Forecasting with more than one model

This paper comprises an editorial review for the Special Issue on Combining Forecasts. It gives a background to the current growth of interest in this topic and speculates upon some of the reasons for this popularity. Some of the main methodological issues in practice are also described.     

Forecasting the economic recession in the U.K. 1979-1982: A comparison of model-based ex ante Forecasts

This paper compares the forecasts of recession and recovery made by five non-government U.K. teams modelling the economy (Cambridge Econometrics, the London Business School, the National Institute of Economic and Social Research, the Cambridge Economic Policy Group and the Liverpool Research Group). The paper concentrates on annual ex ante projections as published over the period 1978-1982, i.e. forecasts made, before the event, of the onset, length, depth and character of the economic recession in the U.K. which began in 1979. The comparison is in terms of year by year changes in production, unemployment, prices and other variables. It concludes that no group was systematically better or worse than other groups (confirming U.S. experience) and that the groups tended to perform better in their chosen areas of specialization, e.g. medium-term groups did better at forecasting the medium-term outcome.     

Linear combination of forecasts: A general Bayesian model

We provide a general Bayesian model for combining forecasts from experts (or forecasting models) who might be biased and correlated with each other. The combination procedure involves debiasing and then combining unbiased forecasts. We also provide a sequential method for learning about the forecasters' biases in the process of combining information from them.     

调和平均组合预测中的参数估计技术

本文从几何距离角度出发，研究调和平均组合预测中的参数估计技术，提出三种确定组合预测权系数的新方法。理论分析和预测实例表明，新的组合预测参数估计技术行之有效。     

Are household subjective forecasts of personal finances accurate and useful? A directional analysis of the British Household Panel Survey

The purpose of the paper is to analyse the accuracy and usefulness of household subjective forecasts of personal finance. We use non‐parametric directional analysis to assess the subjective forecasts which are based on qualitative judgments. Using the British Household Panel Survey (BHPS) we are able to analyse a large number of individuals over a number of years. We also take into account individual characteristics such as gender, age, education and employment status when assessing their subjective forecasts. The paper extends the existing literature in two ways: the accuracy and usefulness of subjective forecasts, based on directional analysis, are assessed at the household level for the first time. Secondly, we adapt and extend the methods of directional analysis, which are applied to the household panel or longitudinal survey. Copyright © 2008 John Wiley & Sons, Ltd.     

Nonparametric density forecast based on time‐ and state‐domain

We propose a new nonparametric density forecast based on time‐ and state‐domain smoothing. We analyze some of its asymptotic properties and provide an empirical illustration. Copyright © 2010 John Wiley & Sons, Ltd.     

Estimating private information usage amongst analysts: evidence from UK earnings forecasts

This paper introduces a methodology for estimating the likelihood of private information usage amongst earnings analysts. This is achieved by assuming that one group of analysts generate forecasts based on the underlying dynamics of earnings, while all other analysts are assumed to issue forecasts based on the prevailing consensus forecast. Given this behavioural dichotomy, we are able to derive (and estimate) a structural econometric model of forecast behaviour, which has implications regarding the determinants of analysts' private information endowments and forecast accuracy over the forecast horizon. Copyright © 2010 John Wiley & Sons, Ltd.     

On the association between IPO underpricing and reversal and Taiwan's regulatory reforms for mandatory forecasts

The unique institutions in Taiwan may add to our understanding of the effect of initial public offering (IPO) firm disclosures. Consistent with the notion of market mispricing, most of Taiwan's IPOs were with consecutive up‐limit hits followed by substantial price reversals. In this study, we decompose IPO underpricing into two components: pure underpricing and subsequent reversal, exploring the impact of the 1991 mandate that IPO firms should include their management forecasts in the prospectuses on these two anomaly measures. Our results support the notion that disclosure regulations ameliorate investors' mispricing the stocks. First, pure underpricing and reversal are significantly less (more) pronounced for post‐mandate (pre‐mandate) IPO stocks. In contrast, consistent with the cheap talk hypothesis, the pre‐mandate voluntary forecasters (non‐forecasters) appear to be more (less) underpriced. Second, the duration of underpricing for the post‐mandate (pre‐mandate) IPOs appears to be shorter (longer). Nevertheless, underpricing lasted relatively longer (shorter) for the pre‐mandate IPOs with (with no) voluntary disclosures. Copyright © 2009 John Wiley & Sons, Ltd.     

Professional forecasters' expectations,consistency, and international spillovers

This paper focuses on the expectation formation process of professional forecasters by relying on survey data on forecasts regarding gross domestic product growth, consumer price index inflation and 3-month interest rates for a broad set of countries. We examine the interrelation between macroeconomic forecasts and also the impact of uncertainty on forecasts by allowing for cross-country interdependencies and time variation in the coefficients. We find that professional forecasts are often in line with the Taylor rule and identify significant expectation spillovers from monetary policy in the USA.     

PARX model for football match predictions

We propose an innovative approach to model and predict the outcome of football matches based on the Poisson autoregression with exogenous covariates (PARX) model recently proposed by Agosto, Cavaliere, Kristensen, and Rahbek (Journal of Empirical Finance, 2016, 38(B), 640–663). We show that this methodology is particularly suited to model the goal distribution of a football team and provides a good forecast performance that can be exploited to develop a profitable betting strategy. This paper improves the strand of literature on Poisson‐based models, by proposing a specification able to capture the main characteristics of goal distribution. The betting strategy is based on the idea that the odds proposed by the market do not reflect the true probability of the match because they may also incorporate the betting volumes or strategic price settings in order to exploit betters' biases. The out‐of‐sample performance of the PARX model is better than the reference approach by Dixon and Coles (Applied Statistics, 1997, 46(2), 265–280). We also evaluate our approach in a simple betting strategy, which is applied to English football Premier League data for the 2013–2014, 2014–2015, and 2015–2016 seasons. The results show that the return from the betting strategy is larger than 30% in most of the cases considered and may even exceed 100% if we consider an alternative strategy based on a predetermined threshold, which makes it possible to exploit the inefficiency of the betting market.