From 7b9c58418a4b268282ff1267a42ef43ee67908dd Mon Sep 17 00:00:00 2001 From: Magnus Date: Tue, 9 Oct 2018 14:21:10 +0200 Subject: [PATCH] Added paper 01B. --- 01B_Better_Long-Term_Stock_Forecasts.ipynb | 719 +++++++++++++++++++++ README.md | 5 + returns.py | 84 +++ 3 files changed, 808 insertions(+) create mode 100644 01B_Better_Long-Term_Stock_Forecasts.ipynb diff --git a/01B_Better_Long-Term_Stock_Forecasts.ipynb b/01B_Better_Long-Term_Stock_Forecasts.ipynb new file mode 100644 index 0000000..c53b94a --- /dev/null +++ b/01B_Better_Long-Term_Stock_Forecasts.ipynb @@ -0,0 +1,719 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Better Long-Term Stock Forecasts\n", + "\n", + "by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n", + "/ [GitHub](https://github.com/Hvass-Labs/FinanceOps) / [Videos on YouTube](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmlHaWuVxIA0pKL1yjryR0Z)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Introduction\n", + "\n", + "The [previous paper](https://github.com/Hvass-Labs/FinanceOps/blob/master/01_Forecasting_Long-Term_Stock_Returns.ipynb) showed a strong predictive relationship between the P/Sales ratio and long-term returns of some individual stocks and the S&P 500 stock-market index. \n", + "\n", + "However, there was a considerable amount of noise in those scatter-plots, because we considered fixed investment periods of exactly 10 years, for example. So even though the P/Sales ratio was a strong predictor for the mispricing at the buy-time, it was impossible to predict the mispricing at the sell-time, because the stock-market could be in a bubble or in a crash 10 years into the future, which would distort the estimated returns.\n", + "\n", + "This paper presents a simple solution, which is to consider the average returns for all investment periods between 7 and 15 years, and then make a scatter-plot of the mean returns versus the P/Sales ratio. This produces incredibly smooth curves for estimating the future long-term returns of the S&P 500 and some individual stocks.\n", + "\n", + "Along with the [previous paper](https://github.com/Hvass-Labs/FinanceOps/blob/master/01_Forecasting_Long-Term_Stock_Returns.ipynb), this is a very important discovery and it has implications for many areas of both theoretical and applied finance. It means that the U.S. stock-market as a whole is not \"efficient\" and does not follow a purely \"random walk\" in the long-term. It is possible to estimate the future long-term return of the stock-market and some individual stocks from just a single indicator variable." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Python Imports\n", + "\n", + "This Jupyter Notebook is implemented in Python v. 3.6 and requires various packages for numerical computations and plotting. See the installation instructions in the README-file." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "%matplotlib inline" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# Imports from Python packages.\n", + "import matplotlib.pyplot as plt\n", + "from matplotlib.ticker import FuncFormatter\n", + "import pandas as pd\n", + "import numpy as np\n", + "import os" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "# Imports from FinanceOps.\n", + "from curve_fit import CurveFitReciprocal\n", + "from data_keys import *\n", + "from data import load_index_data, load_stock_data\n", + "from returns import prepare_mean_ann_returns" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Load Data\n", + "\n", + "We now load all the financial data we will be using." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "# Define the ticker-names for the stocks we consider.\n", + "ticker_SP500 = \"S&P 500\"\n", + "ticker_JNJ = \"JNJ\"\n", + "ticker_K = \"K\"\n", + "ticker_PG = \"PG\"\n", + "ticker_WMT = \"WMT\"" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "# Load the financial data for the stocks.\n", + "df_SP500 = load_index_data(ticker=ticker_SP500)\n", + "df_JNJ = load_stock_data(ticker=ticker_JNJ)\n", + "df_K = load_stock_data(ticker=ticker_K)\n", + "df_PG = load_stock_data(ticker=ticker_PG)\n", + "df_WMT = load_stock_data(ticker=ticker_WMT)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Plotting Functions\n", + "\n", + "These are helper-functions used for making plots." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "def plot_psales(df, ticker, start_date=None):\n", + " \"\"\"\n", + " Plot the P/Sales ratio.