Japanese Stock Market Research Articles

Robustness Investigation of ML Models for Stock Price Prediction During Market Volatility: A Case Study of the Japanese Stock Market Amidst the COVID-19 Pandemic

In the evolving realm of financial markets, precise stock price prediction remains a pivotal challenge. This paper investigates the efficacy of traditional machine learning models for stock price forecasting, particularly during the high volatility phase induced by the COVID-19 pandemic, using the Japanese stock market as a case study. This study utilized a dataset from the JPX Tokyo Stock Exchange Prediction competition, selecting two stocks at random to avoid bias. After standardizing the data for consistency, this study employed linear regression and decision trees to project stock prices, comparing their performance during stable periods and the economic upheaval of the pandemic. The analysis revealed that both models' predictive capabilities were compromised during the pandemic, with the decision tree model particularly underperforming. In normal times, linear regression showed improved accuracy for stock 1301 in 2021, while for stock 6758, the model's performance declined. These findings underscore the necessity for robust models that can withstand market turbulences like those observed during the COVID-19 crisis. The research contributes to both academic discussions on financial forecasting and practical strategies for market participants navigating complex stock environments. Future work will focus on developing more resilient forecasting methods to address these challenges.

Measuring the time‐varying market efficiency in the prewar and wartime Japanese stock market, 1924–1943

Measuring the time‐varying market efficiency in the prewar and wartime Japanese stock market, 1924–1943

Impulsive Response Analysis of Financial Markets in QUAD Economies: A VAR Modelling Approach

Financial market integration remains a key focus in academic finance, especially given how crucial it is to portfolio diversification. The purpose of this research is to investigate a crucial yet underexplored aspect like the cointegration of economies with formal or unofficial military ties, focusing on countries within the Quad strategic forum—India, Japan, Australia, and the United States. The daily closing values of benchmark stock market indices of Quad economies viz. Nikkie 225 for Japan, S&P ASX 200 for Australia, NASDAQ composite for the United States, and S&P Sensex for India were considered. Unit root tests, Johansen Cointegration tests, VAR (Vector Autoregressive) model, and the Granger Causality statistics are computed for data analysis. Additionally, the Impulse response function and variance decomposition are computed for better financial market predictions. The result reveals intriguing dynamics: while the Indian stock market initially responds positively to shocks in the Australian market, this effect diminishes over time. Also, movements in the Australian and United States stock markets significantly contribute to predicting fluctuations in the Indian market, contrasting with the limited predictive power of the Japanese stock market. These findings carry significant practical implications for international investors, offering valuable guidance for optimizing portfolio diversification strategies amidst geopolitical and economic complexities. This paper contributes to academic literature by offering empirical insights into the short-term dynamics and causal relationships of Quad countries’ stock markets, setting a foundation for future studies on long-term trends and market responses to external factors.

Applying LSTM Model to Predict the Japanese Stock Market with Multivariate Data

Applying LSTM Model to Predict the Japanese Stock Market with Multivariate Data

Downside Risk in Australian and Japanese Stock Markets: Evidence Based on the Expectile Regression

The expectile-based Value at Risk (EVaR) has gained popularity as it is more sensitive to the magnitude of extreme losses than the conventional quantile-based VaR (QVaR). This paper applies the expectile regression approach to evaluate the EVaR of stock market indices of Australia and Japan. We use an expectile regression model that considers lagged returns and common risk factors to calculate the EVaR for each stock market and to evaluate the interdependence of downside risk between the two markets. Our findings suggest that both Australian and Japanese stock markets are affected by their past development and the international stock markets. Additionally, ASX 200 index has significant impact on Nikkei 225 in terms of downside tail risk, while the impact of Nikkei 225 on ASX is not significant.

Japanese stock market sectoral dynamics: A time and frequency analysis

AbstractThis study examines the Japanese stock market connectedness across different sectors, focusing on both the time and frequency dimensions. The dataset used spans from January 1999 to April 2022 and employs various methodologies, including time‐varying parameter vector autoregressions, TVP‐VAR frequency dependency, and Quantile coherency. The empirical findings reveal that cyclical or aggressive stocks predominantly act as net transmitters of shocks across sectors. Moreover, short‐term spillovers are more significant compared to intermediate‐term spillovers, indicating that Japanese sectors are more pronounced to market shocks in the short run. The spillover effects are also asymmetric and vary over time. Additionally, the real estate sector exhibits diversification benefits across different time horizons, while the energy sector provides protection primarily in the short run. This research contributes to the development of financial policies aimed at reducing sectoral imbalances and promoting stable growth. Furthermore, it offers insights for investors seeking to devise optimal portfolio diversification strategies.

Revisiting the residual momentum in Japan

This study examines whether the residual momentum effect is actually at play in the Japanese stock market. The results confirm that the effects of residual momentum are not significant after adjusting for short-term and long-term reversal effects. We, therefore, establish that there is a problem with the method used to compute residual momentum in previous studies. By using the corrected method to calculate residual momentum, it is evident that the residual momentum effect is not significant.

