answer, I will test the various dynamics of scientific knowledge used with reference to financial modelling. All these dynamics are specific ways of describing the relationship between knowledge of a phenomenon (here, the representation of a stock market dynamic) and the phenomenon itself (here, stock price fluctuations). Observing that it is impossible for the positivist approach to solve the financial puzzle, I turn to the three principal postpositivist dynamics, developed by Kuhn, Lakatos and Quine. I shall try to make to speak these representations of science for financial research, in order to reflect on the dominance of the Brownian representation in finance. We shall see that none of the epistemologies examined can explain why the Brownian representation continues to be used in mathematical finance research. I shall then propose an alternative hypothesis, concerning a significant pervading mental model that has irrigated both academics and practitioners in the financial sector: the “principle of continuity” introduced into economics by Marshall in (Principles of economics, Macmillan, London, 1890). I consider that this principle of continuity has become a “persistent idea” in the form of a viral approach to representations, and I give this persistent idea the metaphorical name of the “Brownian virus”. Then, to explain the spread of this Brownian virus through the financial sector, the contamination of financial practices by this mental representation founded on the principle of continuity, I introduce the concept of the “financial Logos”, a discourse that structures practices and organisations, calculations, prudential regulations and accounting standards, leading to a general financialisation of society from the 1980s onwards.

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Notes

  1. French: “continue à droite, limite à gauche”, i.e. right continuous with left limits.

  2. Lévy processes, labelled after the French mathematician Paul Lévy, are continuous-time stochastic processes with independent and identically distributed (IID) increments. With the exception of Brownian motion with drift, they consist entirely of jumps. See for example Bertoin (1996) and Sato (1999).

  3. “Standard” means W0 = 1, the increments are independent and for 0 < s <t, the increment W(t)−W(s) is normally distributed with mean zero and variance ts.

  4. A replicating portfolio for a given asset is a portfolio of assets with the same financial properties (e.g. cash flows).

References

  • Aït-Sahalia Y, Jacod J (2009) Testing for jumps in a discretely observed process. Ann Stat 37(1):184–222

    Article  Google Scholar 

  • Aït-Sahalia Y, Jacod J (2010) Is Brownian motion necessary to model high-frequency data. Ann Stat 38(5):3093–3128

    Google Scholar 

  • Alexander S (1961) Price movements in speculative markets: trends or random walks. Ind Manag Rev 2(2):7–26

    Google Scholar 

  • Ané T, Geman H (2000) Order flow, transaction clock and normality of asset returns. J Finance 55(5):2259–2284

    Article  Google Scholar 

  • Bachelard G (1934) Le nouvel esprit scientifique, Paris. The New Scientific Spirit, Trans. A Goldhammer. Boston: Beacon Press

  • Bachelier L (1900) Théorie de la spéculation » , Annales scientifiques de l’École normale supérieure, série 3 tome 27, pp 21–86. Translated of the 1900 French edition in P. Cootner, ed., The Random Character of Stock Market Prices, pp 17–78. MIT Press, Cambridge, 1964

  • Ball C, Torous W (1985) On jumps in common stock prices and their impact on call option pricing. J Finance 40:155–173

    Article  Google Scholar 

  • Barnea A, Downes DH (1973) A reexamination of the empirical distribution of stock price changes. J Am Stat Assoc 68:348–350

    Article  Google Scholar 

  • Ben-David J, Teresa S (1975) Sociology of science. Ann Rev Sociol 1(1):203–222

    Article  Google Scholar 

  • Bertoin Jean (1996) Lévy processes. Cambridge University Press, Cambridge

    Google Scholar 

  • Black F, Scholes M (1973) The pricing of options and corporate liabilities. J Political Econ 81(3):637–659

    Article  Google Scholar 

  • Blattberg R, Gonedes N (1974) A comparison of the stable and student distributions as statistical models for stock prices. J Bus 47:244–280

