Leong Kwan Li

Development of a partnering performance index (PPI) for construction projects in Hong Kong: a Delphi study

Over the past decade, research studies on benefits, critical success factors, difficulties, process, conceptual and theoretical models of construction partnering have been ubiquitous in the construction management discipline. In fact, there is adequate evidence that an increasing number of client organizations are adopting a partnering approach to undertake their building and construction projects both locally and worldwide during the last decade. With the perceived benefits that partnering brings about, research into Key Performance Indicators (KPIs) to evaluate the success of partnering projects in construction becomes vital as it can help set a benchmark for measuring the performance level of partnering projects. However, although there are some related studies and papers on this research area, few, if any, comprehensive and systematic studies focus on developing a comprehensive, objective, reliable and practical performance evaluation model for partnering projects. A model has been developed using the Delphi survey technique to objectively measure the performance of partnering projects in Hong Kong based on a consolidated KPIs conceptual framework previously developed for partnering projects. Four rounds of Delphi questionnaire survey were conducted with 31 construction experts in Hong Kong. The results reveal that the top seven weighted KPIs to evaluate the success of partnering projects in Hong Kong were: (1) time performance; (2) cost performance; (3) top management commitment; (4) trust and respect; (5) quality performance; (6) effective communications; and (7) innovation and improvement. A statistically significant consensus on the top seven weighted KPIs was also obtained. Finally, a composite Partnering Performance Index (PPI) for partnering projects in Hong Kong was derived to provide an all‐round assessment of partnering performance. Different partnering projects can now be assessed on the same basis for benchmarking purposes. Construction senior executives and project managers can thus use the Index to measure, evaluate and improve the performance of their partnering projects to strive for construction excellence. Although the PPI was developed locally in Hong Kong, the research method could be replicated in other parts of the world to produce similar indices for international comparison. Such an extension would aid the understanding of managing partnering projects across different geographic locations.

Pricing Discrete Barrier and Hindsight Options with the Tridiagonal Probability Algorithm

This paper develops an algorithm to calculate the Brownian multivariate normal probability subject to any preset error tolerance criteria. The algorithm is founded upon the computational simplicity of the tridiagonal structure of the inverse of the Brownian correlation matrix. Compared with existing pricing technologies without the barrier too close problem, our calculation method can produce a more accurate and efficient analytic evaluation of barrier options monitored at discrete instants with well- or ill-behaved barrier levels, or discrete hindsight options, for a reasonably large number of monitorings.

Pricing Discrete Dynamic Fund Protections

Abstract The authors investigate the pricing of discretely monitored dynamic fund protections when the fund price follows a lognormal process or a constant elasticity of variance (CEV) process. A backward recursive pricing formula is derived. By employing a numerical technique that combines function approximation and numerical quadrature, the authors demonstrate how to complete each recursion level efficiently. Numerical experiments show that the results compare favorably with those obtained by other pricing methods.

Minimal Feedforward Parity Networks Using Threshold Gates

This article presents preliminary research on the general problem of reducing the number of neurons needed in a neural network so that the network can perform a specific recognition task. We consider a single-hidden-layer feedforward network in which only McCulloch-Pitts units are employed in the hidden layer. We show that if only interconnections between adjacent layers are allowed, the minimum size of the hidden layer required to solve the n-bit parity problem is n when n 4.

Pricing and Hedging of Discrete Dynamic Guaranteed Funds

We derive a risk-neutral pricing model for discrete dynamic guaranteed funds with geometric Gaussian underlying security price process. We propose a dynamic hedging strategy by adding a gamma factor to the conventional delta. Simulation results demonstrate that, when hedging discretely, the risk-neutral gamma-adjusted-delta strategy outperforms the dynamic delta hedging strategy by reducing the expected hedging error, lowering the hedging error variability, and improving the self-financing possibility. The discrete dynamic delta-only hedging not only causes potential overcharge to clients but also could be costly to the issuers. We show that a naive application of continuous-time hedging formula to a discrete-time hedging setting tends to worsen these possibilities.

Evaluating American put options on zero-coupon bonds by a penalty method

In this paper, American put options on zero-coupon bonds are priced under a single factor model of short-term rate. The linear complementarity problem of the option value is solved numerically by a penalty method, by which the problem is transformed into a nonlinear PDE by adding a power penalty term. The solution of the penalized problem converges to that of the original problem. A numerical scheme is established by using the finite volume method and the corresponding stability and convergence are discussed. Numerical results are presented to show the usefulness of the method.

Compression of UV spectrum with recurrent neural network

In order to save time or storage space, compression techniques are applied. Recently compression techniques based on approximation theory are dominated by the fast Fourier and the wavelet transforms if noise is tolerated. For a given sequence, the compressed signal is represented as a linear sum of basic functions. In this note, we introduce a dynamical system approach for signal compressions. We demonstrate how to compress a UV spectrum by a discrete-time recurrent neural network. As an initial valued problem, the parameters we stored are the connection weights of the neural network and also the initial states. Compression ratio is also discussed. Storage space and energy is saved if good compression techniques are applied.

New Error Function for Single Hidden Layer Feedforward Neural Networks

Feedforward neural networks (FNN) are most heavily used to identify the relation between a given set of input and desired output patterns. By the universal approximation theorem, it is clear that a single-hidden layer FNN is suffcient for the outputs to approximate the corresponding desired outputs arbitrarily close and so we consider a single-hidden layer FNN. In practice, we set up an error function so as to measure the performance of the FNN. As the error function is nonlinear, we define an iterative process, learning algorithm, to obtain the optimal choice of the connection weights and thus set up a numerical optimization problem. In this paper, we consider a new error function defined on the hidden layer We propose a new learning algorithm based on the least square methods converges rapidly. We discuss our method with the classic learning algorithms and the convergence for these algorithms.

Fast evaluation of some probability integrals arisen from the valuations of discretely monitored derivative securities

In this paper, we propose a fast numerical method to evaluate discretely monitored derivatives. The key is to compute the involved probability integrals interactively. Our method can avoid the curse of dimensionality that most other methods suffer. Also, we give a constructive proof for explicit error estimation that based on a simple and systematic quadrature technique. The numerical frameworks are included for applications of barrier options on a stock and a short rate.