scholarly journals Crash Diagnosis and Price Rebound Prediction in NYSE Composite Index Based on Visibility Graph and Time-Evolving Stock Correlation Network

Entropy ◽  
2021 ◽  
Vol 23 (12) ◽  
pp. 1612
Author(s):  
Yuxuan Xiu ◽  
Guanying Wang ◽  
Wai Kin Victor Chan
Keyword(s):  
Stock Market ◽  
Power Law ◽  
Stock Exchange ◽  
Composite Index ◽  
Detection Algorithm ◽  
Value Theory ◽  
Visibility Graph ◽  
Stock Index ◽  
Power Law Model ◽  
Market Crashes

This study proposes a framework to diagnose stock market crashes and predict the subsequent price rebounds. Based on the observation of anomalous changes in stock correlation networks during market crashes, we extend the log-periodic power-law model with a metric that is proposed to measure network anomalies. To calculate this metric, we design a prediction-guided anomaly detection algorithm based on the extreme value theory. Finally, we proposed a hybrid indicator to predict price rebounds of the stock index by combining the network anomaly metric and the visibility graph-based log-periodic power-law model. Experiments are conducted based on the New York Stock Exchange Composite Index from 4 January 1991 to 7 May 2021. It is shown that our proposed method outperforms the benchmark log-periodic power-law model on detecting the 12 major crashes and predicting the subsequent price rebounds by reducing the false alarm rate. This study sheds light on combining stock network analysis and financial time series modeling and highlights that anomalous changes of a stock network can be important criteria for detecting crashes and predicting recoveries of the stock market.

META-ANALYSIS ON AMERICAN PRESIDENTIAL ELECTION - 2016 AND AMERICAN STOCK MARKET

2020 ◽  
Vol 38 (1) ◽  
Author(s):  
Farhan Ahmed ◽  
Salman Bahoo ◽  
Sohail Aslam ◽  
Muhammad Asif Qureshi
Keyword(s):  
Content Analysis ◽  
Stock Market ◽  
Event Study ◽  
Presidential Election ◽  
Republican Party ◽  
Stock Exchange ◽  
Meta Analysis ◽  
Composite Index ◽  
Stock Index ◽  
Political Event

This paper aims to analyze the efficient stock market hypothesis as responsive to American Presidential Election, 2016. The meta-analysis has been done combining content analysis and event study methodology. The all major newspapers, news channels, public polls, literature and five important indices as Dow Jones Industrial Average (DJIA), NASDAQ Stock Market Composit Indexe (NASDAQ-COMP), Standard & Poor's 500 Index (SPX-500), New York Stock Exchange Composite Index (NYSE-COMP) and Other U.S Indexes-Russell 2000 (RUT-2000) are critically examined and empirically analyzed. The findings from content analysis reflect that stunned winning of Mr Trump from Republican Party worked as shock for American stock market. From event study, findings confirmed that all the major indices reflected a decline on winning of Trump and losing of Ms. Clinton from Democratic. The results are supported empirically and practically through the political event like BREXIT that resulted in shock to Global stock index and loss of $2 Trillion.

scholarly journals VOLATILITAS INDEKS KOMPOSIT PASAR MODAL ASEAN-3

2020 ◽  
Vol 5 (4) ◽  
Author(s):  
Anhar Fauzan Priyono
Keyword(s):  
Stock Market ◽  
Stock Exchange ◽  
Exchange Rate Regime ◽  
Composite Index ◽  
Stock Index ◽  
Movement Behavior ◽  
Stock Market Index ◽  
Monthly Basis ◽  
Volatility Model ◽  
Aggregate Investment

Rapid integration between domestic and world economy in the last decade has been a major issue. For Indonesia, the situation has been accelerated by the adoption of floating exchange rate regime in 1997, also with the development of Indonesia stock exchange. One notable financial variable that often exposed to external shocks is stock market index. This research will analyzed the behavior of 3 major stock market indices in ASEAN, those are Jakarta Composite Index (JCI), Kuala Lumpur stock index (KLSE), and Singapore stock index (STI). The employment of volatility model is chosen to figured the behavior of those 3 indices, and to analyze the aggregate investment in each stock market. Observation will be based upon monthly basis, from 2010 until 2015.The findings in this research are (i) similarity in the movement behavior of ASEAN-3 stock market indices, (ii) Indonesia stock market shows the highest aggregate investment return relative to Malaysia and Singapore, (iii) Singapore stock market shows the lowest aggregate investment risk relative to Indonesia and Malaysia, as the representation of more developed stock market.

scholarly journals Analisa Korelasi Return Indeks – Indeks Saham terhadap Indeks Harga Saham Gabungan pada Bursa Efek Indonesia

2015 ◽  
Vol 6 (2) ◽  
pp. 330 ◽  
Author(s):  
Mulyono Mulyono
Keyword(s):  
Stock Market ◽  
Stock Price ◽  
Price Index ◽  
Stock Exchange ◽  
Composite Index ◽  
Stock Index ◽  
Stock Trading ◽  
Close Relationship ◽  
Coefficient Corrélation ◽  
Stock Price Index

