Long-Term Patterns and Market Timing for Interest Rates and Stocks

By: Murray A. Ruggiero

The following is an excerpt from Murray A. Ruggiero's Cybernetic Trading Strategies

This article will show you how to use fundamental data to predict long-term trends in both interest rates and stock prices.

This type of long-term analysis is very important for people who switch mutual funds, as well as anyone with a variable rate loan. It is also important for short-term traders because many systems are based on buying pullbacks in long-term uptrends of both stocks and bonds, which started during the early 1980s. When these bull markets end, these systems will stop working – with disastrous results.

INFLATION AND INTEREST RATES

It is commonly known that interest rates are positively correlated to inflation. As inflation rises, so do interest rates. In general, this relationship is true, but it is not constant. We will examine this relationship using 3-month T-Bill yields and yields on the longest government bond. We will compare these yields to the 1-year inflation rate, calculated by taking a 12-month percentage change in the Customer Price Index (CPI). These data, as well as the other fundamental data used in this article, were supplied by Pinnacle Data Corporation and are part of their index database.

To study the relationship between T-bill yields and inflation, we researched monthly data going back to 1943. Most major increases in short- term occur when the inflation rate is a negative real rate – that is, it is greater that the T-bill yield. It last happened in 1993, just before the start of a severe bear market in bonds. In general, rising premiums on T-bills lead to lower rates, and falling premiums lead to higher rates. We studied many different ways of comparing inflation to interest rates and have found that one of the best methods is to use a ratio of interest rates to inflation. During the past 53 tears, on average, T-Bill yields have been about twice the average inflation rate.

The relationship between long-term interest rates and inflation is not as reliable as the one between short-term interest rates and inflation. In general, the spread between inflation and long-term interest rates is between 300-400 basis points. Currently, it is about 380 basis points or 3.80 points as of early April 1996. The ratio between long-term interest rates and inflation is currently about 250 percent; for example, a 3 percent inflation rate would relate to a 7.5 percent long term bond. This relationship is varied over the years. Long-term rates were kept artificially low during the mid-1970s. On January 31, 1975, long-term rates were at 5.05 percent, which was only about half of the actual inflation rate. Another example occurred during the early 1960s, when inflation was under 2 percent and long-term bond rates were about 4 percent. This was only a 2.00 point difference, but the ratio of long-term interest rates to inflation has ranged from 220 percent to 260 percent. This type for premium is common during long periods of economic growth with low inflation. This concept is very important because it means that a 1 percent increase in inflation can produce a 2.5 percent increase in long-term interest.

In May 1996, the Treasury Department discussed issuing a bond that yields a fixed number of basis points over the rate of inflation. This would be a smart move because it would because it would reduce the cost of borrowing over the next few years. During the early 1990s, the Treasury moved its own borrowing to the short end of the yield curve just before short-term rates dropped to a low of 3 percent, when it looked as though short-term rates were going to start to rise, the Treasury the issuing of an inflation-based bond.

This type of bond would save the treasury money during periods of long-term growth and moderate inflation. During these periods, the premium between interest rates and inflation can be expected to remain over 200 percent. For example, suppose the inflation rate rises to 4.0 percent from its current 2.8 percent. On an inflation bond purchased at a 400-basis-point- premium, the yield would rise from 6.8 percent to 8.0 percent. Our research has shown that during moderate increases in inflation, long-term rates can retain over 200 percent premium to inflation. In 1996, the ratio was 243 percent. Based on my model of long-term yields to inflation, the long-term bond yield would increase from 6.8 percent to 9.72 percent. Under these conditions, this new inflation bond, issued in January 1997, would save the government 1.72 percent in interest per year.

PREDICTING INTREST RATES USING INFLATION

Let’s now use the interaction between inflation and short-term interest rates to develop a long term 3-month T-Bill yield model. Inflation became a better measure of interest rates after 1971, when the U.S. government allowed the price of gold to float and dropped the gold standard to back the U.S. dollar. Table 3.1 shows how inflation can be used to model short-term interest rates.

This is a very robust model for short-term interest rates since the United States abandoned the gold standard in 1971. The results from January 1, 1971, to April 1, 1996, are shown in table 3.2

Even more amazing, the average correct signal lasts 24 months and the average wrong signal only lasts about 2 months. This model has not produced a losing signal since January 31, 1986.

This is a good model to longer-term interest rates. The effect of inflation on longer-term rates is not as strong as it is on shorter-term rates. Using the same general model with different trigger levels, we can predict longer-term rates using inflation, but not as well as shorter-term rates. The results as well as our new model, for the period from 1/1/71 to 4/1/96, are shown in Table 3.3.

FUNDAMENTAL ECONOMIC DATA FOR PERDICTING INTREST RATES

Given this interaction between interest rates and inflation, how many other fundamental factors affect both long-term and short-term rates? Using data supplied by Pinnacle Data Corporation, let’s see how various fundamental factors can be used to predict interest rates. We will use money supply, consumer confidence, and unemployment data to build out models.

We start by showing how changes in the money supply affect interest rates. We use three standard measures of money supply:

M1= money stored as cash and in checking accounts.

M2= M1 plus money stored in time deposits, such as CDs.

M3= M2 plus assets and liabilities of financial institutions, which can be easily converted into spendable forms.

In general, the greater the amount of money in the system, the more the economy will grow. This growth translates into higher interest rates.

