The Federal Reserve adjusts interest rates up or down, which impacts bond yields including short-term bonds. However, long-term yields might not be as impacted because many other factors impact long-term yields including inflation and economic growth expectations. As a result, the expectations theory doesn't take into account the outside forces and fundamental macroeconomic factors that drive interest rates and ultimately bond yields.
The yields on short-term bonds are more volatile than long-term bonds. The yields on long-term bonds tend to be higher than short-term bonds.
The expectations hypothesis has been advanced to explain the 1st 2 characteristics and the premium liquidity theory have been advanced to explain the last characteristic. The market segmentation theory explains the yield curve in terms of supply and demand within the individual segments.
Market Segmentation Theory Because bonds and other debt instruments have set maturities, buyers and sellers of debt usually have preferred maturities. Bond buyers want maturities that will coincide with their liabilities or when they want the money, while bond issuers want maturities that will coincide with expected income streams. Market Segmentation Theory MST posits that the yield curve is determined by supply and demand for debt instruments of different maturities.
Generally, the debt market is divided into 3 major categories in regard to maturities: short-term, intermediate-term, and long-term. The difference in the supply and demand in each market segment causes the difference in bond prices, and therefore, yields. There are many different factors that would cause differences in the supply and demand for bonds of a certain maturity, but much of that difference will depend on current interest rates and expected future interest rates.
If current interest rates are high, then future rates will be expected to decline, thus increasing the demand for long-term bonds by investors who want to lock in high rates while decreasing the supply, since bond issuers do not want to be locked into high rates.
Therefore, long-term interest rates will be lower than short-term rates. On the other hand, if current interest rates are low, then bond buyers will tend to avoid long-term bonds so that they are not locked into low rates, especially since bond prices will decline when interest rates rise, which will generally happen if interest rates are already low.
On the other hand, borrowers generally want to lock in low rates, so the supply for long-term bonds will increase. Hence, a lower demand and a higher supply will cause long-term bond prices to fall, thereby increasing their yield.
Preferred Habitat Theory Preferred Habitat Theory PHT is an extension of the market segmentation theory, in that it posits that lenders and borrowers will seek different maturities other than their preferred or usual maturities their usual habitat if the yield differential is favorable enough to them. For instance, if short-term rates are a lot lower than long-term rates, then bond issuers will issue more short-term bonds to take advantage of the lower rates even though they would prefer longer maturities to match their expected income streams; likewise, lenders will tend to buy long-term debt if the yield advantage is significant, even though carrying long-term debt has increased risks.
Expectations Hypothesis There are several versions of the expectations hypothesis, but essentially, the expectations hypothesis aka Pure Expectation Theory, Unbiased Expectations Theory states that different term bonds can be viewed as a series of 1-period bonds, with yields of each period bond equal to the expected short-term interest rate for that period.
For example, compare buying a 2-year bond with buying 2 1-year bonds sequentially. Hence, the sequential 1-year bonds are equivalent to the 2-year bond. Actually, the geometric mean gives a slightly more accurate result, but the average is simpler to calculate and the argument is the same. Note that this relationship must hold in general, for if the sequential 1-year bonds yielded more or less than the equivalent long-term bond, then bond buyers would buy either one or the other, and there would be no market for the lesser yielding alternative.
For instance, suppose the 2-year bond paid only 4. In the 1st year, the buyer of the 2-year bond would make more money than the 1st year bond, but he would lose more money in the 2nd year—earning only 4. Additionally, the price of the 2-year bond would decline in the secondary market, since bond prices move opposite to interest rates, so selling the bond before maturity would only decrease the bond's return.
Note, however, that expected future interest rates are just that — expected. There is no reason to believe that they will be the actual rates, especially for extended forecasts, but, nonetheless, the expected rates still influence present rates.
According to the expectations hypothesis, if future interest rates are expected to rise, then the yield curve slopes upward, with longer term bonds paying higher yields. Given the relative immaturity of financial markets in emerging economies, it is noteworthy that the null hypothesis of no cointegration is rejected in four of our six emerging economies.
Only India and South Africa fail the test, with structural change the likely reason in both cases. In , the Reserve Bank of India adopted a multiple-indicator approach, a departure from earlier monetary policy that appeared to foster a permanent reduction in long and short interest rates.
The relatively long sample available for South Africa clearly makes structural breaks a potential problem. Following the end of apartheid in the early s, international interest in South Africa resumed, accompanied by strong inflows of foreign financial capital, and like several other countries, South Africa adopted inflation targeting in early , with a concomitant reduction in long interest rates. An important feature of Table 2 is that the critical values of the Bonferroni EG test are to the left of the standard unit-root EG critical value, once uncertainty regarding the exact value of the largest autoregressive root in the data has been taken into account.
This adjustment of critical values is crucial, as it is key to valid inference when variables do not have exact unit roots. Failing to make this adjustment tends to make traditional tests of cointegration over-sized. As seen here, the standard EG cointegration test, based on the unit-root assumption, and the robust Bonferroni test lead to similar conclusions. However, the Bonferroni test, which is correctly sized under more general conditions than the standard test, gives us greater confidence in rejections of the null hypothesis of no cointegration.
That is, by performing inference with the Bonferroni test, one no longer needs to condition on the auxiliary assumption that the data were generated by a pure unit-root process when interpreting the cointegration results. The evidence in favour of cointegration is valid also if the data were generated by a weakly mean-reverting process.
