Reducing the blunders in forecasting

Forecasting is going through a crisis, partly attributable to its failure to anticipate so many developments (including the present recession). Specific problems that need tackling by the research community include the tendency to exclude the less quantifiable factors; the difficulties of identifying, relating and foreseeing explanatory variables; assessing degrees of uncertainty; and making the best use of consultants. Prospective analysis, in which forecasts are generated in the light of scenarios, can assist those concerned with actions and the future.     

Insights from history: The next great empire

An analysis of the evolution of the phenomenon of Empire is presented, together with some general observations on the nature of empires. It is concluded that empires are becoming more frequent and larger in size. Extrapolation of the results leads to some intriguing speculations about the future.     

The magnet effect of price limits: A logit approach

We investigate the magnet effect of price limits using transaction data from the Taiwan Stock Exchange. A logit model incorporates explanatory variables from microstructure literature and reveals that the conditional probability of a price increase (decrease) increases significantly when the price approaches the upper (lower) price limit, in support of the magnet effect. Our approach recognizes when the magnet effect starts to emerge and identifies possible determinants of magnet effect. The probability of information-based trading has a significant impact on the magnet effect for lower price limits.     

An empirical investigation of multiperiod tail risk forecasting models

In the context of multiperiod tail risk (i.e., VaR and ES) forecasting, we provide a new semiparametric risk model constructed based on the forward-looking return moments estimated by the stochastic volatility model with price jumps and the Cornish–Fisher expansion method, denoted by SVJCF. We apply the proposed SVJCF model to make multiperiod ahead tail risk forecasts over multiple forecast horizons for S&P 500 index, individual stocks and other representative financial instruments. The model performance of SVJCF is compared with other classical multiperiod risk forecasting models via various backtesting methods. The empirical results suggest that SVJCF is a valid alternative multiperiod tail risk measurement; in addition, the tail risk generated by the SVJCF model is more stable and thus should be favored by risk managers and regulatory authorities.     

The real risk in pension forecasting

The purpose of this paper is to shed light on some of the flaws in the forecasting approach undertaken by the pension industry. Specifically, it considers the treatment of inflation and shows that the current modeling framework is too simplistic. I identify the flaws of the existing regulatory framework and provide an alternative full model framework constructed around the three-factor diffusion model recently proposed by the Danish Society of Actuaries. By use of a simulation study I compare the deterministic inflation scheme applied in the industry to a stochastic scheme and show that the real value of the pension saver’s investment portfolio at retirement is highly dependent on the inflation scheme. As the deterministic scheme does not take state variable correlations into account it overestimates the expected portfolio value in real terms compared to the stochastic scheme. Moreover, the deterministic scheme gives rise to a more heavy-tailed distribution implying a misestimation of downside risk and upside potential. Finally, it is shown in a realistic case study that the pension saver’s expected retirement payout profile is heavily affected.     

The maximum entropy mortality model: forecasting mortality using statistical moments

ABSTRACT

The age-at-death distribution is a representation of the mortality experience in a population. Although it proves to be highly informative, it is often neglected when it comes to the practice of past or future mortality assessment. We propose an innovative method to mortality modeling and forecasting by making use of the location and shape measures of a density function, i.e. statistical moments. Time series methods for extrapolating a limited number of moments are used and then the reconstruction of the future age-at-death distribution is performed. The predictive power of the method seems to be net superior when compared to the results obtained using classical approaches to extrapolating age-specific-death rates, and the accuracy of the point forecast (MASE) is improved on average by 33% respective to the state-of-the-art, the Lee–Carter model. The method is tested using data from the Human Mortality Database and implemented in a publicly available R package.     

The Delphi technique and the forecasting of specific fringe benefits

The value of the Delphi technique is its ability to forecast the possible occurrence of events in the future. In 1981, a follow-up study was completed of an original Delphi study that was conducted in 1976. The basis of the 1981 study was to check the accuracy of the forecast made by school professionals on the future of specific fringe benefits in public education.     

The importance of the volatility risk premium for volatility forecasting

In this paper, we study the role of the volatility risk premium for the forecasting performance of implied volatility. We introduce a non-parametric and parsimonious approach to adjust the model-free implied volatility for the volatility risk premium and implement this methodology using more than 20 years of options and futures data on three major energy markets. Using regression models and statistical loss functions, we find compelling evidence to suggest that the risk premium adjusted implied volatility significantly outperforms other models, including its unadjusted counterpart. Our main finding holds for different choices of volatility estimators and competing time-series models, underlying the robustness of our results.     

Volatility forecasting: Intra-day versus inter-day models

Volatility prediction is the key variable in forecasting the prices of options, value-at-risk and, in general, the risk that investors face. By estimating not only inter-day volatility models that capture the main characteristics of asset returns, but also intra-day models, we were able to investigate their forecasting performance for three European equity indices. A consistent relation is shown between the examined models and the specific purpose of volatility forecasts. Although researchers cannot apply one model for all forecasting purposes, evidence in favor of models that are based on inter-day datasets when their criteria based on daily frequency, such as value-at-risk and forecasts of option prices, are provided.     

Economic perspectives of technological progress: New dimensions for forecasting technology

The environment of technology is changing, research and development budgets are no longer growing rapidly, and the objectives of research and development are increasingly directed to solving environmental problems and the pressure on natural resources. The causal relationship between the allocation of finance and technological growth is discussed. The author suggests that financial cross-impact, previously ignored by most forecasters, is becoming an important determinant of technological progress. Technology-forecasting techniques must be modified to incorporate economic constraints. Current technological scenarios which ignore the financial dimension are likely to prove over-optimistic.     

