Analysis of Linkage Effects among Currency Networks Using REER Data

We modeled the currency networks through the use of REER (real effective exchange rate) instead of a bilateral exchange rate in order to overcome the confusion in selecting base currencies. Based on the MST (minimum spanning tree) approach and the rolling-window method, we constructed time-varying and correlation-based networks with which we investigate the linkage effects among different currencies. In particular, and as the source of empirical data, we chose the monthly REER data for a set of 61 major currencies during the period from 1994 to 2014. The study demonstrated that obvious linkage effects existed among currency networks and the euro (EUR) was confirmed as the predominant world currency. Additionally, we used the rollingwindow method to investigate the stability of linkage effects, doing so by calculating the mean correlations and mean distances as well as the normalized tree length and degrees of those currencies. The results showed that financial crises during the study period had a great effect on the currency network's topology structure and led to more clustered currency networks. Our results suggested that it is more appropriate to estimate the linkage effects among currency networks through the use of REER data

Does online media attention improve China’s green fund performance?

This study investigates the relationship between online media attention and the performance of China’s green funds. The results show that increased media attention can boost the performance of green funds in the short term, however, this effect is short-lived. The mechanism of short-term positive effects may be due to increased media attention leading to larger purchases, which may undermine funds’ long-term performance. In particular, online media attention has a greater impact on larger and older funds. Moreover, it indicates that media attention reduces the returns of individual investor-dominated funds, but has little effect on institutional investor-dominated funds

Analysis of Linkage Effects among Currency Networks Using REER Data

We modeled the currency networks through the use of REER (real effective exchange rate) instead of a bilateral exchange rate in order to overcome the confusion in selecting base currencies. Based on the MST (minimum spanning tree) approach and the rolling-window method, we constructed time-varying and correlation-based networks with which we investigate the linkage effects among different currencies. In particular, and as the source of empirical data, we chose the monthly REER data for a set of 61 major currencies during the period from 1994 to 2014. The study demonstrated that obvious linkage effects existed among currency networks and the euro (EUR) was confirmed as the predominant world currency. Additionally, we used the rolling-window method to investigate the stability of linkage effects, doing so by calculating the mean correlations and mean distances as well as the normalized tree length and degrees of those currencies. The results showed that financial crises during the study period had a great effect on the currency network’s topology structure and led to more clustered currency networks. Our results suggested that it is more appropriate to estimate the linkage effects among currency networks through the use of REER data

Analysis on the sources of value added of American crop exports and employment

This paper uses the WIOD database combined with the global value chain decomposition to measure the value added of the crop industry and other industries included in the US crop exports. Use the employment coefficient to further analyze the impact of US crop exports on the employment of its own industry and other industries and the impact of exports from other industries on employment in the crop industry. We found: (1) The value-added of the service industry included in the export of the US crop industry is higher than that of the manufacturing industry and the primary industry. (2) Among the exports of other industries, the crop industry included in the manufacturing export has the most value-added and continues to increase, while the value added of the service industry and the primary industry is low. (3) The number of employed people in the industry driven by the export of the US crop industry is increasing. Among the other industries, the service industry has the largest number of employed people driven by the export of the crop industry

Open-End Funds for Sustainable Economic Growth in China: The Relationship between Load Fees, Performance, and Flows

The financial market, including the fund market, has an increasingly important role in facilitating sustainable economic development. In this study, we examine whether investors react rationally to fund fees through the investigation of the impact of fee structures on investor behavior with open-end funds in China. We aim to determine whether performance influences the effect of the load fee on fund flows. Based on panel data that contained 240 open-end funds for the period of 2008 to 2017, we offer insight into the relationship between fee structure and the flow of open-end funds in China and find that investors react more sensitively to the load fee than operating expenses. Specifically, the coefficients of operating expenses were found to be insignificant in all regression analyses, while almost all the coefficients of load fees were statistically significant. In addition, our findings indicate that the load fee decreases net flow mainly through increasing redemption, and high load fees can make investors more rational to redeem funds with low performance. High load fees can influence investors to sell funds that perform worse in moderately performing funds, where a high load fee can increase investors’ rationality and motivate them to sell funds, resulting in the mitigation of the disposition effect. We also find that investors in larger funds and aggressive growth funds, as well as those who invest with institutional investors and higher liquidity, react more insensitively to load fees, which can be illustrated by the distraction effect

Can Network Linkage Effects Determine Return? Evidence from Chinese Stock Market

<div><p>This study used the dynamic conditional correlations (DCC) method to identify the linkage effects of Chinese stock market, and further detected the influence of network linkage effects on magnitude of security returns across different industries. Applying two physics-derived techniques, the minimum spanning tree and the hierarchical tree, we analyzed the stock interdependence within the network of the China Securities Index (CSI) industry index basket. We observed that that obvious linkage effects existed among stock networks. CII and CCE, CAG and ITH as well as COU, CHA and REI were confirmed as the core nodes in the three different networks respectively. We also investigated the stability of linkage effects by estimating the mean correlations and mean distances, as well as the normalized tree length of these indices. In addition, using the GMM model approach, we found inter-node influence within the stock network had a pronounced effect on stock returns. Our results generally suggested that there appeared to be greater clustering effect among the indexes belonging to related industrial sectors than those of diverse sectors, and network comovement was significantly affected by impactive financial events in the reality. Besides, stocks that were more central within the network of stock market usually had higher returns for compensation because they endured greater exposure to correlation risk.</p></div

Dynamic normalized tree length.

<p>(a) shows the one-tier MST (2002/1/6-2015/7/1). (b) shows the two-tier MST (2009/1/6-2015/7/1). (c) shows the three-tier MST (2009/1/6-2015/6/25).</p

Hierarchical tree of one-tier CSI industry indices.

<p>(2002/1/6-2015/7/1).</p

Hierarchical tree of two-tier CSI industry indices.

<p>(2009/1/6-2015/7/1).</p

Dynamic mean correlation coefficients.

<p>(a) shows the one-tier MST (2002/1/6-2015/7/1). (b) shows the two-tier MST (2009/1/6-2015/7/1). (c) shows the three-tier MST (2009/1/6-2015/6/25).</p