160 ACTA WASAENSIALye, J. N. & V. L. Martin (1991). Modelling and testing stationary exchange ratedistributions: The case of the generalized Student’s t distribution. mimeo, Universityof Melbourne.Ma, S.-K. (1976). Modern Theory of Critical Phenomena, volume46ofFrontiers inPhysics. Addison-Wesley, Reading, Massachusetts.MacDonald, R. & M. P. Taylor, editors (1992). Exchange Rate Economics, volume1.Edward Elgar, Aldershot, England.MacKinlay, A. C. (1995). Multifactor models do not explain deviations from theCAPM. Journal of Financial Economics 38, 3—28.MacKinnon, J. G. (1994). Approximate asymptotic distribution functions for unit-rootand cointegration tests. Journal of Business and Economic Statistics 12:2, 167—176.MacKinnon, J. G. (1996). Numerical distribution functions for unit root and cointegrationtests. Journal of Applied Econometrics 11:6, 601—618.Madan, D. B., P. P. Carr & E. C. Chang (1998). The variance gamma process andoption pricing. European Finance Review 2, 79—105.Madan, D. B. & E. Senata (1990). The Variance Gamma (V.G.) model for share marketreturns. Journal of Business 63:4, 511—524.Maheu, J. M. (2005). Can GARCH models capture long-range dependence? Studiesin Nonlinear Dynamics and Econometrics 9:4, Article 1.Malkiel, B. G. (1979). The capital formation problem in the United States. Journal ofFinance 34:2, 291—306.Mandelbrot, B. (1963). The variation of certain speculative prices. Journal of Business36:4, 394—419.Mandelbrot, B. (1966). Forecasts of future prices, unbiased markets, and “martingale”models. Journal of Business 39:1, 242—255.Mandelbrot, B., A. Fisher & L. Calvet (1997). A multifractal model of asset returns.Discussion Paper 1164, Cowles Foundation for Research in Economics, Yale University.
ACTA WASAENSIA 161Mandelbrot, B. & H. M. Taylor (1967). On the distribution of stock price differences.Operations Research 15, 1057—1062.Manski, C. F. & D. McFadden, editors (1981). Structural Analysis of Discrete Datawith Econometric Applications. MIT Press, Cambridge, Massachusetts.Mantegna, R. N. & H. E. Stanley (1994). Stochastic process with ultraslow cnvergenceto a Gaussian: The truncated Lévy flight. Physical Review Letters 73:22, 2946—2949.Mantegna, R. N. & H. E. Stanley (1995). Scaling behaviour in the dynamics of aneconomic index. Nature 376, 46—49.Mantegna, R. N. & H. E. Stanley (2000). An Introduction to Econophysics. CambridgeUniversity Press, Cambridge.Markowitz, H. (1959). Portfolio Seclection: Efficient Diversification of Investments.John Wiley & Sons, New York.Martikainen, T. (2000). Efficiency and anomalies in the Finnish stock market. InKeim,D.&W.Ziemba,editors,Security Market Imperfections in World Wide EquityMarkets, pages 390—415. Cambridge University Press.Matia,K.,Y.Ashkenazy&H.E.Stanley(2003). Multifractal properties of pricefluctuations of stocks and commodities. Europhysics Letters 61:3, 422—428.Matteo, T. D., T. Aste & M. M. Dacorogna (2005). Long-term memories of developedand emerging markets: Using the scaling analysis to characterize their stage ofdevelopment. Journal of Banking and Finance 29:4, 827—851.McDonald, J. B. & W. K. Newey (1988). Partially adaptive estimation of regressionmodels via the generalized t distribution. Economic Theory 4, 428—457.McDonald, J. B. & Y. J. Xu (1995). A generalization of the beta distribution withapplications. Journal of Econometrics 66, 133—152.Menkhoff, L. (1998). The noise trading approach–questionaire evidence from foreignexchange. Journal of International Money and Finance 17:3, 547—564.Merton, R. C. (1976). Option pricing when underlying stock returns are discontinuous.Journal of Financial Economics 3, 125—144.
