scholarly journals Predicting Stock Market Indexes, Two Days In Advance, Using NewsInn Algorithm

2015 ◽  
Vol 5 (2) ◽  
pp. 308
Author(s):  
Radu Nicoara
Keyword(s):  
Stock Market ◽  
Sentiment Analysis ◽  
Stock Markets ◽  
News Article ◽  
World News ◽  
Opinion Extraction ◽  
Extraction Algorithm ◽  
Market Indexes

<p class="ber"><span lang="EN-GB">NewsInn is an A.I. Driven Algorithm that processes and conglomerates news from major news publications. It uses an opinion extraction algorithm to do a sentiment analysis on every news article. </span></p><p class="ber"><span lang="EN-GB">Considering that stock markets are heavily influenced be world news, we conducted a study to show the link between the detected sentiment inside the news, and the most used Stock Market Indexes: S&amp;P 500, Dow Jones and NASDAQ. Results showed an almost 70.00% accuracy in predicting market fluctuation two days in advance.</span></p>

scholarly journals Financial contagion and 2016 oil crisis: a factor analysis

2020 ◽  
Author(s):  
Turki Maya
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Principal Component ◽  
Financial Contagion ◽  
Market Returns ◽  
Component Structure ◽  
Stock Market Returns ◽  
Oil Crisis ◽  
Market Indexes ◽  
Variance Explained

<p>The paper tries to answer the following question: could the 2016 oil price crisis generate financial contagion among stock markets? </p> <p>The study period is composed of two sub-periods; a quiet one from 3/01/2012 to 01/08/2014 and turbulent one from 04/08/2014 to 25/05/2016. Raw data consists of daily international stock market indexes prices. The co-movements of the stock market returns are analyzed through a principal component analysis (PCA).</p> <p>The results revealed that the <em>KMO</em> index (Kaiser-Mayer-Olkin) is higher during the turbulent period than during the quiet one and that the proportion of variance explained by the first component during the turbulent period reached 35% while during the quiet one it represented only 26,7%.Regarding the component structure, for the turbulent period, three factors are able to explain the stock markets indexes movements while for the quiet period four factors are required. </p> <p>The findings give more credit to the thesis supporting the linkage between cross correlation and financial contagion and classify the 2016 oil crisis, as just a coupling episode and not an extreme one.</p>

scholarly journals A study of co-movements between U.S. and Latin American stock markets: A cross-bicorrelations perspective

DYNA ◽  
2016 ◽  
Vol 83 (196) ◽  
pp. 143-148 ◽  
Author(s):  
Semei Coronado-Ramirez ◽  
Omar Rojas-Altamirano ◽  
Rafael Romero-Meza ◽  
Francisco Venegas-Martínez
Keyword(s):  
Stock Market ◽  
Latin American ◽  
Stock Markets ◽  
Nonlinear Dependence ◽  
Standard And Poor's ◽  
Non Linear ◽  
Market Indexes

<p>This work applies a test that detects dependence between pairs of variables. The kind of dependence is a non-linear one, and the test is known as cross-bicorrelation, which is associated with Brooks and Hinich [1]. We study dependence periods between U.S. Standard and Poor's 500 (SP500), used as a benchmark, and six Latin American stock market indexes: Mexico (BMV), Brazil (BOVESPA), Chile (IPSA), Colombia (COLCAP), Peru (IGBVL) and Argentina (MERVAL). We have found windows of nonlinear dependence and comovement between the SP500 and the Latin American stock markets, some of which coincide with periods of crisis, leading to an interpretation of a possible contagion or interdependence.</p>

scholarly journals An empirical comparison of stock market bubbles

2021 ◽  
Vol 9 (4) ◽  
pp. 1286-1299
Author(s):  
Özge Korkmaz ◽  
Bilgin Bari ◽  
Zafer Adalı
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Emerging Market ◽  
High Growth ◽  
Capital Inflows ◽  
Market Values ◽  
Stock Market Bubbles ◽  
Foreign Capital Inflows ◽  
Rational Bubble ◽  
Market Indexes

Financial asset bubbles occur due to systematic and continuous differences between fundamental and market values. Due to high growth periods and foreign capital inflows, bubbles are also seen in stock market indexes, especially in emerging market economies. This study analyzes the existence of bubbles in BIST100, IDX COMPOSITE, BOVESPA, MDEX, NIFTY 50, SHANGAI, and S&P 500 stock markets for the period 2009:01-2021:06.  RADF, SADF, and GSADF tests are applied to detect bubbles on stock market closing prices. In addition, the emergence and demise dates of the bubbles are determined by employing the date-stamping method. The GSADF test gives more effective results and determines bubbles with different durations in all stock markets, except the S&P 500. The results reveal that the most inefficient market is IDX COMPOSITE, and S&P 500is the most efficient market. The analysis includes the S&P 500, the world's most liquid and most prominent stock market, for comparison. In this respect, bubbles occur more in emerging market exchanges. The findings also confirm the validity of the rational bubble law.

scholarly journals Global Equity Markets and International Diversification

2011 ◽  
Vol 2 (9) ◽  
Author(s):  
Javad Kashefi ◽  
Gilbert J. McKee
Keyword(s):  
Stock Market ◽  
Risk Reduction ◽  
Stock Markets ◽  
Equity Markets ◽  
International Diversification ◽  
Equity Returns ◽  
Efficient Frontiers ◽  
Risk Return ◽  
Coefficients Of Variation ◽  
Market Indexes