\n", + "\n", + " :param df: Pandas DataFrame with PSALES.\n", + " :param ticker: Ticker-name for the stock or index.\n", + " :param start_date: Start-date for the plot.\n", + " :return: Nothing.\n", + " \"\"\"\n", + "\n", + " psales = df[PSALES][start_date:].dropna()\n", + " psales.plot(title=ticker + \" - P/Sales\", grid=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "def plot_ann_returns(ticker, df, key=PSALES,\n", + " min_years=7, max_years=15,\n", + " use_colors=True):\n", + " \"\"\"\n", + " Create a single scatter-plot with P/Sales or P/Book\n", + " vs. Mean Annualized Returns for e.g. 7-15 years.\n", + " \n", + " :param ticker: Ticker-name for the stock or index.\n", + " :param df: Pandas DataFrame containing key and TOTAL_RETURN.\n", + " :param key: Name of data-column to use e.g. PSALES or PBOOK.\n", + " :param min_years: Min number of years for return periods.\n", + " :param max_years: Max number of years for return periods.\n", + " :param use_colors: Boolean whether to use colors in plot.\n", + " :return: Nothing.\n", + " \"\"\"\n", + "\n", + " # Prepare the data.\n", + " # x is the P/Sales or P/Book and y is the Mean Ann. Returns.\n", + " x, y = prepare_mean_ann_returns(df=df, key=key,\n", + " min_years=min_years,\n", + " max_years=max_years)\n", + "\n", + " # Create a single plot.\n", + " fig = plt.figure(figsize=(10, 10))\n", + " ax = fig.add_subplot(211)\n", + "\n", + " # Scatter-plot.\n", + " if use_colors:\n", + " # Give each dot in the scatter-plot a shade of blue\n", + " # according to the date of the data-point.\n", + " ax.scatter(x, y,\n", + " c=list(range(len(x))), cmap='Blues',\n", + " alpha=1.0, marker='o')\n", + " else:\n", + " # Use the same color for all dots.\n", + " ax.scatter(x, y, marker='o')\n", + " \n", + " # First part of the title.\n", + " title1 = \"[{0}] {1} vs. {2}-{3} Years Mean Ann. Return\"\n", + " title1 = title1.format(ticker, key, min_years, max_years)\n", + "\n", + " # X-values for plotting fitted curves.\n", + " x_min = np.min(x)\n", + " x_max = np.max(x)\n", + " x_range = np.arange(x_min, x_max, (x_max/x_min)/1000)\n", + " \n", + " # Plot reciprocal curve-fit.\n", + " curve_fit_reciprocal = CurveFitReciprocal(x=x, y=y)\n", + " y_pred = curve_fit_reciprocal.predict(x=x_range)\n", + " ax.plot(x_range, y_pred, color='red')\n", + " # Title with these curve-fit parameters.\n", + " title2 = \"Mean Ann. Return = {0:.1%} / \" + key + \" + {1:.1%}\"\n", + " title2 = title2.format(*curve_fit_reciprocal.params)\n", + "\n", + " # Combine and set the plot-title.\n", + " title = \"\\n\".join([title1, title2])\n", + " ax.set_title(title)\n", + "\n", + " # Set axis labels.\n", + " ax.set_xlabel(key)\n", + " ax.set_ylabel(\"Mean Ann. Return\")\n", + " \n", + " # Convert y-ticks to percentages.\n", + " # We use a custom FuncFormatter because PercentFormatter\n", + " # is inconsistent with string-formatters used elsewhere.\n", + " formatter = FuncFormatter(lambda y, _: '{:.0%}'.format(y))\n", + " ax.yaxis.set_major_formatter(formatter)\n", + " \n", + " # Show grid.\n", + " ax.grid()\n", + " \n", + " # Show the plot.\n", + " plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Case Study: S&P 500\n", + "\n", + "The S&P 500 is a stock-market index consisting of the stocks of 500 of the largest companies in USA. The S&P 500 covers about 80% of the whole U.S. stock-market in terms of size so it is useful as a gauge for the entire U.S. stock-market.\n", + "\n", + "We consider the Total Return of the S&P 500 which is what you would get from investing in the S&P 500 and re-investing all dividends back into the S&P 500. We ignore all taxes here.\n", + "\n", + "The following scatter-plot shows the P/Sales ratio versus the Mean Annualized Returns of the S&P 500 for periods between 7 and 15 years.\n", + "\n", + "For each day we calculate the Total Return of the S&P 500 over the next 7-15 years, then we calculate the Mean Annualized Return from those, and then we put a blue dot in the scatter-plot for that date's P/Sales ratio and the Mean Annualized Return we just calculated. This process is continued for all days in the time-series, until we have calculated and plotted the P/Sales vs. Mean Annualized Return for all days.\n", + "\n", + "As can be seen from this scatter-plot, the P/Sales ratio is a very strong predictor for long investment periods between 7-15 years. We call the fitted red curve for the \"return curve\"." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plot_ann_returns(ticker=ticker_SP500, df=df_SP500, key=PSALES,\n", + " min_years=7, max_years=15, use_colors=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can forecast the future long-term returns using the fitted \"return curve\" from the scatter-plot above. Towards the end of 2017, the P/Sales ratio was almost 2.2 for the S&P 500, which was about the previous high point of the \"Dot-Com\" bubble around year 2000." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Date\n", + "2017-12-29 2.170896\n", + "Name: P/Sales, dtype: float64" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_SP500[PSALES].dropna().tail(1)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plot_psales(df=df_SP500, ticker=ticker_SP500)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "So if you purchased the S&P 500 in December 2017 at this P/Sales ratio and will keep the investment for more than 7 years, while reinvesting all dividends during those years (all taxes are ignored), then the formula forecasts an annualized return of about 1.35%:\n", + "\n", + "$$\n", + "Annualized\\ Return = 14.4\\% / (P/Sales) - 5.2\\% = 14.4\\% / 2.2 - 5.2\\% \\simeq 1.35\\%\n", + "$$\n", + "\n", + "The formula cannot predict exactly what will happen in the future, because there might be a stock-market bubble or a crash in any given year. The formula merely predicts an average annualized return for long-term investments of about 7-15 years in the S&P 500." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Case Study: Johnson & Johnson (JNJ)\n", + "\n", + "Now let us consider individual companies instead of a whole stock-market index. The first company we consider is Johnson & Johnson with the ticker symbol JNJ. This is a very large company with over 130.000 employees worldwide that manufacture a wide range of health-care related products.\n", + "\n", + "When we plot the P/Sales ratio versus the mean annualized return for 7-15 year periods, we see that the \"return curve\" fits quite well although there appears to be a few separate \"return curves\" for P/Sales ratios roughly between 2 and 3.\n", + "\n", + "The blue shades in the scatter-plot indicate the time of the data-points and suggest that the separate curves belong to different periods of time. More research would be needed to establish why these periods have different \"return curves\". Perhaps the periods had significantly different profit-margins or sales-growth." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plot_ann_returns(ticker=ticker_JNJ, df=df_JNJ, key=PSALES,\n", + " min_years=7, max_years=15, use_colors=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Towards the end of 2017 the P/Sales ratio was about 4.9 which is close to the all-time historical highs experienced during the stock-market bubble around year 2000." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Date\n", + "2017-12-31 4.895577\n", + "Freq: D, Name: P/Sales, dtype: float64" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_JNJ[PSALES].dropna().tail(1)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plot_psales(df=df_JNJ, ticker=ticker_JNJ)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Using the formula for the fitted \"return curve\" from the scatter-plot above, we get this forecasted long-term return:\n", + "\n", + "$$\n", + "Annualized\\ Return \\simeq 77.9\\% / (P/Sales) - 8.9\\%\n", + "\\simeq 77.9\\% / 4.9 - 8.9\\% \\simeq 7.0\\%\n", + "$$\n", + "\n", + "So according to this formula, the annualized return of the JNJ stock will be around 7.0% if you own the stock for at least 7 years, when dividends are reinvested and ignoring taxes.\n", + "\n", + "Again there is the caveat that it is impossible to predict whether there will be a stock-market bubble or crash several years into the future, so the forecasted return is an average for 7-15 year investment periods." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Case Study: Procter & Gamble (PG)\n", + "\n", + "Another very large company is Procter & Gamble with the ticker symbol PG, which sells a wide range of consumer products and has almost 100.000 employees.\n", + "\n", + "If we plot the P/Sales ratio versus the mean annualized return we get an incredibly regular curve of data-points. The red line shows a reciprocal curve-fit, which is apparently not the correct formula for this data, as it doesn't fit so well at the ends. You are encouraged to try and find a better curve-fit and a theoretical explanation why your formula is better." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plot_ann_returns(ticker=ticker_PG, df=df_PG, key=PSALES,\n", + " min_years=7, max_years=15)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "When we plot the historical P/Sales ratio, we see that at the end of 2017 it was around 3.5 which was near its all-time high experienced during the bubble around year 2000." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plot_psales(df=df_PG, ticker=ticker_PG)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Using the fitted reciprocal curve from the scatter-plot above, we get a forecasted return of about 6.1% per year, when dividends are reinvested without taxes:\n", + "\n", + "$$\n", + "Annualized\\ Return \\simeq 24.4\\% / (P/Sales) - 0.9\\% \\simeq \n", + "24.4\\% / 3.5 - 0.9\\% \\simeq 6.1\\%\n", + "$$\n", + "\n", + "But it should again be noted that this formula doesn't fit so well towards the ends of the data, and looking at the scatter-plot suggests a slightly lower return of maybe 5.5%." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Case Study: Kellogg's (K)\n", + "\n", + "The next company is Kellogg's which trades under the ticker symbol K. The company has about 33.000 employees and is especially known for making breakfast cereals.\n", + "\n", + "When we plot the P/Sales ratio versus the mean annualized return it shows a strong trend that higher P/Sales ratios gives lower long-term returns, although the curve-fit is not as good as for the other companies we studied above, especially for lower P/Sales ratios.\n", + "\n", + "The blue shades show the time of the data-points. It can be hard to see in this plot, but for P/Sales ratios between 1.50 and 1.75, there is a \"blob\" of light-blue data-points well above the fitted red curve. This clearly indicates that the outlying data-points belong to a specific period in time. But we would have to do more research into the financial data for that period, to uncover the reason why the returns are so different." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plot_ann_returns(ticker=ticker_K, df=df_K, key=PSALES,\n", + " min_years=7, max_years=15, use_colors=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Towards the end of 2017 the P/Sales ratio was about 1.8 which was actually very close to the historical average." + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1.8626938835082578" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_K[PSALES].dropna().mean()" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plot_psales(df=df_K, ticker=ticker_K)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Using the fitted \"return curve\" from the scatter-plot above with the P/Sales ratio of 1.8 we get the forecasted return:\n", + "\n", + "$$\n", + "Annualized\\ Return \\simeq 27.5\\% / (P/Sales) - 6.2\\% \\simeq \n", + "27.5\\% / 1.8 - 6.2\\% \\simeq 9.1\\%\n", + "$$\n", + "\n", + "So a forecasted return of about 9.1% per year over the next 7-15 years when dividends are reinvested without taxes. That is about 2% (percentage points) higher than the return forecasted for JNJ and 3% higher than forecasted for PG above." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Case Study: Wal-Mart (WMT)\n", + "\n", + "Now let us consider the company Wal-Mart which trades under the ticker symbol WMT. It is an extremely large retail-company with about 2.3 million employees.\n", + "\n", + "If we plot the P/Sales ratio versus the mean annualized return, we see that the red curve fits very poorly. There seems to be several separate trends in the data, and the blue shades indicate that the trends belong to different periods in time. But more research into the company's financial history would be needed to uncover the reason for this, perhaps it is because of significantly different sales-growth, profit margins, etc." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plot_ann_returns(ticker=ticker_WMT, df=df_WMT, key=PSALES,\n", + " min_years=7, max_years=15, use_colors=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Conclusion\n", + "\n", + "We have shown that the P/Sales ratio is a very strong predictor for the long-term returns of the S&P 500 index and some individual stocks.