Stock market generally has the stock price index that measures the performance of stock trading, the Indonesia Stock Exchange has a stock price index that is widely known as Jakarta Composite Index (IHSG). During its development, the Indonesia Stock Exchange has many alternative indexes that measure the performance of stock trading. Research that is to be conducted on the correlation between return of the stock index listed in Indonesia Stock Exchange and return of Jakarta Composite Index. Return stock index listed on the Indonesia Stock Exchange, namely, LQ45 Index, Jakarta Islamic Index (JII), KOMPAS100 Index, BISNIS-27 Index, PEFINDO25 Index and SRI-KEHATI Index, has a close relationship with the return Jakarta Composite,Index which is a reflection of the movement of all existing stock in the market. Return of stocks index that have the highest coefficient correlation is KOMPAS100 In dex, which have return index coefficient correlation is 0.949, thus KOMPAS100 Index that consisting of 100 stocks, based on the results of the study can be used as an alternative investment to get a return that is at least equal or close to the yield given by Jakarta Composite Index(IHSG) that consists of 445 stocks

Do Indian stock market sentiments impact contemporaneous returns?

2018 ◽  
Vol 7 (3) ◽  
pp. 332-346
Author(s):  
Divya Aggarwal ◽  
Pitabas Mohanty
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Temporal Dynamics ◽  
Stock Exchange ◽  
Principal Component ◽  
Stock Index ◽  
Content Type ◽  
Investor Sentiments ◽  
Indian Stock Market ◽  
The Impact

Purpose The purpose of this paper is to analyse the impact of Indian investor sentiments on contemporaneous stock returns of Bombay Stock Exchange, National Stock Exchange and various sectoral indices in India by developing a sentiment index. Design/methodology/approach The study uses principal component analysis to develop a sentiment index as a proxy for Indian stock market sentiments over a time frame from April 1996 to January 2017. It uses an exploratory approach to identify relevant proxies in building a sentiment index using indirect market measures and macro variables of Indian and US markets. Findings The study finds that there is a significant positive correlation between the sentiment index and stock index returns. Sectors which are more dependent on institutional fund flows show a significant impact of the change in sentiments on their respective sectoral indices. Research limitations/implications The study has used data at a monthly frequency. Analysing higher frequency data can explain short-term temporal dynamics between sentiments and returns better. Further studies can be done to explore whether sentiments can be used to predict stock returns. Practical implications The results imply that one can develop profitable trading strategies by investing in sectors like metals and capital goods, which are more susceptible to generate positive returns when the sentiment index is high. Originality/value The study supplements the existing literature on the impact of investor sentiments on contemporaneous stock returns in the context of a developing market. It identifies relevant proxies of investor sentiments for the Indian stock market.

scholarly journals Realita Dinamika Pasar: Studi Intensif Distingsi Syariah Konvensional

2019 ◽  
Vol 3 (2) ◽  
pp. 190-202
Author(s):  
Yadi Nurhayadi ◽  
Daram Heriansyah ◽  
Eva Susanti ◽  
Siti Azizziah Azzahra
Keyword(s):  
Multivariate Analysis ◽  
Stock Exchange ◽  
Composite Index ◽  
Stock Index ◽  
Weak Correlation ◽  
Company Stock ◽  
Regression Correlation

The research confirm the differences between sharia company stock index and conventional company stock index as the issuer at The Indonesia Stock Exchange. This research is a continuation of a series of previous studies by Nurhayadi et al earlier on the comparison between the sharia market and the conventional market. The Data consist of Jakarta Stock Exchange (JSX) Composite Index (Indeks Harga Saham Gabungan (IHSG)), Jakarta Stock Exchange Liquid Index (LQ45), Jakarta Islamic Index (JII), Indonesia Sharia Stock Index (ISSI), ten companies of sharia issuer, and ten companies of conventional issuer. There are seven scenarios based on bivariate and multivariate analysis that conducted regression, correlation, and determination test to know whether conventional company influence on sharia company. The research scenarios cover five years data from January 2014 to December 2018. The result confirms that the fluctuation of conventional issuer's stocks is different from the fluctuation of sharia issuer's stocks. Conventional issuers have a weak correlation with sharia issuers. This condition implies that between the conventional market and the Islamic market there is no correlation.

scholarly journals ANALISIS PENGARUH INDEKS HARGA SAHAM GABUNGAN REGIONAL ASIA TERHADAP INDEKS HARGA SAHAM GABUNGAN INDONESIA

2018 ◽  
Vol 1 (2) ◽  
pp. 148
Author(s):  
Widodo Widodo
Keyword(s):  
South Korea ◽  
Significant Influence ◽  
Stock Exchange ◽  
Composite Index ◽  
Stock Index ◽  
Kuala Lumpur ◽  
Korea Strait ◽  
Independent Variables

