Investing

1st July
2009
written by simplelight

It’s a pity that Yahoo is still maintaining the 5000 query limit per IP address. 5000 stock quotes is the equivalent of 10 years of daily data for two companies only.

18th June
2009
written by simplelight
Returns by Asset Class 1997 - 2006

Returns by Asset Class 1997 - 2006

It’s hard to look at this chart and not conclude that picking asset classes is difficult and that relative returns are not durable over time. Also, unsurprisingly, correlations between asset class returns are fairly high.

1st February
2009
written by simplelight
Many people have pointed out that stocks all become perfectly correlated in times of crisis. That’s not strictly true but correlations do increase dramatically. Over the past six months (August 4th, 2008 to January 30th, 2009) notice how correlations (for a portfolio containing a selection of the Dow components) have averaged 0.67 and volatility across the portfolio has been 3.1% for the daily return standard deviation.
 
    BAC GE IBM INTC JNJ KO MCD MMM MRK MSFT PFE PG T WMT Return StdDev
Bk Of America Cp BAC                             -95.8% 9.8%
Gen Electric Co GE 0.63                           -80.9% 4.8%
Intl Business Mac IBM 0.66 0.68                         -48.1% 3.0%
Intel Corporation INTC 0.57 0.64 0.74                       -66.9% 4.1%
Johnson And Johns JNJ 0.50 0.58 0.67 0.69                     -28.4% 2.5%
Coca Cola Co The KO 0.39 0.45 0.56 0.66 0.72                   -35.8% 2.8%
Mcdonalds Cp MCD 0.54 0.62 0.66 0.66 0.69 0.66                 -5.5% 2.7%
3 M Company MMM 0.56 0.66 0.68 0.68 0.77 0.66 0.75               -39.3% 3.0%
Merck Co Inc MRK 0.55 0.62 0.71 0.75 0.80 0.66 0.73 0.72             -23.6% 3.5%
Microsoft Corpora MSFT 0.58 0.55 0.75 0.80 0.72 0.68 0.68 0.68 0.73           -54.0% 4.0%
Pfizer Inc PFE 0.61 0.60 0.66 0.70 0.76 0.64 0.67 0.71 0.80 0.70         -37.5% 3.2%
Procter Gamble PG 0.53 0.62 0.68 0.69 0.84 0.70 0.73 0.78 0.82 0.72 0.77       -30.1% 2.6%
At&T Inc. T 0.60 0.57 0.72 0.72 0.77 0.64 0.69 0.69 0.79 0.75 0.75 0.76     -29.7% 3.6%
Wal Mart Stores WMT 0.44 0.51 0.57 0.57 0.75 0.61 0.72 0.66 0.71 0.61 0.64 0.73 0.66   -34.4% 2.7%
Exxon Mobil Cp XOM 0.49 0.56 0.71 0.72 0.81 0.64 0.71 0.72 0.78 0.76 0.76 0.78 0.81 0.67 1.9% 4.3%
Portfolio -44.6% 3.1%

Historically, the same portfolio has exhibited correlations between the various components which have been considerably lower. In fact, over the past twenty years (February 2nd, 1989 to Jan 30th, 2009), correlations have averaged 0.32, approximately half the correlation we have seen recently. The standard deviation of the daily returns was only 1.1%

 
  BAC GE IBM INTC JNJ KO MCD MMM MRK MSFT PFE PG T WMT Return StdDev
Bk Of America Cp BAC                             3.2% 2.5%
Gen Electric Co GE 0.49                           8.4% 1.8%
Intl Business Mac IBM 0.31 0.41                         7.3% 1.9%
Intel Corporation INTC 0.31 0.40 0.45                       15.4% 2.7%
Johnson And Johns JNJ 0.27 0.39 0.23 0.22                     14.5% 1.5%
Coca Cola Co The KO 0.28 0.38 0.21 0.22 0.41                   12.4% 1.6%
Mcdonalds Cp MCD 0.27 0.36 0.24 0.22 0.30 0.34                 12.9% 1.7%
3 M Company MMM 0.35 0.45 0.28 0.29 0.31 0.34 0.28               9.1% 1.5%
Merck Co Inc MRK 0.27 0.36 0.23 0.22 0.51 0.35 0.26 0.28             8.2% 1.9%
Microsoft Corpora MSFT 0.31 0.41 0.41 0.55 0.28 0.27 0.23 0.26 0.26           21.5% 2.3%
Pfizer Inc PFE 0.30 0.40 0.25 0.23 0.52 0.35 0.27 0.29 0.54 0.29         12.0% 1.8%
Procter Gamble PG 0.27 0.37 0.19 0.20 0.41 0.43 0.33 0.34 0.35 0.21 0.36       14.3% 1.6%
At&T Inc. T 0.32 0.37 0.26 0.25 0.32 0.32 0.27 0.29 0.29 0.28 0.29 0.30     8.4% 1.8%
Wal Mart Stores WMT 0.32 0.45 0.29 0.30 0.34 0.36 0.32 0.35 0.31 0.33 0.33 0.34 0.32   13.8% 1.8%
Exxon Mobil Cp XOM 0.29 0.37 0.26 0.24 0.33 0.34 0.25 0.37 0.31 0.28 0.32 0.27 0.35 0.29 13.5% 1.5%
Portfolio 13.2% 1.1%

 All these results were created using the tools at AssetCorrelation.com

15th January
2009
written by simplelight

Stats from Howard Marks’ letter to Oaktree clients:

  • Consumer credit outstanding grew 260 times from 1947 to 2008 (4% of GDP to 18%)
  • Bank indebtedness: 21% of GDP in 1980, 116% in 2007
  • Federal debt: $1 trillion in 1980, $11 trillion in 2008
  • State debt: $1.2 trillion in 2000, $1.85 trillion on 2005 (9.2% CAGR)
  • Solvency became contingent on the continuous availability of credit
  • An upward sloping yield curve promotes short term borrowing to cover investing long.