Let’s now develop a simple model using the monthly change in M2. When M2 is in an uptrend and rates have begun to increase, then the rates will continue to increase. If M2 is in a downtrend and rates have begun to fall, then rates will continue to drop. Using the same period as earlier---January 1971 to April 1, 1996---we can develop a short-term interest rate model based on M2. Our rules are as follows:

1. If M2Chg>M2Chg [6] and 90-day Yields > 90-day Yields 11 months ago, then 90 day interest rates will rise.
2. If M2Chg<M2Chg [6] and 90-day Yields < 90-day Yields 11 months ago, then 90 day interest rates will fall.

The results of this simple system since 1971 are shown in Table 3.4

This model has produced about 100 basis points per year for the past 26 years. The average trade is about 23 months. The last signal this system gave was in October 1995, when it predicted a drop in short-term interest rates.

Money supply is highly predictive of short-term interest rates but not a predictive of long-term interest rates. Using the same basic model with different parameters did not produce results as good as those when predicting short-term rates. Current M2Chg was compared with the reading 16 bars before, and current yields were compared with those three months before. The model did a fair job of predicting long-term rates. For example, it produced 17.44 points since 1970 and was 65 percent accurate on 26 trades. The draw down was only 1.64 points, and the average trade was .67 points. These are good results but not as good as for the prediction of shorter-term rates.

With this background in money supply and inflation, we can now discuss how some other measures of economic activity can be used to predict interest rates. Let’s start by using consumer sentiment to predict short-term rates. Our model is based on the fact that if consumers are positive, then growth will increase and, consequently, interest rates will rise.

Our model compares consumer sentiment and T-Bill yields between a given number of bars. The rules are:

1. If CSenti > CSenti [12] and CSenti > CSenti [11] and Yields > Yields [4], then rates will rise.
2. If CSenti < CSenti [12] and CSenti < CSenti [11] and Yields < Yields [4], then rates will fall.                         

Table 3.5 shows us the results of this model during the period from 4/30/56 to 4/1/96.

Using consumer sentiment to predict short-term interest rates, the average winning position is 20 months and the average losing position is 12 months. The model predicted that rates would start to fall on May 31, 1995, when 3-month rates were at 5.72 percent. As of March 31, 1996, this position is profitable by .73 points

Let’s now look at how unemployment information---specifically, the average duration of someone’s unemployment---can help to predict short-term interest rates. The theory is that the longer someone is without a job, the slower the economy will be, and interest rates will drop in order to stimulate the economy.

Our simple model is based on unemployment duration as a factor in predicting 90-day T-Bill rates. The rules are:

1. If NoJobDur < NoJobDur [3] and Yields > Yields [6], then interest rates will rise.
2. If NoJobDur > NoJobDur [3] and Yields < Yields [6], then interest rates will fall.

For the period from 4/30/52 to 3/30/96, this simple model produced the results shown in Table 3.6.

This model does not work as well as some of our other models, but it does show that the unemployment duration is predictive of short-term interest rates.

How can we use unemployment claims to predict short-term interest rates? Our system for timing short-term rates is based on unemployment claims. The rules are:

1. If Claims < Claims [11] and Claims > Claims [14], then interest rates will rise
2. If Claims > Claims [11] and Claims < Claims [14], then interest rates will fall. 

This simple model was tested on T-Bill yields in the period from 1/31/52 to 3/31/96 and produced the results shown in Table 3.7

This simple model does a great job of predicting short-term interest rates. Its last trade was predicting a drop in rates on July 31, 1995. On long-term interest rates, the same model produces 18.20 points and wins 67 percent of its trades, with an average trade profit of .61 point. It is profitable on both long and short moves. Even though this model did not perform as well as it did on short-term rates, it still shows that unemployment claims are predictive of interest rates.

Research showed that, when using fundamental-type data, it was easier to predict short-term (rather than long-term) interest rates on a weekly to monthly basis. I think  the reason for this is that short-term interest rates are based on current economic activity, and longer-term rates are also affected by the perceived effects of future activity.

A FUNDAMENTAL STOCK MARKET TIMING MODEL

We have seen how fundamental data can predict interest rates. Let’s now see how we can use it to predict the Dow Jones Industrial Average (DIJA)

We need a model that combines the prime rate, the Federal Reserve (Fed) discount rate, and long bond yields. Out model is inspired by Martin Zweig’s book, Winning on Wall Street. Zweig discusses how a cut in the prime rate is bullish for stocks as long as the prime is below a given level.

Another important factor is Fed discount rate. When the last move in the Fed discount rate is a cut, that is very bullish for stocks. During the past 50 years, there have been several false moves in the prime rate. The number of false moves drops to almost zero when the change in the prime is in the direction of the last fed move in the discount rate.

The prime rate and discount rate have a strong effect on stock prices, but so do long-term interest rates. Often, the market will lower rates before the Fed or the banks make a move. For example, during 1995, the stock market rallied because of a drop in long-term interest rates. This drop occurred months before the Fed cut rates, which led to a drop in the prime rate. An ideal interest rate stock timing model would combine all three of these factors. We developed a model that used all of these concepts but only traded the market on the long side. This model was tested for the period from 8/11/44 to 4/12/96, using weekly data. During this time, the DJIA rose about 5,490 points in about 2,640 weeks, or a little over 2 points per week. The rules for our model and the results for our test period are shown in Table 3.8.

This long-term model is an incredible tool for asset allocation. It performed as well as buy and hold while being exposed to the market only 50% of the time.