    Article  Google Scholar 

  • Bouchaud J-P, Potters M (1997) Théorie des risques financiers, Saclay, CEA (collection Aléa). English translation 2003, Theory of Financial Risk and Derivative Pricing: From Statistical Physics to Risk Management, Cambridge, Cambridge UP

  • Bouchaud J-P, Potters M (2001) Welcome to a non-Black-Scholes world. Quant Finance 1(5):482–483

    Article  Google Scholar 

  • Boyarchenko S, Levendorskii S (2002) Non-gaussian merton-black-scholes theory. World Scientific, Advanced Series on Statistical Science and Applied Probability, p 9

    Book  Google Scholar 

  • Brenner M (1974) On the stability of the distribution of the market component in stock price changes. J Financ Quant Anal 9(6):945–961

    Article  Google Scholar 

  • Bruin De, Boudewijn, Walter, Christian (2017) Research habits in financial modelling: the case of non-normality of market returns in the 1970s and the 1980s. In: Ippoliti E, Chen P (eds) Methods and finance. A unifying view on finance, mathematics and philosophy. Springer, Cham, pp 79–93

    Google Scholar 

  • Callon M, Licoppe C, Muniesa F (2003) Technologies de Marché, Réseaux, 21 (122). Hermès Science, Paris

    Google Scholar 

  • Carnap R (1947) Meaning and necessity: a study in semantics and modal logic. University of Chicago Press, Chicago

    Google Scholar 

  • Carr P, Madan D, Geman H, Marc Y (2002) The fine structure of asset returns: an empirical investigation. J Bus 75(2):305–332

    Article  Google Scholar 

  • Chen P (2017) Mathematical representation in Economics and Finance: philosophical preference, mathematical simplicity and empirical evidence. In: Ippoliti E,  Chen P (eds) Methods and finance, A unifying view on finance, mathematics and philosophy. Springer, Cham, pp 17–49

    Google Scholar 

  • Chiapello E, Walter C (2016) The three ages of financial quantification: a conventionalist approach to the financier’s metrology. Hist Soc Res 41(2):155–177

    Article  Google Scholar 

  • Cont R (2001) Empirical properties of asset returns: stylized facts and statistical issues. Quant Financ 1(2):223–236

    Google Scholar 

  • Duhem P (1906), La théorie physique. Son objet, sa structure, Paris, Chevalier et Rivière. The Aim and Structure of Physical Theory. Translated by Wiener PP, Princeton University Press, Princeton, 1954

  • Durkheim E (1894), Les règles de la méthode sociologique. Paris: Les Presses universitaires de France, 16e édition, 1967. Tr. The rules of sociological method: and selected texts on sociology and its method. Free Press, New York, 2014

  • Engle R (1982) Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom Inflation. Econometrica 50:987–1007

    Article  Google Scholar 

  • Eberlein E, Keller U (1995) Hyperbolic distributions in finance. Bernoulli 1:281–299

    Article  Google Scholar 

  • Eberlein E, Keller U, Prause K (1998) New insights into smiles, mispricing and value at risk: the hyperbolic model. J Business 71(3):371–405

    Article  Google Scholar 

  • Fielitz B, Smith E (1972) Asymmetric stable distributions of stock price changes. J Am Stat Assoc 67:813–814

    Article  Google Scholar 

  • Granger Clive W J, Orr Daniel (1972) Infinite variance and research strategy in time series analysis. J Am Stat Assoc 67(338):275–285

    Google Scholar 

  • Hagerman R (1978) More evidence of the distribution of security returns. J Financ 33:1213–1221

    Article  Google Scholar 

  • Harrison M, Kreps D (1979) Martingales and arbitrage in multiperiod securities markets. J Econ Theory 20:381–408

    Article  Google Scholar 

  • Harrison M, Pliska S (1981) Martingales and Stochastic Integrals in the Theory of Continuous Trading. Stoch Process Appl 11:215–260

