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Uncategorized » The Calculating Investor » Page 5

Inflation Expectations and the Breakeven Inflation Rate

Jan 242011

Extracting Inflation Expectations from Treasury and TIPS Yield Curves

Update (08/22/2012): I have posted a similar but simplified method for calculating the breakeven rate here.

What level of inflation do market participants expect over the next 5, 10, or even 30 years?   There are many methods of varying complexity that investors and policymakers use to estimate the level of expected inflation, but one relatively straightforward method is to examine the “breakeven” inflation rate which is the difference in interest rates between Treasuries and TIPS.  This method has the advantage of being determined by market prices, so it reflects the views of investors who have money on the line.

A simple example illustrating the 5-year breakeven inflation rate is shown here:

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Fama-French Factor Loadings for Popular ETFs

Jan 162011

How well can the small-value premium be captured using ETFs?

In a previous post, I plotted the returns of 25 portfolios which were formed by sorting stocks on both size and value characteristics.  The data, from the Kenneth French website, showed a clear pattern of increasing returns as size decreased and value (measured by book-to-market ratio) increased.  In other words, the small-value portfolio had outperformed the broader market over most periods of 20 years or more, and the margin of outperformance was often quite large. 

Fama and French, who built the size and value effects into an asset pricing model, believe that the higher returns of small stocks and value stocks are related to the higher risks associated with holding these stocks.  This may be true, and there is some persuasive evidence supporting the Fama-French viewpoint.  However, another issue with capturing the small-value premium is cost.  The returns of the Fama-French 25 portfolios do not include trading costs, fees, or taxes, and these costs are likely to be higher for investors who are trying to implement a small-value tilt in their personal portfolio.   

In this post, I will evaluate several ETFs which track popular indexes and calculate how well these funds capture the theoretical returns predicted by the Fama-French model.  In addition, I will place the factor loadings of these funds in the context of the Fama-French 25 portfolios.  For example, does a fund which is described as a “small-value” fund really behave similarly to the most extreme small-value portfolio from the Fama-French 25 portfolios?  If not, which of the portfolios does it approximate most closely? 

The Fama-French regression equation is shown here:

r_{i}-r_{f}=\alpha _{i}+b_{i}\left ( R_{M}-r_{f}^{} \right )+s_{i}SMB+h_{i}HML+\epsilon _{i}

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Where in the world is my money? – Version 1.0

Jan 102011

Displaying Country Weights for International ETFs in Google Earth

Google Earth is a great tool for looking at many different types of data.  A quick Google search will show hundreds of on-line Google Earth projects which use the tool to display data on everything from the health of marine ecosystems to the status of U.S. airline flights. 

I’ve put together a Python script to display the country weights for two international ETFs;   EFA is an iShares ETF which tracks the MSCI EAFE index, and VWO is a Vanguard ETF which tracks the MSCI Emerging Markets index.  I used red placemarks for EFA and blue for VWO.  In both cases, the area of the placemark is proportional to the country’s weight in the respective fund.  These weights vary over time with a country’s market cap, so each country weight shown is for a particular date (9/30/2010 for EFA and 11/30/2010 for VWO).

A screenshot of the European section of the map is shown here:

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Visualizing the Small Cap and Value Effects

Jan 052011

Over the years, investors and academics have noted that small market capitalization stocks and value stocks have tended to outperform the broader market.  This outperformance has been observed over long periods of time in both U.S. and international stock markets.

The plot below utilizes data on 25 portfolios formed by sorting stocks on both size (market capitalization) and value (book to market ratio) characteristics to illustrate the magnitude of these effects in the United States.  The historical return data used to generate these plots was compiled by Eugene Fama and Kenneth French, and the data is available at Kenneth French’s website.  The z-axis of the plot shows the geometric average of the monthly returns for each of these 25 portfolios over the past 78 years.

 

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Calculating Investment Returns

Jan 012011

Money Weighted Returns vs. Time Weighted Returns

What is the proper way to calculate investment returns?  Unfortunately, the answer is somewhat complicated.  The two most frequently used  methodologies are the “money-weighted” and “time-weighted” methods.  In addition, an approximation of the money-weighted method, known as the “Modified-Dietz” method, is also commonly used.  These three methods can sometimes give very different results.  The “correct” calculation method to use will depend on how you plan to use the results. 

My objective in this post is to compare the three common return measures: the money-weighted return, the time-weighted return, and the Modified-Dietz return.  I will provide examples of how these measures can differ and explain when each should be used.

Consider three investors, Larry, Moe, and Curly, who each contributed $1,000 at the end of each month in 2010 to an S&P500 index fund.  Larry’s starting account value at the beginning of 2010 was $1,000, Moe’s was $10,000, and Curly’s was $100,000.  The 2010 return of each investor, as calculated by each of the three methods, is shown here:

2010 ReturnsStarting BalanceMonthly ContributionEnding BalanceMoney Weighted ReturnTime Weighted ReturnModified Dietz Return
Larry$1,000$1,000$14,668.0426.51%15.05%25.56%
Moe$10,000$1,000$25,022.6819.69%15.05%19.47%
Curly$100,000$1,000$128,569.0215.72%15.05%15.70%

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Market Valuation

Dec 302010

What market return should we expect over the next 10 to 20 years?

Reviewing the Campbell-Shiller Data

What return should you expect to get on your stock market investments over the next 10 to 20 years?  According to data compiled by Yale University’s Robert Shiller, the average annual real return (i.e. after adjusting for the effects of inflation) on an S&P500-like portfolio over the past 139 years has been 8.2%.  The geometric average annual real return, which is a better indication of the real return realized by a buy and hold investor, was 6.6%.  You might think that these numbers would provide a reasonable estimate of future market returns.  However, all stock market eras are not created equal.  In fact, if we look at the cyclically-adjusted price-earnings (CAPE) ratio and the subsequent 10 or 20 year market return, we can see that times of high market valuation (high CAPE ratio) have been followed by periods of low market returns, and periods of low market valuation (low CAPE ratio) have been followed by periods of high returns.  This relationship is clear in the graphs below. 

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Introduction

Dec 222010

What is this blog all about?

I am an investment junkie.  I have spent years learning as much as I can about investing through both formal education (I have an MBA with a concentration in Analytical Finance) and my own reading and research.  Unfortunately, I haven’t discovered any methods for getting rich quick.  In fact, I haven’t discovered any method for beating the market average by even a modest amount which doesn’t require taking on some additional risk.  (Is anyone still reading?) Instead, I’ve become convinced that a low-cost, index-fund-based approach is the best choice for nearly all investors. 

This may sound like a disappointing conclusion.  Is it a waste of time and money to spend time studying your investment options?  Should all investors simply put all their money in a Wilshire 5000 index fund?  Are even the most motivated and intelligent investors destined to average investment performance? Continue reading »

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