scholarly journals Does the CBOE Volatility Index Predict Downside Risk at the Tokyo Stock Exchange?

2016 ◽  
Vol 10 (3) ◽  
pp. 1 ◽  
Author(s):  
Chikashi Tsuji
Keyword(s):  
Stock Price ◽  
Predictive Power ◽  
Price Index ◽  
Stock Exchange ◽  
Downside Risk ◽  
Price Changes ◽  
Volatility Index ◽  
Probit Models ◽  
Tokyo Stock Exchange ◽  
Left Tail

This study investigates the predictability of the preceding day’s US volatility index (VIX) from the Chicago Board Options Exchange (CBOE) for sharp price drops of the Tokyo Stock Price Index (TOPIX) by employing several versions of probit models. All our results indicate that the preceding day’s US S&P 500 VIX movement has predictive power for sharp price declines of the TOPIX in Japan. As we repeatedly examined several left tail risks in TOPIX price changes and we also tested by applying some different versions of probit models, our evidence of the forecast power of the S&P 500 VIX for downside risk of the TOPIX shall be very robust.

scholarly journals Forecasting Large Price Declines of the Nikkei Using the S&P 500 Implied Volatility

2016 ◽  
Vol 8 (1) ◽  
pp. 58
Author(s):  
Chikashi Tsuji
Keyword(s):  
Quantile Regression ◽  
Regression Models ◽  
Implied Volatility ◽  
Predictive Power ◽  
Downside Risk ◽  
Price Changes ◽  
Empirical Results ◽  
Left Tail

This paper empirically examines the forecast power of the previous day’s US implied volatility for large declines of the Nikkei by using several versions of quantile regression models. All our empirical results suggest that the previous day’s US S&P 500 implied volatility has forecast power for large price drops of the Nikkei 225 in Japan. Since we repeatedly and carefully tested the several left tail risks in price changes of the Nikkei and we also tested by using some different versions of quantile regression models, our evidence of the predictive power of the S&P 500 implied volatility for downside risk of the Nikkei is very robust.

scholarly journals PENGARUH BURSA SAHAM GLOBAL TERHADAP INDEKS HARGA SAHAM GABUNGAN DI BURSA EFEK INDONESIA

2018 ◽  
Vol 4 (1) ◽  
pp. 1-10
Author(s):  
Lisa Kustina ◽  
Samsul Anwar ◽  
Imas Mawar
Keyword(s):  
Stock Price ◽  
Price Index ◽  
Stock Exchange ◽  
Composite Index ◽  
Stock Exchanges ◽  
Significance Level ◽  
Jones Index ◽  
Tokyo Stock Exchange ◽  
Stock Price Index ◽  
Global Stock

Tujuan Penelitian ini adalah untuk mengetahui pengaruh bursa saham global terhadap indeks harga saham gabungan di Bursa Efek Indonesia. Bursa saham global yang digunakan dalam penelitian ini adalah Dow Jones Index (DJI), Korea Stock Price Composite Index (KOSPI), Tokyo Stock Exchange (Nikkei heikin kabuki / Nikkei 225), dan Australian Securities Exchange (ASX). Sampel yang diteliti dalam penelitian ini adalah periode 2015 hingga 2017. Penelitian ini menggunakan regresi linear berganda untuk mengolah data penelitian. Hasil Penelitian ini menunjukkan bahwa Dow Jones Index (DJI), Korea Stock Price Composite Index (KOSPI), Tokyo Stock Exchange (Nikkei heikin kabuki / Nikkei 225), dan Australian Securities Exchange (ASX) secara parsial berpengaruh terhadap Indek Harga Saham Gabungan diIndonesia. Dow Jones Index (DJI), Korea Stock Price Composite Index (KOSPI), dan Australian Securities Exchange (ASX) berpengaruh signifikan pada tingkat signifikansi 0.000 sedangkan Tokyo Stock Exchange (Nikkei 225) pada tingkat signifikansi 0.001. The purpose of this study was to determine the effect of global stock exchanges on the composite stock price index on the Indonesia Stock Exchange. The global stock exchanges used in this study are the Dow Jones Index (DJI), the Korea Stock Price Composite Index (KOSPI), the Tokyo Stock Exchange (Nikkei Heikin Kabuki / Nikkei 225), and the Australian Securities Exchange (ASX). The sample examined in this study is the period 2015 to 2017. This study uses multiple linear regression to process research data. The results of this study indicate that the Dow Jones Index (DJI), the Korea Stock Price Composite Index (KOSPI), the Tokyo Stock Exchange (Nikkei Heikin Kabuki / Nikkei 225), and the Australian Securities Exchange (ASX) partially affect the Composite Stock Price Index in Indonesia. The Dow Jones Index (DJI), the Korea Stock Price Composite Index (KOSPI), and the Australian Securities Exchange (ASX) have a significant effect on the significance level of 0,000 while the Tokyo Stock Exchange (Nikkei 225) is at a significance level of 0.001.

