Permutation entropy and statistical analysis of the historical evolution of the Mexican stock market index

2022 ◽  
Author(s):  
M. Rodríguez-Achach ◽  
A. Suárez-Solís ◽  
A. R. Hernández Montoya ◽  
J. E. Escalante-Martínez ◽  
C. Calderón-Ramón
Keyword(s):  
Stock Market ◽  
Time Window ◽  
Stock Index ◽  
Permutation Entropy ◽  
Stock Market Index ◽  
Statistical Tools ◽  
Efficient Market ◽  
Market Index ◽  
Before And After ◽  
Year 2000

The objective of this work is to analyze the Indice de Precios y Cotizaciones (IPC), which is the Mexican stock market index, by using several statistical tools in order to study the tendencies that can shed light on the evolution of the IPC towards a more efficient market. The methodology used is to apply the statistical tools to the Mexican index and compare the results with a mature and well-known market index such as the Dow Jones Industrial Average (DJIA). We employ an autocorrelation analysis, and the volatility of the indexes, applied to the daily returns of the closing price on a moving time window during the studied period (1980–2018). Additionally, we perform an order three permutation entropy analysis, which can quantify the disorder present in the time series. Our results show that there is evidence that the IPC has become more mature since its creation and that it can be considered an efficient market since around year 2000. The behavior of the several techniques used shows a similar behavior to the DJIA which is not observed before that year. There are some limitations mainly because there is no high frequency data that would permit a more detailed analysis, specifically in the periods before and after a crisis is located. Our conclusion is that since around the year 2000, the Mexican stock index displays the typical behavior of other mature markets and can be considered as one.

scholarly journals The Role of Gold Prices and Interest Rate in Stock Index: Insights from Vietnam by Using the Autoregressive Distributed Lag Approach

2020 ◽  
Vol 12 (1) ◽  
pp. 178
Author(s):  
Le Thi Minh Huong ◽  
Phan Minh Trung
Keyword(s):  
Interest Rate ◽  
Stock Market ◽  
Interest Rates ◽  
Stock Index ◽  
Stock Market Index ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Market Index ◽  
Long Run ◽  
Short Run

This study aimed to determine the impact of domestic gold prices, interest rates in the stock market index (VNI) in Vietnam for the period of January 2009 to December 2018. This study employed the Autoregressive Distributed Lag (ARDL) to check the association of Independent variable gold prices and the interest rate on the dependent variable stock market index. The results show a close correlation together in the long-run. The Vietnam stock index is adversely affected by fluctuations in the credit market in the short-run. We observed that domestic gold prices and interest rates have one-way causal relations to the stock price index. Similarly, interest rates were causal for gold prices and still not yet had any particular direction. The adjustment in the short-run moves the long-run equilibrium, although the change is quite slow.

scholarly journals Linkages Between Brent Oil Price And Iran Stock Market: New Evidence From The Corona Pandemic

2021 ◽  
Author(s):  
Vida Varahrami ◽  
Masoumeh Dadgar
Keyword(s):  
Stock Market ◽  
Oil And Gas ◽  
Causal Effect ◽  
Oil Prices ◽  
Jel Classification ◽  
Oil Price ◽  
Stock Index ◽  
Impulse Response Functions ◽  
Stock Market Index ◽  
Market Index

Abstract This article reviews the relationship between the oil market and the stock market during the Corona outbreak. This study aims to analyze the stock market and the effect of oil prices on this market during the corona pandemic. The hypothesis of this paper is whether while oil prices shocks happen due to business cycle fluctuations and some other reasons like political reasons, occur; The correlations between changes in Brent oil prices and stock market indices tend to be affected by named corona indexes. Forecasting the stock market in each period has been difficult and the value of stock index has been affected by various factors. Among these factors has been the oil and gas sector, especially in countries dependent on the revenue from their sales. On the other hand, the outbreak of Covid-19 pandemic has led to profound changes in both areas. This study examines relationship between Brent oil price and Iran stock market Index during the outbreak of corona pandemic. Research method is, vector autoregression model (VAR) which using daily data covering the period from February 20, 2020 to August 21,2020. The findings of this study suggest that a negative causal effect from Brent oil price changes to the Iran stock market Index. Also, the results of impulse response functions and variance decompositions showed that some corona pandemic indicators have significant effects on the stock index.JEL Classification: I18, E44, Q4, C5

scholarly journals The impact of GST implementation on the Malaysian stock market index volatility

