Asset Pricing

This article presents results from the first statistically significant study of cost escalation in transportation infrastructure projects. Based on a sample of 258 transportation infrastructure projects worth US$90 billion and representing different project types, geographical regions, and historical periods, it is found with overwhelming statistical significance that the cost estimates used to decide whether such projects should be built are highly and systematically misleading. Underestimation cannot be explained by error and is best explained by strategic misrepresentation, that is, lying. The policy implications are clear: legislators, administrators, investors, media representatives, and members of the public who value honest numbers should not trust cost estimates and cost-benefit analyses produced by project promoters and their analysts.

This article presents results from the first statistically significant study of traffic forecasts in transportation infrastructure projects. The sample used is the largest of its kind, covering 210 projects in 14 nations worth U.S.$59 billion. The study shows with very high statistical significance that forecasters generally do a poor job of estimating the demand for transportation infrastructure projects. For 9 out of 10 rail projects, passenger forecasts are overestimated; the average overestimation is 106%. For half of all road projects, the difference between actual and forecasted traffic is more than ±20%. The result is substantial financial risks, which are typically ignored or downplayed by planners and decision makers to the detriment of social and economic welfare. Our data also show that forecasts have not become more accurate over the 30-year period studied, despite claims to the contrary by forecasters. The causes of inaccuracy in forecasts are different for rail and road projects, with political causes playing a larger role for rail than for road. The cure is transparency, accountability, and new forecasting methods. The challenge is to change the governance structures for forecasting and project development. Our article shows how planners may help achieve this.

Let χ be a family of stochastic processes on a given filtered probability space (Ω, F, (Ft)t∈T, P) with T⊆R+. Under the assumption that the set Me of equivalent martingale measures for χ is not empty, we give sufficient conditions for the existence of a unique equivalent martingale measure that minimizes the relative entropy, with respect to P, in the class of martingale measures. We then provide the characterization of the density of the minimal entropy martingale measure, which suggests the equivalence between the maximization of expected exponential utility and the minimization of the relative entropy.

The article first describes characteristics of major infrastructure projects. Second, it documents a much neglected topic in economics: that ex ante estimates of costs and benefits are often very different from actual ex post costs and benefits. For large infrastructure projects the consequences are cost overruns, benefit shortfalls, and the systematic underestimation of risks. Third, implications for cost–benefit analysis are described, including that such analysis is not to be trusted for major infrastructure projects. Fourth, the article uncovers the causes of this state of affairs in terms of perverse incentives that encourage promoters to underestimate costs and overestimate benefits in the business cases for their projects. But the projects that are made to look best on paper are the projects that amass the highest cost overruns and benefit shortfalls in reality. The article depicts this situation as ‘survival of the unfittest’. Fifth, the article sets out to explain how the problem may be solved, with a view to arriving at more efficient and more democratic projects, and avoiding the scandals that often accompany major infrastructure investments. Finally, the article identifies current trends in major infrastructure development. It is argued that a rapid increase in stimulus spending, combined with more investments in emerging economies, combined with more spending on information technology is catapulting infrastructure investment from the frying pan into the fire.

This paper focuses on problems and their causes and cures in policy and planning for large-infrastructure projects. First, it identifies as the main problem in major infrastructure developments pervasive misinformation about the costs, benefits, and risks involved. A consequence of misinformation is cost overruns, benefit shortfalls, and waste. Second, it explores the causes of misinformation and finds that political-economic explanations best account for the available evidence: planners and promoters deliberately misrepresent costs, benefits, and risks in order to increase the likelihood that it is their projects, and not those of their competition, that gain approval and funding. This results in the ‘survival of the unfittest’, in which often it is not the best projects that are built, but the most misrepresented ones. Finally, it presents measures for reforming policy and planning for large-infrastructure projects with a focus on better planning methods and changed governance structures, the latter being more important.

A major source of risk in project management is inaccurate forecasts of project costs, demand, and other impacts. The paper presents a promising new approach to mitigating such risk, based on theories of decision making under uncertainty which won the 2002 Nobel prize in economics. First, the paper documents inaccuracy and risk in project management. Second, it explains inaccuracy in terms of optimism bias and strategic misrepresentation. Third, the theoretical basis is presented for a promising new method called "reference class forecasting," which achieves accuracy by basing forecasts on actual performance in a reference class of comparable projects and thereby bypassing both optimism bias and strategic misrepresentation. Fourth, the paper presents the first instance of practical reference class forecasting, which concerns cost forecasts for large transportation infrastructure projects. Finally, potentials for and barriers to reference class forecasting are assessed.

"Over budget, over time, over and over again" appears to be an appropriate slogan for large, complex infrastructure projects. This article explains why cost, benefits, and time forecasts for such projects are systematically over-optimistic in the planning phase. The underlying reasons for forecasting errors are grouped into three categories: delusions or honest mistakes; deceptions or strategic manipulation of information or processes; or bad luck. Delusion and deception have each been addressed in the management literature before, but here they are jointly considered for the first time. They are specifically applied to infrastructure problems in a manner that allows both academics and practitioners to understand and implement the suggested corrective procedures. The article provides a framework for analyzing the relative explanatory power of delusion and deception. It also suggests a simplified framework for analyzing the complex principal-agent relationships that are involved in the approval and construction of large infrastructure projects, which can be used to improve forecasts. Finally, the article illustrates reference class forecasting, an outside view de-biasing technique that has proven successful in overcoming both delusion and deception in private and public investment decisions.

