Stable Portfolio Selection Strategy for Mean-Variance-CVaR Model under High-Dimensional Scenarios

<div>Out-of-sample performance of <svg height="12.3054pt" id="M241" style="vertical-align:-3.29108pt" version="1.1" viewbox="-0.0498162 -9.01432 16.9204 12.3054" width="16.9204pt" 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="M856 669C824 657 796 643 772 628C709 667 631 687 551 687C314 687 158 548 158 412C158 332 216 282 300 282C445 282 516 426 527 561H507C478 406 414 312 302 312C245 312 199 352 199 408C199 535 345 657 550 657C617 657 687 644 742 609C644 538 583 430 495 271C383 71 317 16 193 16C122 16 73 60 73 95H75C82 84 97 83 105 83C133 83 148 106 148 131C148 160 125 179 97 179C64 179 38 151 38 108C38 42 104 -15 211 -15C368 -15 496 71 610 302C672 426 704 522 770 588C803 559 825 518 825 465C825 382 787 316 731 316C710 316 697 328 697 345C697 358 700 380 733 399L723 417C688 398 665 367 665 338C665 303 688 272 737 272C821 272 886 359 886 447C886 516 850 572 797 612C816 627 836 639 863 650L856 669Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,11.83,3.132)"><path d="M290 377C321 398 342 415 358 430C378 450 389 473 389 502C389 578 329 635 238 635H237C184 635 137 610 109 578L64 515L88 493C112 529 154 573 208 573S303 542 303 482C303 409 233 370 141 341L149 308C165 313 190 319 215 319C272 319 341 283 341 193C342 98 292 43 222 43C163 43 122 72 96 94C88 101 79 100 70 94C61 87 47 73 46 60C44 47 48 37 62 23C76 10 118 -12 165 -12C238 -12 430 62 430 223C430 297 379 359 290 375V377Z"></path></g></svg>–<svg height="12.1958pt" id="M242" style="vertical-align:-3.181479pt" version="1.1" viewbox="-0.0498162 -9.01432 16.9204 12.1958" width="16.9204pt" 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="M856 669C824 657 796 643 772 628C709 667 631 687 551 687C314 687 158 548 158 412C158 332 216 282 300 282C445 282 516 426 527 561H507C478 406 414 312 302 312C245 312 199 352 199 408C199 535 345 657 550 657C617 657 687 644 742 609C644 538 583 430 495 271C383 71 317 16 193 16C122 16 73 60 73 95H75C82 84 97 83 105 83C133 83 148 106 148 131C148 160 125 179 97 179C64 179 38 151 38 108C38 42 104 -15 211 -15C368 -15 496 71 610 302C672 426 704 522 770 588C803 559 825 518 825 465C825 382 787 316 731 316C710 316 697 328 697 345C697 358 700 380 733 399L723 417C688 398 665 367 665 338C665 303 688 272 737 272C821 272 886 359 886 447C886 516 850 572 797 612C816 627 836 639 863 650L856 669Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,11.83,3.132)"><path d="M462 177V227H365V632H320C217 496 116 350 21 208V177H284V109C284 43 280 38 190 31V0H451V31C369 38 365 43 365 108V177H462ZM284 227H88C155 336 218 430 282 519H284V227Z"></path></g></svg> (<span class="nowrap"><svg height="11.7782pt" id="M243" style="vertical-align:-3.42938pt" version="1.1" viewbox="-0.0498162 -8.34882 36.9709 11.7782" width="36.9709pt" 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="M471 401C471 442 455 448 440 448C421 448 389 439 366 424C314 390 233 331 165 242H163L187 345C193 372 197 393 197 409C197 435 189 448 174 448C146 448 80 408 23 349L40 327C64 351 97 373 107 373C115 373 118 366 111 337L29 -4L36 -12C56 -4 83 3 110 9C123 69 136 126 150 172C227 283 336 381 377 381C392 381 396 370 379 298L326 74C290 -77 273 -172 273 -197C273 -219 316 -261 346 -261L353 -246C348 -227 352 -174 374 -66L457 310C467 352 471 381 471 401Z"></path></g><g transform="matrix(.013,0,0,-0.013,10.055,0)"><path d="M535 323V373H52V323H535ZM535 138V188H52V138H535Z"></path></g><g transform="matrix(.013,0,0,-0.013,21.318,0)"><path d="M241 635C89 635 