{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "be27992f",
   "metadata": {},
   "source": [
    "# Optimal Transport in linear ICA applied to Econometrics\n",
    "\n",
    "#### In this application we test our methodology to find ICs in a simulated price discovery case between distinct markets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ce700a45",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import torch\n",
    "import scipy.stats\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy.optimize import linear_sum_assignment\n",
    "\n",
    "from wasserstein_ica import WassersteinICA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "efd6fc0a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "\n",
    "# Define a consistent Thesis Theme\n",
    "def set_thesis_theme():\n",
    "    # Academic, colorblind-friendly palette\n",
    "    # Blue, Orange, Green, Red, Purple, Brown\n",
    "    thesis_colors = ['#0173B2', '#DE8F05', '#029E73', '#D55E00', '#CC78BC', '#CA9161']\n",
    "    \n",
    "    mpl.rcParams.update({\n",
    "        # Figure and Layout\n",
    "        'figure.figsize': (8, 5),\n",
    "        'figure.dpi': 300,            # High resolution for print\n",
    "        'axes.prop_cycle': mpl.cycler(color=thesis_colors),\n",
    "        \n",
    "        # Grid lines (light and unobtrusive)\n",
    "        'axes.grid': True,\n",
    "        'grid.alpha': 0.3,\n",
    "        'grid.linestyle': '--',\n",
    "        'axes.axisbelow': True,       # Grid goes behind data\n",
    "        \n",
    "        # Spines (remove top and right borders for a cleaner look)\n",
    "        'axes.spines.top': False,\n",
    "        'axes.spines.right': False,\n",
    "        \n",
    "        # Fonts and Text\n",
    "        'font.size': 11,\n",
    "        'axes.titlesize': 13,\n",
    "        'axes.labelsize': 12,\n",
    "        'xtick.labelsize': 10,\n",
    "        'ytick.labelsize': 10,\n",
    "        \n",
    "        # Legends\n",
    "        'legend.frameon': False,      # No box around the legend\n",
    "        'legend.fontsize': 10,\n",
    "        \n",
    "        # Lines\n",
    "        'lines.linewidth': 2.0\n",
    "    })\n",
    "\n",
    "# Run this before plotting\n",
    "set_thesis_theme()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "03a48eff",
   "metadata": {},
   "outputs": [],
   "source": [
    "def apply_economic_constraints(W_est, W_white):\n",
    "    \"\"\"\n",
    "    Post-process the statistical ICA output to enforce economic meaning.\n",
    "    \n",
    "    Addresses the critique that standard ICA results are permutation/sign indefinite.\n",
    "    We apply:\n",
    "    1. Dominant Diagonal: The shock impacting Market i the most is labeled Shock i.\n",
    "    2. Positive Spillover: Structural shocks are normalized to have positive effects.\n",
    "    \n",
    "    Args:\n",
    "        W_est (Torch Tensor): Unmixing matrix from ICA (Whitened space).\n",
    "        W_white (Torch Tensor): Whitening matrix used.\n",
    "        \n",
    "    Returns:\n",
    "        B_identified (Numpy Array): The economically identified Mixing Matrix.\n",
    "    \"\"\"\n",
    "    # 1. Recover the Raw Mixing Matrix (B_raw)\n",
    "    # The total estimated unmixing is W_tot = W_est @ W_white\n",
    "    # The mixing matrix B is the inverse: X = B * S\n",
    "    W_total = torch.matmul(W_est, W_white)\n",
    "    B_raw = torch.linalg.inv(W_total).cpu().numpy()\n",
    "    \n",
    "    # 2. Permutation Constraint (Dominant Diagonal)\n",
    "    # We use the Hungarian Algorithm (linear_sum_assignment) to match \n",
    "    # Shocks (columns) to Markets (rows) such that the diagonal magnitude is maximized.\n",
    "    # We pass negative absolute values because the algorithm minimizes cost.\n",
    "    row_ind, col_ind = linear_sum_assignment(-np.abs(B_raw))\n",
    "    \n",
    "    # Reorder the columns (shocks) of B\n",
    "    B_permuted = B_raw[:, col_ind]\n",
    "    \n",
    "    # 3. Sign Constraint (Positive Impact)\n",
    "    # Ensure the diagonal elements are positive (B_ii > 0).\n",
    "    # If B_ii is negative, we assume we found the \"negative\" shock and flip the column.\n",
    "    diagonals = np.diag(B_permuted)\n",
    "    sign_corrections = np.sign(diagonals)\n",
    "    \n",
    "    # Broadcast multiplication to flip columns where sign is negative\n",
    "    B_identified = B_permuted * sign_corrections[np.newaxis, :]\n",