Price limits in futures markets: effects on the price discovery process and volatility

Price limits are actively employed by many futures exchanges as a regulatory mechanism directed at reducing volatility and improving price discovery process. The aim of this paper is to investigate whether price limits achieve these goals without affecting market liquidity for a number of agricultural futures contracts. We employ models of changing volatility in order to show that price limits do not appear to significantly reduce market volatility. In addition, we find evidence confirming the hypothesis that price limits delay price discovery instead of facilitating it. Our results also suggest that the impact of price limits on volatility and price reversals, found in previous studies, are mainly due to the properties inherent to the futures returns, such as volatility clustering. Finally, although trading decreases significantly due to the price limits, traders do not seem to switch from the contracts affected by price limits to other maturities in order to minimize the impact of circuit breakers.     

A methodology for the identification of strategic technological competences: An application in the sheet metal equipment industry

This paper proposes a technology foresight methodology based on the development of a complementary approach to the Delphi method that enables the identification of strategic technological competences, and presents its application in a sheet metal processing equipment manufacturer. The proposed methodology takes into consideration synergies between future events through a modified QFD matrix, and the application involved a panel of experts from industry and academia. The proposed methodology can benefit organizations by promoting a homogeneous perspective on existing relationships between external drivers and technology diffusion. This study contributes for the understanding of the links between foresight and technology strategy formulation. Further implementations in industrial environments should be performed to refine the methodology and increase the confidence level on the expected results that these findings can signify.     

The investment decision with technological and market uncertainties

This paper examines how technological uncertainty affects current investment; specifically, what is the impact on a firm’s investment in an existing technology when an improved technology might arrive in the future. The firm can invest in the current technology and upgrade to the new technology after its arrival (sequential investing), or it can bypass the current technology and invest directly in the new technology (leapfrogging). The main result is that, in the presence of market risk, future technological uncertainty has a non-monotonic effect on investment, with the investment trigger being a U-shaped function of the expected speed of arrival of the new technology. In this U-shaped relationship, the investment trigger starts rising later if the new technology is more attractive and also when volatility and interest rate are high and growth rate low; thus, technological uncertainty is more likely to have a positive effect on investment under these conditions. Finally, we apply the model to the sequential versus leapfrog investment decision, and find that leapfrogging becomes more attractive relative to sequential investment when interest rate and new technology earnings enhancement are higher, and when market volatility, growth rate and new technology investment cost are lower.     

The information content of option-implied information for volatility forecasting with investor sentiment

This study explores the effect of investor sentiment on the volatility forecasting power of option-implied information. We find that the risk-neutral skewness has the explanatory power regarding future volatility only during high sentiment periods. Furthermore, the implied volatility has varying volatility forecasting ability depending on the level of investor sentiment. Our findings suggest that the effectiveness of volatility forecasting models based on option-implied information varies over time with the level of investor sentiment. We confirm the important role of investor sentiment in volatility forecasting models exploiting option-implied information with strong evidence from in-sample and out-of-sample analyses. We also present improvements in the accuracy of volatility forecasts from volatility forecasting models derived by incorporating investor sentiment in these models.     

The international system : Limits to forecasting

This article describes the obstacles which stand in the way of analysis of the future of the international system and identifies research needs for surmounting them. Such forecasting must be based on an understanding of the structure of the system and its evolution, yet given the heterogeneity of existing paradigms in the study of international relations, it is difficult to give coherent expression to that structure. Progress in forecasting research on the international system therefore implies a lessening of the heterogeneity of those paradigms, and suggestions are made with this end in view.     

Stock returns forecasting with metals: sentiment vs. fundamentals

Using six prominent metal commodities, we provide evidence on the out-of-sample forecasting of stock returns for the market indices of the G7 countries, for which there is little prior evidence in this context. We find precious metals (gold and silver) can improve forecast accuracy relative to the benchmark and performs well compared to forecast combinations. From an economic gains perspective, forecasting returns provides certainty equivalent gains in a market timing strategy for the G7 countries. These certainty equivalent gains are large enough to make active portfolio management attractive, even for individual investors. Gains remain after considering reasonable transaction costs.     

Siting technological risks: cultural approaches and cross-cultural ethics

Are European national risk prevention regulations reflecting different cultural attitudes towards risk? This article replies positively to this question by elaborating the results of an investigation led between 2004 and 2008 by the Joint Research Centre of the European Commission. The investigation focused on the European national implementations of Article 12 of Directive Seveso II on Dangerous Substances (96/82/EC) and aimed at providing an overview of different methodological approaches to the matter of land use planning in areas subject to the risk of major accidents. Five countries were selected for in‐depth analysis and comparison. This article focuses on one aspect of their different approaches to land use planning in at‐risk areas that was not considered by the European investigation: the influence of national cultural backgrounds on the implementation of Article 12 within the respective national legislations and practices. To explain whether different cultural orientations may have affected them, the article refers to one cultural index in particular, namely the uncertainty‐avoidance index (UAI) proposed by the Dutch sociologist Geert Hofstede. This index provides a key of reading of the different methodological orientations adopted for regulating land uses in the vicinity of hazardous establishments in these countries; by applying it, the study demonstrates that different cultural attitudes towards uncertainty may be a determinant factor in the approaches to and the regulation of the matter of hazardous facility siting. In the conclusions, the regulatory as well as ethical implications of this finding are discussed.