{
“cells”: [
{

“cell_type”: “code”, “execution_count”: 1, “id”: “bca5090a”, “metadata”: {

“execution”: {

“iopub.execute_input”: “2026-03-30T19:38:46.691350Z”, “iopub.status.busy”: “2026-03-30T19:38:46.691087Z”, “iopub.status.idle”: “2026-03-30T19:38:47.347615Z”, “shell.execute_reply”: “2026-03-30T19:38:47.347319Z”

}

}, “outputs”: [], “source”: [

“import pandas as pdn”, “import numpy as npn”, “import matplotlib.pyplot as pltn”, “from pyvallocation.views import FlexibleViewsProcessor, BlackLittermanProcessorn”, “from pyvallocation.portfolioapi import AssetsDistribution, PortfolioWrappern”, “from pyvallocation import probabilities, momentsn”, “n”, “plt.style.use("default")n”, “np.set_printoptions(precision=4, suppress=True)”

]

}, {

“cell_type”: “markdown”, “id”: “c63926ed”, “metadata”: {}, “source”: [

“# Load price data”

]

}, {

“cell_type”: “code”, “execution_count”: 2, “id”: “b7233b78”, “metadata”: {

“execution”: {

“iopub.execute_input”: “2026-03-30T19:38:47.349055Z”, “iopub.status.busy”: “2026-03-30T19:38:47.348959Z”, “iopub.status.idle”: “2026-03-30T19:38:47.464954Z”, “shell.execute_reply”: “2026-03-30T19:38:47.464691Z”

}

}, “outputs”: [

{

“name”: “stdout”, “output_type”: “stream”, “text”: [

“Tickers: [‘DBC’, ‘GLD’, ‘SPY’, ‘TLT’]n”

]

}, {

“data”: {

“image/png”: 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”, “text/plain”: [

“<Figure size 800x400 with 1 Axes>”

]

}, “metadata”: {}, “output_type”: “display_data”

}

], “source”: [

“from pathlib import Pathn”, “n”, “_candidates = [n”, “ Path("examples/ETF_prices.csv"),n”, “ Path("../examples/ETF_prices.csv"),n”, “ Path("../../examples/ETF_prices.csv"),n”, “ Path("../../../examples/ETF_prices.csv"),n”, “]n”, “_csv = next((p for p in _candidates if p.exists()), None)n”, “if _csv is None:n”, “ raise FileNotFoundError("ETF_prices.csv not found")n”, “prices = pd.read_csv(_csv, index_col=0, parse_dates=True)n”, “print("Tickers:", list(prices.columns))n”, “prices.head()n”, “n”, “prices.plot(figsize=(8,4), title="Daily Close Prices")n”, “plt.tight_layout()”

]

}, {

“cell_type”: “markdown”, “id”: “d8cea410”, “metadata”: {}, “source”: [

“# Weekly returns as risk drivers”

]

}, {

“cell_type”: “code”, “execution_count”: 3, “id”: “9f54b842”, “metadata”: {

“execution”: {

“iopub.execute_input”: “2026-03-30T19:38:47.466144Z”, “iopub.status.busy”: “2026-03-30T19:38:47.466050Z”, “iopub.status.idle”: “2026-03-30T19:38:47.697065Z”, “shell.execute_reply”: “2026-03-30T19:38:47.696778Z”

}

}, “outputs”: [

{
“data”: {

“image/png”: 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“text/plain”: [

“<Figure size 2400x500 with 4 Axes>”

]

}, “metadata”: {}, “output_type”: “display_data”

}, {

“data”: {

“image/png”: 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”, “text/plain”: [

“<Figure size 400x300 with 2 Axes>”

]

}, “metadata”: {}, “output_type”: “display_data”

}

], “source”: [

“weekly_prices = prices.resample("W").ffill()n”, “weekly_ret = np.log(weekly_prices).diff().dropna()n”, “T, N = weekly_ret.shapen”, “ANNUALIZE = 52 # weeks per yearn”, “n”, “weekly_ret.plot(kind="hist", subplots=True, bins=30, sharex=True, layout=(1,N), figsize=(6*N,5))n”, “plt.suptitle("Weekly Log‑Return Distributions"); plt.tight_layout(rect=[0,0,1,0.97])n”, “n”, “corr = weekly_ret.corr()n”, “fig, ax = plt.subplots(figsize=(4,3))n”, “im = ax.imshow(corr, vmin=-1, vmax=1)n”, “ax.set_xticks(range(N)); ax.set_xticklabels(corr.columns, rotation=90)n”, “ax.set_yticks(range(N)); ax.set_yticklabels(corr.columns)n”, “fig.colorbar(im, ax=ax, shrink=0.8)n”, “ax.set_title("Weekly Return Correlation"); plt.tight_layout();”

]

}, {

“cell_type”: “markdown”, “id”: “e8cb4532”, “metadata”: {}, “source”: [

“# Scenario probabilities”

]

}, {

“cell_type”: “code”, “execution_count”: 4, “id”: “f228d169”, “metadata”: {

“execution”: {

“iopub.execute_input”: “2026-03-30T19:38:47.698237Z”, “iopub.status.busy”: “2026-03-30T19:38:47.698171Z”, “iopub.status.idle”: “2026-03-30T19:38:47.700158Z”, “shell.execute_reply”: “2026-03-30T19:38:47.699897Z”

}

}, “outputs”: [

{

“name”: “stdout”, “output_type”: “stream”, “text”: [

“Effective # scenarios: 1005.9999999999983n”

]

}

], “source”: [

“p = probabilities.generate_uniform_probabilities(T)n”, “print("Effective # scenarios:", probabilities.compute_effective_number_scenarios(p))”

]

}, {

“cell_type”: “markdown”, “id”: “33ab9015”, “metadata”: {}, “source”: [

“# Moment estimation + shrinkage”

]

}, {

“cell_type”: “code”, “execution_count”: 5, “id”: “938a9505”, “metadata”: {

“execution”: {

“iopub.execute_input”: “2026-03-30T19:38:47.701116Z”, “iopub.status.busy”: “2026-03-30T19:38:47.701060Z”, “iopub.status.idle”: “2026-03-30T19:38:47.704160Z”, “shell.execute_reply”: “2026-03-30T19:38:47.703914Z”

}

}, “outputs”: [

{

“name”: “stdout”, “output_type”: “stream”, “text”: [

“Sample μ (annualized):n”, “ DBC 0.0062n”, “GLD 0.0895n”, “SPY 0.0973n”, “TLT 0.0276n”, “Name: mu, dtype: float64n”

]

}

], “source”: [

“mu, Σ = moments.estimate_sample_moments(weekly_ret, p)n”, “print("Sample μ (annualized):\n", (mu*ANNUALIZE).round(4))n”, “n”, “mu_jorion = moments.shrink_mean_jorion(mu, Σ, T)n”, “Σ_lw_cc = moments.shrink_covariance_ledoit_wolf(weekly_ret, Σ, target="constant_correlation")”

]

}, {

“cell_type”: “markdown”, “id”: “b5951420”, “metadata”: {}, “source”: [

“# Market equilibrium & risk aversion”

]

}, {

“cell_type”: “code”, “execution_count”: 6, “id”: “b192befa”, “metadata”: {

“execution”: {

“iopub.execute_input”: “2026-03-30T19:38:47.705168Z”, “iopub.status.busy”: “2026-03-30T19:38:47.705088Z”, “iopub.status.idle”: “2026-03-30T19:38:47.707146Z”, “shell.execute_reply”: “2026-03-30T19:38:47.706921Z”

}

}, “outputs”: [

{

“name”: “stdout”, “output_type”: “stream”, “text”: [

“Risk‑aversion λ: 6.7256n”

]

}

], “source”: [

“mkt = pd.Series({"DBC":0.05, "GLD":0.05, "SPY":0.40, "TLT":0.50})n”, “market_rets = weekly_ret @ mktn”, “λ = market_rets.mean() / market_rets.var()n”, “print("Risk‑aversion λ:", round(λ,4))”

]

}, {

“cell_type”: “markdown”, “id”: “2ae49d2d”, “metadata”: {}, “source”: [

“# Views”

]

}, {

“cell_type”: “code”, “execution_count”: 7, “id”: “97179056”, “metadata”: {

“execution”: {

“iopub.execute_input”: “2026-03-30T19:38:47.708216Z”, “iopub.status.busy”: “2026-03-30T19:38:47.708147Z”, “iopub.status.idle”: “2026-03-30T19:38:47.709650Z”, “shell.execute_reply”: “2026-03-30T19:38:47.709457Z”

}

}, “outputs”: [], “source”: [

“views = {"SPY":0.06/ANNUALIZE, "GLD":0.03/ANNUALIZE}”

]

}, {

“cell_type”: “markdown”, “id”: “b435607d”, “metadata”: {}, “source”: [

“# Black–Litterman posterior (baseline)”

]

}, {

“cell_type”: “code”, “execution_count”: 8, “id”: “c5325275”, “metadata”: {

“execution”: {

“iopub.execute_input”: “2026-03-30T19:38:47.710595Z”, “iopub.status.busy”: “2026-03-30T19:38:47.710536Z”, “iopub.status.idle”: “2026-03-30T19:38:47.712784Z”, “shell.execute_reply”: “2026-03-30T19:38:47.712581Z”

}

}, “outputs”: [

{

“name”: “stdout”, “output_type”: “stream”, “text”: [

“[BL] \pi source: \delta \Sigma w.n”, “[BL] Built P (2, 4), Q (2, 1).n”, “[BL] Omega = tau*diag(P Sigma P^T).n”, “[BL] Posterior mean and covariance computed.n”, “Posterior μ (annualized):n”, “ DBC 0.0287n”, “GLD 0.0307n”, “SPY 0.0670n”, “TLT 0.0505n”, “dtype: float64n”

]

}

], “source”: [

“bl = BlackLittermanProcessor(n”, “ prior_cov = Σ_lw_cc,n”, “ market_weights = mkt,n”, “ mean_views = views,n”, “ risk_aversion = λ,n”, “ tau = 0.05,n”, “ verbose=Truen”, “)n”, “mu_bl, Σ_bl = bl.get_posterior()n”, “print("Posterior μ (annualized):\n", (mu_bl*ANNUALIZE).round(4))”

]

}, {

“cell_type”: “markdown”, “id”: “8f049808”, “metadata”: {}, “source”: [

“## Sensitivity: τ and λ”

]

