Skip to main content

graphics - How to compute the Multifractal Spectrum of a Financial Series with WTMM


I would like to know if someone knows how to compute the Multifractal Spectrum of a Financial Time Series (Currency) througth the Wavelet Transformation Modulus Maxima (WTMM).


I would highly appreciate any hint in order to calculate Dq, Tau(q), alpha, f(alpha).


I am pasting here the code I am using to get the Multifractal Spectrum (Ref: Gerd Baumann - Mathematica for Theoretical Physics (Mathematica 6.0), Springer Second Edition (2005), page 892) Comments: The following code helps to get the MultiFractal Spectrum, with Mathematica 6.0. I have updated the function ListPlot to ListLinePlot and PlotJoined to Joined as suggested in the Help of Mathematica 8.0.


The code seems to work when the input are the probabilities pi ={p1,p2,....pn} and when the values of each subset of the probability space one is seeking to characterize.


The code doesn't work 100% and I still don't know why (I am new to Mathematica).


The thing is, that the package provided by Mr. Baumann works when you give the input of the probabilities - yet I need that such process should be automated by the WTMM so I can see (analyze) the Whole Multifractal Spectrum.


----------------- ## ----------------------------



BeginPackage["MultiFractal`"];
Clear[Dq, Tau, Alpha, MultiFractal];
MultiFractal::usage = "MultiFractal[p_List,r_List] calculates the
multifractal spectrum D_q for a model based on the probabilities
p and the scaling factors r. This function plots five functions
Tau(q), D_q(q), Alpha(q), f(q) and f(Alpha).";
Begin["Private`"];

(*---calculate the multifractal dimensions---*)
Dq[p_List, r_List] := Block[{l1, l2, listrg = {}},

(*---length of the lists---*)
l1 = Length[p]; l2 = Length[r];
If[l1 == l2,
(*---variation of q and determination of D_q---*)
Do[gl1 = Sum[p[[j]]^q r[[j]]^((q - 1) Dfractal), {j, 1, l1}] - 1;
result = FindRoot[gl1 == 0, {Dfractal, -3, 3}];
result = -Dfractal /. result;
(*---collect the result in a list----*)
AppendTo[listrg, {q, result}], {q, -10, 10, .101}]
,

Print[" "];
Print[" Lengths of lists are different!"];
listrg = {}];
listrg];

(*----calculate Tau---*)
Tau[result_list] := Block[{l1, listtau = {}},
(*----lengths of the lists---*)
l1 = Length[result];
(*---calcultate Tau---*)

Do[AppendTo[
listtau, {result[[k, 1]],
result[[k, 2]] (1 - result[[k, 1]])}], {k, 1, l1}];
listtau];

(*---Legendre transform---*)
Alpha[result_List] :=
Block[{l1, dq, listalpha = {}, listf = {}, listleg = {}, mlist = {},
pl1, pl2},
(*---lengths of the lists---*)

l1 = Length[result];
(*---determine the differential dq---*)
dq = (result[[2, 1]] - result[[1, 1]]) 2;
(*---calculate Alpha by numerical differentiation---*)
Do[AppendTo[
listalpha, {result[[k,
1]], (result[[k + 1, 2]] - result[[k - 1, 2]])/dq}], {k, 2,
l1 - 1}];
l1 = Length[listalpha];
(*---calculate f and collect the result in a list---*)

Do[AppendTo[
listf, {result[[k,
1]], -(result[[k, 1]] listalpha[[k, 2]] - result[[k, 2]])}];
listalpha[[k, 2]] = -listalpha[[k, 2]], {k, 1, 12}];
(*---list of the Legendre transforms---*)
Do[AppendTo[listleg, {listalpha[[k, 2]], listf[[k, 2]]}];
AppendTo[mlist, listf[[k, 2]]], {k, 1, l2}];
(*---plot f and alpha versus q---*)
pl1 = ListLinePlot[listalpha, Joined -> {True, False},
AxesLabel -> {"q", "\[Alpha]"}, Prolog -> Thickness[0.001]];

pl2 = ListLinePlot[listf, Joined -> {True, False},
AxesLabel -> {"q", "f"}, Prolog -> Thickness[0.001]];
Show[{pl1, pl2}, AxesLabel -> {"q", "\[Alpha],f"}];
(*---plot the Legendre transform f versus alpha---*)
ListLinePlot[listleg, AxesLabel -> {"\[Alpha]", "f"}];
(*---print the maximum of f=D_ 0---*)
maxi = Max[mlist];
Print[" "];
Print[" D_0 = ", maxi]];


(*---calcultate the multifractal properties---*)
MultiFractal[p_List, r_List] := Block[{listDq, listTau},
(*---determine D_q---*)
listDq = Dq[p, r];
ListLinePlot[listDq, Joined -> {True, False},
AxesLabel -> {"q", "Dq"}, Prolog -> Thickness[0.001]]
(*---calculate Tau---*)
listTau = Tau[listDq];
ListLinePlot[listTau, Joined -> {True, False},
AxesLabel -> {"q", "\[Tau]"}, Prolog -> Thickness[0.001]]

