Stochastic volatility as a simple generator of apparent financial power laws and long memory

Quantitative Finance

Volumn 1, Issue 6, 2001, Pages 621-631

  Lebaron, Blake ^a,b,c  

^a BRANDEIS UNIVERSITY   (United States)

^b NATIONAL BUREAU OF ECONOMIC RESEARCH   (United States)

^c SANTA FE INSTITUTE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85012545809     PISSN: 14697688     EISSN: 14697696     Source Type: Journal    
DOI: 10.1088/1469-7688/1/6/304     Document Type: Article

References (72)

1. Alizadeh S, Brandt M W and Diebold F X 2001 High- and low-frequency exchange rate volatility dynamics: range-based estimation of stochastic volatility models National Bureau of Economic Research Technical Report 8162
2. Andersen T G, Diebold T B F X and Labys P 2001 Modelling and forecasting realized volatility National Bureau of Economic Research Technical Report 8160 (Cambridge, MA)
3. Ane T and Geman G 2000 Order flow, transaction clock, and normality of asset returns J. Finance 55 2259–84
4. Avnir D, Biham O, Lidar D and Malcai O 1998 Is the geometry of nature fractal? Science 279 39–40
5. Axtell R L 2001 Zipf distribution of US firm sizes Science 293 1818–20
6. Baillie R T, Bollerslev T and Mikkelsen H-O 1996 Fractionally integrated generalized autoregressive conditional heteroskedasticity J. Econometrics 74 3–30
7. Beran J 1994 Statistics for Long-Memory Processes (New York: Chapman and Hall)
8. Black F 1976 Studies of stock price volatility changes Proc. Am. Stat. Assoc. Business Econ. Stat. Section vol 177–81
9. Bollerslev T, Engle R F and Nelson D B 1995 ARCH models Handbook of Econometrics vol 4 (New York: North-Holland)
10. Bouchaud J-P 2001 Power-laws in economy and finance: some ideas from physics Quant. Finance 1 105–12
11. Bouchaud J P, Giardina I and Mezard M 2001 On a universal mechanism for long-range volatility correlations Quant. Finance 1 212–6
12. Breidt F J, Crato N and de Lima P 1998 The detection and estimation of long memory in stochastic volatility J. Econometrics 83 325–48
13. Brock W A 1999 Scaling in economics: a readers guide Ind. Corporate Change 8 409–46
14. Brock W A, Lakonishok J and LeBaron B 1992 Simple technical trading rules and the stochastic properties of stock returns J. Finance 47 1731–64
15. Calvet L and Fisher A 2001 Multifractality in asset returns: theory and evidence Rev. Economics Stat.
16. Campbell J, Grossman S J and Wang J 1993 Trading volume and serial correlation in stock returns Q. J. Economics 108 905–40
17. Campbell J and Shiller R 1988 Stock prices, earnings, and expected dividends J. Finance 63 661–76
18. Campbell J Y, Lo A W and MacKinlay A C 1996 The Econometrics of Financial Markets (Princeton, NJ: Princeton University Press)
19. Chauvet M and Potter S 2001 Nonlinear risk Macroeconomic Dynamics
20. Clark P K 1973 A subordinated stochastic process model with finite variance for speculative prices Econometrica 41 135–55
21. Cont R 2001 Empirical properties of asset returns: stylized facts and statistical issues Quant. Finance 1 223–36
22. Cutler D M, Poterba J M and Summers L H 1989 What moves stock prices? J. Portfolio Management 4–12
23. Dacorogna M M, Gencay R, Muller U A, Olsen R B and Pictet O V 2001 An Introduction to High-Frequency Finance (San Diego, CA: Academic)
24. Dacorogna M M, Muller U A, Pictet O V and de Vries C G 1998 Extremal forex returns in extremely large data sets Timbergen Institute Technical Report Erasmas University, Rotterdam
25. Dacorogna M, Muller U, Olsen R and Pictet O 2001 Defining efficiency in heterogeneous markets Quant. Finance 1 198–201
26. Diebold F X and Inoue A 1999 Long memory and structural change Stern School Technical Report NYU New York
27. Ding Z, Granger C and Engle R F 1993 A long memory property of stock market reutnrs and a new model J. Empirical Finance 1 83–106
28. Embrechts P, Kluppelberg C and Mikosch T 1997 Modelling Extremal Events (Heidelberg: Springer)
29. Engle R F and Lee G G J 1993 A permanent and transitory component model of stock return volatility Technical Report (Berkeley, CA: University of California Press)
30. Farmer J D 1999 Physicists attempt to scale the ivory towers of finance Comput. Sci. Eng. (IEEE) 26–39
31. Franses P H and van Dijk D 2000 Nonlinear Time Series Models in Empirical Finance (Cambridge: Cambridge University Press)
32. Ghysels E 1998 On stable factor structures in the pricing of risk: do time varying betas help or hurt? J. Finance 53 549–74
33. Ghysels E, Harvey A C and Renault E 1996 Stochastic volatility Handbook of Statistics vol 14, ed G S Maddala and C R Rao (Amsterdam: North-Holland) pp 119–1
34. Gourieroux C and Jasiak J 2001 Memory and infrequent breaks Economics Lett. 70 29–41
35. Granger C W 1980 Long memory relationships and the aggregation of dynamic models J. Econometrics 14 227–38
