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The purpose of this paper is to consider two global real estate periods (2000‐2006 and 2007‐2008) that will probably be recorded in history as the most significant periods in terms of a surge and then an eventual downturn in the real estate prices and returns. The paper aims to offer investment strategies in the real estate sector and pinpoint the optimum momentum strategies that provide the maximum returns in the real estate investment trusts (REITs) markets of seven countries.

Within an iterative framework, a two‐step procedure was employed. The first step drew upon an established momentum approach. The second step, however, departed from it and employed an evolutionary (genetic) algorithm to optimize the investment strategies that could be pursued.

The findings suggest that momentum effects have been present during the 2000‐2008 periods. However, in contrast with prior studies, momentum portfolio returns are statistically insignificant during the boom years, but are highly significant during the downturn periods. These findings are attributed to the heterogeneous returns during these periods.

Profitable REITs momentum investment is not uniform across the countries considered. Taking long positions in the winners and short positions in the losers during the boom periods in the real estate market may not necessarily be an optimum strategy. Since the profitability of the investment strategy during the downturn is driven by short positions, the practical implementation of such strategy will be limited if short sales constraints are imposed.

The paper employs a unique and novel approach for the first time in the field of real estate investment. It introduces genetic algorithm into the momentum literature. This approach pinpoints the optimum profitability of the momentum/persistence strategies that could be pursued.

This paper aims to present a method to improve the sensitive and low probabilities of false alarm of a manipulator in a human–robot interaction environment, which can improve the performance of the system owing to non-linear uncertainty in the model of the robot controller.

A novel collision detection method based on adaptive residual estimation is proposed, promoting the detection accuracy of the collision of the manipulator during operation. First, a general momentum residual estimator is designed to incorporate the non-linear factors of the manipulator (e.g. joint friction, speed and acceleration) into the residual-related uncertainty of the model. Second, model parameters are estimated through gradient correction. The residual filter is used to determine the dynamic threshold, resulting in higher detection accuracy. Finally, the performance of the residual estimation scheme is evaluated by comparing the dynamic threshold with residual in real-time experiments where a single Universal Robot 5 robot end–effector collides with the obstacle.

Experimental results demonstrate that the collision detection system can improve sensitivity and lead to low probabilities of false alarm of non-linear uncertainty in the model.

The method proposed in this article can be applied to industry and human–robot interaction area.

An adaptive collision detection method is proposed in this paper to address non-linear uncertainties of the model in industrial application.

The purpose of this paper is to re‐examine the sources of momentum profits by focusing on momentum in monthly returns.

The paper utilizes a decomposition method proposed by Du and Watkins.

Different from previous studies, it is found that momentum may have multiple sources, and that risk or behavioral biases in isolation may not be sufficient to explain momentum.

The paper's finding that momentum may be at least partly due to risk is important for investors to understand the risk of momentum investing.

This paper focuses on the sources of momentum profits in monthly returns. The findings that momentum has multiple sources call for new explanations for momentum because all existing theories of momentum are either rational or behavioral. Furthermore, the finding that lead‐lag relationship plays an important role in momentum suggests that researchers should focus on mis‐reaction to common (market‐wide) information to explain momentum as emphasized by Lo and MacKinlay.

This paper aims to examine the impact of the dividend payout ratio on future stock returns and momentum strategies.

The author uses the portfolio sorting approach used in the momentum literature to examine this impact.

First, the author shows that the returns for the winner stocks tend to be the largest if no dividends are paid and then decrease with the dividend payout ratio; the returns for the loser stocks tend to have an inverted U-shaped relationship with the dividend payout ratio, but the zero-dividend loser stocks have the smallest return; and the returns for the stocks between the winners and the losers tend to remain similar, regardless of the dividend payout ratio. Second, the author shows that momentum profit is the largest for the stocks that do not make dividend payment but appear similar for the stocks that pay dividends. The author's empirical findings imply that stock price momentum is a function of the dividend payout ratio, growth stock momentum tends to be much stronger than value stock momentum and no-dividend stock momentum beats dividend stock momentum. In fact, when the dividend payout ratio is considered, momentum profit can be improved by up to 63 per cent.

This paper is the first one to examine the impact of dividend payout ratios on future stock returns and momentum profit, and it obtained many interesting empirical results. In addition, unlike most studies in the momentum literature that use behavioral theory to explain empirical findings, this paper uses the growth option idea to present a rational explanation for the empirical results in this paper.

The purpose of this paper is to test the performance of momentum strategies and identify the sources of their profits.

To identify the main source of momentum profits, first, the bootstrap method with replacement was used. Then, to eliminate the existence of the small sample bias, the bootstrap method without replacement and the block bootstrap method were employed. In this case, when the authors draw the observations without replacement the random effect is reduced, whereas the resampling procedure is based on the random draw.

The empirical results show the existence of a small sample bias in the bootstrap method with replacement, and that the time‐series relations of stock returns are the main source of momentum profits.