}, {

“cell_type”: “code”, “execution_count”: 9, “id”: “f39330e1”, “metadata”: {

“execution”: {

“iopub.execute_input”: “2026-03-30T19:38:47.713750Z”, “iopub.status.busy”: “2026-03-30T19:38:47.713686Z”, “iopub.status.idle”: “2026-03-30T19:38:47.719276Z”, “shell.execute_reply”: “2026-03-30T19:38:47.719078Z”

}

}, “outputs”: [

{
“data”: {
“text/html”: [

“<div>n”, “<style scoped>n”, “ .dataframe tbody tr th:only-of-type {n”, “ vertical-align: middle;n”, “ }n”, “n”, “ .dataframe tbody tr th {n”, “ vertical-align: top;n”, “ }n”, “n”, “ .dataframe thead th {n”, “ text-align: right;n”, “ }n”, “</style>n”, “<table border="1" class="dataframe">n”, “ <thead>n”, “ <tr style="text-align: right;">n”, “ <th></th>n”, “ <th>DBC</th>n”, “ <th>GLD</th>n”, “ <th>SPY</th>n”, “ <th>TLT</th>n”, “ </tr>n”, “ </thead>n”, “ <tbody>n”, “ <tr>n”, “ <th>tau=0.05, λ=6.7256385622949</th>n”, “ <td>0.0287</td>n”, “ <td>0.0307</td>n”, “ <td>0.0670</td>n”, “ <td>0.0505</td>n”, “ </tr>n”, “ <tr>n”, “ <th>tau=0.05, λ=1</th>n”, “ <td>0.0208</td>n”, “ <td>0.0182</td>n”, “ <td>0.0359</td>n”, “ <td>0.0041</td>n”, “ </tr>n”, “ <tr>n”, “ <th>tau=1, λ=6.7256385622949</th>n”, “ <td>0.0287</td>n”, “ <td>0.0307</td>n”, “ <td>0.0670</td>n”, “ <td>0.0505</td>n”, “ </tr>n”, “ <tr>n”, “ <th>tau=1, λ=1</th>n”, “ <td>0.0208</td>n”, “ <td>0.0182</td>n”, “ <td>0.0359</td>n”, “ <td>0.0041</td>n”, “ </tr>n”, “ </tbody>n”, “</table>n”, “</div>”

], “text/plain”: [

“ DBC GLD SPY TLTn”, “tau=0.05, λ=6.7256385622949 0.0287 0.0307 0.0670 0.0505n”, “tau=0.05, λ=1 0.0208 0.0182 0.0359 0.0041n”, “tau=1, λ=6.7256385622949 0.0287 0.0307 0.0670 0.0505n”, “tau=1, λ=1 0.0208 0.0182 0.0359 0.0041”

]

}, “execution_count”: 9, “metadata”: {}, “output_type”: “execute_result”

}

], “source”: [

“scan = []n”, “for τ in [0.05, 1]:n”, “ for lam in [λ, 1]:n”, “ mu_tmp, _ = BlackLittermanProcessor(n”, “ prior_cov=Σ_lw_cc,n”, “ market_weights=mkt,n”, “ mean_views=views,n”, “ risk_aversion=lam,n”, “ tau=τ,n”, “ ).get_posterior()n”, “ scan.append(pd.Series(mu_tmp*ANNUALIZE, name=f"tau={τ}, λ={lam}"))n”, “n”, “pd.concat(scan, axis=1).T.round(4)”

]

}, {

“cell_type”: “markdown”, “id”: “57709d95”, “metadata”: {}, “source”: [

“#  Flexible views”

]

}, {

“cell_type”: “code”, “execution_count”: 10, “id”: “30fd205f”, “metadata”: {

“execution”: {

“iopub.execute_input”: “2026-03-30T19:38:47.720226Z”, “iopub.status.busy”: “2026-03-30T19:38:47.720173Z”, “iopub.status.idle”: “2026-03-30T19:38:47.723370Z”, “shell.execute_reply”: “2026-03-30T19:38:47.723191Z”

}

}, “outputs”: [

{

“name”: “stdout”, “output_type”: “stream”, “text”: [

“FV posterior μ (annualized):n”, “ DBC -0.0349n”, “GLD 0.0300n”, “SPY 0.0600n”, “TLT 0.0273n”, “dtype: float64n”

]

}

], “source”: [

“fv = FlexibleViewsProcessor(n”, “ prior_risk_drivers=weekly_ret,n”, “ mean_views = views,n”, “)n”, “mu_fv, Σ_fv = fv.get_posterior()n”, “print("FV posterior μ (annualized):\n", (mu_fv*ANNUALIZE).round(4))”

]

}, {

“cell_type”: “markdown”, “id”: “ec2b8c07”, “metadata”: {}, “source”: [

“# Compare priors vs posteriors visually”

]

}, {

“cell_type”: “code”, “execution_count”: 11, “id”: “c76f9549”, “metadata”: {

“execution”: {

“iopub.execute_input”: “2026-03-30T19:38:47.724323Z”, “iopub.status.busy”: “2026-03-30T19:38:47.724271Z”, “iopub.status.idle”: “2026-03-30T19:38:47.773547Z”, “shell.execute_reply”: “2026-03-30T19:38:47.773326Z”

}

}, “outputs”: [

{
“data”: {

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”, “text/plain”: [

“<Figure size 800x300 with 1 Axes>”

]

}, “metadata”: {}, “output_type”: “display_data”

}

], “source”: [

“bar = pd.concat({n”, “ "Sample": mu*ANNUALIZE,n”, “ "Jorion": mu_jorion*ANNUALIZE,n”, “ "BL": mu_bl*ANNUALIZE,n”, “ "Flex": mu_fv*ANNUALIZE,n”, “}, axis=1)n”, “bar.plot(kind="bar", figsize=(8,3))n”, “plt.ylabel("Annualised expectation")n”, “plt.title("Expected Returns – Various Priors/Posteriors")n”, “plt.axhline(0,color="black",linewidth=0.8); plt.tight_layout()”

]

}, {

“cell_type”: “markdown”, “id”: “839d065a”, “metadata”: {}, “source”: [

“# Efficient frontier”

]

}, {

“cell_type”: “code”, “execution_count”: 12, “id”: “6cfd5bc5”, “metadata”: {

“execution”: {

“iopub.execute_input”: “2026-03-30T19:38:47.774645Z”, “iopub.status.busy”: “2026-03-30T19:38:47.774576Z”, “iopub.status.idle”: “2026-03-30T19:38:48.090858Z”, “shell.execute_reply”: “2026-03-30T19:38:48.090634Z”

}

}, “outputs”: [

{

“name”: “stderr”, “output_type”: “stream”, “text”: [

“No constraints set; using default long-only, fully-invested.n”

]

}, {

“name”: “stderr”, “output_type”: “stream”, “text”: [

“No constraints set; using default long-only, fully-invested.n”

]

}, {

“name”: “stderr”, “output_type”: “stream”, “text”: [

“No constraints set; using default long-only, fully-invested.n”

]

}, {

“name”: “stderr”, “output_type”: “stream”, “text”: [

“No constraints set; using default long-only, fully-invested.n”

]