\n", + "\n", + "In the [previous paper](https://github.com/Hvass-Labs/FinanceOps/blob/master/01_Forecasting_Long-Term_Stock_Returns.ipynb) we considered fixed investment periods of e.g. 10 years, which meant that the investment return depended on the P/Sales ratio both at the time of buying and selling. This distorted the data because sometimes the stock-market would be in a bubble or crash 10 years later.\n", + "\n", + "In this paper we presented a simple solution by considering all investment periods between 7 and 15 years, and then using the average return instead. This averages out the distorting effects of future bubbles and crashes, so we get much more smooth data that only depends on the P/Sales ratio at the buy-time.\n", + "\n", + "We then fitted a reciprocal \"return curve\" to the scatter-plots, and although it generally had a very tight fit, it was not so accurate towards the end-points, thus suggesting that the reciprocal formula is not entirely correct for this data. It would be of great interest to not only find a mathematical model that fits better, but also a theoretical explanation why that model makes sense. Perhaps such a model would also allow us to use smaller amounts of data and take into account the changing economics of a business. Perhaps we could use such a model to forecast returns of more companies where the basic method does not work so well, such as Wal-Mart as demonstrated above.\n", + "\n", + "It should be stressed that the forecasted returns will also depend on a *qualitative* assessment of the company. If the company's future will be significantly different from its historical sales, profit-margins and growth, then the forecasted returns will be inaccurate. That is why this forecasting method is perhaps best used on broad stock-market indices such as the S&P 500, or companies whose products and markets are expected to be highly predictable long into the future." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Research Ideas\n", + "\n", + "You are strongly encouraged to do more research on this topic. If you make any new discoveries then please let me know your results. \n", + "\n", + "To my knowledge, there are no academic studies of predicting the long-term returns of stocks and stock-markets as we have done here. This work has presented the basic idea and methodology, but a lot more research can be done on this subject and it may impact many areas of both theoretical and applied finance.\n", + "\n", + "Here are a few more research ideas to get you started, in addition to the ideas from the [previous paper](https://github.com/Hvass-Labs/FinanceOps/blob/master/01_Forecasting_Long-Term_Stock_Returns.ipynb):\n", + "\n", + "- Try other investment periods, for example 5 to 10 years. How does it change the scatter-plots and the fitted \"return curves\"?\n", + "- Try using P/Book as the predictor signal. How does that affect the plots? Why?\n", + "- Although the data in some of these scatter-plots is incredibly smooth, the reciprocal curve does not fit the data exactly, which suggests that it is the wrong formula for this data. Can you find a better formula and perhaps give a theoretical explanation why that is better?\n", + "- What is the reason that some companies such as Wal-Mart have several different trend-lines in the scatter-plot? You will probably need to investigate the historical financial data to uncover the reason. Can you modify the forecasting method to somehow take this into account?" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## License (MIT)\n", + "\n", + "Copyright (c) 2015-18 by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n", + "\n", + "Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:\n", + "\n", + "The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.