Interactive.ipynb

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    "## Interactive Widgets\n",
    "---\n",
    "\n",
    "This notebook provides interactive widgets you can play with to understand some financial concepts. Each widget is provided with a description. Change the parameters and click the submit button to see the changes.\n",
    "\n",
    "> Run the notebook cell to see each widget in action and then play with the parameters"
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from bokeh.plotting import figure\n",
    "from bokeh.io import output_notebook, show\n",
    "from bokeh.resources import INLINE\n",
    "output_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bokeh.layouts import row,column,gridplot,layout\n",
    "from bokeh.models.widgets import (\n",
    "    TextInput, Button, Div, DatePicker, Slider, \n",
    "    RadioButtonGroup, Select, DataTable, TableColumn,\n",
    "    NumberFormatter\n",
    "    )\n",
    "from bokeh.models import ColumnDataSource, NumeralTickFormatter\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Returns Calculation**\n",
    "\n",
    "A simple widget to calculate the returns given buy, sell dates and values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
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       "\n",
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   "source": [
    "def return_calculation(doc):\n",
    "    \n",
    "    # create some widgets\n",
    "    button = Button(label=\"Submit\", button_type=\"success\")\n",
    "    buy_value = TextInput(title=\"Buy Value\", value='2500')\n",
    "    buy_date = DatePicker(title='Buy Date', value='2019-01-01')\n",
    "    sell_value = TextInput(title='Sell Value', value='2620')\n",
    "    sell_date = DatePicker(title='Sell Date', value='2019-03-25')\n",
    "    qty = TextInput(title='Quantity', value='100')\n",
    "    output = Div()\n",
    "\n",
    "    # add a callback to a widget\n",
    "    def update():\n",
    "        bv = float(buy_value.value)\n",
    "        sv = float(sell_value.value)\n",
    "        q = int(qty.value)\n",
    "        start = pd.to_datetime(buy_date.value)\n",
    "        end = pd.to_datetime(sell_date.value)\n",
    "        period = (end - start).days\n",
    "        profit = q*(sv-bv)\n",
    "        ret = profit/bv\n",
    "        ann_ret = ret * (365/period)\n",
    "        text = \"\"\"\n",
    "        Net profit = <b>{profit}</b> <br/>\n",
    "        Holding period = <b>{days} days</b> <br/>\n",
    "        Return = <b>{ret}% </b><br/>\n",
    "        Annualized return = <b>{ann_ret}</b>%\n",
    "        \"\"\"\n",
    "        output.text = text.format(profit=profit, days=period,\n",
    "                                  ret=round(ret, 2), \n",
    "                                  ann_ret=round(ann_ret, 2))\n",
    "    \n",
    "    button.on_click(update)\n",
    "\n",
    "    # create a layout for everything\n",
    "    l = column(\n",
    "        row(buy_value, buy_date),\n",
    "        row(sell_value, sell_date),\n",
    "        row(qty,button),\n",
    "        output\n",
    "    )\n",
    "\n",
    "    # add the layout to curdoc\n",
    "    doc.add_root(l)\n",
    "    \n",
    "show(return_calculation)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "def samples(mu=0.01, sigma=0.01, size=10):\n",
    "    \"\"\"\n",
    "    Return samples from a lognormal distribution\n",
    "    \"\"\"\n",
    "    return np.random.lognormal(mu, sigma, size)    \n",
    "\n",
    "def get_data(data):\n",
    "    \"\"\"\n",
    "    Data for grid plot\n",
    "    \"\"\"\n",
    "    size = len(data)\n",
    "    r = np.random.choice(range(size), 5, replace=False)*0.9\n",
    "    r = r.astype(int)\n",
    "    C = np.cumprod # shortcut to cumprod\n",
    "    df = pd.DataFrame({\n",
    "        'period': range(size),\n",
    "        'v1': C(data)\n",
    "    })\n",
    "    df.loc[r[0]:, 'v2'] = C(data[r[0]:])\n",
    "    df.loc[r[1]:, 'v3'] = C(data[r[1]:])\n",
    "    df.loc[r[2]:, 'v4'] = C(data[r[2]:])\n",
    "    df.loc[r[3]:, 'v5'] = C(data[r[3]:])\n",
    "    df.loc[r[4]:, 'v6'] = C(data[r[4]:])\n",
    "    return df\n",
