58 - Portfolio management II

The aim of this paper is twofold; first we concentrate on the work of Vasicek (1977) and Cox, Ingersoll and Ross (1985). We examine and test empirically each model and discuss its performance in predicting the term structure of interest rates using a parametric estimating approach GMM (Generalized Moments Method). Second we estimate the term structure of interest rate dynamics using a nonparametric approach ANN (Artificial Neural Network). Two neural network models are performed. The first model uses spreads between interest rates of 10 different maturities as the only explanatory variable of interest rate changes. The second model introduces two factors, spreads and interest rates' levels. Using historical U.S. Treasury bill rates and Treasury bond yields, we compare the ability of each model to predict the term structure of interest rates. Data are daily and cover the period from 3 January 1995 to 29 December 2000. Results suggest that neural network, Vasicek (1977) and Cox, Ingersoll and Ross (1985) models generate different yield curves. Neural network models outperform the parametric standard models. The most successful forecast is obtained with a two factors neural network model.

This paper examines the hypothesis that financial markets are myopic by studying the term structure of interest rates. White rejecting decisively the traditional expectations hypothesis regarding the term structure, our statistical results also lead us to conclude that long term interest rates do not overreact to either the level or the change in short termrates. This finding suggests that participants in bond markets are not myopic or overly sensitive to recent events. Our statistical results also suggest that most variations in the yield curve reflect changes in liquidity premia rather than expected changes in interest rates.

Changes in interest rates may be attributed to changes in the supply schedule of funds, changes in the demand schedule, or changes in both schedules. Since interest rates link the financial and real sectors of the economy and thus transmit the major thrust of central bank actions to the ultimate targets of monetary policy, it is important to identify properly the causes underlying changes in rates. An increase in rates resulting from an upward shift in the demand fot funds has substantially different implications for the course of economic activity than an equal rise attributable to a downward shift in the supply of funds. This paper conducts tests to determine whether postwar changes in interest rates have resulted primarily from changes in the demand for funds or in the supply of funds. As a first approximation, interest rates can be assumed to be affected on the supply side primarily by the supply of money and on the demand side primarily by aggregate income or output. We can test the relative strengths of money and output on rates by including them both as explanatory variables in one equation1:

Portfolio managers, traders, and risk managers need measures to quantify exposure to changes in interest rates. Two measures beyond duration that take into account interest rate exposure due to a change in the yield curve are partial durations and key rate durations. Par curve changes are used to compute partial durations, and the spot curve is used to compute key rate durations. Hence, in the case of partial durations, trading strategies and risk analysis are based on par yield changes and only indirectly on the spot curve; users of key rate durations base their strategies directly on the spot curve. Users of these sensitivity measures must understand the relationships between the two types of measures, as the results for the approaches often differ significantly. The analysis illustrates the differences between computing level, slope, and curvature durations using the par and the spot curve, and briefly examines the impact of these methodologies on implied forward rates.

Government Bonds and the Term Structure of Interest Rates

The term structure of interest rates, i.e., yield curve, has long been of interest to monetary policymakers and their advisers. The transmission of monetary is conventionally viewed as running from shortterm interest rates managed by central banks to longer-term rates that influence aggregate demand. A central bank's leverage over longer-term rates comes from fact that market determines these as average expected level of short rates over relevant horizon (abstracting from a term premium and default risk). Working in other direction, long bond rate contains a premium for expected and, thus, serves as an indicator of credibility of a central bank's commitment to low inflation.1 Different theoretical perspectives support two above-mentioned uses of term structure for monetary policy: John Hicks's (1939) expectations theory of term structure supports first, and Irving Fisher's (1896) decomposition of nominal bond rates into expected and an expected real return supports second.2 The two views are compatible in principle, although reconciling them creates difficulties of interpretation in practice. For example, does a steepening yield curve indicate a loss of confidence in central bank's commitment to low inflation, or does it indicate that markets expect tighter in form of a higher path of short rates pursued by central bank? The yield curve contains information of use to monetary policymakers, but it needs to be interpreted in light of judicious subsidiary identifying conditions, together with other data on economy. Some circumstances lend themselves to clearer interpretations than others, and there are many pitfalls. Whether or not one regards longer-term interest rates as economic indicators or as part of transmission mechanism for policy, or both, term structure plays a potentially important role in policymaking process. In spite of its complexity, term structure cannot be ignored. This article addresses some issues involved in using term structure to conduct monetary policy. I begin by discussing long bond rate as an indicator of expectations. Second, I comment on role that bond rates have played in recent U.S. monetary history. Third, I explain how information in yield curve can be used to overcome what I call policy in pipeline problem. Fourth, I review recent empirical evidence supporting two theoretical views underlying our understanding of term structure. I explain how peso problems associated with inflation scares in bond market may help to account for a serious empirical failure of expectations theory of term structure. I also discuss evidence supporting view that significant movements in long-term interest rates are largely driven by expected inflation. Finally, I point out some pitfalls of using term structure to make tactical decisions. 1. PURSUING LOW INFLATION The Chairman of Federal Reserve Board, Alan Greenspan, supports a longrun goal for price stability such that the expected rate of change of general level of prices ceases to be a factor in individual and business decisionmaking.3 The long bond rate is particularly well suited to help a central bank assess degree to which it has achieved low defined in that way. One could compare behavior of yield on a long-term nominal bond to its behavior in a past period in which was very low and public was reasonably confident that it would stay low. For instance, in United States 30-year nominal bond rate ranged from around 3 percent to a little over 4 percent from mid-1950s until mid-1960s, a period in which averaged around 1 to 2 percent, and presumably, long-term expectations were no more than that.4 One would think that if Federal Reserve (the Fed) were to achieve full credibility for low inflation, long bond rate would once again move down to 3 to 4 percent range. …

