A continuous time approach to the pricing of bonds

This paper develops an arbitrage model of the term structure of interest rates based on the assumptions that the whole term structure at any point in time may be expressed as a function of the yields on the longest and shortest maturity default free instruments and that these two yields follow a Gauss-Wiener process. Arbitrage arguments are used to derive a partial differential equation which must be satisfied by the values of all default free bonds. The joint stochastic process for the two yields is estimated using Canadian data and the model is used to price a sample of Government of Canada bonds.     

FROM EXPERIENCE: Balancing the Product Development Process: Achieving Product and Cycle-Time Excellence in High-Technology Industries

Most companies' product development process (PDP) is inefficient and slow. Consequently, products are often late-to-market, over cost and not well-aligned with customer's needs. Because it involves all levels of the organization and crosses all functional boundaries, the PDP is very difficult to control. Unbalanced control is at the root of many of the symptoms of a troubled PDP. Michael T. Anthony and Jonathan McKay investigate the four primary unbalanced PDP behaviors exhibited by organizations and present four balancing mechanisms to correct these flaws. In their view, a balanced PDP contains a structured development methodology and project reviews at specific, high-impact points that involves top management appropriately while still allowing empowerment of the project teams.     

THE DISTRIBUTION OF PUBLIC EXPENDITURE AMONG HOUSEHOLDS IN THE UNITED STATES*

This paper presents an analysis of the distributive impact of government expenditures in the United States. The analysis uses a household-level microdata file drawn from the 1970 U.S. Census of Population, with additional income and tax variables drawn from the Internal Revenue Service 1969—70 Tax File. The results are presented at both federal and local levels and include analyses of the distribution of individual benefits, as well as of overall taxes and net benefits. Since a microdata file was used, distributional effects are examined with respect not only to the “traditional” variables of income class and household size, but also with regard to the number of earners in the household and the sex and race of the household head. In a further paper in a subsequent issue of this review we will present the results of a similar analysis for the United Kingdom, and compare the results for the two countries.     

The impact of misrepresentative data patterns on sales forecasting accuracy

The development of a sales forecasting system involves three major steps. The first step is to obtain prior sales data and to identify the model that will best forecast the patterns that exist in the data. The second step is to estimate parameter values for the selected model by analyzing the prior sales data. The third step is to test the accuracy of the model by use of the prior sales data. Each of the steps requires use of prior data. In all three steps, there is a basic assumption that the past data represent some underlying process that can be identified and modeled. In some cases the past data may not represent the underlying process, and the forecasting process is seriously distorted. Some frequent causes of distorted data are 1) accounting methods that are used to record or collect the data, 2) marketing tactics such as promotions which that create outliers, 3) limits on production capacity that cause stockouts. This paper looks at events and actions that may distort data used for sales forecasting and at the resulting impact the events and actions may have on forecasting accuracy.     

The Effect of Market Regimes on Style Allocation

We analyse time-varying risk premia and the implications for portfolio choice. Using Markov Chain Monte Carlo (MCMC) methods, we estimate a multivariate regime-switching model for the Carhart (1997) four-factor model. We find two clearly separable regimes with different mean returns, volatilities, and correlations. In the High-Variance Regime, only value stocks deliver a good performance, whereas in the Low-Variance Regime, the market portfolio and momentum stocks promise high returns. Regime-switching induces investors to change their portfolio style over time depending on the investment horizon, the risk aversion, and the prevailing regime. Value investing seems to be a rational strategy in the High-Variance Regime, momentum investing in the Low-Variance Regime. An empirical out-of-sample backtest indicates that this switching strategy can be profitable, but the overall forecasting ability for the regime-switching model seems to be weak compared to the iid model.