The dynamic and stochastic instability of betas: implications for forecasting stock returns

Article Abstract:

The dynamic and stochastic behavior of beta coefficients for individual stocks, and their significance on the forecasting of stock returns are analyzed. This study involves aspects such as randomness, nonstationarity, and shifts in the mean and variance parameters of the betas. All the tests assume variable-mean-response random coefficient models with heteroscedasticity, such as error-in-beta, linearly dynamic and parabolically dynamic. The four-step generalized least squares technique is also used for estimation.

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Forecasting interest rates and yield spreads: the informational content of implied futures yields and best-fitting forward rate models

Article Abstract:

The use of futures market in forecasting interest rates and yield spreads proves to be more effective than forward rate models. Usage of futures yields as a forecasting tool is effective due to lower transaction costs. Market participants are observed to have a greater degree of consensus on short-term interest rates than on those long-term interest rates. Forward and future rates are found to have a greater interdependence, which implies that any gap that occurs between these two rates are not permanent.

Financial Forecasting, Futures market, Futures markets, Interest rates, Business forecasting

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Convergence and the constant dynamic linear model

Article Abstract:

It is common knowledge that the posterior parameter variance and the adaptive vector of observable constant dynamic linear models adjoin to limiting values. Nonetheless, majority of the evidence are ambiguous since several have trivial flaws and a number address only certain cases. A sophisticated probabilistic convergence proof shows that the restriction is not influenced by the first parametric prior. The outcome is proffered to a class of multivariate dynamic linear prototypes.

Econometrics & Model Building, Econometrics, Business models, Convergence (Mathematics)

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