Research-Informed Models for Communicating the Value of Court-Connected Alternative Dispute Resolution for Public Funding

The purpose of framing the research in the following models is to assist the court and its court-connected mediation programs in their ongoing dialogue with the funding decision-makers in addressing the question: Is state funding of community mediation centers and court ADR generally a worthwhile investment? As a means of setting forth components of an analytic framework, the following simplified financial models are offered to draw out salient aspects of the nature of the investment. The simplified models are employed primarily for the purpose of illustrating the investment in terms of classic financial models familiar to a budget analyst. These models intend to provide guidance in framing the funding decision. They are presented from a conservative stance – that is guiding where there are good levels of certainty, low levels of risk, and low downside, regarding return on investment

Organisational impact on evaluating training return on investment

Training is one of a great deal matter in human resource development activities. The benefits of a training program conducted can be seen at a very simplified level to a complex stage. Thus, the complex stage of identify the training outcome will be at the organizational results. In order to identify the return from the training invested on organization impact, evaluating return on investment is seemed to be a challenge. The study identifies the models involved in evaluating ROI for training. Further, the importance and the challenges also examined

Risk implications of renewable support instruments: Comparative analysis of feed-in tariffs and premiums using a mean-variance approach

Different support instruments for renewable energy expose investors differently to market risks. This has implications on the attractiveness of investment. We use mean-variance portfolio analysis to identify the risk implications of two support instruments: feed-in tariffs and feed-in premiums. Using cash flow analysis, Monte Carlo simulations and mean-variance analysis, we quantify risk-return relationships for an exemplary offshore wind park in a simplified setting. We show that feedin tariffs systematically require lower direct support levels than feed-in premiums while providing the same attractiveness for investment, because they expose investors to less market risk. These risk implications should be considered when designing policy schemes

Asset pricing and investor risk in subordinated asset securitisation

As a sign of ambivalence in the regulatory definition of capital adequacy for credit risk and the quest for more efficient refinancing sources collateral loan obligations (CLOs) have become a prominent securitisation mechanism. This paper presents a loss-based asset pricing model for the valuation of constituent tranches within a CLO-style security design. The model specifically examines how tranche subordination translates securitised credit risk into investment risk of issued tranches as beneficial interests on a designated loan pool typically underlying a CLO transaction. We obtain a tranchespecific term structure from an intensity-based simulation of defaults under both robust statistical analysis and extreme value theory (EVT). Loss sharing between issuers and investors according to a simplified subordination mechanism allows issuers to decompose securitised credit risk exposures into a collection of default sensitive debt securities with divergent risk profiles and expected investor returns. Our estimation results suggest a dichotomous effect of loss cascading, with the default term structure of the most junior tranche of CLO transactions (“first loss position”) being distinctly different from that of the remaining, more senior “investor tranches”. The first loss position carries large expected loss (with high investor return) and low leverage, whereas all other tranches mainly suffer from loss volatility (unexpected loss). These findings might explain why issuers retain the most junior tranche as credit enhancement to attenuate asymmetric information between issuers and investors. At the same time, the issuer discretion in the configuration of loss subordination within particular security design might give rise to implicit investment risk in senior tranches in the event of systemic shocks. JEL Classifications: C15, C22, D82, F34, G13, G18, G2

Evaluation of Flashing Yellow Arrow Traffic Signals in Indiana

The evaluation of flashing yellow arrow signals for widespread implementation was evaluated. Through the collection of field driver performance data, survey data, crash data, at two test sites in the State, it was concluded that this is a worthwhile practice to be considered for a larger scale deployment. The return on investment includes both increased safety, and improved mobility. Given Indiana’s widespread usage of span and catenary signal supports, installation could be simplified to place a larger four section flashing yellow head in a horizontal orientation while leaving adjacent through lane three section signal heads in a vertical alignment, and not decrease the standard of care provided to the public, given proper engineering judgment

Investment projects evaluation in a fuzzy environment using the simplified WISP method

This paper examines the importance of investment activity for companies and the challenges they face when evaluating investment projects in a fuzzy environment, that is when decisions have to be made based on some predictions and uncertain or imprecise data. The study focuses on the usage of a new extension of the Simplified WISP (Weighted Sum Product) method, which allows the use of triangular fuzzy numbers, as a tool for evaluating investment projects and minimizing the risk associated with such decisions. Investment projects were evaluated based on the following criteria: Net Present Value, Internal Rate of Return, Profitability Index, Payback Period, and Risk of project failure. The proposed extension of the Simplified WISP method can be used to solve other complex decision problems associated with predictions and uncertainties.The paper highlights the benefits of using this MCDM technique in investment project evaluation and the potential to improve decision-making processes. The study also discusses the challenges associated with applying MCDM techniques in a fuzzy environment and proposes solutions to overcome them. It also provides valuable insights for academics, practitioners, and policymakers interested in investment evaluation and decision-making processes

Simplified Estimation of Economic Seismic Risk for Buildings

A seismic risk assessment is often performed on behalf of a buyer of commercial buildings in seismically active regions. One outcome of the assessment is that a probable maximum loss (PML) is computed. PML is of limited use to real-estate investors as it has no place in a standard financial analysis and reflects too long a planning period. We introduce an alternative to PML called probable frequent loss (PFL), defined as the mean loss resulting from shaking with 10% exceedance probability in 5 years. PFL is approximately related to expected annualized loss (EAL) through a site economic hazard coefficient (H) introduced here. PFL and EAL offer three advantages over PML: (1) meaningful planning period; (2) applicability in financial analysis (making seismic risk a potential market force); and (3) can be estimated using a single linear structural analysis, via a simplified method called linear assembly-based vulnerability (LABV) that is presented in this work. We also present a simple decision-analysis framework for real-estate investments in seismic regions, accounting for risk aversion. We show that market risk overwhelms uncertainty in seismic risk, allowing one to consider only expected consequences in seismic risk. We illustrate using 15 buildings, including a 7-story nonductile reinforced-concrete moment-frame building in Van Nuys, California, and 14 buildings from the CUREE-Caltech Woodframe Project

Adaptive Statistical Evaluation Tools for Equity Ranking Models

A major challenge in the investment management business is to identify which stocks are likely to outperform in the future, and which are likely to perform relatively poorly. To this end the strategy adopted by Genus is to identify factors (auxiliary information about the stock such as earnings-to-price ratio or dividend yield) that they believe are associated with future out-performance (i.e. factors that have predictive ability). The best of these factors are then combined (Genus use a weighted average) into a model which is used to rank the universe of stocks month-by-month. This ranking is then used to as the input to a trading strategy, resulting in a modified portfolio. Genus had provided us with sample data, consisting of just over 12 years worth of monthly returns on a universe of 60 stocks, along with time series of 34 factors for each of the stocks. Using these data, the approach was to build software (MATLAB) models for: 1. ranking the stocks based on factor information; 2. implementing a trading strategy based on a stock ranking and assessing the performance of a given trading strategy by looking at measures such as hit ratio, information ratio and spread. The IPSW team implemented a simplified trading strategy of selling the entire portfolio each month, and using the proceeds to invest equally in the top 20% of stocks as given by the computed ranking. They also implemented the following measures of portfolio performance: excess return, hit ratio and information ratio