Interest in global investing has increased tremendously over the last several years. U.S. investors seek to reduce risk by diversifying globally. The risk reduction benefits hinge upon the relationships between U.S. stock market indexes and other international stock market indexes. Portfolio research studies have shown that adding new assets that have low correlation with those already held will enhance the risk to return ratio for the new portfolio. Global diversification may provide a similar risk reduction when an investors portfolio is expanded to include foreign securities. This study examines relationships between U.S. stock markets and world equity markets to investigate whether international diversification provides additional diversification benefits to U.S. investors.The data for this study include the annualized equity returns and standard deviations computed for 61 indexes (11 Morgan Stanley Capital International (MSCI) Indexes and 50 national market indexes that were calculated for the period January 1988 to November 2001. Nine portfolio diversification strategies are examined to obtain efficient frontiers. These portfolios are constructed based upon risk-reward ratios (coefficients of variation), systematic risk (beta) and using different MSCI International Market Indexes.Our analysis suggests that: (1) a portfolio constructed based on coefficients of variation of less than 2 (no index had a ratio of less than 1) as a criterion had the best result; (2) the domestic portfolio (S&P500) provided the second best risk-return to the investors; (3) among MSCI Indexes, FAREAST indexes had the worst performance as did China among the 50 countries; (4) the presumption that low correlations (less than 0.5) would be an attractive means of reducing the portfolio risk did not produce the best risk-return trade off; and (5) the size of the coefficients and long-term stability of the correlations between country indexes have increased.Finally, the efficient frontiers point of inflection for this study (January 1988-November 2001) for most of the portfolios occurred at more than 45 percent investment in U.S. market. This result is consistent with prior studies that found the point of inflection for a portfolio consisting of U.S. and foreign stock markets generally occurs at about 40 percent. Our result is dramatically different from the Sharma, Obar, and Moser (1996) study that concluded the point of inflection for their four portfolios occurred with only 10 percent invested in the U.S. market.

scholarly journals Financial contagion and 2016 oil crisis: a factor analysis

2020 ◽  
Author(s):  
Turki Maya
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Principal Component ◽  
Financial Contagion ◽  
Market Returns ◽  
Component Structure ◽  
Stock Market Returns ◽  
Oil Crisis ◽  
Market Indexes ◽  
Variance Explained

<p>The paper tries to answer the following question: could the 2016 oil price crisis generate financial contagion among stock markets? </p> <p>The study period is composed of two sub-periods; a quiet one from 3/01/2012 to 01/08/2014 and turbulent one from 04/08/2014 to 25/05/2016. Raw data consists of daily international stock market indexes prices. The co-movements of the stock market returns are analyzed through a principal component analysis (PCA).</p> <p>The results revealed that the <em>KMO</em> index (Kaiser-Mayer-Olkin) is higher during the turbulent period than during the quiet one and that the proportion of variance explained by the first component during the turbulent period reached 35% while during the quiet one it represented only 26,7%.Regarding the component structure, for the turbulent period, three factors are able to explain the stock markets indexes movements while for the quiet period four factors are required. </p> <p>The findings give more credit to the thesis supporting the linkage between cross correlation and financial contagion and classify the 2016 oil crisis, as just a coupling episode and not an extreme one.</p>

Pemodelan Data Time Series Garch(1,1) Untuk Pasar Saham Indonesia

2015 ◽  
Vol 11 (1) ◽  
pp. 13
Author(s):  
Elfa Rafulta ◽  
Roni Tri Putra
Keyword(s):  
Time Series ◽  
Stock Market ◽  
Stock Markets ◽  
Financial Data ◽  
International Stock Markets

This paper introduced a method pengklusteran for financial data. By using the model Heteroskidastity Generalized autoregressive conditional (GARCH), will be estimated distance between the stock market using GARCH-based distance. The purpose of this method is mengkluster international stock markets with different amounts of data.

Momentum Effect in Stock Market: Empirical Evidence from Pakistan Stock Exchange

2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Shahid Rasheed ◽  
Umar Saood ◽  
Waqar Alam
Keyword(s):  
Stock Market ◽  
Empirical Evidence ◽  
Stock Markets ◽  
Stock Exchange ◽  
Momentum Effect ◽  
Using Data

This study aims to examine the momentum effect presence in selected stocks of Pakistan stock market using data from Jan 2007 to Dec 2016. This study constructed the strategies includes docile, equal weighted and full rebalancing techniques. Data was extracted from the PSX – 100 index ranging from 2007 to 2016. STATA coding ASM software was used for calculating momentum portfolios, finally top 25 stocks were considered as a winner stocks and bottom 25 stocks were taken as a loser stocks. In conclusion, the results of the study found a strong momentum effect in Pakistan stock exchange PSX 100- index. As by results it has been observed that a substantial profit can earn by the investors or brokers in constructing a portfolio with a short formation period of three months and hold for 3, 6 and 12 months. There is hardly a study is present on the same topic on Pakistan Stock Exchange as preceding studies were only conducted on individual stock markets before merger of stock markets in Pakistan while this study leads the explanation of momentum phenomenon in new dimension i.e. Pakistan Stock Exchange. Keywords: Momentum, Portfolio, Winner Stocks, Loser Stocks

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