{"metadata":{"kernelspec":{"display_name":"Python 3 (ipykernel)","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":"3.7.12"}},"nbformat_minor":5,"nbformat":4,"cells":[{"cell_type":"code","source":"# Import Modules\nimport math\nimport numpy as np\nimport pandas as pd\nimport yfinance as yf\nfrom scipy import stats\nfrom datetime import date\nimport plotly.graph_objects as go\nimport matplotlib.pyplot as plt\nimport matplotlib.ticker as mtick\n\n# Input Variables\nticker = \"XBI\"\nstart_date = \"2010-01-01\"\nend_date = date.today()\ntime_interval = \"1wk\"\nrounding_base = 1\n\n# Download Historical Data from Yahoo Finance\ndef get_stock_data(ticker, start_date, end_date, time_interval):\n    df = yf.download(ticker, start_date, end_date, interval = time_interval).dropna()\n    return df\n\n\n# Extract the Last Closing Price\ndef get_last_price(df):\n    last_price = df.Close[len(df.Close) - 1]\n    return last_price\n\n\n# Calcualate Standard Deviation of the Log Return\ndef get_st_dev(df):\n    df[\"log_r\"] = np.log(df.Close) - np.log(df.Close.shift(1))\n    st_dev_pct = np.std(df.log_r)\n    return st_dev_pct\n\n\n# Round Historical Data\ndef round_data(df, rounding_base):\n    df = rounding_base * round(df / rounding_base)\n    return df\n\n\n# Group Historical Data by counting the sum of Opens, High, Lows and Closes (OHLC) for each Price Point\ndef group_data(df):\n    df[\"Date\"] = df.index\n\n    # Individually group OHLC columns\n    df_group_open = pd.DataFrame(\n        df.groupby(\"Open\").count().sort_values(by=\"Date\", ascending=False).Date\n    )\n    df_group_high = pd.DataFrame(\n        df.groupby(\"High\").count().sort_values(by=\"Date\", ascending=False).Date\n    )\n    df_group_low = pd.DataFrame(\n        df.groupby(\"Low\").count().sort_values(by=\"Date\", ascending=False).Date\n    )\n    df_group_close = pd.DataFrame(\n        df.groupby(\"Close\").count().sort_values(by=\"Date\", ascending=False).Date\n    )\n\n    # Join OHLC columns\n    df_joined = df_group_open.join(df_group_high, how=\"outer\", rsuffix=\"o\", sort=True)\n    df_joined = df_joined.join(df_group_low, how=\"outer\", rsuffix=\"h\", sort=True)\n    df_joined = df_joined.join(df_group_close, how=\"outer\", rsuffix=\"l\", sort=True).fillna(0)\n    # Rename columns and index\n    df_joined.columns = [\"count_open\", \"count_high\", \"count_low\", \"count_close\"]\n    df_joined.index.name = \"dollar_price_point\"\n    # Add sum column\n    df_joined[\"count_sum\"] = df_joined.sum(axis=1)\n    # Add percentage sum column\n    df_joined[\"count_sum_pct\"] = df_joined.count_sum / np.sum(df_joined.count_sum)\n    # Sort by percentage sum\n    df_joined = df_joined.sort_values(by=\"count_sum_pct\", ascending=False)\n    return df_joined\n\n\n# Plot the Grouped Data\ndef plot_data(df, ticker, start_date, end_date, rounding_base):\n    fig, ax = plt.subplots()\n    # Set X and Y\n    X = df.index\n    Y = df.count_sum_pct\n    # Create Bar Plot\n    ax.bar(X, Y, alpha=0.7)\n    # Add Grid\n    ax.grid()\n    # Resize Plot\n    fig.set_size_inches(56, 16)\n    # Add X-ticks\n    ax.xaxis.set_ticks(np.arange(np.min(X), np.max(X), rounding_base))\n    # Change Y-axis format to percent\n    ax.yaxis.set_major_formatter(\n        mtick.PercentFormatter(xmax=1, decimals=None, symbol=\"%\", is_latex=False)\n    )\n    # Set X-label\n    ax.set_xlabel(\"Price Point ($)\", size=15)\n    # Set Y-label\n    ax.set_ylabel('Time (%) spent at the Price Point', size=15)\n    # Set Title\n    ax.set_title(\n        \"Price Probability Plot for: \"\n        + ticker\n        + \", from = \"\n        + str(start_date)\n        + \" to \"\n        + str(end_date)\n        + \", at interval =  \"\n        + time_interval,\n        size=30,\n    )\n    # Add data labels\n    for x, y in zip(X, Y):\n        label = \"${:.0f}\".format(x)\n        plt.annotate(\n            label,  \n            (x, y),  \n            textcoords=\"offset points\",  \n            xytext=(-10, 15),  \n            fontsize=8,\n            ha=\"left\",\n        )  \n    # Set axes limits\n    ax.set_xlim(np.min(X) * 0.95, np.max(X) + np.min(X) * 