scholarly journals Crosscorrelation Analysis between P2P Lending Market and Stock Market in China

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Bin Wang ◽  
Zhonghui Ding ◽  
Xiang Wang ◽  
Kai Shi
Keyword(s):  
Stock Market ◽  
Hurst Index ◽  
Range Analysis ◽  
Rescaled Range ◽  
Rescaled Range Analysis ◽  
P2p Lending

We first use the Hurst index and the Vn statistic to study the respective characteristics of the P2P lending market and the stock market by rescaled range analysis. In terms of fluctuations, there is an antipersistence in the P2P lending market and long-term persistence in the stock market. Then, we studied the crosscorrelation between the daily logarithmic return series of P2P lending market and stock market and found that the crosscorrelation was multifractal and antipersistent.

Rescaled range analysis of paleoclimatic proxies

1992 ◽  
Vol 29 (2) ◽  
pp. 296-300 ◽  
Author(s):  
Y. Wang ◽  
M. E. Evans ◽  
T. C. Xu ◽  
N. Rutter ◽  
Z. Ding ◽  
...  
Keyword(s):  
Oxygen Isotope ◽  
Deep Sea ◽  
Range Analysis ◽  
Climatic Variations ◽  
Oxygen Isotope Ratios ◽  
Rescaled Range ◽  
Rescaled Range Analysis ◽  
Climatic System ◽  
Susceptibility Profiles

Two geophysical measurements have been widely used as paleoclimatic indicators: oxygen-isotope ratios from deep-sea cores and magnetic susceptibility of loess sediments. Both types of record have been shown to possess climatic information, as they share the same dominant frequencies of the Earth's orbital movements, which, according to Milankovitch's theory, drive the climatic system. But these two physical quantities may respond to climatic variations in different ways. Consequently, they may possess different long-term characteristics, which can be detected by the technique of rescaled range (R/S) analysis. Here we report results from four sets of data: two oxygen-isotope records and two loess susceptibility profiles. Analysis indicates that Hurst exponents of about 0.8 are typical for deep-sea oxygen data, whereas values of about 0.9 characterize loess susceptibility sequences. If Mandelbrot's explanation is taken, these distinct values imply that the loess data are more self-correlated and possess stronger persistence compared with the deep-sea records. This may reflect differences in the ways in which these proxy recorders respond to climatic variations, or differences between continental and oceanic climates.

A Study of Longterm Memory in Stock Market Prices Using Rescaled Range Analysis

2003 ◽  
Vol 1 (1) ◽  
pp. 134-146
Author(s):  
A. Chandra Babu ◽  
G. Arivarignan ◽  
Punithavathy Pandian
Keyword(s):  
Stock Market ◽  
Range Analysis ◽  
Market Prices ◽  
Rescaled Range ◽  
Rescaled Range Analysis ◽  
Longterm Memory

scholarly journals Effectiveness of Electricity Derivatives Market Based on Hurst Exponent

2019 ◽  
Vol 118 ◽  
pp. 02061
Author(s):  
Yunzhi Fei ◽  
Xufang Shao ◽  
Gang Wang ◽  
Li Zhou ◽  
Xue Xia ◽  
...  
Keyword(s):  
Hurst Exponent ◽  
Long Term Memory ◽  
Analysis Method ◽  
Random Walk Process ◽  
Range Analysis ◽  
Rescaled Range ◽  
Electricity Derivatives ◽  
Rescaled Range Analysis ◽  
Method R

The Rescaled Range Analysis method (R/S Analysis method) is applied to analyze the PJM electricity derivatives market through calculating V statistics and Hurst Exponent of three types of products. The study finds that there is no obvious average cycle in the PJM electricity derivatives market. The price fluctuation of various products is not a non-random walk process but has a long-term memory. It shows that the PJM electricity derivatives market is not completely effective. The study also finds that PJM electricity option market is more effective than PJM electricity futures market.

scholarly journals Fractal Characteristics, Multiple Bubbles, and Jump Anomalies in the Chinese Stock Market

