The Empirical Analysis of Long-term Memory in Stock Market

By Zeng Zhen-yu. 2003

259 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/c96feeb85b120df920a3f7c6f2c108efe88e40ee

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

Microeconomic Models for Long Memory in the Volatility of Financial Time Series (2001, background): “The parameter is small, and even very small if we are considering daily series, but we have seen in equation (55) that this parameter is constrained.”
The Long Memory of the Efficient Market (2003, unknown): “In fact, Lo [3] showed that even for a short-memory process, such as a simple AR(1) process, the classical R/S test does not reject the null hypothesis of short-memory.”
Tests of Long Memory: A Bootstrap Approach (2005, unknown): “More recently Lo (1991) discusses the lack of robustness of the R/S statistic in the presence of short memory or heteroskedasticity.”
Long range dependence in financial markets (2005, unknown): “Such tests have been criticized by Lo [42] who pointed out that, after accounting for short range dependence, they might yield a different result and proposed a modified test statistic.”
Estimating fractal dimension using stable distributions and exploring long memory through ARFIMA models in Athens Stock Exchange (2001, methodology): “The Autoregressive Fractally Integrated Moving Average (ARFIMA) model provides an appropriate framework ± Mandelbrot (1977), Granger and Joyeux (1980), Hosking (1981), Lo (1991) ± for analysis of the long-term dependence structure of a time series.”
Stochasticity, nonlinearity and forecasting of streamflow processes (2006, methodology): “, the Lo’s modified R/S test (Lo, 1991), and the GPH test (Geweke and Porter-Hudak, 1983).”
On non-Gaussianity and dependence in financial time series: a nonextensive approach (2005, methodology): “Looking at a stock market index time series plot such as figure 1 one is almost induced to make an analogy with random walks. Considering the independence of variables and the nonexistence of memory throughout all process, like Bachelier (1900) did when he introduced his biased random walk model, we”
Multi-scaling in finance (2007, background): “Lo (1991) suggested a modified version of the R/S analysis that can detect long-term memory in the presence of short-term dependence (Moody and Wu 1996).”
How Markets Slowly Digest Changes in Supply and Demand (2008, unknown): “This property has been verified by many authors on many different financial time series (for example, Mandelbrot [1963], Lux [1996], Gopikrishnan et al.”
Long memory and regime switching: A simulation study on the Markov Regime-Switching ARFIMA model (2015, unknown): “Taking {yt} as an example, the corresponding R/S statistic is defined as: QT = 1 σ̂T (q) [ max 1≤k≤T k∑ t=1 (yt − ȳ)− min 1≤k≤T k∑ t=1 (yt − ȳ) ] (1) 5 where ȳ = (1/T ) ∑T t=1 yt, and σ̂T (q) is the square root of the Newey-West estimate of the long run variance with bandwidth q. Lo (1991) shows ”
An empirical investigation of the usefulness of ARFIMA models for predicting macroeconomic and financial time series (2006, methodology): “…evidence has been reported in the context of comparing one or two classes of estimators/tests, such as rescaled range (RR) type estimators (as introduced by Hurst (1951) and modified by Lo (1991), for example) and log periodogram regression estimators due to Geweke and Porter-Hudak (GPH: 1983).”
The Impact of Heterogeneous Trading Rules on the Limit Order Book and Order Flows (2007, background): “Real markets show a very long range volatility autocorrelation (Lo (1991)). Nonetheless, our model only shows very long term memory when the chartist component is activated. Hence, we not only observe a direct relationship between the chartist component and large returns but also detect that long me”
On discriminating between long-range dependence and changes in mean (2006, background): “That research was elaborated on by Giraitis, Kokoszka and Leipus [16] who showed that several statistics akin to the modified R/S statistic of Lo [31] diverge to infinity under either long-range dependence or weak dependence with change-points.”
Rescaled variance and related tests for long memory in volatility and levels (2003, unknown): “It should be noted that for the special case of the AR(1) model, Andrews (1991) proposed a formula for the optimal choice of q. Lo (1991) showed that Andrews' formula works well for the modiÿed R/S test in cases of = 0 (then optimal q = 0) and = 0:5.”
Long memory in stock returns: some international evidence (2002, methodology): “Interestingly, Lobato and Savin (1997) ®nd some evidence of long memory in the squared return data, which supports the conclusions of Ding et al. (1993). This paper makes two main contributions.”
The Evolution of Stock Market Efficiency Over Time: A Survey of the Empirical Literature (2011, methodology): “To accommodate the changing degree of market efficiency over time, Lo (2004) proposes a new version of the EMH derived from evolutionary principles. Our discussion on the AMH borrows heavily from Lo (2004, 2005). With the issue of rationality in human behaviour at the heart of the controversy betwee”
Modeling and predicting the CBOE market volatility index (2014, methodology): “Finally, Table 1 also displays the rescaled range (R/S) and rescaled variance (V/S) tests for long memory by Lo (1991) and Giraitis, Kokoszka, Leipus and Teyssière (2003), respectively.”
No Arbitrage Without Semimartingales (2009, methodology): “First, price processes which are not semimartingales are appearing more regularly in the empirical literature estimating stock price processes (see Lo [14] and references therein), and our methods would provide tools that can be used to determine whether these more general processes are consistent w”
Dealing with Structural Breaks (2005, methodology): “But this is also exactly the basis of the popular rescaled range procedure used to test the null hypothesis of short-memory versus the alternative of long memory (see, in particular, Hurst, 1951, Mandelbrot and Taqqu, 1979, Bhattacharya et al., 1983, and Lo, 1991).”