(*---determine the Hoelder exponent---*)
Alpha[listTau]];

End[];

EndPackage[];

Answer



The code (Importation de la série)


ClearAll["Global`*"]
d = Import[SystemDialogInput["FileOpen"]];

ima = Flatten[d];
ima = ima + 0.000001;
n1 = Length[d];
n2 = Log[2, Length[ima]];
ny = Table[2^i, {i, 3, n2}];

(*Calcul des valeurs Dq pour chaque sous série*)

f[n_] := Module[{xx = ima, d2, stot, freqpuis, somfreqpuis, pq},
d2 = Partition[xx, n];

fmaxmin[x_List] := Mean[x];
stot = Map[fmaxmin, d2] // N;
stot = stot/Total[Flatten[stot]];
freqpuis = Table[stot^j, {j, -7, 7, 0.5}];
somfreqpuis = Total[Transpose[freqpuis]];
pq = Log[2, somfreqpuis]
]

logmuql = Flatten[Table[f[i], {i, ny}]] // N;
logmuqlt = Partition[logmuql, 29];

pqpart = logmuqlt;
logtaille = Log[2, ny] // N;

f2[nn_] :=
Module[{a = logtaille, b = logmuqlt, essai, line, linen, fa1},
essai = Partition[Riffle[logtaille, logmuqlt[[All, nn]]], 2];
line = LinearModelFit[essai, x, x];
linen = Normal[line];
fa1 = linen[[2, 1]] // N
]


Dq = Table[f2[i], {i, 1, 29}];
qq = Table[i, {i, -7, 7, 0.5}];
q = 1/(qq - 1.000001);
Dqq = q*Dq;
kq = 2 - Dqq;
cq = kq*q;
qmoin = qq - 1;
rq = qmoin*Dq;
ecartDq = Dqq[[1]] - Dqq[[29]] // N;

Print["ecart Dq = ", ecartDq]
ListPlot[{pqpart[[All, 1]], pqpart[[All, 5]], pqpart[[All, 10]],
pqpart[[All, 15]], pqpart[[All, 20]], pqpart[[All, 29]]},
ImageSize -> {300, 200}, Joined -> True,
AxesLabel -> {"log_tailleboite", "SomPiQ"}, PlotRange -> All,
PlotStyle -> PointSize[Medium]]

dqrel = Dqq - 1;
d3 = Riffle[qq, Dqq];
d6 = Partition[d3, 2];

d6 = Drop[d6, {17}];

ListPlot[{d6},
ImageSize -> {300, 200}, Joined -> True,
AxesLabel -> {"q", "Dq"}, PlotRange -> All, PlotStyle -> {Black}]

d3 = Riffle[qq, kq];
d6 = Partition[d3, 2];
d6 = Drop[d6, {17}];


ListPlot[{d6}, ImageSize -> {300, 200}, Joined -> True,
AxesLabel -> {"q", "Kq"}, PlotRange -> All, PlotStyle -> {Black}]

d3 = Riffle[qq, cq];
d6 = Partition[d3, 2];
d6 = Drop[d6, {17}];
ListPlot[{d6},
ImageSize -> {300, 200}, Joined -> True,
AxesLabel -> {"q", "Cq"}, PlotRange -> All, PlotStyle -> {Black}]


d3 = Riffle[qmoin, rq];
d6 = Partition[d3, 2];
d6 = Drop[d6, {17}];
ListPlot[{d6},
ImageSize -> {300, 200}, Joined -> True,
AxesLabel -> {"q", "Tauq"}, PlotRange -> All, PlotStyle -> {Black}]

d3 = Riffle[qq, dqrel];
d6 = Partition[d3, 2];
d6 = Drop[d6, {17}];

ListPlot[{d6},
ImageSize -> {300, 200}, Joined -> True,
AxesLabel -> {"q", "Dq_Relatif"}, PlotRange -> All,
PlotStyle -> {Black}]

fo[n_] :=
Module[{xx = ima, d2, stot, tfreqpuis, freqpuis, logfreqpuis,
produitfreq, somfproduit4},
d2 = Partition[xx, n];
fmaxmin[x_List] := Mean[x];

stot = Map[fmaxmin, d2] // N;
freqpuis = Table[stot^j, {j, -7, 7, 0.5}];
tfreqpuis = Total[Transpose[freqpuis]];
freqpuis = freqpuis/tfreqpuis;
logfreqpuis = Log[10, freqpuis];
produitfreq = freqpuis*logfreqpuis;
somfproduit4 = Map[Total, produitfreq] // N
]

totlogmuql = Flatten[Table[fo[i], {i, ny}]];

logmuqlt = Partition[totlogmuql, 29];
pqpart = logmuqlt;
logtaille = Log[10, ny] // N;

fo2[nn_] :=
Module[{a = logtaille, b = logmuqlt, essai, line, linen, fa1},
essai = Partition[Riffle[logtaille, logmuqlt[[All, nn]]], 2];
line = LinearModelFit[essai, x, x];
linen = Normal[line];
fa1 = ToExpression[linen[[2, 1]]] // N

