augmented-tbc-design/math-translation-for-z.ipynb

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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import random\n",
"import math"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"u_min = .97\n",
"u_max = 1.04\n",
"\n",
"tx_spread = 10"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"#vesting (should this be exposed in the app?)\n",
"cliff = 8 #weeks before vesting starts ~ 2 months\n",
"halflife = 52 #26 weeks, half life is ~6 months\n",
"#percentage of the hatch tokens which vest per week (since that is our timescale in the sim)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"1.005"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"(u_min+u_max)/2"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"##########################################\n",
"# This block is a literal translation of #\n",
"# src/math.ts #\n",
"##########################################\n",
"\n",
"#fair warning i pulled in analytically correct equations\n",
"#these equations have roots in them so always need to double check\n",
"#the packages we use to make sure edges near 0 are well handled.\n",
"\n",
"# Computes the price at a specific reserve `R`\n",
"def getPriceR(R, V0, k):\n",
" return (k * R ** ((k - 1) / k)) / V0 ** (1 / k)\n",
"\n",
"# Compute the reserve `R` for a given supply `S`\n",
"def getR(S, V0, k):\n",
" return (S)**k / V0\n",
"\n",
"def getS(R, V0, k):\n",
" return (V0*R)**(1/k)\n",
"\n",
"# compute the reserve if all that supply is burned\n",
"def getMinR(S,H,V0,k):\n",
" return getR(S-H, V0, k)\n",
"\n",
"# compute the price if all that supply is burned\n",
"def getMinPrice(S, H, V0, k):\n",
" if S == H:\n",
" myR = getR(S,V0,k)\n",
" myP = getPriceR(myR, V0, k) #numerical precision make complex numbers just suppress it\n",
" return abs(myP)\n",
" else:\n",
" minR = getMinR(S,H,V0,k)\n",
" return getPriceR(minR, V0, k)\n",
"\n",
"# Compute slippage at a point `R`, given a `deltaR`\n",
"def getSlippage(R, deltaR, V0, k):\n",
" S = (V0 * R) ** (1 / k)\n",
" deltaS = (V0 * (R + deltaR)) ** (1 / k) - S\n",
" realizedPrice = deltaR / deltaS\n",
" spotPrice = getPriceR(R, V0, k)\n",
" return abs(realizedPrice - spotPrice) / spotPrice\n",
"\n",
"# Get deltaR for a given price growth factor\n",
"def getDeltaR_priceGrowth(R, k, priceGrowth):\n",
" return -R + (priceGrowth * R ** (1 - 1 / k)) ** (k / (-1 + k))\n",
"\n",
"# Computes a tx distribution using a normal distribution,\n",
"# Given a sum of tx value and a number of transactions\n",
"# Demo: https://codepen.io/anon/pen/mNqJjv?editors=0010#0\n",
"def getTxDistribution(_sum, num, spread):\n",
" #spread is not exactly the variance\n",
" #we could refactor it so it was but i don't think its the best use of time\n",
" mean = _sum / num\n",
" off = mean * spread \n",
" x = []\n",
" for i in range(0, int(num)):\n",
" x.append(randn_bm(mean - off, mean + off))\n",
" return x\n",
"\n",
"# Random variable uniformly distributed\n",
"def rv_U(min, max):\n",
" return random.random() * (max - min) + min\n",
"\n",
"\n",
"# Standard Normal variate using Box-Muller transform.\n",
"# by https://stackoverflow.com/questions/25582882/javascript-math-random-normal-distribution-gaussian-bell-curve/36481059#36481059\n",
"def randn_bm(min, max):\n",
" u = 0\n",
" v = 0\n",
" while (u == 0):\n",
" u = random.random() # Converting [0,1) to (0,1)\n",
" while (v == 0):\n",
" v = random.random()\n",
" num = math.sqrt(-2.0 * math.log(u)) * math.cos(2.0 * math.pi * v)\n",
" \n",
" num = num / 10.0 + 0.5; # Translate to 0 -> 1\n",
" if (num > 1) or (num < 0):\n",
" num = randn_bm(min, max) # resample between 0 and 1 if out of range\n",
" num *= max - min # Stretch to fill range\n",
" num += min # offset to min\n",
" return num\n",
"\n",
"def vest_tokens(week,unvested_hatch_tokens, halflife, cliff):\n",
" #check cliff\n",
" if week < cliff:\n",
" return 0\n",
" else:\n",
" #rate of release given half-life \n",
" vest_fraction = .5**(1/halflife)\n",