- Page 5 and 6:
ACTA WASAENSIA 52.10.1 Cross-Sectio
- Page 7 and 8:
ACTA WASAENSIA 7A5 Matlabcodeforerr
- Page 10 and 11:
10 ACTA WASAENSIAIn chapter 5 I sha
- Page 12 and 13:
12 ACTA WASAENSIA2 Statistical Prop
- Page 14:
14 ACTA WASAENSIA2.2 Absence of Ser
- Page 17 and 18:
ACTA WASAENSIA 17The survival or ta
- Page 19 and 20:
ACTA WASAENSIA 19& Scheinkman (1987
- Page 21 and 22:
ACTA WASAENSIA 212.6 Long Range Dep
- Page 23 and 24:
ACTA WASAENSIA 23A particular class
- Page 26 and 27:
26 ACTA WASAENSIAMultiscaling may t
- Page 28 and 29:
28 ACTA WASAENSIAHansen (1982) to c
- Page 30 and 31:
30 ACTA WASAENSIAThe leverage hypot
- Page 32 and 33:
32 ACTA WASAENSIAIn order to aviod
- Page 34 and 35:
34 ACTA WASAENSIAon a risk-adjusted
- Page 36 and 37:
36 ACTA WASAENSIAplanations for the
- Page 38 and 39:
38 ACTA WASAENSIAspeculative prices
- Page 40 and 41:
40 ACTA WASAENSIAindex α is howeve
- Page 42 and 43:
42 ACTA WASAENSIAThis approach has
- Page 44 and 45:
44 ACTA WASAENSIAimplying exponenti
- Page 46 and 47:
46 ACTA WASAENSIA3.2.4 Descriptive
- Page 48 and 49:
48 ACTA WASAENSIAdivisible version
- Page 50 and 51:
50 ACTA WASAENSIAto check their ade
- Page 52 and 53:
52 ACTA WASAENSIAvolatility into th
- Page 54 and 55:
54 ACTA WASAENSIAfeedback of the co
- Page 56 and 57:
56 ACTA WASAENSIAarriving at the fo
- Page 58 and 59:
58 ACTA WASAENSIAat iteration k com
- Page 60 and 61:
60 ACTA WASAENSIAmultipliers in the
- Page 62 and 63:
62 ACTA WASAENSIALux & Ausloos (200
- Page 64 and 65:
64 ACTA WASAENSIAmarkets dominated
- Page 66 and 67:
66 ACTA WASAENSIAThe “representat
- Page 68 and 69:
68 ACTA WASAENSIA(1983) 114 motivat
- Page 70 and 71:
70 ACTA WASAENSIAIn the following w
- Page 72 and 73:
72 ACTA WASAENSIASethi (1996) exten
- Page 74 and 75:
74 ACTA WASAENSIASummation over all
- Page 76 and 77:
76 ACTA WASAENSIAthe microscopic un
- Page 78 and 79:
78 ACTA WASAENSIA& Winker (2003) an
- Page 80 and 81:
80 ACTA WASAENSIAWe wish to obtain
- Page 82 and 83:
82 ACTA WASAENSIAindividual markets
- Page 84 and 85:
84 ACTA WASAENSIAreturn series. I l
- Page 86 and 87:
86 ACTA WASAENSIASwitches between c
- Page 88 and 89:
88 ACTA WASAENSIAfollowing necessar
- Page 90 and 91:
90 ACTA WASAENSIATable 1. Parameter
- Page 92 and 93:
92 ACTA WASAENSIAin stepwise search
- Page 94 and 95:
94 ACTA WASAENSIA0.2Logreturns Para
- Page 96 and 97:
96 ACTA WASAENSIA0.8Chartist Index
- Page 98 and 99:
98 ACTA WASAENSIATable 3. Kurtosis
- Page 100 and 101:
100 ACTA WASAENSIAthe most extreme
- Page 102 and 103:
102 ACTA WASAENSIATable 4. Estimate
- Page 104 and 105:
104 ACTA WASAENSIATable 8. Results
- Page 106 and 107:
106 ACTA WASAENSIATable 9. Results