    Article  Google Scholar 

  • Hempel CG (1966) Philosophy of Natural Science. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  • Hsieh D (1991) Chaos and nonlinear dynamics: application to financial markets. J Finance 46(5):1839–1877

    Article  Google Scholar 

  • Hsu DA, Miller R, Wichern D (1974) On the stable paretian behavior of stock market prices. J Am Stat Assoc 69:108–113

    Article  Google Scholar 

  • Hume D (1739) A treatise of human nature. Oxford University Press, 2000

  • Hume D (1748) An enquiry concerning human understanding. Hackett Publishing, Indianapolis, 1977

  • Ippoliti E (2017a) Methods and finance: a view from outside. In: Ippoliti E, Chen P (eds) Methods and finance. A unifying view on finance, Mathematics and philosophy. Springer, Cham, pp 3–14

    Google Scholar 

  • Ippoliti E (2017b) Methods and finance: a view from inside. In: Ippoliti E, Chen P (eds) Methods and finance. A unifying view on finance, mathematics and philosophy. Springer, Cham, pp 121–128

    Google Scholar 

  • Ippoliti E (2017c) Dark data. Some methodological issues in finance. In: Ippoliti E, Chen P (eds) Methods and finance. A unifying view on finance, mathematics and philosophy. Springer, Cham, pp 179–194

    Google Scholar 

  • Jarrow R, Rosenfeld E (1984) Jump risks and intertemporal capital asset pricing. J Bus 57(3):337–351

    Article  Google Scholar 

  • Jorion P (1988) On jump processes in the foreign exchange and stock markets. Rev Financ Stud 1(4):259–278

    Article  Google Scholar 

  • Jorion P (2000) Value at risk. McGraw-Hill, Blacklick

    Google Scholar 

  • Knorr-Cetina K (1999) Epistemic cultures. How the Sciences Make Knowledge. Harvard University Press, Cambridge

    Google Scholar 

  • Kou SG (2002) A jump-diffusion model for option pricing. Manage Sci 48(8):1086–1101

    Article  Google Scholar 

  • Kuhn T (1962) The structure of scientific revolutions. University of Chicago Press, 1970, Chicago

    Google Scholar 

  • Lakatos I (1970), “History of science and its rational reconstructions”, PSA: Proceedings of the biennial meeting of the philosophy of science association, pp 91–136

  • MacKenzie D (2006) An engine, not a camera: how financial models shape markets. MIT Press, Cambridge

    Book  Google Scholar 

  • MacKenzie D, Spears T (2014) The formula that killed wall street’: the gaussian copula and modelling practices in investment banking. Soc Stud Sci 44:393–417

    Article  Google Scholar 

  • Madan D, Peter C, Chang E (1998) The variance gamma process and option pricing. Eur Finance Rev 2(1):79–105

    Article  Google Scholar 

  • Mandelbrot B (1963) The variation of certain speculative prices. J Bus 36:394–419

    Article  Google Scholar 

  • Mandelbrot B (1967) The variation of some other speculative prices. J Bus 40:393–413

    Article  Google Scholar 

  • Mandelbrot B (1997) Fractals and scaling in finance: discontinuity, concentration, risk. Springer, New York

    Book  Google Scholar 

  • Mantegna R, Stanley E (2000) An introduction to Econophysics: correlations and complexity in finance. Cambridge University Press, Cambridge

    Google Scholar 

  • Mantzavinos C (2001) Individuals, institutions, and markets. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Marshall A (1890) Principles of economics, 1st edn. Macmillan, London

    Google Scholar 

  • Merton R (1973) Theory of rational option pricing. Bell J Econ Manag Sci 4(1):141–183

    Article  Google Scholar 

  • Meyerson É (1908) Identité et réalité. Translated Identity and reality. Dover, New York, p 1962