Predictable Patterns after Large Stock Price Changes on the Tokyo Stock Exchange

1997 ◽  
Vol 32 (3) ◽  
pp. 345 ◽  
Author(s):  
Marc Bremer ◽  
Takato Hiraki ◽  
Richard J. Sweeney
Keyword(s):  
Stock Price ◽  
Stock Exchange ◽  
Price Changes ◽  
Tokyo Stock Exchange

scholarly journals Analisis Pengaruh Nilai Tukar Rupiah, Inflasi Dan Indeks Dow Jones Terhadap Indeks Harga Saham Gabungan (IHSG) Di Bursa Efek Indonesia (BEI)

KINDAI ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. 542-562
Author(s):  
Delila Putri Syarina
Keyword(s):  
Exchange Rate ◽  
Exchange Rates ◽  
Stock Price ◽  
Quantitative Method ◽  
Price Index ◽  
Stock Exchange ◽  
Sampling Techniques ◽  
Jones Index ◽  
Stock Price Index

Abstract: This study aims to study both partially and simultaneously, large, Analysis, Analysis, Value, Exchange, Inflation, and the Dow Jones Index Against the Composite Stock Price Index (CSPI) on the Indonesia Stock Exchange (BEI) and the dominant dominant variable on the Price Index Joint Stock (CSPI)).The method used in this study is a quantitative method and with a population of 10 (ten) years, samples were taken with census sampling techniques of 10 (ten) years per year-end period, research instruments using classical data assumptions - data used using regression linear multiple.The results of this study indicate that (1) Rupiah Exchange Rates, Inflation and the Dow Jones Index influence simultaneously on the Composite Stock Price Index (CSPI) on the Indonesia Stock Exchange (2) the Dow Jones Index is partially related to the Composite Stock Price Index (CSPI) in The Indonesian Stock Exchange, while the Rupiah Exchange Rate and Inflation are not partially on the Composite Stock Price Index (CSPI) on the Indonesia Stock Exchange (3) The dominant dominant variable on the Composite Stock Price Index (CSPI) on the Indonesia Stock Exchange is the Dow Jones Index..Keywords  : Rupiah Exchange Rate, Inflation, Dow Jones Index and Composite Stock Price Index (CSPI)   Abstrak: Penelitian ini bertujuan untuk mengetahui baik secara parsial dan simultan seberapa besar Analisis Pengaruh Nilai Tukar Rupiah, Inflasi Dan Indeks Dow Jones Terhadap Indeks Harga Saham Gabungan (IHSG) Di Bursa Efek Indonesia (BEI) serta variabel yang berpengaruh dominan terhadap Indeks Harga Saham Gabungan (IHSG). Metode yang digunakan dalam penelitian ini adalah metode kuantitatif dan dengan populasi sebanyak 10 (sepuluh) tahun, diambil sampel dengan teknik sampling sensus sebanyak 10 (sepuluh) tahun per periode akhir tahun, instrument penelitian uji asumsi klasik data – data diuji dengan menggunakan regresi linear berganda. Hasil penelitian ini menunjukkan bahwa (1) Nilai Tukar Rupiah, Inflasi dan Indeks Dow Jones berpengaruh secara simultan terhadap Indeks Harga Saham Gabungan (IHSG) di Bursa Efek Indonesia (2) Indeks Dow Jones berpengaruh secara parsial terhadap Indeks Harga Saham Gabungan (IHSG) di Bursa Efek Indonesia, sedangkan Nilai Tukar Rupiah dan Inflasi tidak berpengaruh secara parsial terhadap Indeks Harga Saham Gabungan (IHSG) di Bursa Efek Indonesia (3) Variabel yang berpengaruh dominan terhadap Indeks Harga Saham Gabungan (IHSG) di Bursa Efek Indonesia adalah Indeks Dow Jones. . Kata kunci :     Nilai Tukar Rupiah, Inflasi, Indeks Dow Jones dan Indeks Harga Saham Gabungan (IHSG).

scholarly journals PENGARUH VARIABEL AKUNTANSI TERHADAPPERUBAHAN HARGA SAHAM PERUSAHAAN YANG GO PUBLIC DI BURSA EFEK JAKARTA