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Sun Meng ◽  
Hairui Fang ◽  
Dongping Yu
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Chinese Stock Market ◽  
Range Analysis ◽  
Current State ◽  
Rescaled Range ◽  
Rescaled Range Analysis ◽  
Stock Market Bubbles ◽  
Fractal Characteristics ◽  
Multiple Bubbles

To consider the jump problem of the Chinese stock market, this paper takes the CSI 300 Index from April 2005 to November 2015 as the research object, uses the rescaled range analysis (R/S analysis) method to examine the fractal characteristics of the Chinese stock market in the past ten years, and deduces the possibility of multiple bubbles in the Chinese stock market. Based on this, combined with the log-periodic power law (LPPL) model, the stock market bubbles are identified in different periods. The results show that China’s stock market has some anomalies in terms of positive bubbles, negative bubbles, and reverse bubbles, as well as the cross occurrence of reverse-negative bubbles. Besides, through a comparison with the major foreign stock markets, it is found that the fluctuation range of the Chinese stock market is much larger than that of the Dow Jones Industrial Average and the FTSE 100 indices in the same period and there are also more types of multibubbles, which is a connotative anomaly that makes the Chinese stock market different from other major stock markets. Furthermore, the bubble phenomenon in the Chinese stock market during the periods of 2005/4–2007/10 and 2015/6–2015/11 is studied, and it is found that there is a jump anomaly in the Chinese stock market. Finally, based on the above empirical analysis and the current state of the stock market, this paper provides some suggestions for improving the mechanism of the Chinese stock market.

Multivariate rescaled range analysis

2021 ◽  
pp. 126631
Author(s):  
M. Meraz ◽  
J. Alvarez-Ramirez ◽  
E. Rodriguez
Keyword(s):  
Range Analysis ◽  
Rescaled Range ◽  
Rescaled Range Analysis

Rescaled range analysis in the presence of stochastic trend

2007 ◽  
Vol 77 (12) ◽  
pp. 1165-1175 ◽  
Author(s):  
Alexander Aue ◽  
Lajos Horváth ◽  
Josef Steinebach
Keyword(s):  
Range Analysis ◽  
Stochastic Trend ◽  
Rescaled Range ◽  
Rescaled Range Analysis

LONG-TERM MEMORY IN EMERGING MARKETS: EVIDENCE FROM THE CHINESE STOCK MARKET

2006 ◽  
Vol 05 (03) ◽  
pp. 495-501 ◽  
Author(s):  
CHAOQUN MA ◽  
HONGQUAN LI ◽  
LIN ZOU ◽  
ZHIJIAN WU
Keyword(s):  
Stock Market ◽  
Emerging Markets ◽  
Emerging Market ◽  
Long Term Memory ◽  
Chinese Stock Market ◽  
Market Returns ◽  
Stock Market Returns ◽  
Term Memory ◽  
Rescaled Range Analysis

The notion of long-term memory has received considerable attention in empirical finance. This paper makes two main contributions. First one is, the paper provides evidence of long-term memory dynamics in the equity market of China. An analysis of market patterns in the Chinese market (a typical emerging market) instead of US market (a developed market) will be meaningful because little research on the behaviors of emerging markets has been carried out previously. Second one is, we present a comprehensive research on the long-term memory characteristics in the Chinese stock market returns as well as volatilities. While many empirical results have been obtained on the detection of long-term memory in returns series, very few investigations are focused on the market volatility, though the long-term dependence in volatility may lead to some types of volatility persistence as observed in financial markets and affect volatility forecasts and derivative pricing formulas. By means of using modified rescaled range analysis and Autoregressive Fractally Integrated Moving Average model testing, this study examines the long-term dependence in Chinese stock market returns and volatility. The results show that although the returns themselves contain little serial correlation, the variability of returns has significant long-term dependence. It would be beneficial to encompass long-term memory structure to assess the behavior of stock prices and to research on financial market theory.

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