2019 ◽  
Vol 26 (1) ◽  
pp. 17-33
Author(s):  
Razali Haron ◽  
Salami Mansurat Ayojimi
Keyword(s):  
Stock Market ◽  
Global Financial Crisis ◽  
Stock Index ◽  
Empirical Estimation ◽  
Stock Market Index ◽  
Content Type ◽  
Noticeable Increase ◽  
Market Index ◽  
The Government ◽  
The Impact

Purpose The purpose of this paper is to examine the impact of the Goods and Service Tax (GST) implementation on Malaysian stock market index. Design/methodology/approach This study used daily closing prices of the Malaysian stock index and futures markets for the period ranging from June 2009 to November 2016. Empirical estimation is based on the generalised autoregressive conditional heteroscedasticity (1, 1) model for pre- and post-announcement of the GST. Findings Result shows that volatility of Malaysian stock market index increases in the post-announcement than in the pre-announcement of the GST which indicates that educative programs employed by the government before the GST announcement did not yield meaningful result. The volatility of the Malaysian stock market index is persistent during the GST announcement and highly persistent after the implementation. Noticeable increase in post-announcement is in support with the expectation of the market about GST policy in Malaysia. Practical implications The finding of this study is consistent with expectation of the market that GST policy will increase the price of the goods and services and might reduce standard of living. This is supported by a noticeable increase in the volatility of the Malaysian stock market index in the post-announcement of GST which is empirically shown during the announcement and after the implementation of GST. Although the GST announcement could be classified as a scheduled announcement, unwillingness to accept the policy prevails in the market as shown by the increase in the market volatility. Originality/value Past studies on Malaysian stock market index volatility focus on the impact of Asian and global financial crisis whereas this study examines the impact of the GST announcement and implementation on the volatility of the Malaysian stock market index.

NONLINEARITIES AND GARCH INADEQUACY FOR MODELING STOCK MARKET RETURNS: EMPIRICAL EVIDENCE FROM LATIN AMERICA

2010 ◽  
Vol 15 (5) ◽  
pp. 713-724 ◽  
Author(s):  
Claudio A. Bonilla ◽  
Rafael Romero-Meza ◽  
Carlos Maquieira
Keyword(s):  
Stock Market ◽  
Latin American ◽  
Spillover Effects ◽  
Stock Index ◽  
Output Volatility ◽  
Stock Market Index ◽  
Market Returns ◽  
Stock Market Returns ◽  
Market Index ◽  
Data Generating Process

In this paper, we analyze the adequacy of using GARCH as the data-generating process to model conditional volatility of stock market index rates-of-return series. Using the Hinich portmanteau bicorrelation test, we find that a GARCH formulation or any of its variants fail to provide an adequate characterization for the underlying process of the main Latin American stock market indices. Policymakers need to be careful when using autoregressive models for policy analysis and forecast because the inadequacy of GARCH models has strong implications for the pricing of stock index options, portfolio selection, and risk management. In particular, measures of spillover effects and output volatility may not be correct when GARCH-type models are used to evaluate economic policy.

scholarly journals EPAK: A Computational Intelligence Model for 2-level Prediction of Stock Indices

2018 ◽  
Vol 13 (2) ◽  
pp. 268-279
Author(s):  
Li Tang ◽  
Ping He Pan ◽  
Yong Yi Yao
Keyword(s):  
Time Series ◽  
Stock Market ◽  
Prediction Model ◽  
Computational Intelligence ◽  
Financial Time Series ◽  
Extraction Procedure ◽  
Stock Index ◽  
Stock Market Index ◽  
Financial Time ◽  
Market Index

This paper proposes a new computational intelligence model for predicting univariate time series, called EPAK, and a complex prediction model for stock market index synthesizing all the sector index predictions using EPAK as a kernel. The EPAK model uses a complex nonlinear feature extraction procedure integrating a forward rolling Empirical Mode Decomposition (EMD) for financial time series signal analysis and Principal Component Analysis (PCA) for dimension reduction to generate information-rich features as input to a new two-layer K-Nearest Neighbor (KNN) with Affinity Propagation (AP) clustering for prediction via regression. The EPAK model is then used as a kernel for predicting each of all the sector indices of the stock market. The sector indices predictions are then synthesized via weighted average to generate the prediction of the stock market index, yielding a complex prediction model for the stock market index. The EPAK model and the complex prediction model for stock index are tested on real historical financial time series in Chinese stock index including CSI 300 and ten sector indices, with results confirming the effectiveness of the proposed models.