ABSTRACTThe aims of this research is to analyze the influence of NIKKEI 225 Index (^N225), HANG SENG Index (^HSI), KOSPI Index (^KS11), Strait Times Index (^STI), and Kuala Lumpur Stock Exchange (^KLSE) simultaneously and partially in Jakarta Composite Index (^JKSE) during 2009 to 2017. Method of multiple linier regression with significant level 0,05 using STATA 10 program. The populations and samples was used this research is stock index on ASIA regional (NIKKEI 225 (Japan), HANG SENG Index (Hongkong), KOSPI (South Korea), Strait Times Index (Singapore), Kuala Lumpur Stock Exchange (Malaysia), and Jakarta Composite Index (Indonesia)) was conducted during January 2009 to May 2017. Results of this research simultaneously model for all independent variables are influence to dependent variable. However, parcially model ^N225, ^KS11 and ^KLSE variables positive and significant influence to ^JKSE variable. Whereas ^HSI and ^STI variable are not effect to ^JKSE variable during January 2009 to May 2017.Keywords: JKSE; N225; HSI; KS11; STI; KLSE.

In Search of Stock Market Proxy to Calculate Systematic Risk (Beta) of Stocks in Indonesia Stock Exchange

2020 ◽  
Vol 29 (2) ◽  
pp. 80-88
Author(s):  
Mochammad Chabachib
Keyword(s):  
Stock Market ◽  
Real World ◽  
Stock Price ◽  
Price Index ◽  
Stock Exchange ◽  
The Other ◽  
Stock Index ◽  
Market Return ◽  
Stock Market Return ◽  
Stock Index Returns

The calculation of beta stock in Indonesia is still debatable to this day. Though many researchers who have used sophisticated methods mathematically, the assumptions applied in developing the methods are impossible to happen in the real world, such as the ability of stock market return the day after (lead) affects the market return today. This study was conducted to assess the stock price index in Indonesia Stock Exchange that can be used as a proxy of stock market in Indonesia. The results of this study showed that there was a gap between beta stocks counted with JCI return as a market proxy with beta stocks counted with index returns of LQ-45, SRI-KEHATI, PEFINDO-25, BISNIS-27, IDX-30 and KOMPAS-100. This study has also found that the beta counted by using KOMPAS-100 return produced the smallest standard error of the estimate (SEE) that it was more applicable compared to the other stock index returns.

Prediction of Bubbles, Crashes, and Antibubbles

2017 ◽  
Author(s):  
Didier Sornette
Keyword(s):  
Stock Market ◽  
Case Studies ◽  
Power Law ◽  
Statistical Tests ◽  
Statistical Significance ◽  
Large Market ◽  
Simple Power ◽  
Market Crashes ◽  
Successes And Failures

This chapter examines how to predict stock market crashes and other large market events as well as the limitations of forecasting, in particular in terms of the horizon of visibility and expected precision. Several case studies are presented in detail, with a careful count of successes and failures. After providing an overview of the nature of predictions, the chapter explains how to develop and interpret statistical tests of log-periodicity. It then considers the concept of an “antibubble,” using as an example the Japanese collapse from the beginning of 1990 to the present. It also describes the first guidelines for prediction, a hierarchy of prediction schemes that includes the simple power law, and the statistical significance of the forward predictions.

scholarly journals Interdependence and Risk Comparison of Slovak, Hungarian and Polish Stock Markets: Policy and Managerial Implications

2019 ◽  
Vol 69 (2) ◽  
pp. 273-287 ◽  
Author(s):  
Florin Aliu ◽  
Besnik Krasniqi ◽  
Adriana Knapkova ◽  
Fisnik Aliu
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Markets ◽  
Stock Exchange ◽  
Weighted Average ◽  
Stock Index ◽  
Risk Level ◽  
Average Return ◽  
Monetary System ◽  
Managerial Implications

Risk captured through the volatility of stock markets stands as the essential concern for financial investors. The financial crisis of 2008 demonstrated that stock markets are highly integrated. Slovakia, Hungary and Poland went through identical centralist economic arrangement, but nowadays operate under diverse stock markets, monetary system and tax structure. The study aims to measure the risk level of the Slovak Stock Market (SAX index), Budapest Stock Exchange (BUX index) and Poland Stock Market (WIG20 index) based on the portfolio diversification model. Results of the study provide information on the diversification benefits generated when SAX, BUX and WIG20 join their stock markets. The study considers that each stock index represents an independent portfolio. Portfolios are built to stand on the available companies that are listed on each stock index from 2007 till 2017. The results of the study show that BUX generates the lowest risk and highest weighted average return. In contrast, SAX is the riskiest portfolio but generates the lowest weighted average return. The results find that the stock prices of BUX have larger positive correlation than the stock prices of SAX. Moreover, the highest diversification benefits are realized when Portfolio SAX joins Portfolio BUX and the lowest diversification benefits are achieved when SAX joins WIG20.

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