Time-varying risk premia and the cost of capital: An alternative implication of the Q theory of investment

Evidence suggests that expected excess stock market returns vary over time, and that this variation is much larger than that of expected real interest rates. It follows that a large fraction of the movement in the cost of capital in standard investment models must be attributable to movements in equity risk-premia. In this paper we emphasize that such movements in equity risk premia should have implications not merely for investment today, but also for future investment over long horizons. In this case, predictive variables for excess stock returns over long-horizons are also likely to forecast long-horizon fluctuations in the growth of marginal Q, and therefore investment. We test this implication directly by performing long-horizon forecasting regressions of aggregate investment growth using a variety of predictive variables shown elsewhere to have forecasting power for excess stock market returns.     

The October 1979 Change in the U.S. Monetary Regime: Its Impact on the Forecastability of Canadian Interest Rates

Subsequent to the October 1979 shift in monetary policy in the United States, interest rates in North America not only reached unprecedented levels but also exhibited unprecedented volatility. Using Canadian data, the authors show that anticipated quarterly changes in long-term rates associated with the rational-expectations model have remained small during this post-shift period. The authors examine three sets of recorded forecasts of long-term interest rates in Canada and note their failure to improve upon the no-change prediction. The “perverse” relationship between the slope of the yield curve and the subsequent movement in long-term rates exists in the Canadian data but is of only modest value in a forecasting context. The excess returns on long-term bonds implicit in the recorded forecasts of the level of interest rates vary sharply, yet there is little evidence that forecasters have identified a predictable component of time-varying term premia.     

The information in the Mexican term structure of interest rates: capital market implications

This paper employs the term structure approach to examine Mexican security markets during the recent period of political and economic turmoil. We investigate the characteristics of these markets and the forecast applicability of the pure expectations hypothesis to interest rates in Mexico. We find that both forward rates and spot rate spreads are found to have significant forecasting ability for future spot rates for Mexico. Both forecasting approaches suggest greater predictive ability during the period of higher interest rates and general economic volatility (1995–1996) than the more stable economic environment of the early 1990s (1991–1994).     

Long-term dependence in common stock returns

The efficient market, martingale model of security price movements requires that the arrival of new information be promptly arbitraged away. A necessary and sufficient condition for the existence of an arbitraged price is that statistical dependence among prices must decrease very rapidly. If persistent statistical dependence is present, the arbitraged price changes do not follow a martingale and should have an infinite variance. Using a technique for detecting long-term dependence, called R/S analysis, 200 daily stock return series are studied; many series are characterized by long-term dependence. Thus, in the presence of long-term dependence, the martingale model does not hold. Also, the distribution of security returns is non-normal stable Paretian as opposed to Gaussian.     

Interest Rates and Exchange Rate Movements: Analyzing Short-term Investments in Long-term Bonds

Tests of the uncovered interest rate parity (UIP) are subject to various data problems when long-term interest rates are applied: due to the long investment period, time intervals for measuring exchange rate movements are usually overlapping and therefore not independent. This shortfall can be prevented by considering short-term investments in long-term bonds instead of investments to maturity. This article analyzes the explanatory power of long-term interest rates with regard to 1- and 3-month exchange rate movements by relating return differences from 1- and 3-month investments in domestic and foreign 10-year government bonds to nine different exchange rates. From a Swiss perspective, there is only weak support for an interrelation between return differences and the corresponding exchange rate movements, whereas from a US perspective, the resulting estimates are much more in line with UIP.The reader may for instance consider Engel (1996) and Froot and Thaler (1990).     

Forecasts in IPO Prospectuses: The Effect of Corporate Governance on Earnings Management

Prior research suggests that managers may use earnings management to meet voluntary earnings forecasts. We document the extent of earnings management undertaken within Canadian Initial Public Offerings (IPOs) and study the extent to which companies with better corporate governance systems are less likely to use earnings management to achieve their earnings forecasts. In addition, we test other factors that differentiate forecasting from non‐forecasting firms, and assess the impact of forecasting and corporate governance on future cash flow prediction. We find that firms with better corporate governance are less likely to include a voluntary earnings forecast in their IPO prospectus. In addition, we find that while IPO firms use accruals management to meet forecasts; the informativeness of the discretionary accruals depends on whether or not the firm would have missed its forecast without the use of discretionary accruals.     

Semi-rational expectations and exchange-rate dynamics

The Rational Expectations Hypothesis (REH) asserts that, on average, the economic agents are accurate in predicting future economic developments. The paper demonstrates, however, that in a world of costly information, individual rationality may result in consistent and persistent forecasting biases. A distinction is drawn between perfect foresight or efficient forecasting—which is consistent with the REH—and myopic perfect foresight—which is the profit maximizing, and thus the rational one from an individualistic point of view, even though the latter may result in persistently biased forecasting. These concepts are illustrated in a model of exchange rate dynamics which introduces myopic or ‘semi’ rationality into Dornbusch's familiar model.     