As mentioned in the introduction, researchers have typically overlooked interpretation of the estimated vector, either because of a lack of suitable econometric tools in the case of earlier research, or because it has not been the focus. With the methods developed in this paper, we are able to conduct valid inference about the parameter values.
Our focus is the 90 percent confidence interval for ; if this does not cover unity, the null hypothesis of is rejected, which is equivalent to rejecting the cointegrating vector 1, Confidence intervals are also shown. As discussed in Section 2. Both methods lead to qualitatively similar results, and it is evident that the size adjustment is not crucial in this particular application. For all ten countries in which cointegration was detected using the Bonferroni EG test, the cointegrating vector differs significantly from the values predicted by theory.
That is, despite the presence of cointegration, the expectations hypothesis is rejected as a description of the term structure. Interestingly, the values are similar across countries, with significantly smaller than one and clustered between and. The confidence intervals also overlap substantially. The finding of a slope coefficient less than one is not unique to this paper; for example, Engle and Granger , Boothe and MacDonald and Speight report similar coefficients using data from different countries and sample periods.
Unlike previous studies, however, we have the tools to reliably conclude that the deviations from the theoretically-implied relationship are statistically significant. Rather than an outright rejection of the expectations hypothesis, it suggests that something more is at work. Understanding the Adaptive Expectations Hypothesis Adaptive expectations hypothesis suggests that investors will adjust their expectations of future behavior based on recent past behavior.
If the market has been trending downward, people will likely expect it to continue to trend that way because that is what it has been doing in the recent past. The tendency to think this way can be harmful as it can cause people to lose sight of the larger, long-term trend and focus instead on recent activity and the expectation that it will continue. In reality, many items are mean reverting.Rather than an outright rejection of the expectations hypothesis, it suggests that something more is at work. This hypothesis, where prior beliefs are updated as new information arrives is an example of Bayesian updating. One candidate for this additional component is a time-varying but persistent risk premium linked to the state of the term structure. In terms of practical implementation, we obtain a confidence interval for by inverting the ADF-GLS unit-root test statistic, and use the Newey-West estimator to calculate all long-run variances and covariances. Indeed, during recessions, the yield spread between Treasuries and corporate bonds increases, because of the increased credit risk during recessions, as can be seen in the graph below.
Actually, the geometric mean gives a slightly more accurate result, but the average is simpler to calculate and the argument is the same.
That is, despite the presence of cointegration, the expectations hypothesis is rejected as a description of the term structure. Dai and Singleton go further, showing that yield-spread regressions using risk-premium adjusted yields from a broad class of affine term structure models recover expectations-hypothesis predicted coefficients. Denote the ten-year zero-coupon yield as and for the United Kingdom and United States respectively - as the long interest rate.
Another limitation of the theory is that many factors impact short-term and long-term bond yields. Understanding the Adaptive Expectations Hypothesis Adaptive expectations hypothesis suggests that investors will adjust their expectations of future behavior based on recent past behavior.
In other words, if investors are going to hold onto a long-term bond, they want to be compensated with a higher yield to justify the risk of holding the investment until maturity. Disadvantages of Expectations Theory Investors should be aware that the expectations theory is not always a reliable tool. The types of yield curve shifts that regularly occur include parallel shifts, flattening shifts, twisted shifts, and shifts with humpedness. In reality, many items are mean reverting.
However, sometimes the yield curve becomes inverted, with short-term notes and bonds having higher yields than long-term bonds. Treasuries, zero-coupon bonds, par value, euro securities, swaps, forward rates, and there are even curves for specific credit ratings, such as the BBB rated curve, and so on. However, the expectations hypothesis does not explain why the yields on long-term bonds are usually higher than short-term bonds. These choices must be made for each browser that you use.
Most researchers would - rightly so - be reluctant to use traditional cointegration analysis after having detected evidence of stationarity. With the methods developed in this paper, we are able to conduct valid inference about the parameter values. Note that these yield curves are schematic: actual curves will be more wavy and tortuous in their details. For the United Kingdom and the United States, we are able to check whether our choice materially affects our conclusions by performing our analysis on synthetic constant-maturity yields provided by the respective central banks. Preferred Habitat Theory Preferred Habitat Theory PHT is an extension of the market segmentation theory, in that it posits that lenders and borrowers will seek different maturities other than their preferred or usual maturities their usual habitat if the yield differential is favorable enough to them.
Sometimes, the yield curve may even be flat, where the yield is the same regardless of the maturity. The benefits of the Bonferroni EG test are evident in these cases. Note that these yield curves are schematic: actual curves will be more wavy and tortuous in their details. For example, compare buying a 2-year bond with buying 2 1-year bonds sequentially.
Failing to make this adjustment tends to make traditional tests of cointegration over-sized. The econometric framework is robust to deviations from the unit-root hypothesis by nesting the high-persistence and unit-root cases. Additionally, illiquid assets are more difficult to price, since previous sale prices may be stale or nonexistent. Note that opt-out choices are also stored in cookies.
To see how this explanation fits into the present application, consider a generalisation of equation 2 that retains the basic structure of the expectations hypothesis but generalises the term premium: 15 , is the sum of two components, the stationary component posited earlier, , plus a new component, , that is near-integrated and covaries with the short interest rate.