Question: how should one invest in 2009? A global reflation seems the most likely path. Does the US have any option other than inflating its way out of its troubles…

19th November
2008
written by simplelight

Volatility is usually expressed as the annualized standard deviation of returns. Volatility is proportional to the square root of time. That means one can approximate a volatility over a smaller time period than one year by dividing the annual vol by the square root of the number of trading periods one is interested in.

So, to convert annual volatility to a daily vol, divide by 16, which is the square root of 256 — about the number of trading days in the year. This paper on converting 1-day to h-day volatility contains some important caveats. (Summary: Modeling volatility only at one short horizon, followed by scaling to convert to longer horizons, is likely to be inappropriate and misleading, because temporal aggregation should reduce volatility fluctuations, whereas scaling amplifies them.

Back in the days when vol was 15-20% annually (way back in 2007), a daily vol was about 1%. These days, the VIX is closer to 80 which implies a daily return of +- 5%.

On Sept 15th, 2008, when Lehman was allowed to go bankrupt (“Lehman is not too big to fail” – Paulson), the VIX went up to 80 and has been in that region ever since. The Lehman bankruptcy has turned out to be a massive event in financial history.

23rd September
2008
written by simplelight

Others have weighed in on whether volatility should be considered an asset class. From the point of view of a long term investor it clearly doesn’t make sense to buy and hold volatility. (In that sense, it is the ultimate cyclical asset class and we should be glad we don’t live in a world of ever increasing volatility!). However, in terms of the diversification benefit for a portfolio, the VIX does exhibit low (and negative) correlation with many of the major asset classes. The table below shows the correlation matrix for major asset classes over the past 750 days, a period during which the VIX had negative correlation with US stocks and real estate and no correlation with European stocks. Notice, though, that a similar diversification benefit could probably have been achieved with a combination of treasuries and bonds.

    TIP AGG GSG VNQ EEM EFA VB VV
Ishares Lehman Ti TIP                
Ishares Leh Agg F AGG 0.95              
Ishares Gsci Cmdt GSG 0.90 0.78            
Vanguard Sf Reit VNQ -0.78 -0.69 -0.69          
Ishares Msci E.M. EEM 0.56 0.68 0.52 -0.37        
Ishares Msci Eafe EFA -0.14 0.05 -0.14 0.25 0.70      
Vanguard Sm Cap E VB -0.54 -0.38 -0.47 0.63 0.25 0.75    
Vanguard Lg Cap E VV -0.32 -0.12 -0.32 0.39 0.56 0.94 0.89  
Cboe Volatility I ^VIX 0.78 0.81 0.60 -0.80 0.55 0.00 -0.39 -0.14

Note: this chart was generated on the AssetCorrelation website which is an excellent resource for monitoring the diversification of your own portfolio.

31st July
2008
written by simplelight

Until recently, the best way for individuals to gain exposure to commodities was through exchange-traded index funds such as IGE. Unfortunately, the exposure was indirect as you were essentially investing in the equity of companies that dealt in commodities. In the case of IGE, you were mostly holding the stocks of oil-companies. As of 2008, there are better commodity index funds, such as GSG (the Goldman Sachs Commodity Index) which gives you direct exposure to a broad array of commodities. Even better, GSG exhibits less correlation with almost every asset class when compared to IGE.

26th July
2008
written by simplelight

In very rough numbers (good enough for government work) for 2009:

US GDP: $15 trillion

Federal Government spends 20% = $3 trillion

Breakdown of the $3 trillion

  • 20% Defense
  • 20% Medicare/Medicaid
  • 20% Social Security
  • 10% Interest on Debt
  • 30% Everything else

The full budget (and historical trends) is available online. Despite the din, not much has changed. The inexorable rise of medicare / social security continues, though. Medicare and social security represented 20% of the federal budget in 1971. Today they represent 40% and growing…

14th July
2008
written by simplelight

I have to question the need for the wide variety of international country index funds. The AssetCorrelation website has an excellet correlation matrix which covers exchange-traded index funds from various countries around the world.

Take a careful look at the matrix for the various countries. Other than Brazil and Israel (with correlations of 0.73 and 0.35 respectively versus the S&P 500) the rest of the countries’ index funds are all tracking the S&P 500 with >0.90x correlation coefficients.

It might be that the time period is only 90 trading days (about 4 months) and this represents a time in the market which has seen a greater herd mentality than usual. Or it might be that global inflation fears do justify a simultaneous downward revision in global equity asset prices. Either way, lately it has been hard to see the benefits of international equity exposure. Even emerging markets like Turkey, Mexico and Chile have been strongly correlated recently. Inflation really is the great leveller.

19th June
2008
written by simplelight

There is a promising new website called Asset Correlation which shows the correlation matrix for a host of different asset classes over the past 90 trading days. I have been tracking it for a few months and it is amazing how all the asset classes exhibited far higher correlation during the recent panic. As normalcy has gradually returned to the markets it is interesting to see how the historical scenario of lower correlation between asset classes has returned. A few months ago almost all the cells in the matrix were green and correlations were hovering around 80-90% for most of the major classes. As of today, there is far lower correlation between the classes (indicated by the larger number of yellow and red cells). It will be interesting to keep an eye on this website over the next few months.

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