Term Structure of Interest Rates. Review of a Theory of the Term Structure of Interest Rates (CIR)

Interest Rate Risk: Critical Component of Risk in Commercial Banks

Term Structure and the Sluggishness of Retail Bank Interest Rates in Euro Area Countries

Significant amount of research has been dedicated to explaining property yields. Long term interest rate is usually identified as one of the key determinants, and property yields are often benchmarked to long term government bonds, which are considered to represent the closest alternative to property investments. However, empirical evidence provides a mixed picture indicating that the link is less than straightforward even when allowing for a time-varying risk premium. We argue that the relationship between interest rates and property yields is not just contemporaneous and expectations about future interest rates need to be accounted for in order to fully understand the link between these variables. Since real estate is illiquid and involves significant transaction cost, investors are effectively locked in for many years once they commit to a project. An interest rate increase during that period would expose them to a valuation risk. Moreover, when benchmarking to liquid bonds, the opportunity cost is not only the interest they can earn today but also the interest they could expect in the near future. Fundamentally, the term structure of interest rates (yield curve) contains information about the expected future interest rate. Therefore, we would expect that a steeper curve should result in higher property yields. We test this hypothesis using prime office yields in the key centres in Europe and Australia and find convincing evidence that the shape of the yield curve indeed affects property yields.

Purpose: The aim of the study was to assess the effect of interest rate changes on stock market volatility in Congo. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Changes in interest rates have a notable impact on stock market volatility. When central banks adjust interest rates, it influences investor sentiment and economic forecasts. Typically, an increase in interest rates makes borrowing more expensive, which can dampen corporate profits and economic growth, leading to higher market volatility as investors reassess the value of stocks. Conversely, a decrease in interest rates generally lowers borrowing costs, potentially boosting corporate earnings and economic expansion, which can initially reduce market volatility. However, the long-term effects might differ as lower rates can also lead to overvaluation concerns, eventually increasing volatility. Additionally, interest rate changes signal monetary policy shifts and broader economic conditions, further influencing investor behavior and stock market dynamics. Overall, interest rate fluctuations are a critical factor contributing to stock market volatility through their direct and indirect effects on economic activities and investor perceptions. Implications to Theory, Practice and Policy: Efficient market hypothesis, portfolio theory and behavioral finance theory may be used to anchor future studies on assessing the effect of interest rate changes on stock market volatility in Congo. For practical implications, investors and financial institutions should develop risk management strategies that account for the short-term volatility spikes following interest rate announcements. From a policy perspective, policymakers should consider the lagged effects of interest rate changes when formulating monetary policy to ensure smoother market transitions.

Yield Curve Predictors of Foreign Exchange Returns

The question of how monetary policy translates across the yield curve is at the forefront of many recent policy debates. This debate takes on added intensity when the choice of policy regime is heterogeneous. Monetary policy targets the very short end of the yield curve, although real economic activity is largely influenced by medium- to long-term market interest rates. Given efficient market conditions, conventional wisdom asserts that changes to the monetary policy instrument (policy interest rate) lead to an immediate change in market interest rates and bond prices distributed over all maturities; yet evidence supporting this view remains elusive. Using the expectations hypothesis as a benchmark, an empirical analysis of daily yield rates for the Japanese money and government bond markets for the period 2000 to 2009 provides evidence for segmentation over the yield curve. The expectations hypothesis receives little support in either an interest rate targeting or quantitative targeting regime, but the policy impact is weaker in times of quantitative targeting; the observed concentration of impact suggests highly segmented market niches. The empirical findings invite attention of monetary policymakers to the financial system and its structural impediments, especially in an environment of economic uncertainty, low market confidence, and a binding interest rate floor.

This paper investigates the relation between the conditional expected equity risk premium and the slope of the term structure of interest rates. Theoretically, these variables are linked, the relation may be nonlinear, and negative risk premiums are consistent with equilibrium. Given these implications, we employ a nonparametric estimation technique to document the empirical relation between the risk premium and the slope of the term structure using almost two hundred years of data. Of particular interest, the risk premium is increasing in the term structure slope; however, for either small or negative slopes, the risk premium is much more sensitive to changes in interest rates. In addition, the empirical results imply negative expected equity risk premiums for some inverted term structures. Finally, variations in the risk premium do not appear to be related to variations in the variance of equity returns. We illustrate these features in a stylized consumption-based model, and provide the economic intuition behind the results.

This study develops a model for the valuation of Collateralized Mortgage Obligations (CMOs). The model is based on a two-factor model of the term structure of interest rates and embeds an empirically estimated mortgage prepayment function. The model is used to analyze various CMO tranches, including standard sequential pay fixed-rate tranches, Planned Amortization Class (PAC) tranches, Targeted Amortization Class (TAC) tranches, floating-rate tranches, Interest Only (IO) and Principal Only (PO) tranches, Z-bonds and Residuals. The results of this analysis illustrate the sensitivity of the various tranches to differences in CMO structure, changes in interest rates, the characteristics of the underlying collateral, and mortgage prepayments.