    "\n",
    "def get_data_table(data):\n",
    "    \"\"\"\n",
    "    Get data from the dataframe for displaying as datatable\n",
    "    \"\"\"\n",
    "    s = pd.Series({col: data[col].first_valid_index() for col in data})\n",
    "    df = pd.concat([s, data.iloc[-1]], axis=1)\n",
    "    df = df.iloc[1:].reset_index()\n",
    "    df.columns = ['strategy', 'start_period', 'cumulative_returns']\n",
    "    return df\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Drawdown effect\n",
    "\n",
    "Most investors invest in the same strategy as that of their col"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.bokehjs_exec.v0+json": "",
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       "\n",
       "<script src=\"http://localhost:38021/autoload.js?bokeh-autoload-element=16440&bokeh-absolute-url=http://localhost:38021&resources=none\" id=\"16440\"></script>"
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   "source": [
    "def drawdown_effect(doc):\n",
    "    \n",
    "    # create some widgets\n",
    "    button = Button(label=\"Submit\", button_type=\"success\")\n",
    "    returns = Slider(start=-20,end=30,value=2,step=0.25,\n",
    "                     title='Returns in percentage')\n",
    "    label = Div(text=\"Volatility\")\n",
    "    volatility =  RadioButtonGroup(\n",
    "        labels=[\"Very Low\", \"Low\", \"Medium\", \"High\", \"Very High\"],\n",
    "        active=2)\n",
    "    periods = Slider(start=1, end=200, value=30, step=1,\n",
    "                    title=\"Number of periods\")  \n",
    "    src = ColumnDataSource({'period': [], 'v1':[], 'v2': [],\n",
    "                           'v3': [], 'v4': [], 'v5':[]})\n",
    "    src2 = ColumnDataSource({'start_period': [], 'cumulative_returns': []})\n",
    "    table = DataTable(source=src2, columns=[\n",
    "        TableColumn(field='start_period', title='start_period'),\n",
    "        TableColumn(field='cumulative_returns', \n",
    "                    title='cumulative_returns',\n",
    "                   formatter=NumberFormatter(format='$0.00'))\n",
    "    ], width=250, height=250)\n",
    "    table_text = \"\"\"\n",
    "    Cumulative returns for $1 invested in the same<br/>\n",
    "    strategy but started in different periods\n",
    "    \"\"\"\n",
    "    table_label = Div(text=table_text)\n",
    "   \n",
    "        \n",
    "    # add a callback to a widget\n",
    "    def update():\n",
    "        mu = float(returns.value)*0.01\n",
    "        sigma = (int(volatility.active)+1)*mu*2\n",
    "        size = int(periods.value)\n",
    "        print(mu)\n",
    "        s = samples(mu=mu, sigma=sigma, size=size)\n",
    "        data = get_data(s)\n",
    "        tbl = get_data_table(data)\n",
    "        src.data = src.from_df(data)\n",
    "        src2.data = src.from_df(tbl)\n",
    "            \n",
    "    figs = []\n",
    "    TOOLTIPS = [\n",
    "        ('period', '$x{0}'),\n",
    "        ('value', '$y{0.2f}')\n",
    "    ]\n",
    "    \n",
    "    for i in range(5):\n",
    "        figs.append(figure(title='Value of $1 invested',\n",
    "                          x_axis_label='period',\n",
    "                          y_axis_label='Amount',\n",
    "                           tooltips=TOOLTIPS\n",
    "                          ))\n",
    "    for i, col in zip(range(5), ['v1', 'v2', 'v3', 'v4', 'v5']):\n",
    "        figs[i].line('period', col, source=src)\n",
    "        figs[i].yaxis[0].formatter = NumeralTickFormatter(format=\"$0.00\")\n",
    "        \n",
    "    button.on_click(update)\n",
    "    \n",
    "    \n",
    "    grid = gridplot([column(table_label, table)] + \n",
    "                    [fig for fig in figs], \n",
    "                    ncols=3, plot_width=250, plot_height=250)\n",
    "    l = layout([\n",
    "        [returns, periods],\n",
    "        [label, volatility],\n",
    "        [button],\n",
    "        [grid]\n",
    "        \n",
    "    ])\n",
    "    \n",
    "    # add the layout to curdoc\n",
    "    doc.add_root(l)\n",
    "    \n",
    "show(drawdown_effect)"
   ]
  }
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