scholarly journals Developing a New Stock Index for Vietnam’s Securities Market

2014 ◽  
Vol 220 ◽  
pp. 60-78
Author(s):  
Huân Nguyễn Hữu
Keyword(s):  
Stock Market ◽  
Predictive Power ◽  
Securities Market ◽  
Stock Index ◽  
Stock Exchanges ◽  
Securities Markets ◽  
Stock Market Index ◽  
Market Index ◽  
Market Indexes ◽  
Research Show

Stock market index plays an important role as a measure of development of securities markets of a country or a region. Results of this empirical research show that in its 13 years of development, Vietnamese securities market indexes only had limited values because of their poor market representation and predictive power, implying the need to merge Hà Nội and HCMC stock exchanges. The research suggests a new set of stock market indexes to deal with shortcomings of existing indexes, thereby providing relevant entities with a new view on development of securities market in Vietnam.

scholarly journals MENGKAJI PERUBAHAN NILAI TUKAR RUPIAH DAN PASAR SAHAM

2008 ◽  
Vol 10 (4) ◽  
Author(s):  
Untoro Untoro ◽  
Priyo R. Widodo
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Stock Index ◽  
Stock Market Index ◽  
Vector Autoregressive ◽  
Market Index ◽  
Daily Data ◽  
Exchange Rate Movements ◽  
The Exchange Rate ◽  
The Relationship

This paper analyzes the relationship between the Exchange rate and the stock market in Jakarta, Singapore, Malaysia, Thailand, Philippine and Hongkong using a high frequency data. We applied the Vector Autoregressive method on the daily data covering 1 July 1997 to 30 June 2006.The analysis provides several results as follows: (i) the exchange rate movements is influenced by the regional and the Hongkong stock market index, except Thailand, (ii) Jakarta stock market index is influenced by the regional stock market except Thailand, (iii) the Rupiah rate influence the regional and Hongkong stock index, (iv) the Jakarta's stock market index is integrated to the regional stock market index. These results may be a usefull as an additional guidance to evaluate the Rupiah's exchange rate and the regional stock market movement in general.JEL Classification: C32, F31, G15                 Keywords: Stock, Vector Autoregressive, exchange rate.

scholarly journals DPP: Deep predictor for price movement from candlestick charts

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252404
Author(s):  
Chih-Chieh Hung ◽  
Ying-Ju Chen
Keyword(s):  
Stock Market ◽  
Stock Exchange ◽  
Extensive Study ◽  
Stock Index ◽  
Stock Market Index ◽  
Price Movement ◽  
Market Prices ◽  
Taiwan Stock Exchange ◽  
Market Index ◽  
Political Events

Forecasting the stock market prices is complicated and challenging since the price movement is affected by many factors such as releasing market news about earnings and profits, international and domestic economic situation, political events, monetary policy, major abrupt affairs, etc. In this work, a novel framework: deep predictor for price movement (DPP) using candlestick charts in the stock historical data is proposed. This framework comprises three steps: 1. decomposing a given candlestick chart into sub-charts; 2. using CNN-autoencoder to acquire the best representation of sub-charts; 3. applying RNN to predict the price movements from a collection of sub-chart representations. An extensive study is operated to assess the performance of the DPP based models using the trading data of Taiwan Stock Exchange Capitalization Weighted Stock Index and a stock market index, Nikkei 225, for the Tokyo Stock Exchange. Three baseline models based on IEM, Prophet, and LSTM approaches are compared with the DPP based models.

scholarly journals Stock Market Performance and the Term Structure of Credit Spreads

2006 ◽  
Vol 41 (4) ◽  
pp. 863-887 ◽  
Author(s):  
Andriy Demchuk ◽  
Rajna Gibson
Keyword(s):  
Stock Market ◽  
Stock Index ◽  
Credit Spreads ◽  
Business Climate ◽  
Stock Market Index ◽  
Past Performance ◽  
Leverage Ratio ◽  
The Past ◽  
Market Index ◽  
Stock Market Performance

AbstractWe build a structural two-factor model of default where the stock market index is one of the stochastic factors. We allow the firm to adjust its leverage ratio in response to changes in the business climate for which the past performance of the stock market index acts as a proxy. We assume that the firm's log-leverage ratio follows a mean-reverting process and that the past performance of the stock index negatively affects the firms target leverage ratio. We show that for most credit ratings our model may explain actual yield spreads better than other well-known structural credit risk models. Also, our model shows that the past performance of the stock index returns and the firm's assets beta have a significant impact on credit spreads. Hence, our model can explain why credit spreads may be different within the same credit rating groups and why spreads are lower during economic expansions and higher during recessions.

Sign in / Sign up

Export Citation Format

Share Document