Mathematical Model of Stock Prices via a Fractional Brownian Motion Model with Adaptive Parameters

<table class="table-group" width="800px"><tr class="fig-image" id="a"><td><img alt="791418.fig.002a" src="https://static.hindawi.com/articles/isrn/volume-2014/791418/figures/791418.fig.002a.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(a) </b>ADVANC</td></tr></table></td></tr><tr class="fig-image" id="b"><td><img alt="791418.fig.002b" src="https://static.hindawi.com/articles/isrn/volume-2014/791418/figures/791418.fig.002b.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(b) </b>LH</td></tr></table></td></tr></table>

<table>The historical drift rate <svg height="15.875" id="M74" style="vertical-align:-6.53424pt" version="1.1" viewbox="0 0 15.2125 15.875" width="15.2125" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
<g transform="matrix(.017,-0,0,-.017,.062,7.675)"><path d="M538 96q-38 -45 -84 -76.5t-71 -31.5q-44 0 -15 117q12 49 18 89h-2q-99 -128 -163 -178q-36 -28 -70 -28q-26 0 -44 38h-2q-16 -69 -16 -129q0 -43 11 -75.5t24 -42.5l1 -6q-7 -12 -24.5 -23t-37.5 -11q-40 0 -40 76q0 52 35 202l94 407l78 24l5 -5q-32 -122 -72 -310
q-7 -33 0 -55t25 -22q36 0 105.5 75t107.5 145l32 146l75 26h10q-50 -197 -78 -347q-7 -38 6 -38q7 0 31 17t47 39z" id="x1D707"></path></g>
<g transform="matrix(.012,-0,0,-.012,9.5,12.712)"><path d="M394 607q0 -25 -15.5 -43t-39.5 -18q-19 0 -32 13t-13 35t16 41.5t40 19.5q20 0 32 -13.5t12 -34.5zM360 349l-57 -283q-38 -188 -122 -263q-72 -64 -114 -64q-16 0 -30 10.5t-14 22.5q0 24 21 45q15 13 26 6q30 -20 54 -20q41 0 65 95q37 147 86 415q6 34 6.5 42.5
t-5.5 11.5q-18 0 -79 -54l-14 25q48 48 96.5 79t71.5 31q29 0 9 -99z" id="x1D457"></path></g>
</svg> for closed prices prediction from July 11, 2011, to July 8, 2013.</table>

International Scholarly Research Notices

fig2

Figure 2

Figure 2: Mathematical Model of Stock Prices via a Fractional Brownian Motion Model with Adaptive Parameters 