A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
A new method prioritizes project risks using Monte Carlo Simulation.
A new indicator measures project risk from activity durations.
Research identifies risks in selecting project managers for civil engineering projects.
This paper proposes a method to select project schedules with the lowest risk.
Deployment of emerging technologies and rapid change in industries has created a lot of risk for initiating the new projects. Many techniques and suggestions have been introduced but still lack the gap from various prospective. This paper proposes a reliable project scheduling approach. The objectives of project schedu…
This study provides an independent, outside-in estimate of the cost and schedule risks of nuclear waste storage projects. Based on a reference class of 216 past, comparable projects, risk of cost overrun was found to be 202% or less, with 80% certainty, i.e., 20% risk of an overrun above 202%. Based on a reference clas…
Implementing large-scale information and communication technology (IT) projects carries large risks and easily might disrupt operations, waste taxpayers' money, and create negative publicity. Because of the high risks it is important that government leaders manage the attendant risks. We analysed a sample of 1,355 publ…
Teaching tool simplifies Monte Carlo simulation for project risk analysis.
Risk, including economic risk, is increasingly a concern for public policy and management. The possibility of dealing effectively with risk is hampered, however, by lack of a sound empirical basis for risk assessment and management. The paper demonstrates the general point for cost and demand risks in urban rail projec…
This report reviews the Edinburgh tram project's risk management. Projects frequently overrun their cost and timelines and fall short on intended benefits. Cost, schedule, and benefit risk of projects need to be carefully considered to avoid this. The report describes and evaluates risk assessment and management for th…
Network analysis improves risk assessment for surety bonds.
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…
An investor is estimating net present value of a firm project and performs risk analysis. Usually it is created portfolio hierarchies and make comparison of variants of project based on these hierarchies. Then one finds that portfolio which corresponds to the particular needs of individual groups within the firm. We ha…
Study evaluates risk in options using volatility surface projections.
Empirical study finds IT project costs follow a power-law distribution, exposing risk underestimation.
New method improves model risk prediction using cross-audit projection.
Proposes a new method to rank risky investments based on Omega measure.
We introduce a general decision tree framework to value an option to invest/divest in a project, focusing on the model risk inherent in the assumptions made by standard real option valuation methods. We examine how real option values depend on the dynamics of project value and investment costs, the frequency of exercis…
Optimizes differentially private kernel learning with random projection.
The globalization feeded by the technology explosion that begans in the end of the last century, started the world to change faster every day. The only today's certain is the tomorrow's uncertain. Risk is defined as uncertain where one or many causes composed of ocurrence probality can generate an impact or consequence…
This paper solves the inversion problem for jump processes using Markovian projections.
The paper presents a practical method for evaluating investment projects using real options.
Paper quantifies distortion risk measures' robustness to distributional uncertainty.
Project estimates risk-neutral dependence from option prices.
The paper proposes a dynamic risk measure approach for evaluating defined-contribution pension funds.
Credit risk stress tests can misrepresent default probabilities due to inconsistent parameterization.
This paper argues, first, that a major problem in the planning of large infrastructure projects is the high level of misinformation about costs and benefits that decision makers face in deciding whether to build, and the high risks such misinformation generates. Second, it explores the causes of misinformation and risk…
Back cover text: Megaprojects and Risk provides the first detailed examination of the phenomenon of megaprojects. It is a fascinating account of how the promoters of multibillion-dollar megaprojects systematically and self-servingly misinform parliaments, the public and the media in order to get projects approved and b…
Study variance-optimal hedging of forward curve derivatives under stochastic volatility.
The paper solves portfolio selection using Rényi divergence and optimization.
Out-of-control information technology (IT) projects have ended the careers of top managers, such as EADS CEO Noel Forgeard and Levi Strauss' CIO David Bergen. Moreover, IT projects have brought down whole companies, like Kmart in the US and Auto Windscreen in the UK. Software and other IT is now such an integral part o…
AI measures financial risk using linear quantile lasso regression.
A new algorithm estimates sparse gradients on graphs with improved risk bounds.
A novel optimisation framework through quadratic nonlinear projection is introduced for credit portfolio when the portfolio risk is measured by Conditional Value-at-Risk (CVaR). The whole optimisation procedure to search toward the optimal portfolio state is conducted by a series of single-step optimisations under the …
The paper simplifies hedging and portfolio allocation in markets without a risk-free asset.
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 US$59 billion. The study shows with very high statistical significance that forecasters gener…
We compare the risk of ridge regression to a simple variant of ordinary least squares, in which one simply projects the data onto a finite dimensional subspace (as specified by a Principal Component Analysis) and then performs an ordinary (un-regularized) least squares regression in this subspace. This note shows that …
The paper develops a method for optimal projection selection in high-dimensional classification.
This paper proposes a novel PGO framework to optimize systemic risk bailouts using neural networks.
TEC combines multiple RPSTMs to classify big tensors efficiently.
Develops asymptotic theory for deep Cox models to enable valid inference.
CASP improves portfolio optimization by considering asset covariance.
All people have to make risky decisions in everyday life. And we do not know how true they are. But is it possible to mathematically assess the correctness of our choice? This article discusses the model of decision making under risk on the example of project management. This is a game with two players, one of which is…
PCA-based dimensionality reduction improves robustness in overparameterized linear models.
Reference class forecasting is a method to remove optimism bias and strategic misrepresentation in infrastructure projects and programmes. In 2012 the Hong Kong government's Development Bureau commissioned a feasibility study on reference class forecasting in Hong Kong - a first for the Asia-Pacific region. This study …
Paper introduces new risk norms based on ES with flexible distortion functions.
CE improves climate uncertainty quantification using GCM ensembles and observational data.
Machine learning helps estimate risk premiums of stocks without knowing their factors.