International Real Estate Review

2012 ◽  
Vol 15 (3) ◽  
pp. 283-305
Author(s):  
Sanjay Rajagopal ◽  
◽  
Patrick Hays ◽  
Keyword(s):  
Real Estate ◽  
Long Memory ◽  
Stock Exchange ◽  
Emerging Market ◽  
Real Estate Market ◽  
Policy Implications ◽  
Population Pressure ◽  
Range Analysis ◽  
Rescaled Range ◽  
Rescaled Range Analysis

Over the last decade, numerous factors including robust economic growth, population pressure, and the mounting need for office space among growth sectors such as information technology have placed significant upward pressure on Indian realty prices. The easing of government restrictions on foreign investments and venture capital into Indian real estate have provided an additional fillip to the real estate market in the country, and the confluence of such factors appears to have contributed to a speculative bubble in Indian real estate equities in the latter part of the decade. By using this bubble period as a case study, we test for the existence of long memory among real estate equities. For the January 2006-December 2008 period, we employ three self-affine fractal analysis techniques (classical rescaled range, roughness-length, and the variogram/structure function methods) to estimate the Hurst exponent, and find significant evidence of long memory in the Bombay Stock Exchange (BSE) Realty Index. Return persistence is further confirmed by the more powerful Lo¡¦s modified rescaled range analysis (MRSA), which is robust to short-term dependence. In addition to potential regulatory policy implications for this emerging market, our results have ramifications for modeling and forecasting returns, as well as for technical trading rules.

Long Memory of NSE Indices

GIS Business ◽  
2018 ◽  
Vol 13 (6) ◽  
pp. 21-28
Author(s):  
Vijaya Kumar
Keyword(s):  
Key Words ◽  
Long Memory ◽  
Hurst Exponent ◽  
Stock Exchange ◽  
Fractional Dimension ◽  
Range Analysis ◽  
Temporal Dependence ◽  
Rescaled Range ◽  
Rescaled Range Analysis ◽  
Periodic Cycles

Long range memory in share indices show temporal dependence between observations spaced by long intervals of time and has distinct non-periodic cycles. This paper examines the presence of long memory of various indices of National Stock Exchange (NSE). The data consists of closing values of indices over different periods of time. The tests applied to examine long memory are Hurst exponent, Manderbolt-Hurst exponent, Lo’s rescaled-range analysis and Geweke and Porter-Hudak (GPH) test. The results of the estimated Hurst exponent, Manderbolt-Hurst exponent and GPH test show that invariably all NSE indices series have long memory. However, the results of Lo’s rescaled-range analysis indicate the absence of long memory for all indices. Key words: Long memory, rescaled range analysis, fractional dimension, Hurst exponent, GPH test, NSE indices

NEURAL NETWORKS FOR TECHNICAL ANALYSIS: A STUDY ON KLCI

1999 ◽  
Vol 02 (02) ◽  
pp. 221-241 ◽  
Author(s):  
JINGTAO YAO ◽  
CHEW LIM TAN ◽  
HEAN-LEE POH
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Stock Exchange ◽  
Emerging Market ◽  
Neural Nets ◽  
Stock Index ◽  
Range Analysis ◽  
The Neural Network ◽  
Rescaled Range Analysis ◽  
Stock Index Forecasting

This paper presents a study of artificial neural nets for use in stock index forecasting. The data from a major emerging market, Kuala Lumpur Stock Exchange, are applied as a case study. Based on the rescaled range analysis, a backpropagation neural network is used to capture the relationship between the technical indicators and the levels of the index in the market under study over time. Using different trading strategies, a significant paper profit can be achieved by purchasing the indexed stocks in the respective proportions. The results show that the neural network model can get better returns compared with conventional ARIMA models. The experiment also shows that useful predictions can be made without the use of extensive market data or knowledge. The paper, however, also discusses the problems associated with technical forecasting using neural networks, such as the choice of "time frames" and the "recency" problems.

scholarly journals A Raging Bull or a Long-term Speculative Bubble? The Puzzling Case of the Karachi Stock Exchange

