世界経済・社会統計 = World development indicators

1. Introduction and Overview. 2. Detecting Influential Observations and Outliers. 3. Detecting and Assessing Collinearity. 4. Applications and Remedies. 5. Research Issues and Directions for Extensions. Bibliography. Author Index. Subject Index.

Regression Diagnostics: Identifying Influential Data and Sources of Collinearity

During the late 1990s, Huang introduced the algorithm called Empirical Mode Decomposition, which is widely used today to recursively decompose a signal into different modes of unknown but separate spectral bands. EMD is known for limitations like sensitivity to noise and sampling. These limitations could only partially be addressed by more mathematical attempts to this decomposition problem, like synchrosqueezing, empirical wavelets or recursive variational decomposition. Here, we propose an entirely non-recursive variational mode decomposition model, where the modes are extracted concurrently. The model looks for an ensemble of modes and their respective center frequencies, such that the modes collectively reproduce the input signal, while each being smooth after demodulation into baseband. In Fourier domain, this corresponds to a narrow-band prior. We show important relations to Wiener filter denoising. Indeed, the proposed method is a generalization of the classic Wiener filter into multiple, adaptive bands. Our model provides a solution to the decomposition problem that is theoretically well founded and still easy to understand. The variational model is efficiently optimized using an alternating direction method of multipliers approach. Preliminary results show attractive performance with respect to existing mode decomposition models. In particular, our proposed model is much more robust to sampling and noise. Finally, we show promising practical decomposition results on a series of artificial and real data.

Variational Mode Decomposition

本文对国际科学计量学杂志《Ｓｃｉｅｎｔｏｍｅｔｒｉｃｓ》１９７９－１９９１年的研究论文内容、栏目、作者及国别和编委及国别作了计量分析，揭示出科学计量学研究的重点、活动的中心及发展趋势，说明了学科带头人在发展科学计量学这门新兴学科中的作用。

国际刊物《Scientometrics》文献计量研究

Investor Psychology and Security Market Under- and Overreactions

Can volume predict Bitcoin returns and volatility? A quantiles-based approach

Economic growth and energy consumption causal nexus viewed through a bootstrap rolling window

A recent strand in the literature emphasizes the role of news-based economic policy uncertainty (EPU) and equity market uncertainty (EMU) as drivers of oil price movements. Against this backdrop, this paper uses a kth-order nonparametric quantile causality test, to analyse whether EPU and EMU predict stock returns and volatility. Based on daily data covering the period of 2 January 1986 to 8 December 2014, we find that, for oil returns, EPU and EMU have strong predictive power over the entire distribution barring regions around the median, but for volatility, the predictability virtually covers the entire distribution, with some exceptions in the tails. In other words, predictability based on measures of uncertainty is asymmetric over the distribution of oil returns and its volatility.

/pdf/the-role-of-news-based-uncertainty-indices-in-predicting-oil-bwa23nihfc.pdf

The role of news-based uncertainty indices in predicting oil markets: a hybrid nonparametric quantile causality method

Purpose – The purpose of this paper is to investigate the factors affecting capital structure decisions of Istanbul Stock Exchange (ISE) lodging companies.Design/methodology/approach – A model based on the trade‐off and pecking order theories is specified and implications of both theories are empirically tested. The model is estimated using a dynamic panel data approach for five ISE companies for the period of 1994‐2006.Findings – The findings suggest that effective tax rates, tangibility of assets, and return on assets are related negatively to the debt ratio, while free cash flow, non‐debt tax shields, growth opportunities, net commercial credit position, and firm size do not appear to be related to the debt ratio. Although the findings partially support the pecking order theory, neither the trade‐off nor the pecking order theory exactly seem to explain the capital structure of Turkish lodging companies.Research limitations/implications – The data used in this paper are limited to five companies traded ...

Determinants of capital structure: evidence from Turkish lodging companies.

The purpose of this article is to examine the export–output nexus in Japan by taking into account the time variation in the causal link with bootstrap Granger non-causality test and rolling estimation. The data used cover the seasonally adjusted real export and real Gross Domestic Product (GDP) for the 1957:1–2009:1 period. Standard Granger causality tests indicate no causality between export and real GDP series. On the contrary, full sample-modified Granger causality tests based on bootstrap, which are applicable irrespective of integration–cointegration properties of the data, indicate a bi-directional causal link between exports and real GDP. Accordingly, export growth should be an important factor behind Japan’s high-economic growth in the last three decades. Using parameter stability tests, we show that these results are not uniform for different sample periods and results vary due to structural changes. Using bootstrap rolling window estimation, we find that there is a positive bi-directional predictive power from the mid 1970s to the late-1980s between the series, while from the late 1990s to 2009 there is a positive predictive power only from export growth to output growth.

Mehmet Balcilar

Papers

Can volume predict Bitcoin returns and volatility? A quantiles-based approach

Economic growth and energy consumption causal nexus viewed through a bootstrap rolling window

The role of news-based uncertainty indices in predicting oil markets: a hybrid nonparametric quantile causality method

Determinants of capital structure: evidence from Turkish lodging companies.

The export-output growth nexus in Japan: a bootstrap rolling window approach