" #number of tokens that vest in this week\n",
" return unvested_hatch_tokens*(1-vest_fraction)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"##########################################\n",
"# This block represent the user choices #\n",
"# src/App.ts #\n",
"##########################################\n",
"\n",
"# Given data\n",
"d0 = 1e6\n",
"theta = 0.35\n",
"p0 = 0.1\n",
"p1 = 0.3\n",
"wFee = 0.05\n",
"\n",
"# Initial params\n",
"k = p1 / p0 / (1 - theta)\n",
"R0 = (1 - theta) * d0\n",
"S0 = d0 / p0\n",
"V0 = S0 ** k / R0"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [],
"source": [
"##########################################\n",
"# Literal translation of the price walk #\n",
"# in src/App.ts #\n",
"##########################################\n",
"\n",
"# Price walk\n",
"R_t = [R0]\n",
"p_t = [getPriceR(R0, V0, k)]\n",
"S_t = [S0]\n",
"wFee_t = [0]\n",
"slippage_t = []\n",
"avgTxSize_t = []\n",
"\n",
"#hatchers tokens = S0 [section added by Z]\n",
"H_t = [S0] #total hatcher tokens not vested\n",
"floorprice_t= [] #initially the price is the floor as all tokens are hatcher tokens\n",
"\n",
"numSteps = 52\n",
"\n",
"# adding some extra stored variables so i can see\n",
"dR_t = []\n",
"all_tx = []\n",
"mean_slippage_t = []\n",
"\n",
"for t in range(0, numSteps):\n",
" txsWeek = rv_U(5, 2 * t + 5)\n",
" \n",
" R= R_t[-1]\n",
" S = S_t[-1]\n",
" H = H_t[-1]\n",
" #enforce the effects of the unvested tokens not being burnable\n",
" #print((R,S,H))\n",
" #print(getMinR(S,H,V0,k))\n",
" if H == S:\n",
" u_lower = 1\n",
" else:\n",
" R_ratio = np.real(getMinR(S,H,V0,k))/R\n",
" u_lower = max([1-R_ratio,u_min])\n",
" #print(u_lower)\n",
" \n",
" priceGrowth = rv_U(u_lower , u_max) #its misleading to call this price growth (its \"reserve growth\")\n",
"\n",
" deltaR = getDeltaR_priceGrowth(R, k, priceGrowth)\n",
" \n",
" #extra\n",
" dR_t.append(deltaR) #may be commented out if not used for statistics\n",
"\n",
" R_next = R + deltaR\n",
" txs = getTxDistribution(deltaR, txsWeek, tx_spread)\n",
" # Compute slippage\n",
" slippage_txs = [getSlippage(R, txR, V0, k) for txR in txs]\n",
" slippage_mean = np.mean(slippage_txs)\n",
" slippage_median = np.median(slippage_txs)\n",
" \n",
" txsWithdraw = filter(lambda tx: tx < 0, txs)\n",
" wFees = -wFee * sum(txsWithdraw)\n",
"\n",
" #vest\n",
" delta_H = vest_tokens(t,H, halflife, cliff)\n",
" H_next = H-delta_H\n",
" \n",
" #find floor price\n",
" S_next = getS(R, V0,k)\n",
" #print(S)\n",
" floorprice_next = getMinPrice(S_next, S_next-H_next, V0, k)\n",
" \n",
" # Store variables\n",
" R_t.append(R_next)\n",
" p_t.append(getPriceR(R_next, V0, k))\n",
" S_t.append(S_next)\n",
" slippage_t.append(slippage_median)\n",
" wFee_t.append(wFees)\n",
" H_t.append(H_next)\n",
" floorprice_t.append(floorprice_next)\n",
" \n",
" #use for statistics\n",
" all_tx = all_tx + slippage_txs \n",
" mean_slippage_t.append(slippage_mean)"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {},
"outputs": [],
"source": [
"change_rate = np.array(dR_t)/np.array(R_t[:-1])"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0.5,1,'Slippage Histogram')"
]
},
"execution_count": 43,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x117a73320>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.hist(all_tx, 30)\n",
"plt.vlines(np.median(all_tx), 0, 1000, 'g')\n",
"plt.vlines(np.mean(all_tx), 0, 1000, 'r')\n",
"plt.title('Slippage Histogram')"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0.5,1,'Log Scaled slippage histogram')"
]
},
"execution_count": 44,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x117cfa940>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.hist(np.log10(all_tx), 30)\n",
"plt.vlines(np.log10(np.median(all_tx)), 0, 1000, 'g') #median of the logs = median of the log of the distribution\n",
"plt.vlines(np.mean(np.log10(all_tx)), 0, 1000, 'k') #mean of the log distribution\n",
"plt.vlines(np.log10(np.mean(all_tx)), 0, 1000, 'r') #log of the mean\n",