2016 ◽  
Vol 55 (2) ◽  
pp. 79-93 ◽  
Author(s):  
Ehsan Ahmed ◽  
J. Barkley Rosser Jr. ◽  
Jamshed Y. Uppal
Keyword(s):  
Stock Prices ◽  
Regime Switching ◽  
Stock Exchange ◽  
Range Analysis ◽  
Policy Makers ◽  
Speculative Bubbles ◽  
Rescaled Range ◽  
Rescaled Range Analysis ◽  
Market Regime ◽  
Fundamental Values

The objective of the study is to examine possible presence of nonlinear speculative bubbles in the Karachi Stock Exchange (KSE). Bubbles are argued to exist when there are substantial deviations of market value from the estimated fundamental values. We estimate a series of fundamental values from a four variable Vector Autoregression Model (VAR) using the main KSE100 index along with measures of world stock prices, the Pakistani exchange rate, and the Pakistani short-term interest rate. Residuals of this estimated fundamental time series are then tested for possible speculative deviations using a Hamilton regime switching test and a rescaled range Hurst coefficient test, with a further test for nonlinearity beyond the ARCH effects using the BDS statistic. For all of these, we reject the null hypotheses of the absence of speculative bubbles and nonlinearities beyond ARCH in these series. While these results suggest the possible presence of such bubbles, we note methodological limits on proving that due to the problem of mis-specified fundamentals. We further discuss some characteristics of the regulatory environment that may make it especially susceptible to such phenomena and may be considered by the policy-makers for the attenuation of speculative and manipulative behaviour. Keywords: Bubble, Pakistan, Stock Market, Regime Switching, Rescaled Range Analysis, Nonlinearity

scholarly journals Examining the Impact of Structural Breaks on Long Memory of Stock Returns: Evidence from Bombay Stock Exchange of India Long Memory

2020 ◽  
Vol 19 (1) ◽  
Author(s):  
Anju Bala
Keyword(s):  
Stock Returns ◽  
Long Memory ◽  
Hurst Exponent ◽  
Structural Breaks ◽  
Stock Exchange ◽  
Subprime Crisis ◽  
Range Analysis ◽  
Rescaled Range Analysis ◽  
Daily Stock Returns ◽  
The Impact

This study examines the presence of long memory of Stock Returns in India with reference to structural breaks. The study used the Hurst Exponent in Rescaled Range Analysis as proposed by Lo (1991) to measure the presence of long memory on daily stock returns of the Bombay Stock Exchange Indices from January 2000 to December 2017. The analysis indicates that all indices show long memory effects. It is also evident that all indices exhibit long memory effect in the pre and post subprime crisis period. These findings are consistent with Bhattacharya and Bhattacharya (2018), Jha et al.(2018), Goudarzi (2010) and Lillo and Farmer (2004). KEYWORDS: Long Memory, Hurst exponent, Market Efficiency. Structural Breaks

scholarly journals Investigating Chaos on the Johannesburg Stock Exchange

2016 ◽  
Vol 8 (5(J)) ◽  
pp. 56-67
Author(s):  
Prince Kwasi Sarpong ◽  
Mabutho Sibanda ◽  
Merle Holden
Keyword(s):  
Chaotic Dynamics ◽  
Stock Exchange ◽  
Range Analysis ◽  
Johannesburg Stock Exchange ◽  
Rescaled Range ◽  
Rescaled Range Analysis ◽  
The Mean ◽  
Top 40 ◽  
Fractal Market Hypothesis ◽  
Bds Test

This study investigates the existence of chaos on the Johannesburg Stock Exchange (JSE) and studies three indices namely the FTSE/JSE All Share, FTSE/JSE Top 40 and FTSE/JSE Small Cap. Building upon the Fractal Market Hypothesis to provide evidence on the behavior of returns time series of the above mentioned indices, the BDS test is applied to test for non-random chaotic dynamics and further applies the rescaled range analysis to ascertain randomness, persistence or mean reversion on the JSE. The BDS test shows that all the indices examined in this study do not exhibit randomness. The FTSE/JSE All Share Index and the FTSE/JSE Top 40 exhibit slight reversion to the mean whereas the FTSE/JSE Small Cap exhibits significant persistence and appears to be less risky relative to the FTSE/JSE All Share and FTSE/JSE Top 40contrary to the assertion that small cap indices are riskier than large cap indices.

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

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 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
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