    Google Scholar 

  • Officer R (1972) The distribution of stock returns. J Am Stat Assoc 67:807–812

    Article  Google Scholar 

  • Osborne M (1959) Brownian motion in the stock market. Oper Res 7(2):145–173

    Article  Google Scholar 

  • Poincaré H (1902) La science et l’hypothèse. Tr. Science and hypothesis. Dover Publications, New York, p 1957

    Google Scholar 

  • Popkin R (1968) Scepticism, theology and the scientific revolution in the seventeenth century. Stud Logic Found Math 49:1–39

    Article  Google Scholar 

  • Popper K (1959) The logic of scientific discovery. Routledge, London

    Google Scholar 

  • Praetz P (1972) The distribution of share price changes. J Bus 45:49–55

    Article  Google Scholar 

  • Prause K (1999), The generalized hyperbolic model: estimation, financial derivatives, and risk measures, Ph. D. thesis, University of Fribourg

  • Press S (1967) A compound events model for security prices. J Bus 40:317–335

    Article  Google Scholar 

  • Putnam H (1975) Mathematics, matter and method. Cambridge University Press, Cambridge

    Google Scholar 

  • Quine, Orman WV (1961) From a logical point of view: nine logico-philosophical essays. Harper and Row, New York

    Google Scholar 

  • Rainelli-Le M, Hélène (2003) Nature et fonctions de la théorie financière: quelques réflexions. PUF, Paris

    Google Scholar 

  • Samuelson AP (1965) Rational theory of warrant pricing. Ind Manag Rev 6(2):13–39

    Google Scholar 

  • Sato K (1999) Lévy processes and infinitely divisible distributions. Cambridge University Press, Cambridge

    Google Scholar 

  • Sewell M (2011), “Characterization of Financial Time Series”, UCL Dept. of Computer Science

  • Sheikh A, Hongtao Q (2009), “Non-normality of market returns: technical report”, JP morgan asset management, strategic investment advisory group

  • Sornette Didier (2003) Why stock markets crash. Princeton University Press, Princeton

    Google Scholar 

  • Teichmoller J (1971) A note on the distribution of stock price changes. J Am Stat Assoc 66:282–284

    Article  Google Scholar 

  • Walter C (1994) Les structures du hasard en économie. Efficience des marchés, lois stables et processus fractals, Thèse de doctorat, Institut d’études politiques de Paris

  • Walter C (1996) Une histoire du concept d’efficience sur les marchés financiers. Ann Hist Sci Soc 51(4):873–905

    Google Scholar 

  • Walter C (2002) Le phénomène leptokurtique sur les marchés financiers. Finance 23(2):15–68 Reprint: Chapter 7 of Walter (2013)

    Google Scholar 

  • Walter C (2005) La gestion indicielle et la théorie des moyennes. Revue d’économie financière 79(2):113–136 Reprint: Chapter 4 of Walter (2013)

    Article  Google Scholar 

  • Walter C (2013) Le modèle de marche au hasard en finance. Paris: Economica

  • Walter C (2016) The financial Logos: the framing of financial decision-making by mathematical modelling. Res Int Bus Finance 37:597–604

    Article  Google Scholar 

  • Walter C (2017) The extreme value problem in finance: comparing the pragmatic programme with the Mandelbrot programme. In: Longin F (ed) Extreme events in finance: a handbook of extreme value theory and its applications. Wiley, Hoboken, pp 25–51

    Google Scholar 

  • Walter C (2019) The leptokurtic crisis and the discontinuous turn in financial modelling. In: Chambost I, Lenglet M, Tadjeddine Y (eds) The making of finance. Perspectives from the social sciences. Routledge, New York, pp 77–89

    Google Scholar 

  • Wiener N (1966) God and Golem Inc. MIT Press, London

    Google Scholar 

Download references

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Walter, C. The Brownian Motion in Finance: An Epistemological Puzzle. Topoi 40, 1–17 (2021). https://doi.org/10.1007/s11245-019-09660-7

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