Stock Trading Strategies Based on Deep Reinforcement Learning

<div>The network structure for extracting features of a candlestick chart. <svg height="9.10848pt" id="M20" style="vertical-align:-3.291111pt" version="1.1" viewbox="-0.0498162 -5.81737 8.98808 9.10848" width="8.98808pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M219 86C216 168 211 250 206 337C201 410 189 448 163 448C131 448 79 396 43 344L60 322C91 359 110 375 118 375S132 358 136 298C141 238 152 81 155 -12H182C242 62 331 177 390 258C435 321 451 360 451 391C450 424 432 448 408 448C390 448 372 435 366 419C362 410 362 401 366 394C373 383 376 367 376 350C376 283 262 138 221 86H219Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,5.811,3.132)"><path d="M250 606C250 634 233 656 203 656C168 656 146 618 146 593C146 564 169 545 192 545C227 545 250 573 250 606ZM227 95L212 119C187 98 152 71 135 71C129 71 128 78 134 102L207 373C219 418 217 451 194 451C165 451 92 411 30 351L44 326C77 353 106 371 114 371C124 371 121 357 117 341L55 97C32 5 46 -12 70 -12C108 -12 191 51 227 95Z"></path></g></svg> is the final features.</div>

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Stock Trading Strategies Based on Deep Reinforcement Learning

Figure 5