"plt.title('Log Scaled slippage histogram')"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.LineCollection at 0x117f37470>"
]
},
"execution_count": 45,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x117887b38>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(slippage_t)\n",
"plt.plot(mean_slippage_t)\n",
"plt.xlabel('Weeks')\n",
"plt.ylabel('median slippage')\n",
"\n",
"plt.hlines(np.median(all_tx), 0, 52, 'g')\n",
"plt.hlines(np.mean(all_tx), 0, 52, 'r')"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.LineCollection at 0x117f1c7f0>"
]
},
"execution_count": 46,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x117f1c668>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(all_tx)\n",
"plt.xlabel('txs')\n",
"plt.ylabel('slippage')\n",
"K = len(all_tx)\n",
"\n",
"plt.hlines(np.median(all_tx), 0,K , 'g')\n",
"plt.hlines(np.mean(all_tx), 0, K, 'r')"
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0,0.5,'change_R')"
]
},
"execution_count": 47,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x117d976d8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(change_rate)\n",
"plt.xlabel('Weeks')\n",
"plt.ylabel('change_R')"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(array([ 2., 2., 0., 0., 8., 4., 8., 9., 8., 11.]),\n",
" array([-0.03702697, -0.02840965, -0.01979234, -0.01117503, -0.00255772,\n",
" 0.0060596 , 0.01467691, 0.02329422, 0.03191153, 0.04052884,\n",
" 0.04914616]),\n",
" <a list of 10 Patch objects>)"
]
},
"execution_count": 48,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1181a5cc0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.hist(change_rate)"
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0,0.5,'change_R')"
]
},
"execution_count": 49,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1183e82e8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(change_rate)\n",
"plt.xlabel('Weeks')\n",
"plt.ylabel('change_R')"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0,0.5,'Price')"
]
},
"execution_count": 50,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x118495320>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(np.array(S_t)-np.array(H_t))\n",
"plt.xlabel('Weeks')\n",
"plt.ylabel('Price')"
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0,0.5,'floorprice')"
]
},
"execution_count": 51,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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wHqgeCiKNwubdBfy/t1fy2oIckhJi+Z9L+3P16Wk0i1EYSMMRzlDoAmyusp8NjKyh3eVmdhawCvihu2+u3sDMJgOTAdLS0sJQqsiX89zcTdw9fSlRUXDruadw89mnaK6BNEjhDIWaOk292v6/gefdvdjMbgGeBs77wpvcpwBTADIyMqp/hkjElJVX8NsZy3nqkw2c3TuF+y4fpKGl0qCFMxSyga5V9lOBnKoN3H1Xld2/A/eFsR6Rk2pPYSm3PfcZH63O5cYxPbjz4n5Ea2ipNHDhDIVMIN3MehCMLpoITKrawMw6ufvW0O44YHkY6xE5adbnHuCGpzPZvLuA+y4fyJXD1a0pjUPYQsHdy8zsNmAmwZDUqe6+1MzuAbLcfTpwu5mNA8qA3cC14apH5GSZvSaX7/3zM6IMnr1hJCN18xtpRMy9YXXRZ2RkeFZWVqTLkCbE3VmyZS/vLN/Of5ZtZ9nWvaS3b8ET1wwnrZ0mn0nDYGbz3T3jWO00o1mkBoUl5Xy6bhf/Wb6dd5fvYNveIqIMhnVL4s6L+jJpZBotNbpIGiGFggjB2cD63APMWrmTWat2MnfdLorLKkiIi+bs3ilc0K8D5/ZtT9vEuEiXKhJWCgVp0gpKyvjLrLW8tiCHTbsLAOiZkshVI7txTp8URvRoq5nI0qQoFKTJenf5du56bSlb8gs5p08KN57Zg3N6t9d1AmnSFArS5GzdU8ivpy/jraXb6N2hBf+6ZRTDu7eNdFki9cIxQ8HMegN/ATq4+6lmNggY5+6/DXt1IidReYXz9CcbePDtlZRVOD/9ah9uOrMncTFRkS5NpN6ozZnC34GfAn8DcPdFZvYcoFCQBuOzTXn8z6tLWJqzl3P6pHDPuFPVTSRSg9qEQoK7z6u2/ntZmOoROal2HyjhvjdX8ELWZjq0asZjk4Zy8cCOup+ByBHUJhRyzewUQovZmdkEYOvR3yISWeUVzrTMTdz/1koOFJdx81k9+f756bRopstoIkdTm38htxKsUNrXzLYA64Grw1qVSBX7i8tYuW0vxaUVlLtTVuFUVDjloa24rIKSsgqKy8opLquguKyCmUu3sSh7D6f3bMs940+ld4eWkT4MkQbhmKEQuknOBWaWCES5+77wlyVNWU5+IVkb88jasJusDXms2LaXiuNcjaVDq2Y8MnEw407rrK4ikeNQm9FHvwfud/f80H4S8GN3/2W4i5PGyd2ZtXInq7bvY9eBEnL3F7Nrfwm7DhSzfW8xO/cVA5AQF82QtDbcdm4vBqe1ITEuhugoIyrKiDYjOirYmsVE0Sw2mrjoKJrFRtEsJoq46CiFgcgJqE330UXu/vODO+6eZ2YXAwoFOW6Ls/fw638vJWtjHgDNYqJIbtGM5BZxtG8ZT7+OrejfuRUZ3drSr1NLYqI1XFSkLtUmFKLNrJm7FwOYWXOgWXjLksZmx74iHnhrJS99lk27xDjuvWwgl57WmcS4aP1FL1KP1CYUngXeNbMnCUYgXU9w20yRYyouK2fqxxv403urKSmv4KYze3Lbeb10/2KReqo2F5rvN7PFwPkE913+jbvPDHtl0qDt3FfMtHmb+OfcTWzbW8QF/Trwi0v60SM5MdKlichR1GrQtru/CbwZ5lqkgXN3FmzO5+lPNjBj8VZKy50z05P5f988jTHpyZEuT0Rq4YihYGYfu/sYM9tHaOLawZcAd/dWYa9OGoTisnJeX7iVp+dsYFH2Hlo0i+Gqkd349qhunJLSItLlichxOGIouPuY0KNm/UiNcvcX889PN/GPTzeSu7+YXu1b8JvxA/jG0FTNHBZpoI76L9fMooBF7n7qiXy4mY0FHgGigcfd/d4jtJsA/AsY7u66AXM9tzRnD0/O3sD0BTmUlFdwbp8Urh/TgzG9kjWSSKSBO2oouHuFmS00szR333Q8H2xm0cBjwIVANpBpZtPdfVm1di2B24G5x1e61BV3Z82O/by1ZBszl21jyZa9NI+N5srhXbl2dHd1EYk0IrU5x+8ELDWzecCBg0+6+7hjvG8EsCa0TAZmNg0YDyyr1u43wP3AT2pbtIRfUWk5y7fu5e1l25m5ZBvrcoP/9UPT2vDLS/rxzWFdaZ2gYaUijU1tQuHXJ/jZXYDNVfazgZFVG5jZEKCru79uZkcMBTObDEwGSEtLO8FypCb5BSV8uDqXDbkH2LS7gE27Cti0u4Bte4sAiIkyTu/ZjuvG9OAr/TvQoVV8hCsWkXCqzTyFD8ysI8Ff/g5kuvu2Wnx2TZ3LlaOYQtcrHgaurUUNUwhWaiUjI+M4l0aT6vYUlvLOsu28viiHj1fnUhZaba5jq3jS2iYwulcy3dol0CM5kTPTk2mTEBfhikWkrtRmQbwbgbuA9wh+0f/RzO5x96nHeGs20LXKfiqQU2W/JXAqMCt0cbIjMN3Mxuli88lXUlbBm0u28u+FOXy4KpeS8gq6tGnODWN6cNHATvTt2JL42OhIlykiEVab7qOfAkPcfReAmbUDPgGOFQqZQLqZ9QC2ABOBSQdfdPc9QOWMJjObBfxEgXBy7dpfzD/nBsNGd+4rpmOreL49qhuXDurE4K5tNFpIRA5Tm1DIBqreQ2Efh18rqJG7l5nZbcBMgiGpU919qZndA2S5+/QTKVhqZ+W2fUz9eD2vLNhCSVkFZ/dO4boJ3TkrPYWoKAWBiNSsNqGwBZhrZq8RXBMYD8wzsx8BuPtDR3qju78BvFHtubuO0PacWtYsBMNEszbmsWLbPvIPlJBXUEp+QQl5BSXs2FfM0py9xMdGMWFYKted0Z103XlMRGqhNqGwNrQd9FroUb9lImBLfiH/Nz+bl+Zns2l3QeXziXHRtEmIIykxlraJcfz0q32YNCKNpERdJBaR2jvWjOZooIW7/7SO6pEaFJWW89aSbbw0P5vZa3Nxh1E923HHBemM7pVMm4RYmsXoIrGIfHnHmtFcbmZD66oYOdyeglKembOBpz7ZwK4DJaQmNecH56dz+dBUurZNiHR5ItII1ab7aIGZTSdYm6jqjOaXw1ZVE7d1TyFPfLSe5+ZtoqCknHP7pHDTmT05vWc7XSQWkbCqTSi0BXYB51V5zgGFwkm2eXcBj7y7mtcWbKHC4WuDOnHz2afQr5NWKReRulGbGc3X1UUhTVlZeQVTZ6/noXdWAXDVyG7cMKaHuohEpM7VZkZzKvBHYDTBGcLHwA/cPTvMtTUJi7Lz+dn/LWbZ1r1c0K8D94wfQOc2zSNdlog0UbXpPnoSeA74Zmj/6tBzF4arqKbgQHEZD769iqc+WU9yi2b89eqhfHVAR80wFpGIqk0opLj7k1X2nzKzO8JVUGPn7sxYvJXfz1hOzp4irj49jf8a25dW8VqGWkQirzahkGtmVwPPh/a/RXDhWY7T/I27+e2M5Xy+KZ++HVvy6LeGkNG9baTLEhGpVJtQuB74E8Ey1wCzQ89JLW3cdYD731rJjMVbSWnZjPsuH8iEYV2J1vBSEalnajP6aBNwrLusSQ1y9xfz11lreXrOBmKiorjjgnRuOrMnibqpvYjUUxp9FAY79hbxtw/X8c+5Gykuq+CKYV350Vd6665lIlLvafTRSZSTX8hfP1jLtMzNlFc44wd35tZze+nG9iLSYGj00QmoqHBy9xezOa+QLfmFZOcVsGrbPmYs3oo7TBiWyvfO6UVaO00+E5GGRaOPasndeW/FDv48ay2Lt+yhpKzisNfbJsZx5fCu3HL2KaQmKQxEpGE63tFHTnArziYz+sjdmbVqJ394ZxULs/fQtW1zrj2jO12TmpOalECXpOZ0adNcF49FpFHQ6KMjcHc+Wp3Lw/9Zxeeb8unSpjn3XT6Qy4amEhsdFenyRETC4oihYGaPHu2N7n77yS+nfvhkbS4Pvb2KrI15dG4dz++/MZAJw1KJi1EYiEjjdrQzhcuAXwBJQN6JfLiZjQUeAaKBx9393mqv3wLcCpQD+4HJ7r7sRL7XyZC1YTcPvr2KOet20bFVPL8ZP4ArhnfVXc1EpMk4WijsBWYB04Fzj/eDQ7fyfIxg6Go2kGlm06v90n/O3f8aaj8OeAgYe7zf68tauDmfB99ZxYerdpLcohl3XdqfSSPTiI9VGIhI03K0UPgr8BbQE8iq8rwRXHDueYzPHgGscfd1AGY2DRgPVIaCu++t0j4x9LlhUbQvj5xtW9mSX8iWvEK25heyZU/w9ea8QlrFx/C7c7px2dAuNI+Ngv0RmpvXvA3Et47M9xaRJu+IoeDujwKPmtlf3P27J/DZXYDNVfazgZHVG5nZrcCPgDgOv7vbSZX18kOMWf9ozUnWjCCOPg1tkRTdDM6/C07/LkTpTEVE6lZtRh+dSCBAcEbxhY+r4fMfAx4zs0nAL4FrvvBBZpOByQBpaWknVEyX4eP4rE0H2rWIo11iMxKbRWM1lhhhK16Ht38RPH79z9D2WCdkIiInj7mHp8fGzEYBd7v7V0P7dwK4+/8eoX0UkOfuR+07ycjI8KysrKM1adjcYeHz8ObPoKIUvvIbyLgBdPMdEfkSzGy+u2ccq104x1hmAulm1sPM4oCJBBetK5lZepXdS4DVYaynYTCDwZPge59A15Ew48fwj69D/uZjv1dE5EsKWyi4exlwGzATWA686O5Lzeye0EgjgNvMbKmZLSC4rvCFrqMmq3UqfPsVuPRh2JwJfx4FmU9ARcWx3ysicoLC1n0ULo2++6gmeRtg+u2w/gPoNhq+9igk94p0VSLSgNSH7iM5WZK6w3deg/GPwfYl8Jcz4OOHobws0pWJSCOjUGgozGDI1XDrPOj9FfjP3fD3c2HrwkhXJiKNiEKhoWnZEa58Fq54BvZtgynnwFt3QvG+SFcmIo2AQqGh6j8ebpsHw66DT/8CfxoOS18NhrSKiJwghUJD1jwJLn0IbvwPJCbDv66Bf34Tdq+PdGUi0kApFBqD1Ay4aRZ89X9h0xz48+kw6z4oLYx0ZSLSwCgUGovoGBj1PbgtE3qPhVm/h8dGwPLX1aUkIrWmUGhsWnWGK56G70yH2ER44Sp49jLYuTLSlYlIA6BQaKx6ng23fAwX3Q9b5gdzG2b+Aor2RLoyEanHFAqNWXQMjLwZvv8ZDL4K5jwGjw6BeX+H8tJIVyci9ZBCoSlITIZxj8LNH0D7/vDGT4Izh5Vv6XqDiBxGodCUdDoNrvk3THwevAKevxKeGQdbF0W6MhGpJxQKTY0Z9L0YvvcpXPQAbFsCfzsLXp4cLLwnIk2aQqGpio6FkZPh9s9h9O2w7DX4Ywa8+d+wf2ekqxORCFEoNHXN28CF9wThMHhScBH60cHw/v9C0d5IVycidUyhIIFWnYOL0bfOhV7nwwf3BuEw+1EoKYh0dSJSRxQKcrjk9GAF1pveCy5Mv/M/8MhpMOfPWjZDpAlQKEjNugwLbgd63VvQvi/MvBMeGQxzp0BZcaSrE5EwUSjI0XUbFQxjveZ1aNsT3vxpMAFu7t905iDSCIU1FMxsrJmtNLM1ZvazGl7/kZktM7NFZvaumXULZz3yJfQ4E657A779KrRJgzf/C/4wCGY/ohv8iDQiYQsFM4sGHgMuAvoD3zKz/tWafQ5kuPsg4CXg/nDVIyeBGZxyLlz/Flz7BnQYAO/cBX8YCB/cD4X5ka5QRL6kcJ4pjADWuPs6dy8BpgHjqzZw9/fd/eDQlk+B1DDWIydT99HwnVfhxneh6+nw/u/g4QHBont7tkS6OhE5QeEMhS7A5ir72aHnjuQG4M0w1iPhkJoBk6YFK7L2uSi4Negjp8Gr34MdyyNdnYgcp3CGgtXwXI2rr5nZ1UAG8MARXp9sZllmlrVzp2bb1ksdB8LljweT4IbfAEtfCe4A99yVsOFjLbwn0kCEMxSyga5V9lOBnOqNzOwC4BfAOHevcayju09x9wx3z0hJSQlLsXKSJHWDi+6DHy6Fc38B2Znw1CXB+koLp0FZSaQrFJGjCGcoZALpZtbDzOKAicD0qg3MbAjwN4JA2BHGWqSuJbSFs/8rCIevPQLlJfDKzfCHU+GDB+DArkhXKCI1CFsouHsZcBswE1gOvOjuS83sHjMbF2r2ANAC+JeZLTCz6Uf4OGmoYpvDsGuDVVmvfjnoZnr/t/Bwf3g59ltfAAAOyElEQVTtVshZEOkKRaQK8wbW15uRkeFZWVmRLkO+jJ0rYe5fg+6k0gJIHQ7Db4IBX4eYZpGuTqRRMrP57p5xzHYKBYmYwnxY+DxkPg671kBCMgy7JjizaJMW6epEGhWFgjQcFRWwflawbPeq0C1Ce10QhEPvscG9pkXkS6ltKOhfm0ReVBSccl6w5W+Cz5+Fz56BF66CFh1h6LdhyLeDkU0iElY6U5D6qbwMVr8N858KHgF6ngNDroa+lwQXsEWk1nSmIA1bdExwL+m+F0P+5uDsYcFz8H83QHxrOHUCDLkKOg8N1mQSkZNCZwrScFRUwIaPgoBYPh3KiqB9fxh0JQz8JrQ+2ioqIk2bLjRL41aYD0tfDs4esjMBgx5nBQHRfxw0axnpCkXqFYWCNB271sKiF2HRNMjbADHNg26nUycE95vW3AcRhYI0Qe6weV4QDktfhcLdwfWHfuPg1MuDM4mo6EhXKRIRCgVp2spLYd0sWPwSrJgBJfsgsT30Hx/MnE4bpYCQJkWjj6Rpi46F9AuDrbQwGNa6+KXgInXm3yExBfp9Dfp/HbqN1gQ5kRD9S5DGL7Z5cIbQfzwU74c178Cy14K1l7KmQkK7YO5D30uhx9kQGx/pikUiRqEgTUuzFjDgG8FWUgBr/hMExJJXglnUcS2CJTb6XhqcZTRvE+mKReqUQkGarriEYPhq/3FQVgzrP4IVr8PKN2DZqxAVE3Qt9bkoWIOpbY9IVywSdrrQLFJdRQVsyYLl/w4W6MtdFTyf0hd6fxV6XxQs963rENKAaPSRyMmya21woXrlm7BxNlSUBUNdTzkPel0YdDe17BDpKkWOSqEgEg5Fe2Dte7D6P8H1iP3bguc7DgwFxPmQOgJi4iJbp0g1CgWRcHOHbYuD0Uyr/wOb54KXQ2widB8TWg78XEjurUX7JOI0T0Ek3Myg06BgO/PHwVnEho+DM4m178PqmUG7Vl2C2dQ9zg4etXCf1GNhDQUzGws8AkQDj7v7vdVePwv4AzAImOjuL4WzHpGwim8dmu9wSbCftyEIh3WzgmsSC58Pnm97SigkzgrOKFq0j1TFIl8Qtu4jM4sGVgEXAtlAJvAtd19WpU13oBXwE2B6bUJB3UfSIFVUwI5lsP5DWP8BbJgdLL0B0C4duo+GbmOCx1adI1urNEr1oftoBLDG3deFCpoGjAcqQ8HdN4ReqwhjHSKRFxUFHU8NtlHfC+4st3UhbPw4CIglLwd3mQNI6hGszZR2OnQ7A9r10jUJqTPhDIUuwOYq+9nAyDB+P5GGIzoGUocF2+gfQEV5cNF642zY+Emou+m5oG1CuyAkuo6EriOg02AtxSFhE85QqOlPmxPqqzKzycBkgLS0tC9Tk0j9FBUNnQcH26hbg5FNu9bApjmw6dMgKFa8HmobC51OCwIidXiwtU7V2YScFOEMhWyga5X9VCDnRD7I3acAUyC4pvDlSxOp58wgOT3Yhn4neG7/juAuc5vnBVvWVPj0z8FrLTpAl2FVtqHBhW+R4xTOUMgE0s2sB7AFmAhMCuP3E2ncWrQ/fHRTeWnQ5bRlPmRnBY8r3zjUvl06dB5yaOs0COISI1O7NBhhnbxmZhcTDDmNBqa6++/M7B4gy92nm9lw4BUgCSgCtrn7gKN9pkYfiRxFYR7kfA7Z84PHnM9hX+gE3aIguU/Q9dTptCAkOg7UGUUToRnNIhLYtw1yFhwKiW2LYN/WQ6+37QkdBwUjozoMDIKiVWddo2hk6sOQVBGpD1p2hD5jg+2gfduDcNi6MLQtCJYLP6h5EnQ4NQiI9v2hQ39I6RcsNy6NmkJBpClq2QFahm5XelDRXti+FLYvCa5VbF8CWU9CWWGogQX3lOgwIAiKlL7Qvl8wQ1sLADYaCgURCcS3gm6jgu2givJguY7tS4MZ2QcfV8wAD805jYoJJtil9AmCIrl38HW7XsGtUKVBUSiIyJFFRUO7U4Kt/7hDz5cWBTcf2rkCdiwPHrcugmXTOTQdySCpW3BxOzk9CInk9GBUVIv2umZRTykUROT4xcYfWiG2qtKiYNJd7krYuerQ4/oPoKzoULtmrUNh0yt4bHvKofDRaKiIUiiIyMkTG39ojaeqKipgz2bYtRpy14QeVwczthf/i8MWO0hIDkZEte0RPCb1OPR1QjudYYSZQkFEwi8qKuhKSuoW3L60qtIiyFsf3PZ01xrYvRZ2rw+W9lj0IocFRmwiJHUPbd2Cxzahz23dFZq1qLtjaqQUCiISWbHxwSim9v2++FpZMeRtDEJj93rI3xhc+M5bD+veh9KCw9sntIM2acHWumuVx67B+lDxbXSmcQwKBRGpv2KaQUrvYKvOHQ7sDEIjfyPkbzq0bV8Kq2Yefh0DoFmr4E54rbuEHlOr7KdCq05NfikQhYKINExmwSimFu2h6/Avvu4OB3JhzybI3xxc08jfDHu3wJ7sYNLegZ1ffF98m2BG98GtZedgAmCr0GPLzsEZSVRU+I8xAhQKItI4mUGLlGDrMqzmNqVFQUjs3QJ7c6ptW4Jhtgd28oVV/6NigpVpW3aEFh2DyYAtOob2O4TCqgMkpjS4iX0KBRFpumLjDw2FPZLyUti/PVhDam9O8LgvJ1gqZP+24BrHpjlQuLvm9zdvGwqKFEhsHwTFwa9btIfE5OC5xJR6MdlPoSAicjTRscG1h9apR29XVhKEx/4docdqXx/YGSxvfmAnlOyv+TPiWgQhMew6GHPHyT+WWlAoiIicDDFxwSinNl2P3bakAA7sCK55HNgZ2nIP7bfoEP56j0ChICJS1+ISIK57MM+inmmcl89FROSEKBRERKSSQkFERCopFEREpFJYQ8HMxprZSjNbY2Y/q+H1Zmb2Quj1uWbWPZz1iIjI0YUtFMwsGngMuAjoD3zLzPpXa3YDkOfuvYCHgfvCVY+IiBxbOM8URgBr3H2du5cA04Dx1dqMB54Off0ScL6ZljAUEYmUcIZCF2Bzlf3s0HM1tnH3MmAP0C6MNYmIyFGEc/JaTX/x+wm0wcwmA5NDu/vNbOUJ1pQM5J7gexuapnKsTeU4oekca1M5TqjbY+1Wm0bhDIVsoOp871Qg5whtss0sBmgNfGFVKXefAkz5sgWZWZa7Z3zZz2kImsqxNpXjhKZzrE3lOKF+Hms4u48ygXQz62FmccBEYHq1NtOBa0JfTwDec/cvnCmIiEjdCNuZgruXmdltwEwgGpjq7kvN7B4gy92nA08A/zCzNQRnCBPDVY+IiBxbWBfEc/c3gDeqPXdXla+LgG+Gs4ZqvnQXVAPSVI61qRwnNJ1jbSrHCfXwWE29NSIicpCWuRARkUpNJhSOteRGQ2ZmU81sh5ktqfJcWzN7x8xWhx6TIlnjyWBmXc3sfTNbbmZLzewHoecb1bGaWbyZzTOzhaHj/HXo+R6h5WBWh5aHaVg3/z0KM4s2s8/N7PXQfqM7VjPbYGaLzWyBmWWFnqt3P7tNIhRqueRGQ/YUMLbacz8D3nX3dODd0H5DVwb82N37AacDt4b+