The demand for local bus services in England

This paper examines the demand for local bus services in England. The study is based on a dynamic model relating per capita bus patronage to bus fares, income, and service level, and is estimated using a combination of time-series and cross-section data for English counties. The results indicate that patronage is relatively fare-sensitive, with a wide variation in the elasticities

Land use and mobility

This paper analyses the effects of land use characteristics on mode choice and carownership. The study is based on a large sample of individuals from the National TravelSurvey of Great Britain for the years 1989-91 and 1999-2001. Land use characteristics aredefined as population density, size of the municipality, accessibility to public transport andlocal amenities, such as shops and services. Mode choice (shares of total travel by car,public transport and walking) and car ownership are modelled using multinomial andbinomial logit models respectively, which include a large number of socio-economicfactors (income, age, gender, household structure and employment status) as well as landuse indicators. The estimation results strongly support the importance of the land usefactors considered on mode choice and car ownership

Time Varying Risk Aversion: An Application to Energy Hedging

Risk aversion is a key element of utility maximizing hedge strategies; however, it has typically been assigned an arbitrary value in the literature. This paper instead applies a GARCH-in-Mean (GARCH-M) model to estimate a time-varying measure of risk aversion that is based on the observed risk preferences of energy hedging market participants. The resulting estimates are applied to derive explicit risk aversion based optimal hedge strategies for both short and long hedgers. Out-of-sample results are also presented based on a unique approach that allows us to forecast risk aversion, thereby estimating hedge strategies that address the potential future needs of energy hedgers. We find that the risk aversion based hedges differ significantly from simpler OLS hedges. When implemented in-sample, risk aversion hedges for short hedgers outperform the OLS hedge ratio in a utility based comparison

Re-evaluating Hedging Performance

Mixed results have been documented for the performance of hedging strategies using futures. This paper reinvestigates this issue using an extensive set of performance evaluation metrics across seven international markets. We compare the hedging performance of short and long hedgers using traditional variance based approaches together with modern risk management techniques including Value at Risk, Conditional Value at Risk and approaches based on Downside Risk. Our findings indicate that using these metrics to evaluate hedging performance, yields differences in terms of best hedging strategy as compared with the traditional variance measure. We also find significant differences in performance between short and long hedgers. These results are observed both in-sample and out-of-sample.Hedging Performance; Lower Partial Moments; Downside Risk; Variance; Semi- Variance; Value at Risk, Conditional Value at Risk

Hedging Effectiveness under Conditions of Asymmetry

We examine whether hedging effectiveness is affected by asymmetry in the return distribution by applying tail specific metrics to compare the hedging effectiveness of short and long hedgers using crude oil futures contracts. The metrics used include Lower Partial Moments (LPM), Value at Risk (VaR) and Conditional Value at Risk (CVAR). Comparisons are applied to a number of hedging strategies including OLS and both Symmetric and Asymmetric GARCH models. Our findings show that asymmetry reduces in-sample hedging performance and that there are significant differences in hedging performance between short and long hedgers. Thus, tail specific performance metrics should be applied in evaluating hedging effectiveness. We also find that the Ordinary Least Squares (OLS) model provides consistently good performance across different measures of hedging effectiveness and estimation methods irrespective of the characteristics of the underlying distribution.Hedging Performance; Asymmetry; Lower Partial Moments, Value at Risk, Conditional Value at Risk.

Hedging: Scaling and the Investor Horizon

This paper examines the volatility and covariance dynamics of cash and futures contracts that underlie the Optimal Hedge Ratio (OHR) across different hedging time horizons. We examine whether hedge ratios calculated over a short term hedging horizon can be scaled and successfully applied to longer term horizons. We also test the equivalence of scaled hedge ratios with those calculated directly from lower frequency data and compare them in terms of hedging effectiveness. Our findings show that the volatility and covariance dynamics may differ considerably depending on the hedging horizon and this gives rise to significant differences between short term and longer term hedges. Despite this, scaling provides good hedging outcomes in terms of risk reduction which are comparable to those based on direct estimation.Hedging Effectiveness; Scaling; Volatility Modelling, Forecasting

