On the estimation and comparison of short-rate models using the generalised method of moments

Subsequent to the influential paper of [Chan, K.C., Karolyi, G.A., Longstaff, F.A., Sanders, A.B., 1992. An empirical comparison of alternative models of the short-term interest rate. Journal of Finance 47, 1209-1227], the generalised method of moments (GMM) has been a popular technique for estimation and inference relating to continuous-time models of the short-term interest rate. GMM has been widely employed to estimate model parameters and to assess the goodness-of-fit of competing short-rate specifications. The current paper conducts a series of simulation experiments to document the bias and precision of GMM estimates of short-rate parameters, as well as the size and power of [Hansen, L.P., 1982. Large sample properties of generalised method of moments estimators. Econometrica 50, 1029-1054], J-test of over-identifying restrictions. While the J-test appears to have appropriate size and good power in sample sizes commonly encountered in the short-rate literature, GMM estimates of the speed of mean reversion are shown to be severely biased. Consequently, it is dangerous to draw strong conclusions about the strength of mean reversion using GMM. In contrast, the parameter capturing the levels effect, which is important in differentiating between competing short-rate specifications, is estimated with little bias. (c) 2006 Elsevier B.V. All rights reserved.

Market reaction to takeover rumour in internet discussion sites

We examine the market reaction to takeover rumour postings in the Hotcopper Internet Discussion Site (IDS). Results from the interday analysis show abnormal returns and trading volumes on the day before and the day of the posting. Results of the intraday analysis show abnormal returns and trading volumes during the 10 min posting interval and abnormal trading volume during the 10 min interval immediately preceding it. Sensitivity analyses indicate that the results are robust to concerns regarding potential confounds, credibility and bid–ask spread bias. Taken together, these findings are consistent with the market reacting to the posting of takeover rumours in IDS.

Zero-non-zero patterned vector error correction modeling for I(2) cointegrated time series with applications in testing PPP and stock market relationships

Vector error-correction models (VECMs) have become increasingly important in their application to financial markets. Standard full-order VECM models assume non-zero entries in all their coefficient matrices. However, applications of VECM models to financial market data have revealed that zero entries are often a necessary part of efficient modelling. In such cases, the use of full-order VECM models may lead to incorrect inferences. Specifically, if indirect causality or Granger non-causality exists among the variables, the use of over-parameterised full-order VECM models may weaken the power of statistical inference. In this paper, it is argued that the zero–non-zero (ZNZ) patterned VECM is a more straightforward and effective means of testing for both indirect causality and Granger non-causality. For a ZNZ patterned VECM framework for time series of integrated order two, we provide a new algorithm to select cointegrating and loading vectors that can contain zero entries. Two case studies are used to demonstrate the usefulness of the algorithm in tests of purchasing power parity and a three-variable system involving the stock market.

Are there non-linearities in short-term interest rates?

The present paper investigates the characteristics of short-term interest rates in several countries. We examine the importance of nonlinearities in the mean reversion and volatility of short-term interest rates. We examine various models that allow the conditional mean (drift) and conditional variance (diffusion) to be functions of the current short rate.We find that different markets require different models. In particular, we find evidence of nonlinear mean reversion in some of the countries that we examine, linear mean reversion in others and no mean reversion in some countries. For all countries we examine, there is strong evidence of the need for the volatility of interest rate changes to be highly sensitive to the level of the short-term interest rate. Out-of-sample forecasting performance of one-factor short rate models is poor, stemming from the inability of the models to accommodate jumps and discontinuities in the time series data.

Relationship between franking credits and the market risk premium

In a dividend imputation tax system, equity investors have three potential sources of return: dividends, capital gains and franking (tax) credits. However, the standard procedures for estimating the market risk premium (MRP) for use in the capital asset pricing model, ignore the value of franking credits. Officer (1994) notes that if franking credits do affect the corporate cost of capital, their value must be added to the standard estimates of MRP. In the present paper, we explicitly derive the relationship between the value of franking credits (gamma) and the MRP. We show that the standard parameter estimates that have been adopted in practice (especially by Australian regulators) violate this deterministic mathematical relationship. We also show how information on dividend yields and effective tax rates bounds the values that can be reasonably used for gamma and the MRP. We make recommendations for how estimates of the MRP should be adjusted to reflect the value of franking credits in an internally consistent manner.

Causality detection on US mutual fund movements using evolutionary subset time-series

In this paper we develop an evolutionary kernel-based time update algorithm to recursively estimate subset discrete lag models (including fullorder models) with a forgetting factor and a constant term, using the exactwindowed case. The algorithm applies to causality detection when the true relationship occurs with a continuous or a random delay. We then demonstrate the use of the proposed evolutionary algorithm to study the monthly mutual fund data, which come from the 'CRSP Survivor-bias free US Mutual Fund Database'. The results show that the NAV is an influential player on the international stage of global bond and stock markets.

Do socially responsible fund managers really invest differently?

To date, research into socially responsible investment (SRI), and in particular the socially responsible investment funds industry, has focused on whether investing in SRI assets has any differential impact on investor returns. Prior findings generally suggest that, on a risk-adjusted basis, there is no difference in performance between SRI and conventional funds. This result has led to questions about whether SRI funds are really any different from conventional funds. This paper examines whether the portfolio allocation across industry sectors and the stock-picking ability of SRI managers are different when compared to conventional fund managers. The study finds that SRI funds exhibit different industry betas consistent with different portfolio positions, but that these differences vary from year to year. It is also found that there is little difference in stock-picking ability between the two groups of fund managers.