스튜어드십 코드와 일본기업의 연구개발투자

Purpose: This paper explores the influence of both domestic and international institutional investors, recognized as emerging outside blockholders in Japanese firms, on R&D investment. The study aims to understand how these investors impact R&D spending, a crucial factor for sustainable growth, particularly in the context of the implementation of the Stewardship Code.
 Research design, data, and methodology: The analysis employed panel analysis on 105 manufacturing companies listed on Nikkei225 from 2014 to 2020. We used the intensity of R&D as the dependent variable, with institutional investors holding more than 3% of each company’s shares as the independent variable. By classifying institutional investors, we compared the results between domestic and foreign institutional investors.
 Results: The analysis revealed that outside blockholders had a significantly positive effect on R&D. However, when institutions were classified, different results emerged. While domestic institutional investors had a significant positive impact on R&D, foreign institutional investors did not yield statistically significant results. Additionally, the financial institution variable, acting as the control variable and related to insider investors, consistently demonstrated a significantly negative effect across all models.
 Implications: Despite foreign institutional investors dominating the Japanese stock market, it was found that domestic institutional investors have emerged as significant outside blockholders in each firm. Traditionally criticized as passive investors, domestic institutional investors are shown to influence and promote R&D for long-term growth, in line with the Japanese stewardship code. While foreign investors are often associated with potential decreases in R&D for short-term gains such as ROE and dividends, no significant evidence was found. Moreover, with increasing stake ratios, foreign investors have the potential to positively impact Japanese firms in the future.

External Event Crises on The Stock Market: Taking Japan’s Sea Discharge Incident as An Example

On August 22, 2023, the Japanese government announced that it would start discharging nuclear wastewater into the sea from August 24. This decision was widely questioned and opposed by the international community and caused strong concerns in Japan. This article aims to take the Japanese nuclear sewage discharge incident into the sea as an example to explore the impact of social crisis on Japan's domestic stock market. The main research method of this article is based on stock return analysis, using the ARIMA model to predict the Japanese stock price trend after excluding the impact of this event, and then comparing it with real data. The results of this study provide evidence that the predicted stock prices are close to the actual stock prices, indicating that as of mid-September, there was no short-term negative impact on the Japanese stock market due to the event, but from a long-term perspective, the predictions remain It is uncertain whether stock prices in Japan's financial markets will fall because of this incident. The main conclusion drawn from this study is that external events may not have a large impact on stock prices in the short term. Different from previous literature, this study uses ARIMA analysis on daily data and weekly data to obtain the relationship between them. Recommendations include organizing a team of experts; hiring a legal team; establishing a complete procedure to handle social media information, and having a dedicated public relations team may be helpful.

Post-Earnings Announcement Drift and Ownership Structure in the Modern Japanese Stock Market

Post-Earnings Announcement Drift and Ownership Structure in the Modern Japanese Stock Market

The cross-sectional stock return predictions via quantum neural network and tensor network

In this paper, we investigate the application of quantum and quantum-inspired machine learning algorithms to stock return predictions. Specifically, we evaluate the performance of quantum neural network, an algorithm suited for noisy intermediate-scale quantum computers, and tensor network, a quantum-inspired machine learning algorithm, against classical models such as linear regression and neural networks. To evaluate their abilities, we construct portfolios based on their predictions and measure investment performances. The empirical study on the Japanese stock market shows the tensor network model achieves superior performance compared to classical benchmark models, including linear and neural network models. Though the quantum neural network model attains the lowered risk-adjusted excess return than the classical neural network models over the whole period, both the quantum neural network and tensor network models have superior performances in the latest market environment, which suggests capability of model’s capturing non-linearity between input features.

Quantitative statistical analysis of order-splitting behavior of individual trading accounts in the Japanese stock market over nine years

Quantitative statistical analysis of order-splitting behavior of individual trading accounts in the Japanese stock market over nine years

Comparing competing factor and characteristics models: Evidence in Japan

The main purpose of this study is to simultaneously compare the explanatory abilities of various firm characteristics and factor models in the Japanese stock market. We show that the factor models developed by Fama and French (1993, 2015, 2018), Carhart (1997), and Hou et al. (2015) all fail to be priced in Japan. In addition, value and operating profitability anomalies are prevalent in Japan, while size, investment, and momentum effects are not. Our findings are in line with what is indicated in the existing literature: the characteristics model associated with value and operating profitability better describes the cross-sectional variations of stock returns than factor models in Japan.

US Originated Asymmetric Volatility Spillover Effects: An Intraday Comparison Between Korean and Japanese Stock Markets

US Originated Asymmetric Volatility Spillover Effects: An Intraday Comparison Between Korean and Japanese Stock Markets

Liquidity changes and decomposition in the Japanese equity market

In this study, we investigate the relationship between liquidity changes and stock returns in the Japanese stock market. The results confirm that stocks with increased liquidity have higher stock returns than those with decreased liquidity. This phenomenon indicates that the market under-reacts to changes in liquidity. We also decompose liquidity and analyze how each component is priced. We confirm that stock-specific long-term liquidity changes relate negatively to stock returns in the following month, while stock-specific short-term liquidity changes relate positively to stock returns in the following month. The sensitivity of changes in the liquidity of individual stocks to changes in market liquidity was found not to be priced.