Hedging Effectiveness under Conditions of Asymmetry

We examine whether hedging effectiveness is affected by asymmetry in the return distribution by applying tail specific metrics to compare the hedging effectiveness of short and long hedgers using crude oil futures contracts. The metrics used include Lower Partial Moments (LPM), Value at Risk (VaR) and Conditional Value at Risk (CVAR). Comparisons are applied to a number of hedging strategies including OLS and both Symmetric and Asymmetric GARCH models. Our findings show that asymmetry reduces in-sample hedging performance and that there are significant differences in hedging performance between short and long hedgers. Thus, tail specific performance metrics should be applied in evaluating hedging effectiveness. We also find that the Ordinary Least Squares (OLS) model provides consistently good performance across different measures of hedging effectiveness and estimation methods irrespective of the characteristics of the underlying distribution

Hedging Effectiveness under Conditions of Asymmetry

We examine whether hedging effectiveness is affected by asymmetry in the return distribution by applying tail specific metrics to compare the hedging effectiveness of short and long hedgers using Oil futures contracts. The metrics used include Lower Partial Moments (LPM), Value at Risk (VaR) and Conditional Value at Risk (CVAR). Comparisons are applied to a number of hedging strategies including OLS and both Symmetric and Asymmetric GARCH models. Our findings show that asymmetry reduces in-sample hedging performance and that there are significant differences in hedging performance between short and long hedgers. Thus, tail specific performance metrics should be applied in evaluating hedging effectiveness. We also find that the Ordinary Least Squares (OLS) model provides consistently good performance across different measures of hedging effectiveness and estimation methods irrespective of the characteristics of the underlying distribution.Hedging Performance; Asymmetry; Downside Risk; Value at Risk, Conditional Value at Risk. JEL classification: G10, G12, G15. ____________________________________________________________________ John Cotter, Director of Centre for Financial Markets, Department of Banking and Finance, University College Dublin, Blackrock, Co. Dublin, Ireland, tel 353 1 716 8900, e-mail [email protected]. Jim Hanly, School of Accounting and Finance, Dublin Institute of Technology, tel 353 1 402 3180, e-mail [email protected]. The authors would like to thank the participants at the Global Finance Annual Conference for their constructive comments.

Linear Beamforming for the Spatially Correlated MISO broadcast channel

A spatially correlated broadcast setting with M antennas at the base station and M users (each with a single antenna) is considered. We assume that the users have perfect channel information about their links and the base station has only statistical information about each user's link. The base station employs a linear beamforming strategy with one spatial eigen-mode allocated to each user. The goal of this work is to understand the structure of the beamforming vectors that maximize the ergodic sum-rate achieved by treating interference as noise. In the M = 2 case, we first fix the beamforming vectors and compute the ergodic sum-rate in closed-form as a function of the channel statistics. We then show that the optimal beamforming vectors are the dominant generalized eigenvectors of the covariance matrices of the two links. It is difficult to obtain intuition on the structure of the optimal beamforming vectors for M > 2 due to the complicated nature of the sum-rate expression. Nevertheless, in the case of asymptotic M, we show that the optimal beamforming vectors have to satisfy a set of fixed-point equations.Comment: Published in IEEE ISIT 2010, 5 page

Visual display and alarm system for wind tunnel static and dynamic loads

A wind tunnel balance monitor and alarm system developed at NASA Ames Research Center will produce several beneficial results. The costs of wind tunnel delays because of inadvertent balance damage and the costs of balance repair or replacement can be greatly reduced or eliminated with better real-time information on the balance static and dynamic loading. The wind tunnel itself will have enhanced utility with the elimination of overly cautious limits on test conditions. The microprocessor-based system features automatic scaling and 16 multicolored LED bargraphs to indicate both static and dynamic components of the signals from eight individual channels. Five individually programmable alarm levels are available with relay closures for internal or external visual and audible warning devices and other functions such as automatic activation of external recording devices, model positioning mechanisms, or tunnel shutdown