0.05)\n    ax.set_ylim(np.min(Y) * 0.95, np.max(Y) * 1.05)\n    return (fig, ax)\n\n\ndef plot_normal(fig, ax, last_price, st_dev_pct):\n    # Add second Y-axis\n    ax1 = ax.twinx()\n    # Plot the bell-curve\n    mu = last_price\n    st_dev_dollar = st_dev_pct * last_price\n    snd = stats.norm(mu, st_dev_dollar)\n    x = np.linspace(0, 100, 1000)\n    y = snd.pdf(x)\n    ax1.plot(x, y, \"--r\")\n    ax1.set_ylim(0, 0.75)\n\n    # Plot Stadnard Deviation Points\n    sigmas = [\n        mu,\n        mu + st_dev_dollar,\n        mu + st_dev_dollar * 2,\n        mu - st_dev_dollar,\n        mu - st_dev_dollar * 2,\n    ]\n\n    heights = [\n        np.max(y),\n        np.max(y) / 1.6,\n        np.max(y) / 7,\n        np.max(y) / 1.6,\n        np.max(y) / 7,\n    ]\n\n    for x, y in zip(sigmas, heights):\n        ax1.plot([x, x], [0, y], \"--*r\", markersize=12)\n\n        plt.annotate(\n            \"${:.2f}\".format(x),\n            (x, y),\n            textcoords=\"offset points\",\n            xytext=(-10, 15),\n            fontsize=8,\n            ha=\"left\",\n        )\n\n    return ax.plot\n\n# Putting it together\ndef execute():\n    df = get_stock_data(ticker, start_date, end_date, time_interval)\n    last_price = get_last_price(df)\n    st_dev_pct = get_st_dev(df)\n    df = round_data(df, rounding_base)\n    df = group_data(df)\n    df.to_csv(\n        \"price_frequency_\"\n        + ticker\n        + \"_\"\n        + str(start_date)\n        + \"_\"\n        + str(end_date)\n        + \".csv\"\n    )\n    fig, ax = plot_data(df, ticker, start_date, end_date, rounding_base)\n    plot_normal(fig, ax, last_price, st_dev_pct)\n    plt.savefig(\n        \"price_probability_plot_\"\n        + ticker\n        + \"_\"\n        + str(start_date)\n        + \"_\"\n        + str(end_date)\n        + \".png\"\n    )\n    \n    print(df)\n\n\nif __name__ == \"__main__\":\n    execute()","metadata":{"trusted":true},"execution_count":13,"outputs":[{"name":"stdout","text":"[*********************100%***********************]  1 of 1 completed\n","output_type":"stream"},{"name":"stderr","text":"/srv/conda/envs/notebook/lib/python3.7/site-packages/ipykernel_launcher.py:33: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n","output_type":"stream"},{"name":"stdout","text":"                    count_open  count_high  count_low  count_close  count_sum  \\\ndollar_price_point                                                              \n20.0                      27.0        15.0       29.0         27.0       98.0   \n21.0                      24.0        30.0       16.0         23.0       93.0   \n84.0                      17.0        14.0       11.0         15.0       57.0   \n18.0                      17.0         6.0       18.0         16.0       57.0   \n19.0                      11.0        20.0       13.0         13.0       57.0   \n...                        ...         ...        ...          ...        ...   \n159.0                      0.0         1.0        0.0          0.0        1.0   \n162.0                      0.0         1.0        0.0          0.0        1.0   \n164.0                      1.0         0.0        0.0          0.0        1.0   \n143.0                      0.0         1.0        0.0          0.0        1.0   \n175.0                      0.0         1.0        0.0          0.0        1.0   \n\n                    count_sum_pct  \ndollar_price_point                 \n20.0                     0.037348  \n21.0                     0.035442  \n84.0                     0.021723  \n18.0                     0.021723  \n19.0                     0.021723  \n...                           ...  \n159.0                    0.000381  \n162.0                    0.000381  \n164.0                    0.000381  \n143.0                    0.000381  \n175.0                    0.000381  \n\n[147 rows x 6 columns]\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"<Figure size 4032x1152 with 2 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\n"},"metadata":{"needs_background":"light"}}],"id":"873fec60-a1f9-4c64-9d2d-e6b3e5730250"},{"cell_t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