    "    \n",
    "    return B_identified"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c8662488",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running Experiment on cuda...\n",
      "Target True IS: [0.12 0.24 0.64]\n",
      "Constraint Mode: Dominant Diagonal & Positive Signs\n"
     ]
    }
   ],
   "source": [
    "# ==============================================================================\n",
    "# EXPERIMENT SETUP (Replicating Zema & Cordoni DGP)\n",
    "# ==============================================================================\n",
    "\n",
    "# Simulation Settings\n",
    "N_SIMULATIONS = 500       # Number of Monte Carlo runs\n",
    "T_SAMPLES = 5000          # Observations per run (Daily returns)\n",
    "N_MARKETS = 3\n",
    "DEVICE = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
    "\n",
    "# Define the \"True\" Structure\n",
    "# We target Information Shares: [0.12, 0.24, 0.64]\n",
    "# Assuming a standard VECM where the orthogonal complement to beta is [1, 1, 1],\n",
    "# The IS is proportional to the squared column sums of B.\n",
    "target_is = np.array([0.12, 0.24, 0.64])\n",
    "psi = np.array([1.0, 1.0, 1.0]) # Long-run impact vector\n",
    "\n",
    "# Construct a True Mixing Matrix B that yields these shares.\n",
    "# For simplicity, we use a diagonal B scaled by sqrt(target).\n",
    "# (Note: Even with a diagonal B_true, the ICA has to work because we whiten the data,\n",
    "# effectively destroying the structure, and ICA must rotate it back).\n",
    "B_true = np.diag(np.sqrt(target_is)) \n",
    "\n",
    "print(f\"Running Experiment on {DEVICE}...\")\n",
    "print(f\"Target True IS: {target_is}\")\n",
    "print(f\"Constraint Mode: Dominant Diagonal & Positive Signs\")\n",
    "\n",
    "results_is = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6873a940",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    }
   ],
   "source": [
    "for sim in range(N_SIMULATIONS):\n",
    "    \n",
    "    # --- A. Data Generation (Student-t Innovations) ---\n",
    "    # Independent shocks with degrees of freedom 5, 6, 7 (Heavy tails)\n",
    "    s1 = np.random.standard_t(df=5, size=T_SAMPLES)\n",
    "    s2 = np.random.standard_t(df=6, size=T_SAMPLES)\n",
    "    s3 = np.random.standard_t(df=7, size=T_SAMPLES)\n",
    "    \n",
    "    # Stack and Normalize to unit variance (Standard ICA assumption)\n",
    "    S = np.vstack([s1, s2, s3])\n",
    "    S = S / S.std(axis=1, keepdims=True)\n",
    "    \n",
    "    # Mix the signals\n",
    "    X_np = B_true @ S\n",
    "    X_torch = torch.tensor(X_np, dtype=torch.float32, device=DEVICE)\n",
    "    \n",
    "    # --- B. Wasserstein ICA ---\n",
    "    model = WassersteinICA(X_torch)\n",
    "    model.whiten()\n",
    "    \n",
    "    dim = X_torch.shape[0]\n",
    "    num_restarts = min(dim * 4, 150)\n",
    "    \n",
    "    # \n",
    "    # OPTIMIZATION PHASE 1: Deflationary SGD\n",
    "    # Sequentially extract components to form a robust initialization matrix\n",
    "    W_init_list = []\n",
    "    prev_components = torch.empty((0, dim), device=DEVICE)\n",
    "    \n",
    "    for k in range(dim):\n",
    "        w_k, _ = model.optimize_wasserstein2(\n",
    "            prev_components=prev_components,\n",
    "            continuous=True,\n",
    "            max_iter=200,\n",
    "            lr=0.1,\n",
    "            n_restarts=num_restarts\n",
    "        )\n",
    "        W_init_list.append(w_k)\n",
    "        prev_components = torch.cat([prev_components, w_k.unsqueeze(0)], dim=0)\n",
    "        \n",
    "    W_init = torch.stack(W_init_list)\n",
    "    \n",
    "    # OPTIMIZATION PHASE 2: Symmetric Stiefel Optimization\n",
    "    # Refine the initial matrix simultaneously on the Stiefel manifold\n",
    "    W_opt = model.optimize_symmetric(\n",
    "        n_components=dim,\n",
    "        optimizer='stiefel',\n",
    "        init_w=W_init,\n",
    "        use_sinkhorn=False,\n",
    "        max_iter=300,\n",
    "        lr=1.0\n",
    "    )\n",
    "    \n",
    "    # --- C. Economic Identification ---\n",
    "    B_final = apply_economic_constraints(W_opt, model.W_white)\n",
    "    \n",
    "    # --- D. Calculate Information Share ---\n",
    "    # Calculate the long-run impact of each shock: Psi * B_column\n",
    "    # Since Psi=[1,1,1], this is just the column sum.\n",
    "    impacts = psi @ B_final\n",
    "    \n",
    "    # Variance contribution = impact^2\n",