36. Granger C W J and Ding Z 1996 Varieties of long memory models J. Econometrics 73 61–77
37. Granger C W J and Hyung N 1999 Occasional structural breaks and long memory Technical Report (Berkeley, CA: University of California Press)
38. Hamilton J D and Lin G 1996 Stock market volatility and the business cycle J. Appl. Econometrics 11 573–93
39. Jefferies P, Hart M, Hui P M and Johnson N F 2000 From market games to real-world markets Physics Department Technical Report (Oxford: Oxford University Press)
40. Kirman A P and Teyssiere G 1998 Microeconomic models for long-memory in the volatility of financial time series EHESS Universite d’ Aix-Marseille III Technical Report
41. Koedijk K G, Schafgans M M A and de Vries C G 1990 The tail index of exchange rate returns J. Int. Economics 29 93–108
42. LeBaron B 1992 Some relations between volatility and serial correlations in stock market returns J. Business 65 199–219
43. LeBaron B 2000 The stability of moving average technical trading rules on the Dow Jones index Derivatives Use, Trading, Regulation 5 324–38
44. LeBaron B 2001a Empirical regularities from interacting long and short memory investors in an agent based stock market IEEE Trans. Evolutionary Comput. 5 442–55
45. LeBaron B 2001b Evolution and time horizons in an agent based stock market Macroecon. Dyn. 5 225–54
46. Levy M, Levy H and Solomon S 1994 A microscopic model of the stock market: cycles, booms, and crashes Economics Lett. 45 103–11
47. Liu M 1995 Modelling long memory in stock volatility Duke University Technical Report
48. Lo A W and MacKinlay A C 1988 Stock prices do not follow random walks: evidence from a simple specification test Rev. Financial Stud. 1 41–66
49. Loretan M and Phillips P C B 1994 Testing the covariance stationarity of heavy-tailed time series: an overview of the theory with some applications to several financial series J. Empirical Finance 1 211–48
50. Lux T 1999 Muti-fractal processes as models for financial returns: a first assessment Department of Economics Technical Report University of Bonn
51. Malcai O, Lidar D A, Biham O and Avnir D 1997 Scaling range and cutoffs in empirical fractals Phys. Rev. E 56 2817–28
52. Mandelbrot B B 1963 The variation of certain speculative prices J. Business 36 394–419
53. Mandelbrot B B 1997 Fractals and Scaling in Finance (New York: Springer)
54. Mandelbrot B B and Taylor H M 1967 On the distribution of stock price differences Operations Res. 15 1057–62
55. Mantegna R N and Stanley H E 1996 Scaling behaviour in the dynamics of an economic index Nature 376 46–9
56. Mantegna R N and Stanley H E 1998 Modelling of financial data: comparison of the truncated Levy flight and the ARCH(1) and GARCH(1,1) processes Physica A 254 77–84
57. Mantegna R N and Stanley H E 1999 An Introduction to Econophysics: Correlations and Complexity in Finance (Cambridge: Cambridge University Press)
58. Mikosch T and Starica C 2000 Change of structure in financial time series, long range dependence and the GARCH model Department of Mathematics Technical Report University of Groningen
59. Mills T C 1999 The Econometric Modelling of Financial Time Series 2nd edn (Cambridge: Cambridge University Press)
60. Muller U A, Dacorogna M M, Olsen R B, Pictet O V, Schwarz M and Morgenegg C 1990 Statistical study of foreign exchange rates, empirical evidence of a price change scaling law, and intraday analysis J. Banking Finance 14 1189–208
61. Pasquini M and Serva M 1999 Multiscale behaviour of volatility autocorrelations in a financial market Economics Lett. 65 275–9
62. Peters E 1994 Fractal Market Analysis (New York: Wiley)
63. Plerou V, Gopikrishnan P, Amaral L A N, Meyer M and Stanley H E 1999 Scaling of the distribution of price fluctuations of individual companies Phys. Rev. E 60 6519–29
64. Plerou V, Gopikrishnan P, Gabaix X, Amaral L A N and Stanley H E 2001 Price fluctuations, market activity and trading volume Quant. Finance 1 262–9
65. Schwert G W 1989 Why does stock market volatility change over time? J. Finance 44 1115–54
66. Stanley H E, Amaral L A N, Canning D, Gopikrishnan P, Lee Y and Liu Y 1999 Econophysics: can physicists contribute to the science of economics Physica A 269 156–69
67. Stanley M H R, Buldyrev S V, Havlin S, Mantegna R, Salinger M A and Stanley H E 1996 Zipf plots and the size distribution of firms Economics Lett. 49 453–7
68. Stock J H 1987 Measuring business cycle time J. Political Economy 95 1240–61
69. Sullivan R, Timmerman A and White H 1999 Data-snooping, technical trading rule performance and the bootstrap J. Finance 54 1647–91
70. Vandewalle N and Ausloos M 1998 Multi-affine analysis of typical currency exchange rates Eur. Phys. J. B 4 257–61
71. White H 1984 Asymptotic Theory for Econometricians (New York: Academic)
72. Wu G 2001 The determinants of asymmetric volatility Rev. Financial Stud. 14 837–60