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Momentum effect has been widely studied for almost 30 years now by both conventional and behavioral scientists, as well as practitioners. The goal of this paper is to investigate the profitability of momentum trading strategy, consisting only of holding a long position in past winner stocks at the New York Stock Exchange (NYSE). We found presence of statistically significant momentum over a period of almost three decades (1990 – 2018). We further performed an in-depth analysis of the companies comprising the list of winners. As a result, we provide a summary of the most frequent winners as well as their industries of operation. We also document the most profitable industries on the NYSE based on the application of winners-only momentum trading strategy. [ABSTRACT FROM AUTHOR]

Since the seminal paper of Jagadeesh and Titman (Jagadeesh & Titman, 1993) momentum effect has been a central research topic in the field of behavioral finance. By its essence, it reflects the investors’ belief that best (worst) performing securities over the past short-term period tend to continue to perform well (poorly) over the subsequent period of up to 12 months. This paper studies some of the statistical properties of the raw returns series derived under momentum trading strategies on the New York Stock Exchange for the period spanning from Jan-1995 to Apr-2018. In particular, we discuss scaling behavior in the context of presence of dominant investment horizons. Furthermore, we analyze the presence of persistent and hetoroscedastic characteristics. [ABSTRACT FROM AUTHOR]

This goal of this paper is to test the possibility to predict the timing of the 2008 financial crash. For this purpose we apply the log-periodic power law model of (Johansen, et al., 2000) to the daily closing log-prices of S&P500 for the period 15-May-2008 – 30-Oct-2008. Using a sliding window, we track changes in the model’s parameters and find that all the conditions necessary to conclude on crash are first satisfied at 15-Aug-2008. [ABSTRACT FROM AUTHOR]

This paper demonstrates the utilization of wavelet-based tools for the analysis and prediction of financial time series exhibiting strong long-range dependence (LRD). Commonly emerging markets' stock returns are characterized by LRD. Therefore, we track the LRD evolvement for the return series of six Southeast European stock indices through the application of a wavelet-based semi-parametric method. We further engage the á trous wavelet transform in order to extract deeper knowledge on the returns term structure and utilize it for prediction purposes. In particular, a multiscale autoregressive (MAR) model is fitted and its out-of-sample forecast performance is benchmarked to that of ARMA. Additionally, a data-driven MAR feature selection procedure is outlined. We find that the wavelet-based method captures adequately LRD dynamics both in calm as well as in turmoil periods detecting the presence of transitional changes. At the same time, the MAR model handles with the complicated autocorrelation structure implied by the LRD in a parsimonious way achieving better performance. [ABSTRACT FROM PUBLISHER]

This paper addresses the problem of solving discrete-time H¥ control problems for periodic systems. The approach for solving such a type of equations is well known in the literature. However, the focus of our research is set on the numerical computation of the stabilizing solution. In particular, two effective methods for practical realization of the known iterative processes are described. Furthermore, a new iterative approach is investigated and applied. On the basis of numerical experiments, we compare the presented methods. A major conclusion is that the new iterative approach is faster than rest of the methods and it uses less RAM memory than other methods. [ABSTRACT FROM AUTHOR]

The current paper investigates how has been evolving the integration of the Greek stock market to the major world stock exchanges for a period spanning from the early 2000s till the middle of 2013. The idea of wavelet coherency is adopted in the analysis in order to identify linkages and co-movement patterns that are otherwise not that obvious. It is further investigated if the detected relationships are of short or of long-run character. Also particular attention is paid to the co-movement patterns during the period of the 2007-2009 financial crisis as well as during the period of the Eurozone debt crisis. In addition, conclusions on presence of contagion and transmission of crises are drawn. [ABSTRACT FROM AUTHOR]