2016 ◽  
Vol 5 (1) ◽  
pp. 1
Author(s):  
Setyaningsih Setyaningsih
Keyword(s):  
Stock Prices ◽  
Random Sampling ◽  
Stock Price ◽  
Stock Exchange ◽  
Financial Accounting ◽  
Study Analysis ◽  
Price Changes ◽  
Leverage Ratio ◽  
Independent Variables ◽  
The Relationship

The objective of this study is to investigate the relationship between accounting variables and stock price changes in Jakarta Stock Exchange (JSX). Some accounting variables in this study are devidend payout  ratio, assets size, assets growth , leverage ratio, variability in earning and covariability in earning as independent variables, the independent variables are stock  price changes. The study analysis 80 cases of active firms  in  the period of 1994 to 1997.  Data is collected by means of purpo sive random sampling. Regression analysis is used to analyse the data.The  result  of  the study  shows  that  there  is significant  affect  of  the  sevent financial accounting informations in the model as predictor of stock price changes (Y); there are two variables to be dropped because there is multicolinierity among variables. Those variables are leverage ratio (X5) and covariability in earning (X7) . There are five other independent variables affect significantly to stock prices changes (Y), which their contribution is 49%.

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.

Evaluating Predictive power of Data Envelopment Analysis Technique Compared with Logit and Probit Models in Predicting Corporate Bankruptcy

2012 ◽  
Vol 02 (09) ◽  
pp. 38-46
Author(s):  
Khalili Araghi Maryam ◽  
Makvandi Sara
Keyword(s):  
Data Envelopment Analysis ◽  
Predictive Power ◽  
Environmental Changes ◽  
Stock Exchange ◽  
Rapid Development ◽  
Manufacturing Firms ◽  
Data Envelopment ◽  
Probit Models ◽  
Analysis Technique ◽  
Logit And Probit Models

Simultaneous with extensive environmental changes and the rapid development of technology which has increasingly accelerated economy, competitiveness economical enterprises have restricted earning profit and make probable closing of bankrupt firms. Thus it seems necessary to find a model that can predict financial crisis and bankruptcy of companies. Nowadays occurrence of significant progress in other sciences, such as computer and math attract the attention of the financial scholars toward designing and using more exact patterns like Data Envelopment Analysis (DEA). For this purpose, this study uses DEA technique to predict the bankruptcy likelihood of manufacturing firms and also compare its predictability with2 methods : Logit and Probit models. Study sample includes all manufacturing firms listed in Stock Exchange of Tehran from 2000-2010. The results showed that the accuracy of the designed model under DEA technique is %72 and the predictability of Logit and Probit models has been81, and %80 respectively. The results also showed DEA was proved to be an effective tool for predicting bankruptcy likelihood of manufacturing firms; but,it acted less efficient than Logit and Probit models.

A Study on the Predictive Power of the Stock Price Index

2016 ◽  
Vol 30 (1) ◽  
pp. 95-122
Author(s):  
Kyoung-Woo Sohn ◽  
Sang-Su Kim
Keyword(s):  
Stock Price ◽  
Predictive Power ◽  
Price Index ◽  
Stock Price Index

Testing for Overreaction and Return Continuations in Stock Price Index Returns

2010 ◽  
Vol 1 (2) ◽  
pp. 93-112 ◽  
Author(s):  
Nathan Lael Joseph ◽  
Khelifa Mazouz
Keyword(s):  
Market Efficiency ◽  
Stock Markets ◽  
Stock Price ◽  
Price Index ◽  
Abnormal Returns ◽  
Market Size ◽  
Price Shocks ◽  
Price Changes ◽  
Stock Indices ◽  
Initial Results

In this paper, the authors examine the impacts of large price changes (or shocks) on the abnormal returns (ARs) of a set of 39 national stock indices. Their initial results support returns continuations for both positive and negative shocks in line with prior results. After controlling for market size, their findings provide support for over-reaction, return continuations and market efficiency, but these result depend on the magnitude of the price shocks. Whilst the market is efficient when the positive shocks are large, the market also over-reacts when negative shocks are large. To illustrate, for large stock markets that are more liquid, positive shocks of more than 5% generate an insignificant day one CAR of -0.004%, whilst negative shocks of more than 5% generate a positive and significant day one CAR of 0.662%. In contrast, positive (negative) shocks of less than 5% generate a significant one day CAR of 0.119% (-0.174%) for these same (large) stock markets.

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