    "    variances = impacts ** 2\n",
    "    \n",
    "    # Information Share = Variance / Total Variance\n",
    "    estimated_is = variances / np.sum(variances)\n",
    "    results_is.append(estimated_is)\n",
    "    \n",
    "    if (sim + 1) % 10 == 0:\n",
    "        print(f\"Simulation {sim+1}/{N_SIMULATIONS} completed.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "fc361326",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "Market / Source | True IS    | Est. IS (Mean)  | Std Dev   \n",
      "------------------------------------------------------------\n",
      "Market 1              | 0.1200     | 0.1212          | 0.0170    \n",
      "Market 2              | 0.2400     | 0.2386          | 0.0249    \n",
      "Market 3              | 0.6400     | 0.6402          | 0.0273    \n",
      "============================================================\n"
     ]
    }
   ],
   "source": [
    "#==============================================================================\n",
    "# RESULTS TABLE\n",
    "# ==============================================================================\n",
    "results_is = np.array(results_is)\n",
    "mean_is = np.mean(results_is, axis=0)\n",
    "std_is = np.std(results_is, axis=0)\n",
    "\n",
    "print(\"\\n\" + \"=\"*60)\n",
    "print(f\"{'Market / Source':<15} | {'True IS':<10} | {'Est. IS (Mean)':<15} | {'Std Dev':<10}\")\n",
    "print(\"-\" * 60)\n",
    "\n",
    "for i in range(N_MARKETS):\n",
    "    print(f\"Market {i+1:<14} | {target_is[i]:<10.4f} | {mean_is[i]:<15.4f} | {std_is[i]:<10.4f}\")\n",
    "\n",
    "print(\"=\"*60)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1759bbd6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2400x1500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 5))\n",
    "plt.boxplot(results_is, tick_labels=['Market 1', 'Market 2', 'Market 3'])\n",
    "plt.title(f\"Information Share Distribution (N={N_SIMULATIONS})\\nMetric: Wasserstein-2 (Sorted)\")\n",
    "plt.ylabel(\"Information Share\")\n",
    "# Draw True IS lines\n",
    "colors = ['red', 'green', 'blue']\n",
    "for i in range(3):\n",
    "    plt.axhline(target_is[i], color=colors[i], linestyle='--', alpha=0.5, label=f'True Market {i+1}')\n",
    "plt.legend()\n",
    "plt.grid(True, alpha=0.3)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c2a9aae7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3000x1800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns # Optional, for nicer plots\n",
    "\n",
    "# Plotting the distributions of Estimated Information Shares\n",
    "plt.figure(figsize=(10, 6))\n",
    "\n",
    "colors = ['#1f77b4', '#ff7f0e', '#2ca02c'] # Blue, Orange, Green\n",
    "labels = ['Market 1 (Target 0.12)', 'Market 2 (Target 0.24)', 'Market 3 (Target 0.64)']\n",
    "targets = [0.12, 0.24, 0.64]\n",
    "\n",
    "for i in range(3):\n",
    "    # Extract the column for Market i across all 500 simulations\n",
    "    data = results_is[:, i]\n",
    "    \n",
    "    # Plot Histogram/KDE\n",
    "    sns.kdeplot(data, color=colors[i], fill=True, alpha=0.3, label=labels[i])\n",
    "    plt.axvline(targets[i], color=colors[i], linestyle='--', linewidth=2)\n",
    "\n",
    "plt.title(f'Distribution of Estimated Information Shares\\n(Wasserstein-ICA, N={N_SIMULATIONS}, T={T_SAMPLES})')\n",
    "plt.xlabel('Information Share')\n",
    "plt.ylabel('Density')\n",
    "plt.legend()\n",
    "plt.grid(True, alpha=0.3)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d51b5ef0",
   "metadata": {},
   "source": [
    "### Economic Identification Strategy\n",
    "Unlike the statistical output of raw ICA, which is permutation and sign indeterminate, we impose two strict economic constraints to recover the structural parameters:\n",
    "\n",
    "1. **Dominant Diagonal (Permutation):** We strictly enforce that the structural shock assigned to Market $i$ must be the one that contributes the maximum variance to that specific market. This is implemented via the Hungarian Algorithm to solve the assignment problem.\n",
    "2. **Positive Impact (Sign):** We assume positive spillovers, meaning a structural innovation (good news) must have a positive initial impact on its own price. Negative coefficients are sign-flipped."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1115e192",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "ot_ica",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.4"
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