Pza2Yy0GznP304DBwFgzO51gGZiHQ8eZR7BMTGPxA2B5lf3GeqznuvvgKsNQ693PbpMIBWq35EaD5e4f8sX5HVWXEHka+HqdFhUG7r7V3T8Lfb2P4JdIFxrZsXrg4E18Y0ObA+cRLAcDjeA4DzKzVOAS4PHQvtFIj7UG9e5nt6mEQm2W3GhsOrj7Vgh+mQLtI1zPSRVaUXcIMJdGeKyh7pQFwA7gHWAtkB9aDgYa18/wH4D/AipC++1onMfqwNtmNj+0SgPUw5/dpnKP5lotpyENg5m1AP4PuMPd9zbGNRTdvRwYbGZtgFeAfjU1q9uqTj4zuxTY4e7zzeycg0/X0LTBHysw2t1zzKw98I6ZrYh0QTVpKmcKtVlyo7HZbmadAEKPOyJcz0lhZrEEgfBPd3859HSjPFYAd88HZhFcQ2kTWg4GGs/P8GhgnJltIOjWPY/gzKHRHau754QedxAE/Qjq4c9uUwmF2iy50dhUXULkGuC1CNZyUoT6mp8Alrv7Q1VealTHamYpoTMEzKw5cAHB9ZP3CZaDgUZwnADufqe7p7p7d4J/l++5+1U0smM1s0Qza3nwa+ArwBLq4c9uk5m8ZmYXE/wFcnDJjd9FuKSTxsyeB84hWHFxO/Ar4FXgRSAN2AR8092/sNhgQ2JmY4CPgMUc6n/+OcF1hUZzrGY2iOCiYzTBH24vuvs9ZtaT4K/ptsDnwNXuXhy5Sk+uUPfRT9z90sZ2rKHjeSW0GwM85+6/M7N21LOf3SYTCiIicmxNpftIRERqQaEgIiKVFAoiIlJJoSAiIpUUCiIiUkmhIBJiZg+b2R1V9mea2eNV9h80sx+dwOfuP3YrkfpBoSByyCfAGQBmFkUw72NAldfPAGZHoC6ROqNQEDlkNqFQIAiDJcA+M0sys2YE6w99bmY/NbNMM1t08F4HAGZ2deg+CAvM7G+hJdup8nqymc0xs0vMrJOZfRhqu8TMzqyrgxQ5GoWCSEhobZoyM0sjCIc5BLOlRwEZwCKCmePpBOvWDAaGmdlZZtYPuJJg0bPBQDlw1cHPNrMOwAzgLnefAUwCZobangYsqJODFDmGprJKqkhtHTxbOAN4iGDJ5jOAPQTdS18JbZ+H2rcgCIlBwDAgM7Rqa3MOLW4WS3ADlVvd/YPQc5nA1NACf6+6u0JB6gUtcyFShZndCvQBxgDDgdbAv4C9wFSCM4VV7v63au/7PtDZ3e+s4TMPENwwZou7/7zK850Jbi5zO/CAuz8TjmMSOR7qPhI53GzgUmC3u5eHFidrQ9CFNAeYCVwfuqcDZtYltD7+u8CE0NcH773bLfSZDlwP9LXQ/cFDr+1w978TrPw6tM6OUOQo1H0kcrjFBKOOnqv2XAt3zyW4c1Y/YE6om2g/wQqey8zsl6HXo4BS4FZgIwQ3zTGzicC/zWwvcAD4qZmVhj7jO3VzeCJHp+4jERGppO4jERGppFAQEZFKCgUREamkUBARkUoKBRERqaRQEBGRSgoFERGppFAQEZFK/x/v8hv/8joE4gAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x118604048>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"##########################################\n",
"# Same graph as the one showed after #\n",
"# clicking \"Run simulation\" #\n",
"##########################################\n",
"\n",
"plt.plot(p_t)\n",
"plt.xlabel('Weeks')\n",
"plt.ylabel('Price')\n",
"\n",
"plt.plot(floorprice_t)\n",
"plt.xlabel('Weeks')\n",
"plt.ylabel('floorprice')"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x1187a1978>]"
]
},
"execution_count": 52,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1183844e0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(S_t)\n",
"plt.plot(H_t)\n",
"plt.plot(R_t)"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"Text(0,0.5,'price gap')"
]
},
"execution_count": 53,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x118821e10>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(np.array(p_t[:-1])-np.array(floorprice_t))\n",
"plt.xlabel('Weeks')\n",
"plt.ylabel('price gap')"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0,0.5,'price gap as a percent of price')"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x116754278>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(100*(np.array(p_t[:-1])-np.array(floorprice_t))/np.array(p_t[:-1]))\n",
"plt.xlabel('Weeks')\n",
"plt.ylabel('price gap as a percent of price')"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0,0.5,'percent of price at that is supported by unvested tokens')"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x116819470>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(100*(1-(np.array(p_t[:-1])-np.array(floorprice_t))/np.array(p_t[:-1])))\n",
"plt.xlabel('Weeks')\n",
"plt.ylabel('percent of price at that is supported by unvested tokens')"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0,0.5,'percent of tokens that are unvested tokens')"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x116971550>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(100*np.array(H_t)/np.array(S_t))\n",
"plt.xlabel('Weeks')\n",
"plt.ylabel('percent of tokens that are unvested tokens')"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0,0.5,'percent of price at that is supported by unvested tokens')"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1166d20b8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#this is for my analysis purposes. careful about using it for a plot\n",
