Incluye bibliografía ; We propose a fundamentals-based econometric model for the weekly changes in the euro-dollar rate with the distinctive feature of mixing economic variables quoted at different frequencies. The model obtains good in-sample fi t and, more importantly, encouraging outof-...

According to the Reserve Bank of Australia (2006) the increased supply of Commercial Mortgage-Backed Securities (CMBS), with a range of subordination, has broadened the investor base in real estate debt markets and reduced the commercial property sector’s dependence on bank financing The CMBS...

CMBS are an important segment of the real estate debt markets which reduce the commercial property sector's dependence on bank financing. Until the advent of the credit squeeze in Q3:2007, the CMBS market was one of the most dynamic and fastest-growing sectors in the capital markets, for a...

Using artificial neural networks (ANN) and ordinal regression (OR) as alternative methods to predict LPT bond ratings, we examine the role that various financial and industry variables have on Listed Property Trust (LPT) bond ratings issued by Standard and Poor’s from 1999-2006. Our study...

The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these...

Optimal daily operation of electric power generating plants is very essential for any power utility organization to reduce input costs and possibly the prices of electricity in general. For a fossil fuel – fired power plant for example, the benefits of power generation optimalization (i.e....

The unknown nature of the future requires us to question our decisions and seek reliable methods. The artificial neural networks approach, which is one of the methods used to best predict the future and one that is important for decision making has been thought of, particularly in recent years,...

This article evaluates dynamic driver behaviour models that can be used, in the context of intelligent transport systems (ITS), to predict drivers' compliance with traffic information. The inputs to this type of models comprise drivers' individual socio-economic characteristics and other...

Bidding is a very competitive process in the construction industry; eachcompetitor’s business is based on winning or losing these bids. Contractors would like topredict the bids that may be submitted by their competitors. This will help contractors toobtain contracts and increase their...

Short-term electricity price forecasting is now crucial practice in deregulated electricity markets, as it forms the basis for maximizing the profits of the market participants. In this thesis, short-term electricity prices are forecast using three different predictor schemes, Artificial Neural...