}, {

“data”: {

“image/png”: 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9k8i5NJEyUSI124iEhIq/YmBFRERE5tj3hUjiGJHMv/5uK1tVpPt0kdie4o84FUhERETmBFVL+9sHVZCZktuO836IgRURERF5f/ovcYyIaE5OXmtLHJvbz88wsCIiIiLv+n1T3pEqO5pI5rHcfn6GgRURERF517k0Y/v5EAZWRERE5F1loozt50MYWBEREZF31WyTu/pPLC46WETKVsvt52cYWBEREZF3hYTmllRQHIOra8fdp/llPSsGVmSq7BxNNh8+KZ/vPKaecUxEREEgtqdIn49EysbYt2MkC+1+WseKBULJNIl7UmTSin2SkpFlbYuJDJeJd8dK94YO/9CIiCjwxPYUqZ8QUJXXLZqmcYjAQzIzMyUyMlIyMjKkbNmyZl+OzwVVQxYm56lgog8Iv/1wMwZXRETkd7+/ORVIXofpPoxU5VMWTp3ntCAREfkbBlbkdUlHTtlN/zlCOIXz6EdERORPGFiR16WfzTK0HxERka9gYEVeVyUi3NB+REREvoKrAsnr4mpXUKv/UjOynOZZIYE9OjJc9aMAhs1VA2glEBERMLAirwsNsaiSClgViCBKc7IqEOfRjwLUvi9yd7a33YQVtWtQMNBPa9cQEQGnAskUKKWAkgoYmbKFY5ZaCIKgamn/vDvbZ6bktuM8EZGfYh0rD2Idq+tDSQWs/kOiOnKqMP3HkaoAn/6b3TBvUGW3P1hVkRG7OS1IRKbx+zpWb731ltSqVUvCw8OlVatWkpSUlG//ZcuWSf369VX/Ro0ayerVq+3OI1Z84YUXJCYmRkqWLCmdO3eWQ4cO2fWZMmWKtGnTRkqVKiXlypXL9/1OnjwpN9xwg1gsFjlz5kwRPlNyhCCqdZ2Kck+TauqZQVWAQ06Vy6AKNJHMY7n9iIj8kOmB1ZIlS2TkyJEyceJESU5OlsaNG0u3bt0kPT3daf9NmzZJv379ZNCgQbJjxw7p1auXeuzZs8faZ8aMGTJnzhx55513ZMuWLVK6dGn1mllZfy/fv3z5sjzwwAMyZMiQ614j3uvWW2816DMmCmJIVDeyHxGRjzF9KhAjVC1btpS5c+eq45ycHKlevboMGzZMxo4dm6d/37595fz587Jy5Upr22233SZNmjRRgRQ+napVq8qoUaNk9OjR6jyG8qKiouTDDz+UBx980O710DZixAiXI1Fvv/22Cv4wAhYfHy+nT5++7giXjlOBRA6OfC+y4K7r9xuwUqT27d64IiKiwJkKxKjR9u3b1VSd9YJCQtTx5s2bnX4M2m37A0aj9P5HjhyR1NRUuz64OQjgXL2mK/v27ZOXXnpJPvroI3Vd13Pp0iX1xbB9EJENlFRADpV1/aezHKtquf2IiPyQqYHViRMnJDs7W40m2cIxgiNn0J5ff/3Zndd0FSRhyvHVV1+VGjVqFOhjpk6dqoI4/YGRNyKygYR0lFRQHIOra8fdpzFxnYiCq47VunXr1AN5UJi6szV//nwJBOPGjZMGDRrIww8/7NbHIF9MhxErBldEDlCnqs9HLupYTWMdKyIKrsBq0qRJanqsRYsWatUdVsoVVqVKlSQ0NFTS0uwTVXEcHR3t9GPQnl9//RltuD7bPsjDKqj169fL7t27Zfny5epYT0XDNT///PPqPjgqUaKEehDRdSB4qp/AyutEFHDcDqyQII6E70ceeaTIb168eHFp3ry5Gv3Cyj7ACBiOn3rqKacf07p1a3UeCee6tWvXqnaoXbu2Cq7QRw+kMHKE1YEFWQGo++STT+TixYvW461bt8pjjz0m33//vdSpU6fQnzMRXYMgignqRBTsgRUSzlH/ySiYOhswYIAaAYuLi5PZs2erVX8DBw5U5/v37y/VqlVT+UswfPhwad++vcycOVMSEhJk8eLFsm3bNpk3b546jxE0BF2TJ0+WevXqqUBrwoQJaqWgHrzB0aNH5dSpU+oZeV47d+5U7XXr1pUyZcrkCZ6QDwaYHizoqkAiIiIKLm4HVv/4xz9k0aJFKlgxAsonHD9+XJUzQHI5RpkSExOtyecIfGxX5CGow/uPHz9ennvuORU8ffbZZ9KwYUNrn2effVYFZ4MHD1ZlFNq1a6deEwVFdXi/BQsWWI+bNm2qnjds2CAdOnQw5HMjIiKi4OJ2HSuMGKH8AApm4lGsWDG787NmzTL6Gv0W61gREREF1+9vt0esdu3aZc1dsq12DkVJZCciN/bbY9I3EZFPciuwQi4SVsNhf77y5ct77qqIyLl9X7goUzCdZQqIiPytQChKI3Tt2pUbEROZFVQt7Z93E+PMlNx2nCciIv+qvI4k8V9//dUzV0NErqf/MFIlzlIir7Uljs3tR0RE/hNYoYwBNjfGJsgpKSncGy8IZOdosvnwSfl85zH1jGPyMuRUOY5U2dFEMo/l9iMiItO4nbzeo0cP9dyzZ0+7ZHUsLsQx8rAocCTuSZFJK/ZJSkaWtS0mMlwm3h0r3Rv+XdmePAyJ6kb2IyIi3wisUOeJgieoGrIwOc/kU2pGlmp/++FmDK68Bav/jOxHRES+EVih6jkFPkz3YaTKVUYPxipxvktstISGsMyGx6GkAlb/IVHd6VfFknse/YiIyH8Cq++++y7f83fccUdRrod8RNKRU3bTf47wqx3n0a91nYpevbaghDpVKKmA1X8qrLUNrq4Ftt2nsZ4VEZG/BVbOtnuxzbVijlVgSD+bZWg/MgDqVPX5yEUdq2msY0VE5I+B1enTp+2Or1y5Ijt27FB7B06ZMsXIayMTVYkIN7QfGQTBU/0EVl4nIgqUwAp75zjq0qWLFC9eXEaOHCnbt2836trIRHG1K6jVf0hUd5HRI9GR4aofeRmCqNq3m30VRERkRB0rV6KiouTAgQNGvRyZDAnpKKkAjqnp+jHOM3GdiIioiJsw20L9KhQKnTZtmnVzZgoMKKWAkgqOdawwUsU6VkRERAYEVgiekKyOgMrWbbfdJvPnz3f35cjHIXhCSQWs/kOiOnKqMP3HkSoiIiIDAqsjR47YHYeEhEjlypUlPJxJzIEKQVTAl1TAHntMCCci8lnZOdmSnJ4sxy8cl8qlKkuzKs0k1Ad/TrsdWH377bfSt29fKVGihF375cuXZfHixdK/P+rsEPmRfV+4KGEwnSUMiIh8wNe/fy3TkqZJ2oW/t+2KKhUlY+PGSueancWXWDTHOb3rCA0NVTlVVapUsWs/efKkamMdq79hU2qsoszIyJCyZcuafTnkKqhSRTcd/xlcm+pE3SgGV0REpgZVI78ZKZrDz2nLtZ/TszrMMjy4Ksrvb7dXBeqbLTv6888/nZZiIPLp6T+MVLncuAcbJo7N7UdERKZM/01LmpYnqAK9bXrSdNXP76YCmzZtqgIqPOLj4yUs7O8PxSgVcq+6d+/uqeskMh5yqmyn//LQRDKP5fZj3SgiIq9LTk+2m/5zFlylXkhV/VpGtxS/Cqx69eqlnnfu3CndunWTMmXKWM+hOGitWrWkd+/enrlKIk9AorqR/YiIyFBIVDeyn08FVhMnTlTPCKCQvM5VgOT3sPrPyH5ERGQorP4zsp83uJ1jNWDAAMnKypL33ntPxo0bJ6dOnVLtycnJcuzYMU9cI5FnoKQCVv/lqS2vs4iUrZbbj4iIvK5ZlWZq9Z+eqO4I7dGlolU/vw2sUHn9pptukunTp8trr70mZ86cUe3/+9//VKBF5DdQ/wQlFfLbuKf7NNazIiIySWhIqCqpAI7BlX48Jm6MT9WzcjuweuaZZ+TRRx+VQ4cO2U0H9ujRQ7777jujr4/Is1BKASUVyjpsz4ORLJZaIPIrWBm2NXWrrP51tXr2pZViVHgopYCSClVK2Zd5wkiWJ0oteL1A6LZt22TevHl52qtVqyapqalGXReR9yB4qp/AyutEfsyfCkiS+/A17Fi9Y2BWXkfFdRTOcnTw4EG1tQ2RX8I/TpZUIAqoApLpF9JVuy+OapD7EET5SkkFQ6cCe/bsKS+99JJcuXJFHaOu1dGjR2XMmDEst0BERF7ljwUkKbC5HVjNnDlTzp07p7avuXjxorRv317q1q0rERERMmXKFM9cJRERURELSBL55FQgtq1Zu3atbNy4UX766ScVZDVr1kw6d+YwKxEReZc/FpCkwOZWYIXpv5IlS6rq623btlUP8i/ZOZokHTkl6WezpEpEuMTVriChIa7qOBER+TZ/LCBJgc2twKpYsWJSo0YNtTcg+Z/EPSkyacU+ScnIsrbFRIbLxLtjpXtDh3ID3oK8B67GI6IiFpBEorqzPCvUOsJ5XyogSYHN7Ryr559/Xp577jlrxXXyn6BqyMJku6AKUjOyVDvOe92+L0RmNxRZcJfIJ4Nyn3GMdiKiAC0gSYHNomla3hA/H02bNpVffvlFTQvWrFlTSpcubXceW9tQLpSlQE5aRkaGlC1b1tTpv3bT1+cJqnT40RMdGS4/jOnkvWlBBE9L+6vU0rxXIyzOSURFrmOFrU4QVLHUAnnz97fbyeu9evVy90PIZMipchVUybXQBufRr3Wdit6Z/ksc4ySo0q/GIpI4NrdoJ//KJJNhmb4/FCUMdv5UQJICm9uB1cSJEz1zJeQxSFQ3sl+RIacq8698Omgimcdy+7FoJ5mI1bz9i78UkKTA5naOFfkfrP4zsl+RIVHdyH5EHqzm7VgjSa/mjfNERD4ZWL311ltSq1Yttalzq1atJCkpKd/+y5Ytk/r166v+jRo1ktWrV9udR9rYCy+8IDExMao8BGpsYdNoWyhm2qZNGylVqpSUK1cuz3ugRle/fv2kevXq6jUaNGggb7zxhvgjlFTA6j9X2VNox3n08wqs/jOyH5HBWM2biPw2sFqyZImMHDlSTTEi8b1x48bSrVs3SU9Pd9p/06ZNKuAZNGiQ7NixQ+V84bFnzx5rnxkzZsicOXPknXfekS1btqgEe7xmVtbfU12XL1+WBx54QIYMGeL0fbZv366qyy9cuFD27t2rVkOOGzdO5s6dK/4GCekoqQCOwZV+jPNeS1xHSYWyVZ1cjc1Vla2W24/IBKzmTUReWxVoNIxQtWzZ0hqw5OTkqFGiYcOGydixuUtobfXt21fOnz8vK1eutLbddttt0qRJExVI4dOpWrWqjBo1SkaPHq3OI6s/KipKPvzwQ3nwwQftXg9tI0aMkDNnzlz3WocOHSo///yzrF+/3q9WBfpkHSvrqkCw/RbkqkAy3+pfV8uY77HAIn/Tb58uPW7s4ZVrIqIAXRVoJIwaYWQII0G6kJAQNXW3efNmpx+Ddoxw2cJo1Geffab+/8iRI5Kammq3xQ5uDgI4fKxjYOUO3OAKFVxPl126dEk9bL8wvgTBU5fYaN+ovI6gCcETVgfaJrJjJKv7NAZVZCpW8yaiwipQYOUYyORn1qxZBe574