Graph and download economic data for Volatility of Stock Price Index for Japan (DDSM01JPA066NWDB) from 1984 to 2021 about volatility, stocks, Japan, price index, indexes, and price.

Prices for Japan Stock Market Index (JPVIX) including live quotes, historical charts and news. Japan Stock Market Index (JPVIX) was last updated by Trading Economics this July 13 of 2025.

Stock price volatility in Japan was reported at 19.26 in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Japan - Stock price volatility - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Predictions indicate a sustained upward trend for the Nikkei 225 index. Positive global economic conditions, strong corporate earnings, and government stimulus measures are expected to support growth. However, potential risks include geopolitical tensions, interest rate hikes, and supply chain disruptions, which could lead to volatility and a slowdown in growth.

China will launch the stock index futures in the later of 2007. This paper forecasts the impact of stock index futures on the volatility of the Chinese stock market based on the empirical test of Japan and Taiwan. The GARCH model will be used to examine on the effect of stock index futures on the volatility of the spot market. The forecasts will be made based on analysing the Japanese and Taiwanese stock market. However, the forecasts are suggestive not conclusive. The further studies are needed based on Chinese data. The importance of stock index futures on the Chinese stock market and the impact of SGX FTSE Xinhua A 50 stock index futures on the volatility of the Chinese stock market will also be discussed.

India's S&P All-World Equity Index Volatility is 15.77% which is the 17th highest in the world ranking. Transition graphs on S&P All-World Equity Index Volatility in India and comparison bar charts (USA vs. China vs. Japan vs. India), (China vs. United States of America vs. India) are used for easy understanding. Various data can be downloaded and output in csv format for use in EXCEL free of charge.

In this paper we present an exact maximum likelihood treatment for the estimation of a Stochastic Volatility in Mean (SVM) model based on Monte Carlo simulation methods. The SVM model incorporates the unobserved volatility as an explanatory variable in the mean equation. The same extension is developed elsewhere for Autoregressive Conditional Heteroscedastic (ARCH) models, known as the ARCH in Mean (ARCH-M) model. The estimation of ARCH models is relatively easy compared with that of the Stochastic Volatility (SV) model. However, efficient Monte Carlo simulation methods for SV models have been developed to overcome some of these problems. The details of modifications required for estimating the volatility-in-mean effect are presented in this paper together with a Monte Carlo study to investigate the finite sample properties of the SVM estimators. Taking these developments of estimation methods into account, we regard SV and SVM models as practical alternatives to their ARCH counterparts and therefore it is of interest to study and compare the two classes of volatility models. We present an empirical study of the intertemporal relationship between stock index returns and their volatility for the United Kingdom, the United States and Japan. This phenomenon has been discussed in the financial economic literature but has proved hard to find empirically. We provide evidence of a negative but weak relationship between returns and contemporaneous volatility which is indirect evidence of a positive relation between the expected components of the return and the volatility process.

Global liquefied natural gas prices have shown less volatility in 2024 and 2025 than the years prior, with the benchmark price reaching **** U.S. dollars per million metric British thermal units in May 2025. This figure represents an increase from the same period a year earlier. The global LNG benchmark, which is largely influenced by Asian market trading, particularly Indonesian LNG in Japan, serves as a key indicator for the industry's pricing trends. Natural gas prices become less volatile The Asian LNG market experienced less turbulence in 2023 compared to the previous year, with price volatility dropping to ** percent. This relative stability followed an exceptionally volatile 2022, when LNG demand surged due to sanctions on Russian imports. The global natural gas price index, which encompasses European, Japanese, and American markets, stood at ***** index points in March 2025, showing a decrease of nearly ** points that month. This upward trend in natural gas prices contrasts with the comparatively lower crude oil price indices and follows greater heating demand in the winter months. Landed prices vis-à-vis export prices Due to its geographical location, Japan is exclusively reliant on LNG trading for its natural gas supply. As such, Japan's landed LNG spot price is often higher than for other markets, reaching approximately ***** U.S. dollars per million British thermal units in January 2024. By comparison, the world's largest LNG exporter, the United States, has seen its LNG export prices decrease to **** U.S. dollars per thousand cubic feet in 2023, down from ***** U.S. dollars the previous year.

Peru's S&P All-World Equity Index Volatility is -12.47% which is the 65th highest in the world ranking. Transition graphs on S&P All-World Equity Index Volatility in Peru and comparison bar charts (USA vs. China vs. Japan vs. Peru), (Saudi Arabia vs. Malaysia vs. Peru) are used for easy understanding. Various data can be downloaded and output in csv format for use in EXCEL free of charge.

Sri Lanka's S&P All-World Equity Index Volatility is -6.88% which is the 52nd highest in the world ranking. Transition graphs on S&P All-World Equity Index Volatility in Sri Lanka and comparison bar charts (USA vs. China vs. Japan vs. Sri Lanka), (Australia vs. Romania vs. Sri Lanka) are used for easy understanding. Various data can be downloaded and output in csv format for use in EXCEL free of charge.