Quantitative wave model of macro-finance

This paper presents macro-finance as ensemble of economic agents and suggests use risk ratings of economic agents as their coordinates on economic space. Financial variables of separate economic agents are defined as functions of time and coordinates on economic space. Aggregations of financial variables of separate economic agents with coordinates near point x on economic space define macro-financial variables as function of x. Hydrodynamic-like equations describe evolution and mutual dependence between macro-financial variables. As example, for simple model of mutual dependence between macro-financial Demand on Investment and Interest Rate we derive hydrodynamic-like equations in a closed form. Perturbations of macro financial variables can generate waves those propagate on economic space and we derive wave equations. Macro financial waves can propagate on economic space with exponential growth of amplitudes and cause time fluctuations of finance variables that may model financial and business cycles. Variety of macro financial waves on economic space gives new look on internal dynamics of macro finance and reveals hidden complexity of macro financial modeling and forecasting.     

Accuracy of International Interest Rate Forecasts

This study exploits a unique data source with contemporaneous forecasts of three-month Euromarket interest rates for five different countries. Professional forecasts are explored in a way that avoids two limitations of previous research. First, rather than being restricted to just U.S. interest rates, data are used for five different countries: the United States, Germany, the United Kingdom, Japan, and Switzerland. Second, the study relies upon data gathered on a single date, rather than over a period of weeks. Consensus forecasts are evaluated against two naive models: a no-change model and a forward rate forecast. In general, the consensus forecasts prove superior to the no-change forecast. The consensus measures, though, are found to be inferior to the forward rate forecast. This is true even considering the dramatic success of the banks in forecasting U.S. rates in this period. However, if the spectacular, and perhaps uniquely successful U.S. results are excluded from consideration, the banks proved dramatically inferior to the forward rate of interest in forecasting interest rates. Thus, the ability of these banks to forecast three-month interest rates for these five countries exceeds that of a no-change forecast, but falls below the forecasting ability of the forward rate.     

预测中国宏观经济变量:专家与模型的组合预测

本文使用组合预测方法,探究以“朗润预测”为代表的专家预测以及计量模型对于中国宏观经济变量的预测效果,并研究对不同预测进行组合预测是否有助于改进预测效果。本文发现,对我国CPI和GDP的增长率,专家预测效果总体上优于模型预测。从原因看,一方面,专家在预测时已经考虑了计量模型的预测信息;另一方面,在经济出现“拐点”的时期,专家通过对实际经济环境和政策的把握,得出更准确的经济预测。组合预测有助于提升预测精度,对专家预测进行组合得到的预测效果优于大多数的专家预测,“模型—专家”组合预测的效果也优于所有的模型和大部分专家预测。     

Long-Term Asset Allocation under Dynamic Interaction of Earnings and Interest Rates

The interaction of interest rates and corporate earnings over the economic cycle generates stock price movements. These movements are captured in the present valuation context. Superior returns are observed when long-term asset allocation techniques are applied to the model.     

Non-renewable resources: A review of long-term projections

This article reviews available estimates of long-term future demand for the major mineral resources, together with estimates of the total world endowment of each. The confrontation of these two sets of estimates is not to be viewed as an exercise in doomsday forecasting. Rather, it yields a set of indices of the lead times available for the exploration of solutions to the problems of the demand for, and the supply of, resources. It is not obvious that market forces will be able to cope with shortages swiftly and flexibly. There is thus a need for a continuing evaluation of the long-run resource implications of world economic expansion.     

Do forecast errors or term premia really make the difference between long and short rates?

Forward rates in the term structure of interest contain predictions of future spot rates plus (possibly) term premia. Realized spot rates contain predicted spot rates plus forecast errors. Under rational expectations forecast errors are not predictable. By forecasting spot rates using publicly available information, bounds on the variation of forecast errors, and term premia are obtained. For one-month treasury bill rates, one to two thirds of the variation in the difference between forward rates and realized spot rates is due to variation in term premia.     

How does Monetary Policy Influence Capital Markets? Using a Threshold Regression Model

This study indicates that the effects of interest rate changes on stock prices could be twofold and that the net effect is determined by which effect is dominant. The study employs a threshold regression model to see if, before and after the central banks cut the interest rates, there is a nonlinear relation between interest rates and the stock index. Based on traditional economic theory, stock prices should be inversely related to interest rates. However, the present study finds that as interest rates start to increase or decrease, the stock index prices are significantly and positively related to the interest rates. The changes in interest rates affect stock indexes inversely only after interest rates have crossed a certain threshold. The inverse U-shaped relationship between interest rates and stock indexes differs from the traditional wisdom. It could make interest rates more valuable in forecasting stock indexes, and it holds implications for monetary policies of central banks. To avoid the spurious regression problem, this study uses a cointegration test and an error correction model to confirm the results from the threshold regression model and finds that there is a significant cointegration relationship before and after central banks cut interest rates.     

