35 resultados para momentum

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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A semiclassical complex angular momentum theory, used to analyze atom-diatom reactive angular distributions, is applied to several well-known potential (one-particle) problems. Examples include resonance scattering, rainbow scattering, and the Eckart threshold model. Pade reconstruction of the corresponding matrix elements from the values at physical (integral) angular momenta and properties of the Pade approximants are discussed in detail.

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Previous researchers use the velocity decay as an input to investigate the ship’s propeller jet induced scour. A researcher indicated that most of the equations used to predict the stability of various protection systems are often missing a physical background. The momentum decay and energy decay are currently proposed as an initial input for seabed scouring investigation, which are more sensible in physics. Computational fluid dynamics (CFD) and laser Doppler anemometry (LDA) experiments are used to obtain the velocity data and then transforming into momentum and energy decays. The findings proposed several exponential equations of velocity, momentum and energy decays to estimate the region exposed to the seabed scouring.

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This paper investigates whether the momentum effect exists in the NYSE energy sector. Momentum is defined as the strategy that buys (sells) these stocks that are best (worst) performers, over a pre-specified past period of time (the 'look-back' period), by constructing equally weighted portfolios. Different momentum strategies are obtained by changing the number of stocks included in these portfolios, as well as the look-back period. Next, their performance is compared against two benchmarks: the equally weighted portfolio consisting of most stocks in the NYSE energy index and the market portfolio, and the S&P500 index. The results indicate that the momentum effect is strongly present in the energy sector, and leads to highly profitable portfolios, improving the risk-reward measures and easily outperforming both benchmarks.

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We develop a continuous-time asset price model to capture the timeseries momentum documented recently. The underlying stochastic delay differentialsystem facilitates the analysis of effects of different time horizons used bymomentum trading. By studying an optimal asset allocation problem, we find thatthe performance of time series momentum strategy can be significantly improvedby combining with market fundamentals and timing opportunity with respect tomarket trend and volatility. Furthermore, the results also hold for different timehorizons, the out-of-sample tests and with short-sale constraints. The outperformanceof the optimal strategy is immune to market states, investor sentiment andmarket volatility.

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A basic intuition is that arbitrage is easier when markets are most liquid. Surprisingly, we find that momentum profits are markedly larger in liquid market states. This finding is not explained by variation in liquidity risk, time-varying exposure to risk factors, or changes in macroeconomic condition, cross-sectional return dispersion, and investor sentiment. The predictive performance of aggregate market illiquidity for momentum profits uniformly exceed that of market return and market volatility states. While momentum strategies are unconditionally unprofitable in US, Japan, and Eurozone countries in the last decade, they are substantial following liquid market states.