In the first phase of the EU Emissions Trading Scheme (EU ETS), the price per ton of CO 2 initially rose to over €30; the price then collapsed to essentially zero by mid 2007. By deriving a structural model of the allowance price under the assumption of efficient markets I examine the ...

This paper examine the unconditional and conditional relationships between beta, size, B/M, E/P and returns in the CSE from 1995 to 2006 by using (FM) (1973) cross-sectional regression test. There is no evidence of a positive risk premium on beta when the unconditional relationship between beta and return is considered. However, when the market is split on the market excess returns, there is a significant positive (negative) relationship between beta and returns in up (down) markets for individual and portfolio of stocks. Further, there is a significant negative size-return and positive B/M-return relations, are unconditional and also insignificant E/P-return relation in the CSE. Thus, we cannot reject the usability of beta in explaining stock returns in the CSE. Beta has a significant relationship with stock returns subject to the condition of the market. Further, size and B/M are significant in explaining stock returns in the CSE and it doesn't seem that they are affected by the condition of the market. Since these findings are important, are could be useful for making investment decisions.

The present study adds to the sparse published Australian literature on the size effect, the book to market (BM) effect and the ability of the Fama French three factor model to account for these effects and to improve on the asset pricing ability of the Capital Asset Pricing Model (CAPM). The present study extends the 1981–1991 period examined by Halliwell, Heaney and Sawicki (1999) a further 10 years to 2000 and addresses several limitations and findings of that research. In contrast to Halliwell, Heaney and Sawicki the current study finds the three factor model provides significantly improved explanatory power over the CAPM, and evidence that the BM factor plays a role in asset pricing.

Survey evidence suggests that many investors form beliefs about future stock market returns by extrapolating past returns. Such beliefs are hard to reconcile with existing models of the aggregate stock market. We study a consumption-based asset pricing model in which some investors form beliefs about future price changes in the stock market by extrapolating past price changes, while other investors hold fully rational beliefs. We find that he model captures many features of actual prices and returns; importantly, however, it is also consistent with the
survey evidence on investor expectations.

The Supplementary Green Book Guidance on Optimism Bias (HM Treasury 2003) with reference to the Review of Large Public Procurement in the UK (Mott MacDonald 2002) notes that there is a demonstrated, systematic, tendency for project appraisers to be overly optimistic and that to redress this tendency appraisers should make explicit, empirically based adjustments to the estimates of a project’s costs, benefits, and duration. HM Treasury recommends that these adjustments be based on data from past projects or similar projects elsewhere, and adjusted for the unique characteristics of the project in hand. In the absence of a more specific evidence base, HM Treasury has encouraged departments to collect data to inform future estimates of optimism, and in the meantime use the best available data. In response to this, the Department for Transport (henceforth DfT), has contracted Bent Flyvbjerg in association with COWI to undertake the consultancy assignment "Procedures for dealing with Optimism Bias in Transport Planning". The present Guidance Document is the result of this assignment.

CHAPTER 4 Complex Evolutionary Systems in Behavioral Finance Cars Hommes and Florian Wagener CeNDEF, School of Economics, University of Amsterdam 4.1. Introduction 218 4.2. An Asset-Pricing Model with Heterogeneous Beliefs 221 4.2. 1. The Fundamental ...

In this paper we present new empirical evidence on the agency based asset pricing model of Brennan (1993). We find strong evidence that in the recent period stocks whose returns covary more with the idiosyncratic component of the S&P500 return have significantly lower ...

This  paper analyzes the asset pricing implications of commonly used portfolio management contracts linking the compensation of fund managers to the excess return of the managed portfolio over a benchmark portfolio. The  contract parameters, the extent of delegation, and equilibrium prices are all  determined endogenously within the model we  consider. Symmetric (fulcrum) performance fees distort the allocation of  managed portfolios in  a  way that induces a  significant and unambiguous positive effect on the prices of the assets included in  the benchmark and a  negative effect on  the Sharpe ratios. Asymmetric performance fees have more complex effects on  equilibrium prices and Sharpe ratios, with the signs of these effects fluctuating stochastically over time in
response to variations in  the funds’ excess performance.

This article reviews how climate change could be considered an additional source of market risk. I discuss the types of data needed to analyse the climate risk drivers that shape the dynamics of the equity market. I present empirical evidence at both the macro and micro-level, analysing whether and to what extent the equity market prices climate change and related risks. Top-down and bottom-up approaches are compared to understand which climate risk is more likely to affect the cross-section of stock returns, both within and across sectors. Emphasis is also placed on investors' beliefs about climate change risks, and the related asset pricing implications are analysed. I conclude by illustrating further directions for both empirical and theoretical research in the field of climate finance.