415 research outputs found
Economic Implications of Bull and Bear Regimes in UK Stock Returns
This paper presents evidence of persistent `bull' and `bear' regimes in UK stock returns and considers their economic implications from the perspective of an investor's portfolio decisions. We find that the perceived state probability has a large effect on the optimal allocation to stocks, particularly at short investment horizons. If ignored, the presence of such regimes gives rise to welfare costs that are substantial, particularly in the bear state where stock holdings should be significantly reduced. When we extend the return forecasting model to allow for predictability from the lagged dividend yield, we find that both dividend yields and regime switching have strong effects on the optimal asset allocation.optimal asset allocation, regime switching, Bull and Bear Markets, model specification
Testing Dependence Among Serially Correlated Multi-category Variables
The contingency table literature on tests for dependence among discrete multi-category variables assume that draws are independent, and there are no tests that account for serial dependencies − a problem that is particularly important in economics and finance. This paper proposes a new test of independence based on the maximum canonical correlation between pairs of discrete variables. We also propose a trace canonical correlation test using dynamically augmented reduced rank regressions or an iterated weighting method in order to account for serial dependence. Such tests are useful, for example, when testing for predictability of one sequence of discrete random variables by means of another sequence of discrete random variables as in tests of market timing skills or business cycle analysis. The proposed tests allow for an arbitrary number of categories, are robust in the presence of serial dependencies and are simple to implement using multivariate regression methods
How Costly is it to Ignore Breaks when Forecasting the Direction of a Time Series?
Empirical evidence suggests that many macroeconomic and financial time-series are subject to occasional structural breaks. In this paper we present analytical results quantifying the effects of such breaks on the correlation between the forecast and the realisation, and on the ability to forecast the sign or direction of a time-series that is subject to breaks. Our results suggest that it can be very costly to ignore breaks. Forecasting approaches that condition on the most recent break are likely to perform better over unconditional approaches that use expanding or rolling estimation windows, provided that the break is reasonably large
Relative Performance Evaluation Contracts and Asset Market Equilibrium
We analyse the equilibrium consequences of performance-based contracts for fund managers. Managerial remuneration is tied to a fund's absolute performance and its performance relative to rival funds. Investors choose whether or not to delegate their investment to better-informed fund managers; if they delegate they choose the parameters of the optimal contract subject to the fund manager's participation constraint. We find that the impact of relative performance evaluation on equilibrium equity premium and on portfolio herding critically depends on whether the participation constraint is binding. Simple numerical examples suggest that the increased importance of delegation and performance evaluation may lower the equity premium.portfolio delegation, relative performance evaluation, equity premium
Testable implications of forecast optimality
Evaluation of forecast optimality in economics and finance has almost exclusively been conducted on the assumption of mean squared error loss under which forecasts should be unbiased and forecast errors serially uncorrelated at the single period horizon with increasing variance as the forecast horizon grows. This paper considers properties of optimal forecasts under general loss functions and establishes new testable implications of forecast optimality. These hold when the forecaster’s loss function is unknown but testable restrictions can be imposed on the data generating process, trading off conditions on the data generating process against conditions on the loss function. Finally, we propose flexible parametric estimation of the forecaster’s loss function, and obtain a test of forecast optimality via a test of over-identifying restrictions
Relative Performance Evaluation Contracts and Asset Market Equilibrium
We analyse the equilibrium consequences of performance-based contracts for fund managers. Managerial remuneration is tied to a fund's absolute performance and its performance relative to rival funds. Investors choose whether or not to delegate their investment to better-informed fund managers; if they delegate they choose the parameters of the optimal contract subject to the fund manager's participation constraint. We find that the impact of relative performance evaluation on equilibrium equity premium and on portfolio herding critically depends on whether the participation constraint is binding. Simple numerical examples suggest that the increased importance of delegation and performance evaluation may lower the equity premium.portfolio delegation, relative performance evaluation, equity premium
Duration Dependence in Stock Prices: An Analysis of Bull and Bear Markets
This paper investigates the presence of bull and bear market states in stock price dynamics. A new definition of bull and bear market states based on sequences of stopping times tracing local peaks and troughs in stock prices is proposed. Duration dependence in stock prices is investigated through posterior mode estimates of the hazard function in bull and bear markets. We find that the longer a bull market has lasted, the lower is the probability that it will come to a termination. In contrast, the longer a bear market has lasted, the higher is its termination probability. Interest rates are also found to have an important effect on cumulated changes in stock prices: increasing interest rates are associated with an increase in bull market hazard rates and a decrease in bear market hazard rates.
Small Sample Properties of Forecasts from Autoregressive Models under Structural Breaks
Autoregressive models are used routinely in forecasting and often lead to better performance than more complicated models. However, empirical evidence is also suggesting that the autoregressive representations of many macroeconomic and financial time series are likely to be subject to structural breaks. This paper develops a theoretical framework for the analysis of small-sample properties of forecasts from general autoregressive models under a structural break. Our approach is quite general and allows for unit roots both pre- and post-break. We derive finite-sample results for the mean squared forecast error of one-step-ahead forecasts, both conditionally and unconditionally and present numerical results for different types of break specifications. Implications of breaks for the determination of the optimal window size are also discussed.small sample properties of forecasts, RMSFE, structural breaks, autoregression
How Costly is it to Ignore Breaks when Forecasting the Direction of a Time Series?
Empirical evidence suggests that many macroeconomic and financial time series are subject to occasional structural breaks. In this paper we present analytical results quantifying the effects of such breaks on the correlation between the forecast and the realization and on the ability to forecast the sign or direction of a time-series that is subject to breaks. Our results suggest that it can be very costly to ignore breaks. Forecasting approaches that condition on the most recent break are likely to perform better over unconditional approaches that use expanding or rolling estimation windows provided that the break is reasonably large.sign prediction, estimation window, structural breaks
Real Time Econometrics
This paper considers the problems facing decision-makers using econometric models in real time. It identifies the key stages involved and highlights the role of automated systems in reducing the effect of data snooping. It sets out many choices that researchers face in construction of automated systems and discusses some of the possible ways advanced in the literature for dealing with them. The role of feedbacks from the decision-maker’s actions to the data generating process is also discussed and highlighted through an example.specification search, data snooping, recursive/sequential modelling, automated model selection
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