To ensure the random effect of the draws, the authors develop a new resampling procedure called the mixed bootstrap method.

The paper aims to investigate whether or not a firm’s capital structure can interact with past stock returns to affect future stock returns. Specifically, the authors examine whether or not capital structure can help improve momentum profit.

The authors use the US common stocks data from 1965 to 2022 to empirically examine the impact of capital structure on momentum profit.

When capital structure is measured either as the ratio of debt to asset or the ratio of liability to asset, we all find out that momentum strategies tend to be more profitable for stocks with large capital structure.

Besides documenting the empirical evidence of the impact of capital structure on momentum profit, the authors also present a simple explanation for their empirical results and show that their finding is consistent with the behavioral finance theory that characterizes investors’ increased psychological bias and the more limited arbitrage opportunity when the estimation of firm value becomes more difficult or less accurate.

This chapter examines momentum in the corporate bond market using a comprehensive data set that includes bonds with different characteristics and provisions. We find that momentum exists in a wide range of corporate bonds. The momentum effect is more significant for callable bonds and lower-rated bonds. This effect cannot be explained by standard risk factors and liquidity in the bond market. Bond momentum prevails over time and remains strong even after the corporate bond market becomes more transparent and liquid with establishment of TRACE. The high magnitude of momentum profits casts doubt that they can be explained by risk-based theories.

To capture the last hour momentum over the intraday session, the authors develop a trading strategy for the exchange-traded fund (ETF) that is effective because of the T+0 trading rule. This strategy generates annualized excess return of 9.673%.

In this study, the authors identify a last hour momentum pattern in which the sixth (seventh) half-hour return predicts the next half-hour return by employing high frequency 2012–2017 data from the China Securities Index (CSI) 300 and its ETF.

Overall, both the predictability and the trading strategy are statistically and economically significant. In addition, the strategy performs more strongly on high volatility days, high trading volume days, high order-imbalance days and days without economic news releases than on other days.

Noise trading, late-information trading, infrequent rebalancing and disposition effects from retail investors may account for this phenomenon.

The purpose of this paper is to investigate the momentum phenomenon in two market segments of the Chinese stock market – the Class A share market and Class B share market over time period spanning from January 1996 to December 2010.

The authors largely follow Jegadeesh and Titman (1993) paper; the authors decompose the momentum returns following the procedure first proposed by Jegadeesh and Titman (1995). In addition, a liquidity factor (Pastor and Stambaugh, 2003) and a share ownership factor (Wang and Xu, 2004) are incorporated in the procedure to gauge the contribution of liquidity and the dynamics of share ownership towards the momentum returns, respectively in the two segments of the Chinese stock market.

The authors find compelling evidence showing distinctively different momentum phenomena exist in the two market segments of the Chinese stock market. Specifically, the momentum phenomenon is more pronounced in the Chinese Class A share market compared to those found in the Chinese Class B share market. Through decomposing the momentum returns, the authors find evidence showing the dismal momentum returns observed in the Class B share market can be attributed to markedly weakened contributions of the liquidity factor and the share ownership factor.

Relatively short sample time horizon compared to the most of major financial markets such as USA and UK. The number of B shares has been rather limited.

Subsequent to the opening of the Chinese Class B share market to domestic investors in 2001 and the opening of the Chinese Class A share market to qualified foreign institutional investors (QFII) in 2003, the empirical evidence found in this study provides a crucial reference point for domestic and foreign portfolio strategists in guiding them to form suitable portfolio strategies concerning investments in a nascent financial market such as the Chinese stock market, fraught with volatility and speculative trading behaviour.

It offers a comprehensive view of the momentum phenomenon in the Chinese Class A and B share markets over the sample period from January 1996 to December 2010. Second, the reasons behind the dichotomy of the momentum returns found in the two market segments were investigated through decomposing the momentum returns based on Jegdeesh and Titman’s (1995) method while incorporating three new explanatory factors – the liquidity factor, share ownership factor and the under reaction towards firm-specific news factor.

A couple of extant papers have visited the topic before. yet this paper offers more comprehensive view on the existence of momentum premium in both Chinese Class A and B share markets and investigates the driving forces behind the subdued momentum returns observed in the B share market.

The computation of structures moving in central force fields generally requires long‐time integration including geometrically nonlinear behavior (large rotations) as such, e.g. satellite structures move for a long time. To achieve a numerically stable computation the energy momentum method which fulfills linear and angular momentum as well as energy conservation within the time step is chosen for the time integration. The focus in the contribution is on Hamiltonian systems. A formulation for the gravitational force in a central force field as external force on a rigid or flexible satellite is given. The presented formulation enables the computation of the exact spatial distribution of the gravitational forces acting on a structure using the FE‐discretization which is necessary to analyze, e.g. the orientation of a satellite in a gravitational field. The fulfillment of the conservation laws within the time step is proved. The necessity for considering the spatial distribution of the gravitational forces is discussed based on numerical examples.