"#in order for it to be intuitive the x-axis should run in reverse\n",
"#because as time progresses the percent of tokens that are unvested goes DOWN\n",
"#by flipped the x-axis to run from 100 to 0, it would be less confusing to look at.\n",
"\n",
"plt.plot(100*np.array(H_t[:-1])/np.array(S_t[:-1]), 100*(1-(np.array(p_t[:-1])-np.array(floorprice_t))/np.array(p_t[:-1])),'.')\n",
"plt.xlabel('percent of tokens that are unvested tokens')\n",
"plt.ylabel('percent of price at that is supported by unvested tokens')"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0,0.5,'unvested')"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x116ad00f0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(H_t)\n",
"plt.xlabel('Weeks')\n",
"plt.ylabel('unvested')"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0,0.5,'delta R')"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x116bbe828>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(dR_t)\n",
"plt.xlabel('Weeks')\n",
"plt.ylabel('delta R')"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0,0.5,'R')"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x116d1ea58>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(R_t)\n",
"plt.xlabel('Weeks')\n",
"plt.ylabel('R')"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
"price = np.array(p_t)"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [],
"source": [
"delta_price = np.diff(price)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0,0.5,'change price')"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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1C3i1pDmAIuIXJbu/WljNzMysLWSZtTULuBDoA3qlZHmsiNhYaM3M2lA33gNilmVo629JpvsOA0eKrY5Z++rme0Csu2UJJAsjwo/bNavB94BYt8qyaOOPJL268JqYtbnyx+T6HpD20ehFDjtNlh7Jm4E/lPQoydCWgIiI1xRaM7M243tA2pOHJPPLEkjeXngtzDpEu98D0o2TBTwkmV+W6b/7AdKHWc0uvEZm1hTdemXuZWnyyzL9913A54FXAk8Ai4FHgBXFVs3MGqlbr8w9JJlflqGtPwVWA3dHxOsknQO8t9hqmVmjdfOVebsPSTZblkByLCIOSZohaUZE3Cvp2sJrZmYN5Svz39aN+aLpyhJIfpGus/X3wG2SnsCLNZp1JF+ZJ7o1XzRdWe4jWQf8GvgPwN8BP8PPIDHrKt12n0WlfJFVl2XW1nMlb28psC5mXa1Vh1K68eq8m/NF05Fl1tbvA9cCp5LcjDhxQ+IpBdfNrGu08pd1N87mcr5oarIMbX0OeFdEzImIUyLipVmDiKS1kvZKGpG0ocL+WZK2pvt3SupLt8+TdK+kZyVdV3bMSkm702P+UhPLEZu1sVYeSpnu0i/tPhy2cvFcrjxnmYNIBlmS7f8vIh6Z6okl9QCbgDXAKLBL0mBEPFxS7HJgLCKWSRog6flcDDwPXAOclf6U+mtgPbADuAtYS/JcebO21cpDKdO5Om/lHpbVX9VAkg5pAQxJ2gp8g5Jl5CPijhrnXgWMRMS+9HxbSBL3pYFkHfDp9PU24DpJSvMyP5C0rKxOpwGnRMR96fsvAxfgQGJtrsihlHrkXqY6m6sbh8O62WQ9ktKZWb8Czi95H0CtQLIAOFDyfhQ4u1qZiBiXdBiYBzw1yTlHy865oEY9zNpCEVNvm9UzaOUeltVf1UASEf8m57kr5S5iGmWmVV7SepIhMBYtWjTJKc06V7N6Bk5Wd5eayXZJt0h6Wcn7uZJuynDuUeD0kvcLgYPVykjqBeYAT9c458Ia5wQgIjZHRH9E9M+fPz9Ddc1aR70S1c18RkqlZHW7J+CtsizJ9tdExC8m3kTEmKTXZThuF7Bc0hLgcWAAeF9ZmUHgMuA+4CLgnoio2iOJiJ9LekbSamAncCnwVxnqYtY26jkc1Uo9AyfgO1eWQDJD0tyIGAOQ9PIsx6U5j6uA7UAPcFNE7JG0ERiKiEHgRuBWSSMkPZGBieMlPQacAsyUdAFwfjrj68PAzcDJJEl2J9qto9R7OKpVlj1xAr5zZQkknyd53O42knzEHwCfzXLyiLiLZIpu6bZPlbx+HnhPlWP7qmwf4nenBJt1jE5NVHdquww0yUjSbwpJZwLnkiS7v1t2L0jL6+/vj6GhoWZXwyyzVl0uJa9ObVenkjQcEf01y2UJJO3OgcTMbOqyBpIsS6SYmZlV5UBiZma5OJCYmVkuDiRmLcA36lk7yzL918wK5Bv1rN25R2LWZK38LBKzLBxIzJqsmethmdWDh7bMmqyV1sMymw4HErOcmvHgKLNW4kBilkO7JMpLgx3g3o/VlQOJWQ7tsKJtabDr7ZkBEYyfiJYOfNZenGw3y6EdEuXlwe7Y8fAMMasr90is69RzBdp2SJSXLt/ek/ZIjp+Ilg181n68+q91lXbJadSbcyQ2HVlX/3WPxLpKq+Y0in5OR/mssFZos3UOBxLrKq34lL5u7SVZ53Agsa7SijmNVu0lmWXlQGJdp9Vu/mvFXpLZVDiQmDVZK/aSzKbCgcSsBbRaL8lsKgq9IVHSWkl7JY1I2lBh/yxJW9P9OyX1ley7Ot2+V9LbSrY/Jmm3pAcleU6vmVmTFdYjkdQDbALWAKPALkmDEfFwSbHLgbGIWCZpALgWuFjSmcAAsAJ4JXC3pFdFxPH0uHMi4qmi6m6/reipqWbW3ooc2loFjETEPgBJW4B1QGkgWQd8On29DbhOktLtWyLiCPCopJH0fPcVWF+roBumpjpQmuVT5NDWAuBAyfvRdFvFMhExDhwG5tU4NoDvSBqWtL7ah0taL2lI0tCTTz6ZqyHdrNOf3jcRKD//nb1ccsMOPzPdbBqKDCSqsK18PZZqZSY79k0R8Xrg7cCVkt5a6cMjYnNE9EdE//z587PW2cq0w6KEeXR6oDRrhCKHtkaB00veLwQOVikzKqkXmAM8PdmxETHx+wlJd5IMef19EQ2w6U9NrfdwUVHDT76Hwyy/IgPJLmC5pCXA4yTJ8/eVlRkELiPJfVwE3BMRIWkQuF3SF0iS7cuBH0t6MTAjIp5JX58PbCywDcbUp6bWO69SZJ7G93CY5VdYIImIcUlXAduBHuCmiNgjaSMwFBGDwI3ArWky/WmSYENa7qskiflx4MqIOC7p94A7k3w8vcDtEfF3RbXBpqfakh/T7VUUvYSI7+Ewy6fQGxIj4i7grrJtnyp5/TzwnirHfhb4bNm2fcBr