Modelization and Calibration of the Power-Law Distribution in Stock Market by Maximization of Varma Entropy

<div>Log-log diagram of the probability distribution of normalized return <svg height="15.8416pt" id="M92" style="vertical-align:-3.291101pt" version="1.1" viewbox="-0.0498162 -12.5505 32.1848 15.8416" width="32.1848pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><rect height="0.65243" width="32.0852" x="0" y="-11.8482"></rect><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M669 636L663 650H260C230 650 221 652 208 675H186C177 621 162 548 144 481L173 479C195 534 211 560 226 578C248 604 266 615 373 615H544C460 511 114 112 23 16L31 0H561C577 34 611 135 622 170L594 182C566 125 544 88 515 65C481 38 416 35 319 35C249 35 197 37 152 41C270 184 542 501 669 636Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,8.931,3.132)"><path d="M610 0V27L347 666L316 657L46 26V0H610ZM504 54H116L310 537L504 54Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,14.878,3.132)"><path d="M329 433H203L239 587L230 596L147 534L123 433H57L30 395L34 388H115L61 129C37 16 59 -12 85 -12C147 -12 222 58 260 98L241 125C212 95 160 62 144 62C132 62 127 71 138 126L192 386L305 394L329 433Z"></path></g><g transform="matrix(.013,0,0,-0.013,18.572,0)"><path d="M300 -147C201 -63 143 98 143 270S200 602 300 686L282 710C136 610 70 450 70 271V270C70 89 136 -72 282 -170L300 -147Z"></path></g><g transform="matrix(.013,0,0,-0.013,23.07,0)"><path d="M324 430H196L233 583L223 592L145 529L120 430H54L29 396L31 388H111L56 126C33 15 54 -12 77 -12C137 -12 214 57 250 95L233 119C208 92 155 59 138 59C126 59 120 70 131 125L186 390L298 394L324 430Z"></path></g><g transform="matrix(.013,0,0,-0.013,27.504,0)"><path d="M275 270C275 450 212 609 64 710L45 686C145 604 203 442 203 270S147 -63 45 -147L64 -170C213 -68 275 89 275 270Z"></path></g></svg> with different time intervals for CSI300.</div>

Complexity

fig2

Figure 2

Figure 2: Modelization and Calibration of the Power-Law Distribution in Stock Market by Maximization of Varma Entropy 