How Can Customized Information Change Financial Plans?

Many workers nearing retirement experienced a dramatic decrease in their retirement assets when the stock market crashed in 2008. In order to maintain their expected standard of living in retirement, workers needed to work longer, save more, or do both. To measure the response of older workers to this downturn, the Center for Retirement Research at Boston College (CRR) fielded the CRR 2009 Retirement Survey on a nationally representative sample of 45-59-year-old labor force participants with relatively high pre-downturn assets. This brief is the final in a series of four based on the CRR 2009 Retirement Survey. The first brief described the Survey and highlighted the inclusion of numerous financial, employment, and behavioral factors that are omitted from other surveys. The second brief explored the relationship between these factors and worker responses to the downturn. The third brief examined how worker responses were affected when their options were made explicit – work longer, save more, or live on less in retirement. This brief explores how respondents reacted once they received information tailored to their specific situation. This brief is organized as follows. The first section provides an overview of the workers’ initial responses – work more, save more, both, or neither. The second section describes how these stated responses changed after respondents received “expert advice” that quantified the trade-off based on their specific circumstances. The third section looks at the characteristics of responders who remained committed to taking no action even after the expert advice. The fourth section assesses whether the expert advice led certain respondents to better calibrate their plans. The final section concludes that providing tailored financial advice may help some individuals improve their response to an adverse financial development.

Empower users of financial information as the IASC Foundation's stakeholders

Nicolas Véron comments on the proposal for governance reform (Â?constitution reviewâ??) published in May 2008 by the IASC Foundation, the private-sector body which oversees the setting of International Financial Reporting Standards (IFRS). He emphasizes the unprecedented nature of this global governance experiment and advocates for more direct representation of investors as the primary stakeholders of international accounting standard-setting, as well a more thorough consultation process.

Financial Information Failure and Lawyer Responsibility

When public firms collapse amid allegations of financial information failure-such as misleading financial statements-society looks beyond the role of accountants to see who else should be held responsible. Lawyers advising the firm increasingly are charged with responsibility, perhaps because modern financial and business complexities, as well as rules that make accounting determinations turn in part on legal conclusions, have blurred the boundary between legal and accounting duties. Lawyers should want to satisfy this responsibility not only to avoid liability but also to safeguard their reputation and integrity. The difficult question, which this article attempts to answer, is what that responsibility should be

On information efficiency and financial stability

We study a simple model of an asset market with informed and non-informed agents. In the absence of non-informed agents, the market becomes information efficient when the number of traders with different private information is large enough. Upon introducing non-informed agents, we find that the latter contribute significantly to the trading activity if and only if the market is (nearly) information efficient. This suggests that information efficiency might be a necessary condition for bubble phenomena, induced by the behavior of non-informed traders, or conversely that throwing some sands in the gears of financial markets may curb the occurrence of bubbles.Comment: 14 pages, 2 figure

Financial markets: very noisy information processing

We report new results about the impact of noise on information processing with application to financial markets. These results quantify the tradeoff between the amount of data and the noise level in the data. They also provide estimates for the performance of a learning system in terms of the noise level. We use these results to derive a method for detecting the change in market volatility from period to period. We successfully apply these results to the four major foreign exchange (FX) markets. The results hold for linear as well as nonlinear learning models and algorithms and for different noise models