Monetary policy and long-term interest rates: An efficient markets approach

This paper is an application of efficient markets theory to analyze empirically the relationship of money supply growth and long-term interest rates. This approach has the advantage over calier research on this subject in that it imposes a theoretical structure on this relationship that flows easier interpretation of the empirical results as well as more powerful statistical tests on the interest of ascertaining the robustness of the results, many different empirical tests are carried out in this paper, and they uniformly do not support the preposition that increases in the money supply are correlated with declines in long rates.     

The Taylor Rule and Forecast Intervals for Exchange Rates

In this paper, we examine the Meese–Rogoff puzzle from a different perspective: out‐of‐sample interval forecasting. While most studies in the literature focus on point forecasts, we apply semiparametric interval forecasting to a group of exchange rate models. Forecast intervals for 10 OECD exchange rates are generated and the performance of the empirical exchange rate models are compared with the random walk. Our contribution is twofold. First, we find that in general, exchange rate models generate tighter forecast intervals than the random walk, given that their intervals cover out‐of‐sample exchange rate realizations equally well. Our results suggest a connection between exchange rates and economic fundamentals: economic variables contain information useful in forecasting distributions of exchange rates. We also find that the benchmark Taylor rule model performs better than the monetary, PPP and forward premium models, and its advantages are more pronounced at longer horizons. Second, the bootstrap inference framework proposed in this paper for forecast interval evaluation can be applied in a broader context, such as inflation forecasting.     

Macroeconomic attention,economic policy uncertainty,and stock volatility predictability

This study adopts the newly constructed macroeconomic attention indices (MAI) and category-specific economic policy uncertainty (EPU) indices to predict stock volatility. Principal component analysis (PCA), scaled PCA (sPCA), and partial least squares (PLS) are used to extract the principal components from indicators. The results show that the combination of MAI and EPU indices can obtain additional information for predicting stock market volatility. In addition, the comprehensive index containing all indicator information (F_t^All) has the strongest short-term forecasting ability, whereas the MAI show the most substantial forecasting ability in long-term forecasting.     

Forecasting Social Security Actuarial Assumptions

Abstract

This paper presents a forecasting model of economic assumptions that are inputs to projections of the Social Security system. Social Security projections are made to help policy-makers understand the financial stability of the system. Because system income and expenditures are subject to changes in law, they are controllable and not readily amenable to forecasting techniques. Hence, we focus directly on the four major economic assumptions to the system: inflation rate, investment returns, wage rate, and unemployment rate. Population models, the other major input to Social Security projections, require special demographic techniques and are not addressed here.

Our approach to developing a forecasting model emphasizes exploring characteristics of the data. That is, we use graphical techniques and diagnostic statistics to display patterns that are evident in the data. These patterns include (1) serial correlation, (2) conditional heteroscedasticity, (3) contemporaneous correlations, and (4) cross-correlations among the four economic series. To represent patterns in the four series, we use multivariate autoregressive, moving average (ARMA) models with generalized autoregressive, conditionally heteroscedastic (GARCH) errors.

The outputs of the fitted models are the forecasts. Because the forecasts can be used for nonlinear functions such as discounting present values of future obligations, we present a computer-intensive method for computing forecast distributions. The computer-intensive approach also allows us to compare alternative models via out-of-sample validation and to compute exact multivariate forecast intervals, in lieu of approximate simultaneous univariate forecast intervals. We show how to use the forecasts of economic assumptions to forecast a simplified version of a fund used to protect the Social Security system from adverse deviations. We recommend the use of the multivariate model because it establishes important lead and lag relationships among the series, accounts for information in the contemporaneous correlations, and provides useful forecasts of a fund that is analogous to the one used by the Social Security system.     

The Structural Relation Between Mortgage and Market Interest Rates

This paper analyzes the dynamic relationship between primary and secondary mortgage markets and the short-term and long-term market interest rates. Using a series of monthly data on fixed rate mortgage rates and GNMA rates, we explore the dependence and speed of adjustment in these primary and secondary mortgage rates to each other as well as to the long and short-term government rates. The results indicate that residential mortgage rates in general, appear to follow the long-term rate and are not very sensitive to movements in the short-term interest rate.     

Forecasting GDP growth with financial market data in Finland: Revisiting stylized facts in a small open economy during the financial crisis

This paper examines the ability of financial variables to predict future economic growth above and beyond past economic activity in a small open economy in the euro area. We aim to clarify potential differences in forecasting economic activity during different economic circumstances.Our results from Finland suggest that the proper choice of forecasting variables is related to general economic conditions. During steady economic growth, the preferred choice for a financial indicator is the short-term interest rate combined with past values of output growth. However, during economic turbulence, the traditional term spread and stock returns are more important in forecasting GDP growth. The time-varying predictive content of the financial variables may be utilized by applying regime-switching nonlinear forecasting models. We propose a novel application using the negative term spread and observed recession as signals to switch between regimes. This procedure yields a significant improvement in forecasting performance at the one-year forecast horizon.