Generates shocks driven by a Cox-Ingersoll-Ross (square-root) stochastic
variance process, Euler-Maruyama discretized, for use as
sim_psy1(..., e = sim_vol_cir(...)).
Arguments
- n
Number of innovations to generate.
- kappa, theta, xi
Positive CIR parameters (mean-reversion speed, long-run variance, vol-of-vol).
- sigma0_sq
Non-negative starting variance. Defaults to
theta.- seed
An object specifying if and how the random number generator (rng) should be initialized. Either NULL or an integer will be used in a call to
set.seedbefore simulation. If set, the value is saved as "seed" attribute of the returned value. The default, NULL, will not change rng state, and return .Random.seed as the "seed" attribute. Results are reproducible across the parallel and non-parallel option when the same seed is used.
Details
$$d\sigma^2(r) = \kappa(\theta - \sigma^2(r))dr + \xi\sigma(r)dB(r)$$
discretized over n steps of r in \([0, 1]\), with variance
reflected at zero if a step would take it negative. Default parameters
(\(\kappa=0.03\), \(\theta=0.25\),
\(\xi=0.1\)) match Harvey, Leybourne & Zu (2019)'s robustness
design, "representative of Bollerslev and Zhou (2002)".
References
Harvey, D.I., Leybourne, S.J. & Zu, Y. (2019). "Testing explosive bubbles with time-varying volatility." Econometric Reviews, 38(10), 1131-1151.
Examples
sim_vol_cir(199, seed = 1)
#> [1] 0.205987356 -0.189689995 0.204056300 0.836760778 0.795004781
#> [6] -0.166196633 -1.141081285 1.251459377 0.335976136 0.273748433
#> [11] -0.006761588 0.260126532 -0.084048984 0.214181382 -0.200604067
#> [16] -0.692191057 0.498870406 0.767401466 -0.156929028 -0.640667816
#> [21] 0.329654725 -0.023093742 -0.900052202 0.001107622 -0.323000038
#> [26] -0.175477623 -0.594991013 0.926614335 -0.168429318 -0.813912001
#> [31] 0.100258326 0.135066518 -0.505582926 -1.485546708 -0.329226292
#> [36] 0.290458463 -0.030318427 -0.049702776 0.283795823 -0.604998689
#> [41] 0.562225617 -0.002736307 0.361527836 0.531110409 0.115217600
#> [46] -0.450874375 0.593803936 -1.023852553 -0.280348815 -0.131465509
#> [51] -0.085936079 0.529331575 0.070364056 0.210809074 -0.035783352
#> [56] -0.128482408 0.365683134 0.601126992 -1.251343888 0.299390368
#> [61] 0.195700426 -0.225686359 0.504558734 -0.207456991 -0.151570396
#> [66] 0.454797629 0.913287760 0.141685714 -0.223681822 -0.630657217
#> [71] -0.178095863 -0.507204854 -0.139085533 0.212690473 -0.456576439
#> [76] 1.408060004 0.083082130 0.600094395 -1.215430942 0.393633068
#> [81] -0.696451207 0.484824784 0.209660360 -0.216303098 0.695680044
#> [86] -0.369852550 -0.306917092 -0.532928868 -0.354985988 0.503386051
#> [91] 0.231389001 0.534331814 -0.209044586 0.203217679 0.132437789
#> [96] -0.781589933 0.978082192 0.073330296 0.416008606 0.514830420
#> [101] -0.027170270 -0.163647113 0.478349043 -0.557181217 1.049880885
#> [106] -0.203418215 0.887392672 0.815075089 0.044984502 0.308318434
#> [111] -0.562972422 0.176755082 0.569366567 0.054554543 -0.249003707
#> [116] -0.359078903 -0.019619302 0.582709567 -0.263291456 -0.066042628
#> [121] -0.705469009 0.268571486 0.716803656 0.819312982 0.445352888
#> [126] -1.021433231 0.264535957 0.250203313 -0.193800461 0.093080351
#> [131] -0.470728789 0.370186908 -0.177586808 -0.854813379 -0.198192064
#> [136] 0.737409093 -0.178830744 0.391213611 0.503599717 0.002329976
#> [141] -0.186551130 -0.276848690 0.389620603 -0.553920945 0.127837440
#> [146] -0.149163407 -1.160927164 -0.732488058 0.476309591 -0.098584281
#> [151] 0.409308853 0.964757314 0.753255231 0.345365554 0.192501509
#> [156] -0.096655978 0.785010735 0.298736189 -0.585416992 -0.076871879
#> [161] -0.960381333 -0.098017438 -1.299119879 0.663410641 -0.322861748
#> [166] -0.217486940 -0.086956379 0.313860185 0.344315080 0.287992242
#> [171] -0.290740273 -0.703349082 -0.200694342 0.143933744 -0.426052356
#> [176] -0.035552436 -0.602884744 -0.004313205 0.067829593 -0.077317874
#> [181] -0.087575294 0.934503489 0.406740793 0.593664355 -0.488296134
#> [186] 0.087224801 0.612270709 -0.030258536 -1.134137717 0.183143129
#> [191] -1.005416030 -0.427614512 0.699837697 0.323807977 0.577387608
#> [196] 0.160844875 -0.057378231 -0.486141104 0.832029629