35 457 35 312C35 153 89 -12 240 -12C390 -12 443 166 443 312C443 466 390 635 241 635ZM238 602C329 602 354 454 354 312C354 172 330 22 240 22C152 22 124 173 124 313S148 602 238 602Z"></path></g><g transform="matrix(.013,0,0,-0.013,27.558,0)"><path d="M113 -12C146 -12 170 11 170 46C170 78 146 103 114 103S58 78 58 46C58 11 82 -12 113 -12Z"></path></g><g transform="matrix(.013,0,0,-0.013,30.522,0)"><path d="M153 550H386L412 615L406 623H120L82 318C104 327 142 338 184 338C294 338 347 275 347 187C347 112 305 39 221 39C160 39 119 71 97 89C88 97 80 96 71 90C59 80 50 67 49 57C48 45 52 36 66 23C80 9 123 -12 169 -12C221 -11 288 15 342 59C403 109 431 165 431 225C431 308 366 395 238 395C212 395 165 379 127 364L153 550Z"></path></g></svg>).</span> (a) Performance of <span class="nowrap"><svg height="12.3054pt" id="M244" style="vertical-align:-3.29108pt" version="1.1" viewbox="-0.0498162 -9.01432 16.9204 12.3054" width="16.9204pt" 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="M856 669C824 657 796 643 772 628C709 667 631 687 551 687C314 687 158 548 158 412C158 332 216 282 300 282C445 282 516 426 527 561H507C478 406 414 312 302 312C245 312 199 352 199 408C199 535 345 657 550 657C617 657 687 644 742 609C644 538 583 430 495 271C383 71 317 16 193 16C122 16 73 60 73 95H75C82 84 97 83 105 83C133 83 148 106 148 131C148 160 125 179 97 179C64 179 38 151 38 108C38 42 104 -15 211 -15C368 -15 496 71 610 302C672 426 704 522 770 588C803 559 825 518 825 465C825 382 787 316 731 316C710 316 697 328 697 345C697 358 700 380 733 399L723 417C688 398 665 367 665 338C665 303 688 272 737 272C821 272 886 359 886 447C886 516 850 572 797 612C816 627 836 639 863 650L856 669Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,11.83,3.132)"><path d="M290 377C321 398 342 415 358 430C378 450 389 473 389 502C389 578 329 635 238 635H237C184 635 137 610 109 578L64 515L88 493C112 529 154 573 208 573S303 542 303 482C303 409 233 370 141 341L149 308C165 313 190 319 215 319C272 319 341 283 341 193C342 98 292 43 222 43C163 43 122 72 96 94C88 101 79 100 70 94C61 87 47 73 46 60C44 47 48 37 62 23C76 10 118 -12 165 -12C238 -12 430 62 430 223C430 297 379 359 290 375V377Z"></path></g></svg>;</span> (b) performance of <span class="nowrap"><svg height="12.1958pt" id="M245" style="vertical-align:-3.181479pt" version="1.1" viewbox="-0.0498162 -9.01432 16.9204 12.1958" width="16.9204pt" 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="M856 669C824 657 796 643 772 628C709 667 631 687 551 687C314 687 158 548 158 412C158 332 216 282 300 282C445 282 516 426 527 561H507C478 406 414 312 302 312C245 312 199 352 199 408C199 535 345 657 550 657C617 657 687 644 742 609C644 538 583 430 495 271C383 71 317 16 193 16C122 16 73 60 73 95H75C82 84 97 83 105 83C133 83 148 106 148 131C148 160 125 179 97 179C64 179 38 151 38 108C38 42 104 -15 211 -15C368 -15 496 71 610 302C672 426 704 522 770 588C803 559 825 518 825 465C825 382 787 316 731 316C710 316 697 328 697 345C697 358 700 380 733 399L723 417C688 398 665 367 665 338C665 303 688 272 737 272C821 272 886 359 886 447C886 516 850 572 797 612C816 627 836 639 863 650L856 669Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,11.83,3.132)"><path d="M462 177V227H365V632H320C217 496 116 350 21 208V177H284V109C284 43 280 38 190 31V0H451V31C369 38 365 43 365 108V177H462ZM284 227H88C155 336 218 430 282 519H284V227Z"></path></g></svg>.</span></div>

Mathematical Problems in Engineering

fig2

Figure 2

Figure 2: Stable Portfolio Selection Strategy for Mean-Variance-CVaR Model under High-Dimensional Scenarios 