- Page 108 and 109:
108 ACTA WASAENSIATable 11. Paramet
- Page 110 and 111: 110 ACTA WASAENSIA1 x 105 Aggr. Inv
- Page 112 and 113: 112 ACTA WASAENSIA200Aggr. Inventor
- Page 114 and 115: 114 ACTA WASAENSIA5 x 105 Aggr. Wea
- Page 116 and 117: 116 ACTA WASAENSIAOverall, we can a
- Page 118 and 119: 118 ACTA WASAENSIAby Lux (1998). Th
- Page 120 and 121: 120 ACTA WASAENSIAwhere s is a disc
- Page 122 and 123: 122 ACTA WASAENSIAprocessing valuat
- Page 124 and 125: 124 ACTA WASAENSIAProof. See append
- Page 126 and 127: 126 ACTA WASAENSIA2.5Logarithmice T
- Page 128 and 129: 128 ACTA WASAENSIA0.4Logreturns Ass
- Page 130 and 131: 130 ACTA WASAENSIA0.4Logreturns Ass
- Page 132 and 133: 132 ACTA WASAENSIATable 17. Probabi
- Page 134 and 135: 134 ACTA WASAENSIATable 18. Median
- Page 136 and 137: 136 ACTA WASAENSIAIn order to test
- Page 138 and 139: 138 ACTA WASAENSIAReferencesAbhyank
- Page 140 and 141: 140 ACTA WASAENSIABaillie, R. T. (1
- Page 142 and 143: 142 ACTA WASAENSIABlack, F. & M. Sc
- Page 144 and 145: 144 ACTA WASAENSIAButler, R. J., J.
- Page 146 and 147: 146 ACTA WASAENSIACont, R. (2001).
- Page 148 and 149: 148 ACTA WASAENSIAEmbrechts, P., C.
- Page 150 and 151: 150 ACTA WASAENSIAFielitz, B. D. (1
- Page 152 and 153: 152 ACTA WASAENSIAGhysels, E., A. C
- Page 154 and 155: 154 ACTA WASAENSIAHeston, S. L. (19
- Page 156 and 157: 156 ACTA WASAENSIAKaldor, N. (1939)
- Page 158 and 159: 158 ACTA WASAENSIALiesenfeld, R. (1
- Page 162 and 163: 162 ACTA WASAENSIAMikosch, T. (2003
- Page 164 and 165: 164 ACTA WASAENSIAPindyck, R. S. (1
- Page 166 and 167: 166 ACTA WASAENSIASethi, R. (1996).
- Page 168 and 169: 168 ACTA WASAENSIATesfatsion, L. &
- Page 170 and 171: 170 ACTA WASAENSIAAAppendixA1Matlab
- Page 172 and 173: 172 ACTA WASAENSIA87 % a3 = 1; %imp
- Page 174 and 175: 174 ACTA WASAENSIA181 nmout = max([
- Page 176 and 177: 176 ACTA WASAENSIA275276 figure;277
- Page 178 and 179: 178 ACTA WASAENSIA45 end464748 % In
- Page 180 and 181: 180 ACTA WASAENSIA454647 % Check wh
- Page 182 and 183: 182 ACTA WASAENSIAA4Matlab code for
- Page 184 and 185: 184 ACTA WASAENSIA888990 % create P
- Page 186 and 187: 186 ACTA WASAENSIA4344 nobs = 500;
- Page 188 and 189: 188 ACTA WASAENSIAA6Matlab code for
- Page 190 and 191: 190 ACTA WASAENSIA9192 for t = 1:T
- Page 192 and 193: 192 ACTA WASAENSIA185 fcash = fcash
- Page 194 and 195: 194 ACTA WASAENSIA279280281 %Output
- Page 196 and 197: 196 ACTA WASAENSIA(4.20), and o(τ
- Page 198 and 199: 198 ACTA WASAENSIAas t = n k P ˙
- Page 200 and 201: 200 ACTA WASAENSIA nBn˙f2 = v B n
- Page 202 and 203: 202 ACTA WASAENSIA f˙1−c1 = v B
- Page 204 and 205: 204 ACTA WASAENSIAlocal stability o