sQJVcUdo0m2cLx//36nH4OgyVl/tOvn9TZXfQoDU5CYtly1apXLPlOnTpVJkyaJL0MQ5ZWSCgWB4AklFVh5nXwMq3kTkUcDK+Qy2UIu1NWrV+Xmm29WxwcPHpTQ0FBp3ry5BCLkb91zzz0qD6xr164u+2HkzTYIxYgVpjUpHwiiWFKBfLSaN1b/IYiyDa5YzZuIihxYbdiwwW5EKiIiQhYsWCDly5dXbadPn5aBAwfK7be79wuyUqVKKiBLS7NPEsVxdHS0049Be3799We0YVWgbR/kYblr3759Eh8fL4MHD5bx48fn27dEiRLqQeRNLGDpGahTNavDLKd1rFjNm4gMy7GaOXOmrFmzxhpUAf5/8uTJajQHSeMFVbx4cTXKtW7dOmtFdySv4/ipp55y+jGtW7dW55Fwrlu7dq1qh9q1a6vgCn30QAojR1gd6GoFoCtYDdipUycZMGCAKs9A5GtYwNKzWM2biDweWCFIOX78eJ52tJ09e9btC8DUGQKXFi1aSFxcnMyePVut+sMIGPTv31+qVaum8pdg+PDh0r59exXgJSQkyOLFi2Xbtm0yb948dd5isaigC4FevXr1VKA1YcIEtVLQdjueo0ePqo2k8Yw8r507d6r2unXrSpkyZdT0H4IqJMbjGvX8LIywVa7MhFXynQKWjjlAegFLjLYwuCo6VvMmIo8GVvfee68KehDYIBACjAb961//kvvuu8/dl1PlExCUoaAngheMMiUmJlqTzxH4YKWgDkU9Fy1apKblnnvuORU8YUVgw4YNrX2effZZFZxh+g5lFNq1a6deEwVFdXg/TGfabi6tT3t26NBBli9frq4Ldazw0GHj6d9++02CCoogMsHcrwpYIg8IBSwx2sLRFSIiH65jdeHCBVUfav78+XLlyhXVFhYWpgp2vvrqq6oYJ/lmHatC15tyWhJhOksimGhr6lZ57KvHrttvfrf5HG0hooCjZWfLhW3b5erx4xJWubKUatFcLKGh/lnHClvA/Pvf/1ZB1OHDh1VbnTp1GFAFImsRT4fYOzMlt51FPE2DfB8j+xER+YvMNWsk7ZWpctWmhFJYdLREPTdOyuazct/nt7RJSUlRD0zFIagyuYA7eWL6DyNVTqaarG2JY3P7kdexgCURBWtQdWz4CLugCq6mpal2nPe7wOrkyZOq/MBNN90kPXr0UMEVYCrQnRWB5OOQU2U7/ZeHJpJ5LLcfmVbAUq+p5Ajt0aWiWcCSiAJq+i/tlakizgZyrrXhPPr5VWD1zDPPSLFixVRSOaYFbZPQkSBOAQKJ6kb2I48UsATH4IoFLIkoEF1ATlV+O6homjqPfn4VWKGG1fTp0+WGG26wa8eU4O+//27ktZGZsPrPyH4mrZxDkjc21MUzjgOxgGWVUlXs2jGSxVILRBRorjop9VSUfp7idvI6yhjYjlTpUBOKVccDCEoqYPUfEtWd5llZcs+jnw8KlsKZLGBJRMEirIA1JAvaz2dGrLBtzUcffWQ9RkFOVEufMWOGdOzY0ejrI7PgFzNKKiiOeTzXjrtP88l6VnrhTNugyrZwJs4HYgHLHjf2UM8MqogoEJVq0Vyt/hOL89xStOM8+vlVHStUJEfyerNmzWT9+vXSs2dPtfULRqw2btyoSi+QOXWssnM0STpyStLPZkmViHCJq11BQkNcfAMWqY5VtdygygdLLWC6r9sn3fIEVbb5Rxi5SuydyACEiMhPVwUqtuHLtWCr2huzDSm54NU6VqhwfvDgQZk7d67ajPncuXOq4vrQoUPtNj0m70rckyKTVuyTlIwsa1tMZLhMvDtWujcswtcFwVP9BL+pvI4pMVdBlV6VPPVCqurHwplERP6lLIKmN2bnrWMVFeUzdazcDqywGrB69ery/PPPOz1Xo0YNo66N3AiqhixMzpMJlZqRpdrffrhZ0YIrBFG1bxd/wMKZRESBrWzXrhIRH+/RyuteDaywqTFqV1WpUiVPfSucw4bG5D2Y/sNIlasynhgcxfkusdFFnxb0AyycSUQU+CyhoVK6Ve5+xb7G7eR1pGQhYd0RpgRtNzkm70BOle30n7PgCufRLxiwcCYREfnFiNXIkSPVM4KqCRMm2JVcwCjVli1bpEmTJp65SnIJiepG9guUwplY/YcgCjlVOhbOJCIinwmsduzYYR2x2r17txQvXtx6Dv/fuHFjGT16tGeuklzC6j+3+qFIpp8kohe1cKazOlYIqgKpjhUREflpYLVhwwb1PHDgQHnjjTe8Uj6Arg8lFbD6D4nqLsp4SnRkbukF56UTqubWq/Jy6QSURfBkUUsWziQiIr+oY4WaDpj6q1Chgl076liFhYUx4DKhjpW+KhBsv5h6lpFaFRiyVWRpfydV1K/16vOR14KrYKmKTkREwff72+3k9QcffFAWL16cp33p0qXqHHkfSikgeMLIlC0cq6AqtkruSJXLtYOIzsbmThN6WLBVRSciouDi9ogVRqpQYb1BgwZ27fv375e2bduqsgvkY5XXj3wvsuCu67/AgJUerVfFquhEZBYtO9tn6x6R7/Fq5fVLly7J1atX87RfuXJFLl686O7LkYEQRLWuUzHvCSSqF0RB+xUSq6ITkVnboOSp1B0d7TOVuimwuD0VGBcXJ/PmzcvT/s4770jz5uZufEguYPWfkf0KiVXRicisveVsgyq4mpam2nGeyEhuj1hNnjxZOnfuLD/99JPajBnWrVsnW7dulTX8BvVNKKmA1X+ZKS7yrCy559HPg1gVnYi8Pf2HkSq7zXqtJzW1cS/OY3sUTguSaSNWyKPavHmz3HDDDSphfcWKFVK3bl3ZtWuX3H67f+wnF3SQr4SSCopjRfJrx92nebyeFauiE5E3qZwqh5EqO5qmzqMfkWkjVoAK64sWLTLsIsgLUEoBJRWc1rGa5pVSC6yKTkTehER1I/sReSywOnz4sHzwwQfy66+/yuzZs9WGzF9++aXUqFFDbrnllsK8JHkDgqf6CUWqvF7Uwp6sik5E3oLVf0b2I/JIuYVvv/1W7rzzTjUl+N1338nPP/8sN954o0ybNk22bdsmy5cv99zV+hlvl1vwp8Kenq68TkSEHKtf4jurRHWneVYWi4RFRUnddV8zx4rMKxA6duxYlcC+du1au/0CO3XqJD/++KO7L0d+wujCngiiUFKhx4091DODKiIyGoIllFTIPXDI7bx2jPMMqshIbgdW2ID53nvvzdOO6cATJ04YdV3kQzC6hJEq25wond42PWm66kdE5EtQp6raG7PVyJQtHKOddazI9ByrcuXKSUpKitSuXduufceOHVKtWjUjr418BAt7EpE/Q/CEkgqsvE4+GVhhP8AxY8bIsmXLxGKxSE5OjtriZvTo0dK/Pzb5pUDDwp5E5O8QRJVuFWf2ZVAQcHsq8JVXXpH69etL9erV5dy5cxIbGyt33HGHtGnTRsaPH++Zq6SCwVQc9gXcvTz32aCpORb2JCIi8tCqQN3Ro0dlz549Krhq2rSp1KtXrzAvE9C8uipw3xcualRNL3KNKn3zZCSqO8uz4ubJREQUSDKL8Pu70IEV6B+KKUEyMbBCULUU07COX8prXxcUBi1icKWvCgRnhT1Rm4o1qIiIKBB4tdwCvP/++9KwYUMJDw9XD/z/e++9V5iXoqLCdB9GqpzuAXitLXFskacF9cKeVUpVsWvHSBWDKiIiokImr7/wwgsya9YsGTZsmLRu3Vq1Ye/AZ555Rk0PvvTSS+6+JBVCdo4mSUdOSfav30k72+m/PDSRzGO51dZr316kIp0InjpW78jCnkREREYFVm+//ba8++670q9fP2tbz5495dZbb1XBFgMrz0vckyKTVuyTlIws6RmyTdr9XafVNWxhY0AVdb2wJxERERkwFXjlyhVp0aJFnvbmzZvL1atX3X05KkRQNWRhsgqqIF3KFewDsS+gh6qoEwU7bJ1yfkuSZKxcpZ5xTETBye3A6pFHHlGjVo7mzZsnDz30kFHXRS6m/zBSZZtNlZRTX/7SKkiOyyUIFpGy1XI3W2YVdSLDZa5Zo/ajOzpggPw1erR6xjHaiSj4uD0VqCevr1mzRm677TZ1vGXLFpVfhQKhI0fmrhwD5GKRcZBTpY9U6XIkRCZd6S9vF5utgqsQuwWa1w66TxO5lgfFKupExkHwdGz4iDwb/GLTX9XOLVOIgo7bI1aoXdWsWTOpXLmyHD58WD0qVaqk2nAOW9vgsXPnzgK/5ltvvSW1atVSKwxbtWolSUlJ+fZH1XcUKUX/Ro0ayerVq/OUgUCSfUxMjJQsWVI6d+4shw4dsuszZcoUVdS0VKlSapseZxAsJiQkqD7YC/Ff//qXqdOd6WftgyrdVzlxMuTKCEmVCvYnUMfKodQCq6gTGQPTfWmvTM0TVOWezG3DeU4LEgUXt0esNmzYYOgFLFmyRI1yvfPOOyqomj17tnTr1k0OHDigghlHmzZtUonzU6dOlbvuuksWLVokvXr1kuTkZFX2AWbMmCFz5syRBQsWqD0NJ0yYoF5z3759KhiDy5cvywMPPKBWNmIEzlF2drYKqqKjo9V7Yn9EjMgVK1ZMVZ83Q5WI3Gt3FVytvdRC4kL2y0udKslNdermTv85rNhjFXUiY6h951JTXXfQNHUe/biVClHwcLtA6PHjx9VolTO7d+9WI0juQDDVsmVLmTt3rjrG3oPYLgcrDMeOHZunf9++feX8+fOycuVKaxumJJs0aaKCM3w6VatWlVGjRqn9CwEFvqKiouTDDz9Uex3aQtuIESPkzJkzdu1ffvmlCtz++usv9bGA18c+ibgHxYvnXYp36dIl9bAtMIbPxagCocixajd9vaRmZDmtWoWJv+jIcPlhTCcJtZ8TtHkNVlEnMgIS1ZFTdT1VX3tNIu9K8Mo1EZEfFghF4LRq1ao87a+99prExbn3VxlGjbZv366m6qwXFBKijlEbyxm02/YHjEbp/Y8cOSKpqal2fXBzEMC5ek1X74PPVQ+q9PfBzd67d6/Tj8EoGt5LfyCoMhKCpYl3x6r/dwyb9GOcdxVU5b5GqCqpkPsx9v304zFxYxhUEV1HmIs/MAvbj4gCg9uBFabtevfuLUOGDJGLFy/KsWPHJD4+Xk2/YVrOHSdOnFBTbrbBC+AYwZEzaM+vv/7szmu68z627+Fo3LhxKrrVH3/88YcYrXvDGHn74WZqZMoWjtGO8/rI1NbUrbL619Xq2XaVH6uoExVdqRbNJSw6Gnt6Oe9gsajz6EdEwcPtHKtnn31WunTposouoCjoqVOn1GjQrl27VD5SMCtRooR6eBqCpy6x0WqVIBLakXsVV7uCdaSqIMU/WUWdqGgsoaES9dy43NV/CK5ssyquBVs4j35EFDwKtVdg3bp1VaL4b7/9pqbGkPdUmKAKqwlDQ0MlLc1++T+OXb0e2vPrrz+785ruvI/te5gpVHKkdcg+uSd0s3rGsbvFP/Uq6j1u7KGeGVQRuQelFKq9MVvCHEa3cYx2llogCj5uB1YbN25UI1UoX4BRKhQLRaI5gqvTp0+79VpIAEfF9nXr1lnbkLyOY30fQkdot+0Pa9eutfbHKkAEPrZ9EPyh1par13T1PkjGT09Pt3sfJLHFxubmOZlm3xcisxuKLLhL5JNBuc+zG0r23s9Y/JPIyxA81V33tdRYsEAlquMZxwyqiIKT21OBnTp1Uhsuv/zyy6r0QIMGDaRjx47y8MMPq2TvP//80+2crQEDBqhtcpD8jnILWPU3cOBAdR4lDqpVq6YSw2H48OHSvn17mTlzpiqHsHjxYtm2bZuq/A4Wi0Wt8ps8ebLUq1fPWm4BKwVRlsG2RhWmMfGMPC+97hZG48qUKSNdu3ZVARSmPJE/hryq8ePHy9ChQ70y3ZdvULW0f+7myrYyUyR5xROSFpO3RIWOxT+JPAPTfSypQESFCqxQcR2Bja06deqokSwU3XQXRrpQvgAFPRG8oGxCYmKiNVEcgQ9WCupQ1BNJ8ghynnvuORU8ffbZZ9YaVnoeGIKzwYMHqzIK7dq1U6+p17ACvB/qXOmaNm1qrdPVoUMHNUWJkg5I0sfoVenSpVUAaOom0xhpShyTN6hSNDlewFwOFv8kIiLykTpW5J06GE4d+T532s+FreEl5LEY+1wPZ+Z3m88RKyIiIjPrWPXo0UO9gW7atGl2RTVPnjxpfu5RoDvneo8/aJZ1SaKuXs1T48q2TlV0qWi1+o+IiIiMV+DA6quvvrKrKo5tXZCjpMMeetiGhjyoTP6jUZgIHHsydwEBi38SERH5cGDlOGPIGUQTYO8/bKycz5hU57AKMqv9TBb/JCIi8ofkdTIRRpq6T7+2KhDBlW1wmxtsZXd7RSLDy8uIZiPk9KXTUr5EeYkqHcXin0RERL4UWKGMAR6ObeRlsT1F+nyUuzow86+/28tWla/jHpFp++Y6rbjOoCo4adnZcmHbdrl6/Ljasw7bq7ASOBGRDwRWmPp79NFHrTWcsrKy5Mknn1RlCMA2/4q8EFzVTxD5fVNuQnuZKPnaclFGfjs6T3FQveI6pwGDT+aaNZL2ylS5arO3JfauwzYrLF5JRGRyuQW9YOf1fPDBB0W9poBheLkFF1BJvdsn3fJsY2ObuI6Rq8TeiRy5CqKgSu1h5/jP+9ooM7dbISLyzO/vAo9YMWDyXaik7iqoAlZcD77pP4xU5Qmq1ElNBVc4HxEfz2lBIiJf2ISZfEtBK6mz4npwUDlVNtN/eWiaOo9+RERkLAZWAaByqcqG9iP/hkR1I/sREVHBsdyCn8m+elX2b/lKLp4+JiXLV5P6rbqpUgrIoUKiumPyum2OFSuuBwes/jOyHxERFRwDKz+y46sFUnXzJLlFTlrb0tZWlL9aT1QlFbD6D0GUbXDFiuvBByUVsPrvalqa8zwri0XCoqJUPyIiMhanAv0oqGq86WmprP0dVAGO0V5x/zFVUoEV1wkJ6SipkHvgUGvu2jHOM3GdiMjEcgtkXrkFTP+dmHyTCqJCnNRkzdFE0i0VpfL4g4IOWP2HRHXkVLHievBiHSsiIh8ut0DmQU6Vmv5zUegewVa0nJS96Nc2gSUVSEHwhJIKrLxOROQ9DKz8ABLVjexHwQNBVOlWcWZfBhFR0GCOlR/A6j8j+xEREZFnMLDyAyipkCYVVS6VM2hPlYqqHxEREZmHgZUfCA0LUyUVwDG40o9TWk9U/YiIiMg8DKz8RNNuA+SnNnPkuKWiXTtWA6Id54mIiMhcLLfgB+UWrld5nSNVRERExmG5hSCCIAolFYiIiMj3MLCigKBlZ7NeExERmY6BFfk9VhgnIiJfweR18vug6tjwEXZBFWADYrTjPBERkbcwsCK/nv7DSJU4W39xrQ3n0Y+IiMgbGFiR31I5VQ4jVXY0TZ1HPyIiIm9gYEV+C4nqRvYjIiIqKgZW5Lew+s/IfkREREXFwIr8FkoqYPWfWCzOO1gs6jz6EREReQMDK/JbqFOFkgq5Bw7B1bVjnGc9KyIi8hYGVuTXUKeq2huzJSwqyq4dx2hnHSsiIvImFgglv4fgKSI+npXXiYjIdAysKCAgiCrdKs7syyAioiDHqUAiIiIigzCwIiIiIjIIAysiIiKiQAqs3nrrLalVq5aEh4dLq1atJCkpKd/+y5Ytk/r166v+jRo1ktWrV9ud1zRNXnjhBYmJiZGSJUtK586d5dChQ3Z9Tp06JQ899JCULVtWypUrJ4MGDZJz587Z9fnqq6/ktttuk4iICKlcubL07t1bfvvtNwM/cyIiIgokpgdWS5YskZEjR8rEiRMlOTlZGjduLN26dZP09HSn/Tdt2iT9+vVTgdCOHTukV69e6rFnzx5rnxkzZsicOXPknXfekS1btkjp0qXVa2ZlZVn7IKjau3evrF27VlauXCnfffedDB482Hr+yJEjcs8990inTp1k586dKsg6ceKE3HfffR6+I0REROSvLBqGd0yEEaqWLVvK3Llz1XFOTo5Ur15dhg0bJmPHjs3Tv2/fvnL+/HkVDOkwqtSkSRMVSOHTqVq1qowaNUpGjx6tzmdkZEhUVJR8+OGH8uCDD8rPP/8ssbGxsnXrVmnRooXqk5iYKD169JA///xTffzy5ctVAHfp0iUJCcmNP1esWKGCLbQVK1bsup9bZmamREZGqvfHyBgREQWu7OxsuXLlitmXQQWA3+Gh+ZTkKcrvb1PLLVy+fFm2b98u48aN+3sILSRETd1t3rzZ6cegHSNctjAa9dlnn1lHmlJTU9Vr6HBzEMDhYxFY4RnTf3pQBeiP98YI17333ivNmzdXxx988IE8+uijaprwP//5j+rnKqhCwIWH7ReGiIgCG/6gx++dM2fOmH0p5AbEAdHR0WJxtS1aIZkaWGFqDRE+RpNs4Xj//v1OPwbfvM76o10/r7fl16dKlSp258PCwqRChQrWPrVr15Y1a9ZInz595IknnlDX2bp16zz5XLamTp0qkyZNkkCjZWez+CYRkQt6UIXfK6VKlTL8FzUZHwhfuHDBmnKEfGwjsUBoPv9QHn/8cRkwYICaEjx79qxKiL///vtVXpazfzgYebMdTcOIFaY1/VnmmjWS9spUuXot4ARsbIw9+LhdDBEFO/zRrQdVFStWNPtyqICwsA0QXOFrl9+0oF8FVpUqVVKfTFpaml07jjE85wza8+uvP6PNNgrFMfKw9D6OyfFXr15VKwX1j8dKRUwhIhFet3DhQhUoYboQeV2OSpQooR6BAkHVseEjEN7btV9NS8tt5158RBTk9JwqjFSRf9G/ZvgaGhlYmboqsHjx4iqXad26ddY2JK/jGNNuzqDdtj9gBEnvjyk8BEe2fTByhGBI74Nn/IWB/C7d+vXr1XsjFwswTKgnrev0G49+gQ7Tfxipcgyqck/mtuE8+hERBTtO//kfi4e+ZqaXW8DU2bvvvisLFixQq/WGDBmiVv0NHDhQne/fv79dcvvw4cPVCr6ZM2eqPKwXX3xRtm3bJk899ZT1Ro0YMUImT54sX3zxhezevVu9Blb6oSwDNGjQQLp3766m+lAza+PGjerjkdiOfpCQkKBWDb700kuqBhZKQeCaatasKU2bNpVAp3KqbKb/8tA0dR79iIiIyEcCK5RPeO2111T+EqbqUDMKgZOefH706FFJSUmx9m/Tpo0sWrRI5s2bp2peoSwCVgQ2bNjQ2ufZZ59V5RpQlwqlHLCiD6+JgqK6//73v6rIaHx8vCqz0K5dO/WaOtSvwvvgtRFIIRDDNB9eR5+bDWRIVDeyHxERUUFhkERf7e9vTK9jFcj8uY7V+S1JcnTAgOv2q7FggZRuFeeVayIi8jUoPI0yP0hDsf3j3R8cP35cDWqsWrVK5SGXL19eDVigrW3btqYHVp9++ql1psnbXzu/rWNFvgslFbD6D4nqTvOsLBYJi4pS/YiIqGiyczRJOnJK0s9mSZWIcImrXUFCQzybt4Vt2lBPEqk4N954owqukJ988uRJj75voDN9KpB8E+pUoaRC7oHDP+5rxzjPelZEREWTuCdF2k1fL/3e/VGGL96pnnGMdk/BAq7vv/9epk+fLh07dlT5w3FxcSqnuWfPnqrPrFmz1H682BYOK+L/+c9/2u2pi91MUGQTO6HcfPPNapXd/fffrxZ/IVjDHsAYBXv66adVWQod2l9++WVVygivXa1aNbUSPz9//PGHqiuJ90PNSeyC4qt79zKwIpdQSqHaG7PVyJQtHKOdpRaIiIoGwdOQhcmSkvH3XraQmpGl2j0VXJUpU0Y9kMdku2OILayMx7672FcXgRJWzyOH2RaCKPRZvHixykH+5ptv1O4lKKaNB3Ys+b//+z+VD23r1VdfVdOO2PMX29dhYRpW+DuDcgjYYSUiIkIFg1hwhmtH7jNG3HwNc6w8yJ9zrGyx8joRkfE5Vpj+w8iUY1Clw9xAdGS4/DCmk0emBT/55BO1Ov7ixYvSrFkzad++vVodf+uttzrtj+DoySefVLum6CNWWC3/yy+/SJ06dVTbk08+qYIpTCsi+AEEQBilwn6+gP/H6vwvv/zS+tp4X/zO1Hc3sc2xQg1JrPRH5QC9RAICKoxeITDsWsg/8j2VY8URK7ouBFFIUI+8K0E9M6giIio65FS5CqoAox44j36eyrH666+/VGkiBD8YbUKAhYAJvv76a7VyHlN1GC165JFHVP4VRql0mP7TgyqIiopSgZMeVOltjkW5HWtV4hiBkzM//fSTCt5wDfpIG6YDERgdPnxYfA2T14mIiEyARHUj+xUGRmq6dOmiHhMmTJB//OMfMnHiROnQoYPcddddqrbklClTVCDzww8/yKBBg9RokV61vFixYnavZ7FYnLYVpbA28rpQTBxlkhxVrlxZfA0DKyIiIhNg9Z+R/YwQGxurptewMwmCIRTj1nchWbp0qWHv8+OPP+Y5xvSgMxhFW7JkidrTzx/SajgVSEREZAKUVIiJDFe5VM6gHefRz2iY0kMhbOQv7dq1S+UaLVu2TO2PixV3devWVUnjb775pvz6668qb0rPkTLCxo0b1XsdPHhQrQjEeyOB3ZmHHnpI7S2M60LyOq4V05ZYbfjnn3+Kr2FgRUREZAIkpE+8O1b9v2NwpR/jvCcS15GnhL1xX3/9dbnjjjvU7iWYCkQy+9y5c9WKPZRbQDkGnMM03NSpUw17/1GjRqnt6LCzCRLT8V5Y+ecMph2/++47qVGjhtx3331qZAtTksix8sURLK4K9KBAWRVIRESeq7yOkgqTVuyzS2THSBWCqu4NYyTQ1KpVS+3pi4eZWHmdiIgoACF46hIb7fXK6+QZDKyCEOtSERH5FgRRretUNPsyyAAMrIJM5po1kvbKVLmammptw56A2J6GldSJiMjTfvPRrWiMwuT1IAuqjg0fYRdUATZaRjvOExERUeExsAqi6T+MVImztQrX2nAe/YiIiKhwGFgFCZVT5TBSZUfT1Hn0IyIiosJhYBUkkKhuZD8iIiLKi4FVkMDqPyP7ERERUV4MrIIESipg9Z9YXNRFsVjUefQjIiKiwmFgFSRQpwolFXIPHIKra8c4z3pWREQEFotFbcjsrhdffFGaNGnidjX22bNni5E6dOhgSnV3BlZBBHWqqr0xW8KiouzacYx21rEiIgoex48flyFDhqg9+EqUKCHR0dFqvz5skFwUo0ePlnXr1kmwYoHQIIPgKSI+npXXiYh8SU62yO+bRM6liZSJEqnZRiTEsz+Xe/fuLZcvX5YFCxbIjTfeKGlpaSogOnnyZKFeD1sPZ2dnqw2e8QhWHLEKQgiiSreKk8i7EtQzgyoiIhPt+0JkdkORBXeJfDIo9xnHaPeQM2fOyPfffy/Tp0+Xjh07Ss2aNSUuLk7GjRsnPXv2tPY7ceKE3HvvvVKqVCmpV6+efPHF39f0zTffqOnCL7/8Upo3b65GvX744Yc8U4GPPvqo9OrVS1577TWJiYmRihUrytChQ+XKlSsur++9996TcuXKWUe+9uzZI3feeacK2KKiouSRRx5R16Y7f/689O/fX53He8ycOVPMwsCKiIjILAielvYXyfzLvj0zJbfdQ8GVPqqEHKpLly657Ddp0iTp06eP7Nq1S3r06CEPPfSQnDp1yq7P2LFjZdq0afLzzz/Lrbfe6vR1NmzYIIcPH1bPGCH78MMP1cOZGTNmqNdcs2aNxMfHqyCwU6dO0rRpU9m2bZskJiaq0TVcl+5f//qXfPvtt/L555+rj0PQl5ycLGZgYEVERGTW9F/iGEyiOTl5rS1xbG4/g4WFhanABkEORobatm0rzz33nAqgbGG0qV+/flK3bl155ZVX5Ny5c5KUlGTX56WXXpIuXbpInTp1pEKFCk7fr3z58jJ37lypX7++3HXXXZKQkOA0D2vMmDEqiR1BEkbQAB+HoArvj4/H/8+fP18FaQcPHlTX9P7776sRMQRijRo1Up/X1atXxQwMrIiIiMyAnCrHkSo7mkjmsdx+Hsqx+uuvv9T0Xvfu3dUoT7NmzexGkmxHoEqXLi1ly5aV9PR0u9dp0aLFdd/rlltukVCbtBNM1zm+Dqbv3n33XTWdiP66n376SQVR+igbHgiwAKNgeCBXrFWrVtaPQYB38803ixkYWBEREZkBiepG9iuE8PBwNdo0YcIE2bRpkxqhmjhxovV8sWLF7PojpyonJ8euDQHX9RQrwOvcfvvtKvl96dKldu0Ykbr77rtl586ddo9Dhw7JHXfcIb6GgRUREZEZsPrPyH4GiI2NVYngZoiLi1OJ8Jjyw7SeDqNoe/fuVbWuMCVp+0BQhylIBG5btmyxfszp06fVNKEZGFgRERGZASUVylbF+I2LDhaRstVy+xkMJRWQEL5w4UKVV3XkyBFZtmyZShy/5557xCxt2rSR1atXq6R5vWAoVhAiYR65Xlu3blVTf1999ZUMHDjQWt5h0KBBKoF9/fr1agUhRt5CQswJcVjHKkBp2dmsVUVE5MtQp6r79NzVfyq4sk1ivxZsdZ/mkXpWCEaQk/T666+rQAWlD6pXry6PP/64SmI3U7t27WTVqlVqFSLysoYNG6aKliKxvWvXrmoVI8pDIC9MD55effVV65RhRESEjBo1SjIyMky5fouGil7kEZmZmRIZGam+uEj489r7rlkjaa9MlaupqdY27AOILWtYXZ2IyDhZWVlqtKd27doqX6lQUFIBqwNtE9kxUoWgKvbvmlLkva9dUX5/c8QqwCCoOjZ8BErg2rVfTUvLbefWNUREvgXBU/0Er1deJ89gYBVg038YqXIMqnJPamqzZZzHljacFiQi8iEIomrfbvZVkAGYvB5AVE6VzfRfHpqmzqMfERERGY+BVQBBorqR/YiIiMg9DKwCCFb/GdmPiIiI3MPAKoCgpAJW/yGXyimLRZ1HPyIiIgrQwOqtt95SFVWx3BF1NRw3eHSEImbYJwj9sdkiionZQgWJF154Qe1FVLJkSencubMqfW8LxcawSzeWUWIDShQXQw0Mx9dB9debbrpJSpQoIdWqVZMpU6aIr0JCOkoq5B44BFfXjnGeietEREQBGlgtWbJERo4cqfYmSk5OlsaNG0u3bt3ybM6ow15GqL6KQGjHjh3Sq1cv9UClVR0qx86ZM0feeecdVeIeJe/xmqhZoUNQhRL5a9eulZUrV8p3330ngwcPtnuv4cOHy3vvvaeCq/3796uNKvXdtn0VSilUe2O2hEXZb4GAY7Sz1AIREZEHaSaLi4vThg4daj3Ozs7Wqlatqk2dOtVp/z59+mgJCQl2ba1atdKeeOIJ9f85OTladHS09uqrr1rPnzlzRitRooT28ccfq+N9+/ahHoG2detWa58vv/xSs1gs2rFjx6x9wsLCtP379xf6c8vIyFDvg2dvy7l6VTv34xbtzIqV6hnHRERkrIsXL6rfF3gm/5Lf164ov79NHbG6fPmybN++XU3V6VCeHsebN292+jFot+0PGI3S+6OKampqql0fVE/FFKPeB8+Y/mvRooW1D/rjvfVNHFesWCE33nijGs1CVVZMVf7jH/9QU4iuoMw+qrXaPsyC6b7SreIk8q4E9czpPyIiIs8zNbA6ceKE2kAxymHaCscIjpxBe3799efr9alSpYrd+bCwMKlQoYK1z6+//iq///67yuf66KOP5MMPP1RB4P333+/y85k6daoK4vQH9l0iIiLyRdio2GKxWB8VK1ZU++9hU2Yd2j/77DNTr9PfmJ5j5atycnLUCBSCqttvv106dOgg77//vmzYsEEOHDjg9GPGjRun9hXSH3/88YfXr5uIiPxPdk62bE3dKqt/Xa2ecewNCKRSUlLUY926dWqQ4a677vLKewcqU7e0qVSpktq5Oi0tza4dx9EoG+AE2vPrrz+jDasCbfs0adLE2scxOf7q1atqmk//eHwsvsGwIlDXoEED9Xz06FG5+eab81wbVg7iQUREVFBf//61TEuaJmkX/v7dFlUqSsbGjZXONe1TX4yG31m2vz/Hjh2rBhOOHz8ulVnz0P9GrIoXLy7NmzdXUbLtSBGOW7du7fRj0G7bH7CyT++PfCh8c9j2Qa4Tcqf0Png+c+aMmtrTrV+/Xr03crGgbdu2Ktg6fPiwtc/BgwfVc82aNQ26A0REFOxB1chvRtoFVZB+IV2147y3oOTQwoULpW7dumpakPx0E2aUWhgwYIBKJEcpg9mzZ8v58+dl4MCB6nz//v1V/SjkL+klENq3by8zZ86UhIQEWbx4sWzbtk3mzZtnnQ8eMWKETJ48WerVq6cCrQkTJkjVqlVVWQZ95AnDn48//rgqyXDlyhV56qmn5MEHH1T99GT2Zs2ayWOPPaauCUHX0KFDpUuXLnajWERERIWB6T6MVGmCBWj20GYRi0xPmi4dq3eUUGzS7AFYoFWmTBn1//jdi9katGExFxWO6Xeub9++qk4UCnpiqm7nzp2SmJhoTT7HtBvmfnVt2rSRRYsWqUAKNa+WL1+uEusaNmxo7fPss8/KsGHDVF2qli1bqigcr4mCorr//ve/qshofHy89OjRQ9q1a2cNzgDfVFgZiOnKO+64QwVxCMgQyBERERVVcnpynpEqx+Aq9UKq6ucpHTt2VL938UBxbqyyv/POO9XiLSocC2ouFPJj6TowBYnVgUhkR4V3T9Kys+XCtu1qg2XsBYhta1higYjIs1B4GmV+MDti+8d7QSBRfcz3Y67bb/rt06XHjT3EE6sCkRZju+oPK/Xxe0uf+cEs0Keffmqd8QmWr11mEX5/mz4VSEWXuWaNpL0yVa7alKjAnoDYvoaV1omIfFPlUpUN7WcEBFKYsbl48aLX3jPQMLAKgKDq2PARKKFv1341LS23ndvYEBH5pGZVmqnVf0hUd5ZnhRwrnEc/T0FZIb1+4+nTp2Xu3Lkqfebuu++29sGoDqYKbSGHGdvFUV4MrPwYpv8wUuUYVOWe1NTGyzgfER/PaUEiIh+DhHSUVMDqPwRRtsEVjmFM3BiPJa4D8o/10kQREREq9xiFsVG70XaRmaPvv/9e5SaTDyavU+GpnCoXFeoVTVPn0Y+IiHwP6lTN6jBLqpSy3w0EI1Vo92QdK+wogjRr/YG8IiSw9+7d29rH9rztg0GVaxyx8mNIVDeyHxEReR+CJ5RUwOq/4xeOq5wqTP95cqSKPIeBlR/D6j8j+xERkTkQRLWMbmn2ZZABOBXox1BSAav/kEvllMWizqMfEREReR4DKz+GhHSUVMg9cAiurh3jPBPXiYiIvIOBlZ9DKYVqb8yWsGuV6nU4RjtLLRAREXkPc6wCAIInlFRg5XUiIiJzMbAKEAiiSreKM/syiIiIghqnAomIiIgMwsCKiIiIyCAMrIiIiIgMwsCKiIgoCD366KNisVjyPO68807p3r2704/BHoHos2vXLq9fr79g8joREZHJtOxsU1Z2I4D64IMP7No2btwoffr0kT///FNuuOEGu3Po26JFC7n11ls9fm3+ioEVERGRiTLXrJG0V6bK1dRUaxt2zUCBZ0/XIixRooREYwcPG/fcc49UrlxZbdI8fvx4a/u5c+dk2bJl8uqrr3r0mvwdpwID5C+d81uSJGPlKvWMYyIi8o+g6tjwEXZBFVxNS1PtOO9tYWFh0r9/fxVYaZpmbUdQlZ2dLf369fP6NfkTBlZ+Dv/ofonvLEcHDJC/Ro9Wzzg24x8jEREVHP4IxkiV2AQvf5/MbcN5T/6xvHLlSilTpoz18cADD6j2xx57TA4fPizffvut3TRg7969JTIy0mPXEwgYWPkxX/xLh4iICkblVDn8/Lajaeo8+nlKx44dZefOndbHnDlzVHv9+vWlTZs2Mn/+fHX8yy+/qMT1QYMGeexaAgUDKz/lC3/pEBFR4SFR3ch+hVG6dGmpW7eu9RETE2M9hyDqk08+kbNnz6rRqjp16kj79u09di2BgoGVn/KFv3SIiKjwsPrPyH5Gw8rAkJAQWbRokXz00UdqehClFih/DKz8lC/8pUNERIWHkgpY/SeughWLRZ1HPzMg56pv374ybtw4SUlJUXWv6PoYWPkpX/9Lh4iI8oc6VSipkHvgEFxdO8Z5b9SzcgXTgadPn5Zu3bpJ1apVTbsOf8I6Vn7+lw4S1Z3mWeEvnago0/7SISKi61N1qt6YnbeOVVSUx+tYoZzC9bRu3dqu5AJdHwMrP/9LB6v/1F82tt/4PvKXDhERXR+Cp4j4eFMqr5PxGFj5MTP/0iEiIuMgiCrdKs7syyADMLDyc/xLh4iIyHcwsAoA/EuHiIjIN3BVIBERURExwdv/aB76mjGwIiIiKqRixYqp5wsXLph9KeQm/Wumfw2NwqlAIiKiQgoNDZVy5cpJenq6Oi5VqhSrk/vBSBWCKnzN8LXD19BIDKyIiIiKIBrV00WswRX5BwRV+tfOSAysiIiIigAjVNi8uEqVKnLlyhWzL4cKANN