\n", + "\n", + "THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE." + ] + } + ], + "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": "3.6.6" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/README.md b/README.md index b82260c..cc7da1b 100644 --- a/README.md +++ b/README.md @@ -15,8 +15,13 @@ modified and run again. ## Papers 1. Forecasting Long-Term Stock Returns ([Notebook](https://github.com/Hvass-Labs/FinanceOps/blob/master/01_Forecasting_Long-Term_Stock_Returns.ipynb)) ([Google Colab](https://colab.research.google.com/github/Hvass-Labs/FinanceOps/blob/master/01_Forecasting_Long-Term_Stock_Returns.ipynb)) + +1-B. Better Long-Term Stock Forecasts ([Notebook](https://github.com/Hvass-Labs/FinanceOps/blob/master/01B_Better_Long-Term_Stock_Forecasts.ipynb)) ([Google Colab](https://colab.research.google.com/github/Hvass-Labs/FinanceOps/blob/master/01B_Better_Long-Term_Stock_Forecasts.ipynb)) + 2. Comparing Stock Indices ([Notebook](https://github.com/Hvass-Labs/FinanceOps/blob/master/02_Comparing_Stock_Indices.ipynb)) ([Google Colab](https://colab.research.google.com/github/Hvass-Labs/FinanceOps/blob/master/02_Comparing_Stock_Indices.ipynb)) + 3. Portfolio Optimization Using Signals ([Notebook](https://github.com/Hvass-Labs/FinanceOps/blob/master/03_Portfolio_Optimization_Using_Signals.ipynb)) ([Google Colab](https://colab.research.google.com/github/Hvass-Labs/FinanceOps/blob/master/03_Portfolio_Optimization_Using_Signals.ipynb)) + 4. Multi-Objective Portfolio Optimization ([Notebook](https://github.com/Hvass-Labs/FinanceOps/blob/master/04_Multi-Objective_Portfolio_Optimization.ipynb)) ([Google Colab](https://colab.research.google.com/github/Hvass-Labs/FinanceOps/blob/master/04_Multi-Objective_Portfolio_Optimization.ipynb)) diff --git a/returns.py b/returns.py index eb8a4d9..6fbd7b3 100644 --- a/returns.py +++ b/returns.py @@ -14,6 +14,7 @@ # ######################################################################## +import numpy as np import pandas as pd from data_keys import * @@ -145,6 +146,89 @@ def prepare_ann_returns(df, years, key=PSALES, subtract=None): return x, y +def prepare_mean_ann_returns(df, min_years=7, max_years=15, + key=PSALES): + """ + Prepare mean annualized returns e.g. for making a scatter-plot. + The x-axis is given by the key (e.g. PSALES) and the y-axis + would be the mean annualized returns. + + For each day we calculate the annualized returns for a whole + range of periods between e.g. 7 and 15 years into the future, + then we take the mean of all those annualized returns. This + smoothens the effect of random mispricing at the time of sale, + so it is more obvious if there is a relationship between the + predictive signal and future returns. + + :param df: + Pandas DataFrame with columns named key and TOTAL_RETURN + both assumed to have daily interpolated data. + :param min_years: + Min number of years for return periods. + :param max_years: + Max number of years for return periods. + :param key: + Name of the data-column for x-axis e.g. PSALES or PBOOK. + :return: + (x, y) Pandas Series with key and mean ANN_RETURN_MEAN. + """ + + # The idea of this algorithm is to step through the data + # one day at a time. For each day we lookup an array of + # Total Return values in the future and calculate the + # annualized returns, and then take the mean of that. + # There is probably a faster and more clever way of + # implementing this, but it is fast enough for our purpose. + + # Min / max number of days for the periods we consider. + # For example, between 7 and 15 years into the future. + min_days = int(min_years * 365.25) + max_days = int(max_years * 365.25) + + # Exponent used for calculating annualized returns. + # Again assuming the Total Return has daily data. + exponent = 365.25 / np.arange(min_days, max_days) + + # Select the data-columns we need. + df2 = df[[TOTAL_RETURN, key]] + + # Drop all rows with NA. + # Note: This gives a strange error if we use inplace=True + df2 = df2.dropna(axis=0, how='any') + + # Get the Total Return series. + tot_ret = df2[TOTAL_RETURN].values + + # We will calculate mean ann. returns for this number of days. + # We assume that the Total Return has values for all days. + num_days = len(tot_ret) - max_days + + # Pre-allocate array for the mean ann. returns for each day. + mean_ann_rets = np.zeros(num_days, dtype=np.float) + + # For each day. + for i in range(num_days): + # Get the Total Return value for the i'th day. + tot_ret_today = tot_ret[i] + + # Get array of Total Return values for future days. + tot_ret_future = tot_ret[i + min_days:i + max_days] + + # Annualized Returns between today and those future days. + ann_rets = (tot_ret_future / tot_ret_today) ** exponent - 1.0 + + # Mean annualized returns. + mean_ann_rets[i] = np.mean(ann_rets) + + # The predictive signal e.g. P/Sales. + x = df2[key][0:num_days] + + # The mean annualized returns. + y = mean_ann_rets + + return x, y + + def bond_annualized_returns(df, num_years): """ Calculate the annualized returns from investing and reinvesting in a bond.