619Tq6dKw0V5ehUefjJrbb6z3equ0nDRpntHpt2r8PCTWWtzILGahvePccf9owRw4esXZvoiLx8ummqvonwYzMNPZq3LgcQmNbx/jPdenwxJAWwbOsBX1r9xyl/q1XoVlfIm3XATpFkncSCxSe3Yd4hjaRABOHY8pp3sLu9VVAsYd9w/ypFjJwj8fA6zduBAYpNavXQeJ/XOeKFHclKP6pbsrnYz4NeGDrxw92lPj5PrZq3OgcQmtXLxXL7ygdVTzpFkUSlvsmPfIcZPJGFEwEUr6/d5ZlYMBxKrqahEd7W8SWlwufD1C+v+uWZWX4ooX/6q8/T398fQkB9d0i68Gq9Za5A0HBH9tcq5R2K5FPGl76m+Zu3FgcSmzdN0zQwKftSudTYvwW5m4EDSkYb3j7Hp3pHCH9LU6c8qMbNsPLTVYRo53OQ1sMwMHEg6TtFLrpdzYtzMPLTVBqYyVOXhJjNrNPdIWtxUh6o83GRmjeZA0uKmM1Tl4SYzayQPbbU4D1WZWatzj6TFeajKzFqdA0mTZVlixENVZtbKHEiayEuMmFknKDRHImmtpL2SRiRtqLB/lqSt6f6dkvpK9l2dbt8r6W1Zz9lOvMSImXWCwnokknqATcAaYBTYJWkwIh4uKXY5MBYRyyQNANcCF0s6ExgAVgCvBO6W9Kr0mFrnbBnD+8cmfSBUpQc7mZm1myKHtlYBIxGxD0DSFmAdUPqlvw74dPp6G3CdJKXbt0TEEeBRSSPp+chwzpYwvH+M916/44VH1G4bOsBX1r/xt4KJE+lm1gmKDCQLgAMl70eBs6uViYhxSYeBeen2HWXHLkhf1zpnU5QnzXfsO8SxNIgAHDseFe8BcSLdzNpdkYFEFbaVP46xWplq2yvldCo+4lHSemA9wKJFi6rXsg4qJc1XL53HSb0zXuiRnNQjD12ZWUcqMpCMAqeXvF8IHKxSZlRSLzAHeLrGsbXOCUBEbAY2Q/Ko3ek1IZtKSfMrz1nGVz6wetIciZlZJygykOwClktaAjxOkjx/X1mZQeAy4D7gIuCeiAhJg8Dtkr5AkmxfDvyYpKdS65wNVy1p7mErM+sGhQWSNOdxFbAd6AFuiog9kjYCQxExCNwI3Jom058mCQyk5b5KkkQfB66MiOMAlc5ZVBuyctLczLqZIgod9WkJ/f39MTQ01OxqmJm1FUnDEdFfq5wXbTQzs1wcSMzMLBcHEjMzy8WBZBJTecStmVm38uq/VXhlXjOzbNwjqcIr85qZZeNAUoUfcWtmlo2HtqrwTYZmZtk4kEzCS5yYmdXmoS0zM8vFgcTMzHJxIDEzs1wcSMzMLBcHEjMzy8WBxMzMcumK55FIehLY34SPfgXwVBM+t5E6vY2d3j7o/DZ2evuguDYujoj5tQp1RSBpFklDWR4K0846vY2d3j7o/DZ2evug+W300JaZmeXiQGJmZrk4kBRrc7Mr0ACd3sZObx90fhs7vX3Q5DY6R2JmZrm4R2JmZrk4kEyDpLWS9koakbShwv5Zkram+3dK6ivZd3W6fa+ktzWy3lMx3TZKmifpXknPSrqu0fWeihxtXCNpWNLu9Pe5ja57Fjnat0rSg+nPQ5Le3ei6Z5Xn32K6f1H6/+rHG1Xnqcrxd+yT9OuSv+UXC6tkRPhnCj9AD/AzYCkwE3gIOLOszEeAL6avB4Ct6esz0/KzgCXpeXqa3aY6t/HFwJuBDwHXNbstBbXxdcAr09dnAY83uz11bt+LgN709WnAExPvW+knTxtL9n8d+Brw8Wa3p4C/Yx/wk0bU0z2SqVsFjETEvog4CmwB1pWVWQfckr7eBpwnSen2LRFxJCIeBUbS87WaabcxIp6LiB8AzzeuutOSp40PRMTBdPseYLakWQ2pdXZ52veriBhPt88GWjWRmuffIpIuAPaR/A1bVa42NooDydQtAA6UvB9Nt1Usk/6DPAzMy3hsK8jTxnZRrzZeCDwQEUcKqud05WqfpLMl7QF2Ax8qCSytZNptlPRi4D8Bf9KAeuaR9//TJZIekPR9SW8pqpJ+QuLUVYr05Vds1cpkObYV5Glju8jdRkkrgGuB8+tYr3rJ1b6I2AmskPRPgFskfTsiWq2XmaeNfwL8RUQ82+CL96nK08afA4si4pCklcA3JK2IiF/Wu5LukUzdKHB6yfuFwMFqZST1AnOApzMe2wrytLFd5GqjpIXAncClEfGzwms7dXX5G0bEI8BzJLmgVpOnjWcDn5P0GPBR4BOSriq6wtMw7TamQ+iHACJimCTX8qoiKulAMnW7gOWSlkiaSZLcGiwrMwhclr6+CLgnkuzXIDCQzrJYAiwHftygek9Fnja2i2m3UdLLgG8BV0fEDxtW46nJ074l6RcSkhYDZwCPNabaUzLtNkbEWyKiLyL6gP8O/FlEtOIswzx/x/mSegAkLSX5vtlXSC2bPSuhHX+Afwn8H5II/8l020bgXenr2SQzQUZIAsXSkmM/mR63F3h7s9tSUBsfI7nqe5bkaunMRte/yDYC/5nkKv3Bkp9Tm92eOrbv/SQJ6AeB+4ELmt2WIv4/LTnHp2nRWVs5/44Xpn/Hh9K/4zuLqqPvbDczs1w8tGVmZrk4kJiZWS4OJGZmlosDiZmZ5eJAYmZmuTiQmE1C0s2SLmp2PQAk/WiK5W+W9GjJKr7nFVU3624OJGZtIiL+2TQO++OI+Kckd28Xt4y4dTUHErOUpEsl/e/06v3Wkl1vlfQjSfsmeieSXiLpu5LuT59Lsi7d3ifpEUnXS9oj6TuSTk73vSE9/32S/lzST9LtPen7Xen+D1ap37Pp738h6XuStkn6qaTbMqz2eh+tuUCodQAHEjNeWIDxk8C5EfFa4I9Kdp9G8oyVdwD/Ld32PPDuiHg9cA7w+ZIv8+XApohYAfyC5A5jgC+RrKT7RuB4yfkvBw5HxBuANwAfSJfQmczrSHoZZ5I8q+JNNcqvBb5Ro4zZtHj1X7PEucC2iHgKICJKFy/8RkScAB6W9HvpNgF/JumtwAmSq/2JfY9GxIPp62GgL12f66URMZHnuJ0kMEGyevBrSnIxc0iC0aOT1PfHETEKIOlBkocY/aBCuT+X9DngVGD1ZP8BzKbLgcQsIaovg3+krBzAJcB8YGVEHEtXkZ1dofxx4GQqL/Vdes5/FxHbp1Df8s+o9m/5j4E7gH9P8vCjlVP4DLNMPLRllvgu8AeSJh7s9PIa5ecAT6RB5Bxg8WSFI2IMeEbSRK9goGT3duDDkk5KP/tV6YOX6iLtTf0PYIakt9XrvGYTHEjMgIjYA3wW+L6kh4Av1DjkNqBf0hBJ7+SnGT7mcmCzpPtIeiGH0+03AA8D96cJ+L+hzqMFkazO+hngP9bzvGaAV/81axRJL4mIiZlXG4DTIuKPahxm1vKcIzFrnH8l6WqSf3f7gT9sbnXM6sM9EjMzy8U5EjMzy8WBxMzMcnEgMTOzXBxIzMwsFwcSMzPLxYHEzMxy+f/mCBfEJl/uRgAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x116d25ac8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(change_rate, delta_price, '.')\n",
"plt.xlabel('change in R')\n",
"plt.ylabel('change price')"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0,0.5,'price')"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x116f6ae10>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(R_t, price, '.')\n",
"plt.xlabel('R_t')\n",
"plt.ylabel('price')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}