/Ro9U6RhYERERGQC/qD31y5r8B5PXiYiIiAzCwIqIiIjIIAysiIiIiAzCHCsvFB/LzMw0+1KIiIiogPTf24UpIsrAyoPOnj2rnqtXr272pRAREVEhfo9HRka69TEWjXX4PSYnJ0f++usviYiIMLRgHCJpBGt//PGHlC1bVoIR70Eu3odcvA+8BzreB94DI+4DQiMEVVWrVpWQEPeypjhi5UH4Ytxwww0ee318owTzPxrgPcjF+5CL94H3QMf7wHtQ1Pvg7kiVjsnrRERERAZhYEVERERkEAZWfqhEiRIyceJE9RyseA9y8T7k4n3gPdDxPvAemH0fmLxOREREZBCOWBEREREZhIEVERERkUEYWBEREREZhIEVERERkUEYWJngrbfeklq1akl4eLi0atVKkpKS8u2/bNkyqV+/vurfqFEjWb16td35//3vf9K1a1epWLGiqvC+c+dOu/OnTp2SYcOGyc033ywlS5aUGjVqyNNPPy0ZGRkSTPfBFtZs3HnnnarfZ599JsF2DzZv3iydOnWS0qVLq8J5d9xxh1y8eFGC6T6kpqbKI488ItHR0eo+NGvWTD755BMJhHtw5coVGTNmjGrH54bq0f3791c7QTj+bHjooYfU90C5cuVk0KBBcu7cOTGTt+/Db7/9pj7v2rVrq5+PderUUSvJLl++LMH0vaC7dOmSNGnS5Lo/QwP5PqxatUq9H74fypcvL7169XLvwrEqkLxn8eLFWvHixbX58+dre/fu1R5//HGtXLlyWlpamtP+Gzdu1EJDQ7UZM2Zo+/bt08aPH68VK1ZM2717t7XPRx99pE2aNEl79913scJT27Fjh91roO99992nffHFF9ovv/yirVu3TqtXr57Wu3dvLZjug61Zs2Zpd955p+r36aefasF0DzZt2qSVLVtWmzp1qrZnzx5t//792pIlS7SsrCwtmO5Dly5dtJYtW2pbtmzRDh8+rL388staSEiIlpycrPn7PThz5ozWuXNn9XXF13fz5s1aXFyc1rx5c7vX6d69u9a4cWPtxx9/1L7//nutbt26Wr9+/TSzmHEfvvzyS+3RRx/VvvrqK/V98Pnnn2tVqlTRRo0apZnBrO8F3dNPP2392Zjfz9BAvQ/Lly/Xypcvr7399tvagQMH1HvjY9zBwMrL8IUcOnSo9Tg7O1urWrWq+iXnTJ8+fbSEhAS7tlatWmlPPPFEnr5Hjhwp8D+GpUuXqm/aK1euaMF2H9BerVo1LSUlxdTAyqx7gI/BDx1fYdZ9KF26tArAbFWoUEEFY4F0D3RJSUnqXvz+++/qGL98cLx161a7IMNisWjHjh3TzGDGfXAGv5xr166tBds9WL16tVa/fn0VTJgdWMWZcB/w+xC/G957770iXTunAr0IQ8vbt2+Xzp072+0niGNMzTiDdtv+0K1bN5f9CwrTgBj+DwsLC6r7cOHCBfl//+//qSFmTAGZxax7kJ6eLlu2bJEqVapImzZtJCoqStq3by8//PCDmMHM7wV8/kuWLFHTYdgwffHixZKVlSUdOnSQQLwH+DeP6R1M+emvgf9v0aKFtQ9eE++N7xFvM+s+uOpToUIFCaZ7kJaWJo8//rj85z//kVKlSomZLpt0H5KTk+XYsWPqvZo2bSoxMTEqZWTPnj1uXT8DKy86ceKEZGdnq19mtnCMfA9n0O5O/4Jex8svvyyDBw+WYLsPzzzzjPqFes8994iZzLoHv/76q3p+8cUX1Q/RxMRElVsUHx8vhw4dkmD6Xli6dKnKu0AeFiozP/HEE/Lpp59K3bp1JdDuAQJG5Jf069fPuhkt+iLAtoU/tBBQFOXni7/dB0e//PKLvPnmm+r7IVjuAWavHn30UXnyySftAm2znDDpPtj+fBw/frysXLlS5Vjhjy38AVZQDKyCTGZmpiQkJEhsbKz65gkmX3zxhaxfv15mz54twQojM4BfGgMHDlR/lb3++utqYcP8+fMlmEyYMEHOnDkjX3/9tWzbtk1Gjhwpffr0kd27d0sgQfCIzwu/PN9++20JVgW5Dxit6N69uzzwwAPqD49guQcIJM+ePSvjxo2TYHDFxX3Qfz4+//zz0rt3b2nevLl88MEHalQLifEFxcDKiypVqiShoaFqyNUWjl1NS6Hdnf75wT8c/NCIiIhQf5kXK1ZMguk+IKg6fPiwGvbFX+b6NCj+AXl7+sese4ChbUBgbatBgwZy9OhR8Taz7gO+D+bOnauCSYzWNW7cWK0Ew1/rmCYOlHug/wL5/fffZe3atXajNOiLqWFbV69eVX+ZmzFNbtZ90GF1WMeOHdWI9rx588QMZt0D/GzElBlGbvFzUR+1xb+HAQMGSLDchxgnPx9xT2688Ua3fj4ysPKi4sWLqwh43bp1dhEyjlu3bu30Y9Bu2x/wzeCqf34jVVh+jmvAyA2WowbbfRg7dqzs2rVLLSHWH4ARG/xVEgz3AEuXscz4wIEDdu0HDx6UmjVrireZdR+QawfIpbCFH+b6X63+fg/0XyCY4sWoHKY8HV8DI3bIZbH9BYv3xlJzbzPrPugjVfjjSh+hcPy+CPR7MGfOHPnpp5+sPxf1MgXIQZwyZYoEy31o3ry5CqRsfz7iY1CSw62fj0VKfadCLSEtUaKE9uGHH6pVOYMHD1ZLSFNTU9X5Rx55RBs7dqzdEtKwsDDttdde037++Wdt4sSJeZaWnzx5Uq3eWLVqlVrhgPfAMVa9QUZGhlod0ahRI1VuAe364+rVq0FzH5wxu9yCGffg9ddfV+UWli1bph06dEitEAwPD1ffG8FyHy5fvqxKC9x+++2q3AI+d7weVsThY/z9HuDz69mzp3bDDTdoO3futPs3f+nSJbtyC02bNlX34IcfflBlWMwut+Dt+/Dnn3+q74X4+Hj1/7Z9guUeFGWFeaDdh+HDh6uVgSi/gbIMgwYNUuU3Tp06VeBrZ2BlgjfffFOrUaOGKneAJaWoIaNr3769NmDAgDylEW666SbV/5Zbbsnzg/+DDz5Q/wgcH/jGgg0bNjg9jwf+AQXLffC1wMrMe4Aly/gBU6pUKa1169aqhpGZzLgPBw8eVPXd8EMT9+HWW2/NU37BX++B/ovR2QM/D2wDUARSZcqUUcH2wIEDtbNnz2pm8vZ9cPW9Yua4gxnfC74WWJl1HxCAoYYZfi5ERESo2leo9+cOC/5T8PEtIiIiInKFOVZEREREBmFgRURERGQQBlZEREREBmFgRURERGQQBlZEREREBmFgRURERGQQBlZEREREBmFgRURERGQQBlZERCbA3nQjRozw6McV9j2IqPAYWBGR6R599FGxWCx5Ht27dxdf4guByv/+9z95+eWXTb0GInItLJ9zRERegyDqgw8+sGvDTvOU6/Lly1K8eHGpUKGC2ZdCRPngiBUR+QQEUdHR0XaP8uXLq3PffPONCiq+//57a/8ZM2ZIlSpVJC0tzTqa9NRTT6lHZGSkVKpUSSZMmICddK0fc+nSJRk9erRUq1ZNSpcuLa1atVKvbWvjxo3qtUqVKqXev1u3bnL69Gk1qvbtt9/KG2+8YR1R++2339TH7NmzR+68804pU6aMREVFySOPPCInTpywvub58+elf//+6nxMTIzMnDnzuvfjxRdflCZNmsh7770ntWvXlvDwcKejZv/+97+lXr166jze+/7773f5mqtWrVL35r///W+BviZE5D4GVkTk8/RgAgFLRkaG7NixQwVNCDoQTOgWLFggYWFhkpSUpAKgWbNmqT46BF2bN2+WxYsXy65du+SBBx5QI2WHDh1S53fu3Cnx8fESGxur+v3www9y9913S3Z2tnq91q1by+OPPy4pKSnqUb16dTlz5ox06tRJmjZtKtu2bZPExEQV7PXp08f6vv/6179UUPb555/LmjVrVDCXnJx83c/7l19+kU8++URN/+HaHOH9nn76aXnppZfkwIED6r3vuOMOp6+1aNEi6devnwqqHnroIbe/BkRUQBoRkckGDBighYaGaqVLl7Z7TJkyxdrn0qVLWpMmTbQ+ffposbGx2uOPP273Gu3bt9caNGig5eTkWNvGjBmj2uD3339X73Hs2DG7j4uPj9fGjRun/r9fv35a27ZtXV4n3mP48OF2bS+//LLWtWtXu7Y//vgDw2TagQMHtLNnz2rFixfXli5daj1/8uRJrWTJknley9bEiRO1YsWKaenp6S6v4ZNPPtHKli2rZWZm5nu9c+fO1SIjI7VvvvnG5fsRkTGYY0VEPqFjx47y9ttv27XZ5hNhKhCjLbfeeqvUrFlTXn/99Tyvcdttt6kpOh1GmDDthhGn3bt3q+ebbrrJ7mMwPVixYkX1/xgVwiiWO3766SfZsGGDmuZzdPjwYbl48aLKj8K0o+3ndfPNN1/3tfF5Vq5c2eX5Ll26qD433nijGnnD495771XTmLrly5dLenq6muJs2bKlW58bEbmPgRUR+QTkPNWtWzffPps2bVLPp06dUg98TEGdO3dOQkNDZfv27erZlh4UlSxZ0u3rxutiunD69Ol5ziGfCtN5hXW9zy8iIkJNKWJqEVOML7zwgsrN2rp1q5QrV071wRQl+syfP19atGhhF3gSkfGYY0VEfgGjP88884y8++67avRnwIABkpOTY9dny5Ytdsc//vijSuxGIIUAAyNWGL1BAGf7QKI8YDRs3bp1Lq8Bo2Z4DVvNmjWTvXv3Sq1atfK8LgKjOnXqSLFixeyuDcnwBw8eNOS+IKesc+fOKpkfeWNIqF+/fr31PN4fI2rI7xo2bJgh70lErjGwIiKfgCm51NRUu4e+sg7BzMMPP6xW6A0cOFCVZUAQ4bi67ujRozJy5EiVyP3xxx/Lm2++KcOHD1fnMAWIpG2szkMy+JEjR1SS+9SpU9VqORg3bpwa7fnnP/+pXn///v1qelK/DgRPCJAQvKANgd3QoUPV6BkSw/GxCAC/+uordZ24boyGDRo0SCWwI+DBCkKsMAwJKfqP35UrV8qcOXPUFObvv/8uH330kbomx2lGfO4IrpAIb3YdLqJAx6lAIvIJWNGGqTNbCBAQ3EyZMkUFDggkAP3mzZungpmuXbtK48aNVTuCJuQ0xcXFqVEqBFWDBw+2vh4CssmTJ8uoUaPk2LFjqiQD8rLuuusuawCCKbXnnntOvQamBjE6hvcBlGrASBlWDeJ9EJwh2EL+0pgxY9S1IEBE3hPynfTg6dVXX7VOGWL6Du+P1Y1Fhek+BImY/svKylKjcwgob7nlljx9cS8R2GGFJe5NQUo+EJH7LMhgL8THERH5FAQMqPs0e/Zssy+FiIIYpwKJiIiIDMLAioiIiMggnAokIiIiMghHrIiIiIgMwsCKiIiIyCAMrIiIiIgMwsCKiIiIyCAMrIiIiIgMwsCKiIiIyCAMrIiIiIgMwsCKiIiISIzx/wHEggP+nf/G7wAAAABJRU5ErkJggg==”, “text/plain”: [