Extreme dependence and spillovers between uncertainty indices and stock markets: Does the US market play a major role?

This study investigates the spillovers and connectedness between uncertainty indices of oil gold, and stock (VIX), the economic policy uncertainty (EPU) and international stock markets (US, EU, UK, Japan, China, and Vietnam) under bearish, normal, and bullish market conditions. We employ a cross-quantilogram and quantile connectedness approach to investigate the contemporaneous linkages and asymmetries among stock markets under various financial market uncertainty. Using the cross-quantilogram approach, we find strong cross-quantilogram dependencies from the US stock market to other markets, even after controlling for the uncertainties. We find greater spillovers under volatile market conditions—bearish and bullish—than under stable market conditions using the quantile connectedness approach. The financial volatility or uncertainty indices are net transmitter (receiver) of spillover in the stock markets, especially in the bearish and tranquil (bullish) market status. Furthermore, all markets and the uncertainty indices except the US, Europe, and the UK are net receivers of spillovers in the lower quantile, while VIX uncertainty index shifts to being a net transmitter of spillovers in the lower and median quantiles. In the upper quantile, Japanese stock market and the uncertainty indices are net receivers of spillovers. VIX is strongly linked to the US (Chinese) market in tranquil (bullish) market conditions. In addition, the maximum amount of spillovers was attained during the beginning of 2020, coinciding with the onset of the COVID-19 pandemic's first wave.

An Investigation on Real Estate Market Dynamics and Bubble Formation Modeling

Abstract A speculative bubble arises when the market price of a financial asset diverges from its fundamental value, resulting in abrupt and disproportionate hikes that cannot be rationally explained by its underlying intrinsic value. This behavior is often followed by market crashes, as observed during historical asset bubbles such as the Dutch Tulip Mania (1634-1637), the Mississippi bubble (1719-1720), the South Sea bubble (1720), the stock-market bubble of the US (1921-1929), the Japanese stock market and real estate bubbles (1986-1991), and the recent US housing bubble and the stock market crash (2002-2006). In the housing market, speculative bubbles can be attributed to excessive public expectations of future price increases, leading to overpricing and eventually diminishing demand and instability of inflated home prices (Case and Shiller, 2003). The cycle of a housing market bubble involves individuals continuing to purchase houses despite awareness of overpricing, with the expectation of compensation through further price increases. This perception of continuous price increases leads to increased demand, which further drives up prices. However, house prices cannot increase indefinitely, and the steady increase eventually becomes unstable, resulting in a downward adjustment that may occur at a much faster pace than price increases. The existence of speculative bubbles in stock and housing markets has led academics to investigate their potential role in financial crises.

The Effect of ESG performance on the stock market during the COVID-19 Pandemic — Evidence from Japan

Environmental, social, and governance (ESG) practices can play a crucial role in promoting green recovery by fostering sustainable and responsible economic growth. Based on a novel dataset of Japanese listed companies from January 2016 to December 2021, this study examines the effect of corporate (ESG) performance on the Japanese stock market during the COVID-19 pandemic. We contribute additional evidence to the literature by exploring the unique role of ESG factors that affect stock markets during economic downturns. The results of the study show a positive association between corporate ESG performance and stock returns during the COVID-19 period. Furthermore, we demonstrate that strong ESG performance contributed to enhanced stock market stability and increased market liquidity in Japan during the COVID-19 pandemic. These results provide a rationale for implementing supportive measures and regulations that encourage companies to adopt and disclose robust ESG practices. By doing so, they can contribute to the stability and liquidity of the stock market and fostering sustainable economic growth.

Decomposing the Momentum in the Japanese Stock Market

Decomposing the Momentum in the Japanese Stock Market

An impact assessment of the COVID-19 pandemic on Japanese and US hotel stocks

This study proposes two new regime-switching volatility models to empirically analyze the impact of the COVID-19 pandemic on hotel stock prices in Japan compared with the US, taking into account the role of stock markets. The first model is a direct impact model of COVID-19 on hotel stock prices; the analysis finds that infection speed negatively affects Japanese hotel stock prices and shows that the regime continues to switch to high volatility in prices due to COVID-19 until September 2021, unlike US stock prices. The second model is a hybrid model with COVID-19 and stock market impacts on the hotel stock prices, which can remove the market impacts on regime-switching volatility; this analysis demonstrates that COVID-19 negatively affects hotel stock prices regardless of whether they are in Japan or the US. We also observe a transition to a high-volatility regime in hotel stock prices due to COVID-19 until around summer 2021 in both Japan and the US. These results suggest that COVID-19 is likely to affect hotel stock prices in general, except for the influence of the stock market. Considering the market influence, COVID-19 directly and/or indirectly affects Japanese hotel stocks through the Japanese stock market, and US hotel stocks have limited impacts from COVID-19 owing to the offset between the influence on hotel stocks and no effect on the stock market. Based on the results, investors and portfolio managers should be aware that the impact of COVID-19 on hotel stock returns depends on the balance between the direct and indirect effects, and varies from country to country and region to region.