]

fqr = Table[fo2[i], {i, 1, 29}];
qq = Table[i, {i, -7, 7, 0.5}];
fq2 = Riffle[qq, fqr];
fq2 = Partition[fq2, 2];

ListPlot[{fq2},
ImageSize -> {300, 200}, Joined -> True,
AxesLabel -> {"q", "f(alpha)q"}, PlotRange -> All,

PlotStyle -> {Black}]
ecartFq = fqr[[29]] - fqr[[1]] // N;
Print["ecart Fq = ", ecartFq]

Comments

Popular posts from this blog

plotting - How to draw lines between specified dots on ListPlot?

I would like to create a plot where I have unconnected dots and some connected. So far, I have figured out how to draw the dots. My code is the following: ListPlot[{{1, 1}, {2, 2}, {3, 3}, {4, 4}, {1, 4}, {2, 5}, {3, 6}, {4, 7}, {1, 7}, {2, 8}, {3, 9}, {4, 10}, {1, 10}, {2, 11}, {3, 12}, {4,13}, {2.5, 7}}, Ticks -> {{1, 2, 3, 4}, None}, AxesStyle -> Thin, TicksStyle -> Directive[Black, Bold, 12], Mesh -> Full] I have thought using ListLinePlot command, but I don't know how to specify to the command to draw only selected lines between the dots. Do have any suggestions/hints on how to do that? Thank you. Answer One possibility would be to use Epilog with Line : ListPlot[ {{1, 1}, {2, 2}, {3, 3}, {4, 4}, {1, 4}, {2, 5}, {3, 6}, {4, 7}, {1, 7}, {2, 8}, {3, 9}, {4, 10}, {1, 10}, {2, 11}, {3, 12}, {4, 13}, {2.5, 7}}, Ticks -> {{1, 2, 3, 4}, None}, AxesStyle -> Thin, TicksStyle -> Directive[Black, Bold, 12], Mesh -> Full, Epilog -> { Line[ ...

list manipulation - Selecting multiple columns from a matrix?

Sample data: data = { {{2013, 1, 1}, 24.13, 167.67, 231.82}, {{2013, 1, 2}, 32.15, 170.92, 225.99}, {{2013, 1, 3}, 35.43, 172.68, 221.67}, {{2013, 1, 4}, 36.73, 173.05, 218.32}, {{2013, 1, 5}, 58.19, 165.96, 197.05}, {{2013, 1, 6}, 69.99, 163.50, 187.52}, {{2013, 1, 7}, 71.37, 154.21, 175.58}, {{2013, 1, 8}, 72.51, 149.66, 163.25}}; I want a DateListPlot with three graphs, so for a matrix formed by columns 1 and 2, one for columns 1 and 3, and 1 for columns 1 and 4. At the moment I'm using this code: data2 = Transpose[{data[[All, 1]], data[[All, 2]]}]; data3 = Transpose[{data[[All, 1]], data[[All, 3]]}]; data4 = Transpose[{data[[All, 1]], data[[All, 4]]}]; DateListPlot[{data2, data3, data4}, Joined -> True, Filling -> {3 -> {1}}] but I have a hunch that this can be done more efficiently. I don't like the Transpose s in particular. Any ideas? edit (for extra credit) What if I need to multiply the second column by 2, which in my solution is simp...

dynamic - How can I make a clickable ArrayPlot that returns input?

I would like to create a dynamic ArrayPlot so that the rectangles, when clicked, provide the input. Can I use ArrayPlot for this? Or is there something else I should have to use? Answer ArrayPlot is much more than just a simple array like Grid : it represents a ranged 2D dataset, and its visualization can be finetuned by options like DataReversed and DataRange . These features make it quite complicated to reproduce the same layout and order with Grid . Here I offer AnnotatedArrayPlot which comes in handy when your dataset is more than just a flat 2D array. The dynamic interface allows highlighting individual cells and possibly interacting with them. AnnotatedArrayPlot works the same way as ArrayPlot and accepts the same options plus Enabled , HighlightCoordinates , HighlightStyle and HighlightElementFunction . data = {{Missing["HasSomeMoreData"], GrayLevel[ 1], {RGBColor[0, 1, 1], RGBColor[0, 0, 1], GrayLevel[1]}, RGBColor[0, 1, 0]}, {GrayLevel[0], GrayLevel...