Multifractal approach for stock market inefficiency
5 Feb 2019 The cryptocurrency market thus already shows notable adherence to the efficient market A multifractal approach for stock market inefficiency. 3 Jul 2013 Exchange rate risk and Philippine stock returns: before and after the Asian financial A multifractal approach for stock market inefficiency. Greece has changed the degree of market development (efficiency) by studying time-varying global Hurst exponents. implications on the degree of development of stock markets. Secondly, we innovate in using a “rolling sample” approach, instead of analyzing If multifractality is present in stock returns then multifractal. 24 Dec 2015 Keywords: East Asian; Efficiency; Multifractal; Stock markets. 1. Introduction The traditional approach to arguing for weak-form effi- ciency is
But in contrast to this approach, a plethora of research finds evidence of stock market empirical data being multifractal in nature, where a single scaling exponent
Multifractal Analysis and Local Hoelder Exponents Approach to Detecting Stock Markets Crashes I. A. Agaev 1, Yu. A. Kuperin 2 1 Division of Computational Physics, Saint-Petersburg State University 198504,Ulyanovskaya st., 1, Saint-Petersburg, Russia E - mail: ilya-agaev@yandex.ru This paper investigates the dynamic relationship between market efficiency, liquidity, and multifractality of Bitcoin. We find that before 2013 liquidity is low and the Hurst exponent is less than 0.5, indicating that the Bitcoin time series is anti-persistent. After 2013, as liquidity increased, the Hurst exponent rose to approximately 0.5, improving market efficiency. For several periods triggered an intense analysis of the existing data. The multifractal approach has been successful to describe foreign exchange markets as well as stock markets [9]. Multifractal analysis of a set of data can be performed in two dierent ways, ana-lyzingeither the statistics or the geometry. A statistical approach consists of dening Our findings show that the stock markets are multifractal and mostly long-term persistent. "Stock market efficiency analysis using long spans of Data: A multifractal detrended fluctuation approach," Finance Research Letters, Elsevier, vol. 28(C), pages 398 "Identifying periods of market inefficiency for return predictability," Applied
This paper investigates the multifractality and efficiency of stock markets in eight using long spans of Data: A multifractal detrended fluctuation approach.
moments approach for estimating multifractal parameters in Markov-switching efficiency of stock markets (middle east and north african stock market and
12 Jun 2019 We introduce a novel approach to multifractal data in order to achieve to model time-varying inefficiency in stock markets using generalized
26 Feb 2019 find that the multifractal degree is related to market efficiency in a non-linear manner. A multifractal approach for stock market inefficiency.
Wang, GJ, C Xie, M Lin and HE Stanely [2017] Stock market contagion during the global financial crisis: A multiscale approach. Finance Research Letters, 22, 163–168. Crossref, ISI, Google Scholar; Weron, A and R Weron [2000] Fractal market hypothesis and two power-laws. Chaos Solitons Fractals, 11, 289–296.
In order to test whether multifractality is associated with the degree of market inefficiency, we employ a binary dependent variable model—see Ref. [46, pp. 663–719]. The dependent variable in our model is a binary variable that takes value one if the stock market under analysis is an emerging market and zero if it is a developed market. Request PDF | A multifractal approach for stock market inefficiency | In this paper, the multifractality degree in a collection of developed and emerging stock market indices is evaluated.
This paper investigates the multifractality and efficiency of stock markets in eight developed (Canada, France, Germany, Italy, Japan, Switzerland, UK and USA) and two emerging (India and South Africa) countries for which long span of data, covering over or nearly a century in each case, is available to avoid sample bias. Wang, GJ, C Xie, M Lin and HE Stanely [2017] Stock market contagion during the global financial crisis: A multiscale approach. Finance Research Letters, 22, 163–168. Crossref, ISI, Google Scholar; Weron, A and R Weron [2000] Fractal market hypothesis and two power-laws. Chaos Solitons Fractals, 11, 289–296. By quantifying the market inefficiency using a “multifractality degree”, we find that the futures markets are more inefficient in the long-term than in the short-term. Furthermore, we investigate the “stylized fact” of volatility dynamics on market efficiency. The simulating and empirical results indicate that volatility clustering