Non-technical skills for managing risk and performance in financial trading

Recent large-scale failures in financial institutions have been found to be caused, in-part, by human factors-related issues in financial trading. In other environments where risk management and performance are intertwined, a human factors approach is often adopted to understand how the ‘non-technical skills (NTS)’ (leadership (LD), decision-making (DM), situation awareness (SA), teamwork) of organisational actors influence outcomes. Yet, to date, there has been minimal application of human factors research in financial trading. This study (i) identifies ‘real-world’ (i.e. non-laboratory) research studies investigating the NTS important for performance in financial trading, (ii) examines and synthesises data on the NTS found to underpin good or poor performance and (iii) considers the quality and coverage of research investigating NTS in financial trading, and identifies potential areas for future research. Nineteen studies were identified through a systematic literature search and then content-analysed for associations between NTS and performance in financial trading. The review found a range of decision-making (e.g. heuristics and biases, intuitive DM, emotional regulation) and LD skills (e.g. setting standards, monitoring behaviour, encouraging speaking-up) to have been identified as important for managing risk and performance in financial trading environments. Furthermore, SA (e.g. information search and assessment strategies, vigilance, identifying ‘noise’ data) and teamwork (e.g. avoiding ‘role’ conflict, communication between traders) were found to be important, yet remain less explored within the literature, and should be the focus of future research. NTS appear essential for effective risk management within the financial sector, yet further field research is required to examine the context-relevant behaviours that underpin safe activity. This will facilitate the development of evidence-based systems for assessing and training NTS competencies.     

Your Governance or Mine?

In response to criticism directed at the resource sector's corporate governance, this paper examines the corporate governance and underlying firm characteristics of resource development stage entities (DSEs) relative to a size‐matched sample of non‐resource firms. We find that resource DSEs have different governance characteristics in the measures of board independence, chair/CEO duality and CEO cash bonuses. Furthermore, there are differences in the information environment measures of analyst following, debt levels, stock market return and stock turnover. Considering we document substantial differences in underlying firm characteristics, corporate governance differences are likely appropriate to the mining industry and should not be uniformly labelled as ‘bad’. Our results suggest that media rankings based on corporate governance scores may not accurately portray the resource sector. Overall, our results are of interest to Australian investors and regulators and contribute to a broader understanding of contextually contingent corporate governance.     

STRATEGIC ASSET ALLOCATION FOR LONG‐TERM INVESTORS: PARAMETER UNCERTAINTY AND PRIOR INFORMATION

We study the effect of parameter uncertainty on the long‐run risk for three asset classes: stocks, bills and bonds. Using a Bayesian vector autoregression with an uninformative prior we find that parameter uncertainty raises the annualized long‐run volatilities of all three asset classes proportionally with the same factor relative to volatilities that are conditional on maximum likelihood parameter estimates. As a result, the horizon effect in optimal asset allocations is much weaker compared to models in which only equity returns are subject to parameter uncertainty. Results are sensitive to alternative informative priors, but generally the term structure of risk for stocks and bonds is relatively flat for investment horizons up to 15 years. Copyright © 2013 John Wiley & Sons, Ltd.     

REPORTING GUIDELINES FOR META-ANALYSIS IN ECONOMICS

Meta-analysis has become the conventional approach to synthesizing the results of empirical economics research. To further improve the transparency and replicability of the reported results and to raise the quality of meta-analyses, the Meta-Analysis of Economics Research Network has updated the reporting guidelines that were published by this Journal in 2013. Future meta-analyses in economics will be expected to follow these updated guidelines or give valid reasons why a meta-analysis should deviate from them.     

(De)Politicization Dynamics in Public–Private Partnerships (PPPs): Lessons from a comparison between UK and Flemish PPP policy

This article analyses the (de)politicization dynamics in complex and technical matters like public–private partnerships, which is necessary given its social impact and budgetary consequences for the years and generations to come. The global financial crisis provides an excellent window of opportunity to present this argument, because PPP policy needs to reinvent itself. We argue that PPP policy needs to be (re)politicized at the broader societal and discursive levels, which means that their public nature is recognized and that policy alternatives are debated in the public forums. The ‘Private Finance Initiative’ reassessment process in the UK may serve as an example.