“<Figure size 640x480 with 1 Axes>”

]

}, “metadata”: {}, “output_type”: “display_data”

}

], “source”: [

“ef = PortfolioWrapper(AssetsDistribution(mu=mu,cov=Σ)).variance_frontier()n”, “plt.scatter(ef.risks,ef.returns,label=’Sample’)n”, “n”, “ef_shrinked = PortfolioWrapper(AssetsDistribution(mu=mu_jorion,cov=Σ_lw_cc)).variance_frontier()n”, “plt.scatter(ef_shrinked.risks,ef_shrinked.returns,label=’Shrinked’)n”, “n”, “ef_bl = PortfolioWrapper(AssetsDistribution(mu=mu_bl,cov=Σ_bl)).variance_frontier()n”, “plt.scatter(ef_bl.risks,ef_bl.returns,label=’BL’)n”, “n”, “ef_fv = PortfolioWrapper(AssetsDistribution(mu=mu_fv,cov=Σ_fv)).variance_frontier()n”, “plt.scatter(ef_fv.risks,ef_fv.returns,label=’FV’)n”, “n”, “plt.ylabel(‘Expected return’)n”, “plt.xlabel(‘Expected risk’)n”, “plt.legend()n”, “plt.show()”

]

}, {

“cell_type”: “code”, “execution_count”: 13, “id”: “1c563d18”, “metadata”: {

“execution”: {

“iopub.execute_input”: “2026-03-30T19:38:48.091943Z”, “iopub.status.busy”: “2026-03-30T19:38:48.091878Z”, “iopub.status.idle”: “2026-03-30T19:38:48.274064Z”, “shell.execute_reply”: “2026-03-30T19:38:48.273816Z”

}

}, “outputs”: [

{
“data”: {

“image/png”: 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”, “text/plain”: [

“<Figure size 600x200 with 1 Axes>”

]

}, “metadata”: {}, “output_type”: “display_data”

}, {

“data”: {

“image/png”: 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”, “text/plain”: [

“<Figure size 600x200 with 1 Axes>”

]

}, “metadata”: {}, “output_type”: “display_data”

}, {

“data”: {

“image/png”: 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”, “text/plain”: [

“<Figure size 600x200 with 1 Axes>”

]

}, “metadata”: {}, “output_type”: “display_data”

}, {

“data”: {

“image/png”: 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”, “text/plain”: [

“<Figure size 600x200 with 1 Axes>”

]

}, “metadata”: {}, “output_type”: “display_data”

}

], “source”: [

“pd.DataFrame(ef.weights,index=weekly_prices.columns).T.plot.bar(stacked=True,title=’Sample EF’,figsize=(6,2)); plt.show()n”, “n”, “pd.DataFrame(ef_shrinked.weights,index=weekly_prices.columns).T.plot.bar(stacked=True,title=’Shrinked EF’,figsize=(6,2)); plt.show()n”, “n”, “pd.DataFrame(ef_bl.weights,index=weekly_prices.columns).T.plot.bar(stacked=True,title=’BL EF’,figsize=(6,2)); plt.show()n”, “n”, “pd.DataFrame(ef_fv.weights,index=weekly_prices.columns).T.plot.bar(stacked=True,title=’FV EF’,figsize=(6,2)); plt.show()”

]

}

], “metadata”: {

“kernelspec”: {

“display_name”: “.venv”, “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”: “3.12.9”

}

}, “nbformat”: 4, “nbformat_minor”: 5

}