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The purpose of this research is to study the impact of divestitures on shareholder wealth. This study covers selloffs of publicly traded companies in Germany, Austria and Switzerland (DACH region) during the period 2002–2018. It aims to understand the overall effect of selloffs on shareholder wealth as well as the impact of important influencing factors.

This study is part of capital market studies which investigate shareholder wealth effects (abnormal returns) using event study methodology. To determine the significance of abnormal returns, a standardized cross-sectional test as suggested by Boehmer et al. (1991) was applied. The sample consists of 393 selloffs of publicly traded companies with a deal value of at least EUR 10m.

The findings confirm the overall positive impact of selloffs on shareholder wealth. The average abnormal return on the announcement day of the sample companies amounts to 1.33%. The type of buyer, the relative size of the transaction as well as the financial situation of the seller in particular seem to influence abnormal returns positively.

This study investigates shareholder wealth creation through selloffs in the DACH region, a largely neglected region in divestiture research, but now very relevant due to increasing pressure of active foreign investors. Sophisticated statistical methods were used to generate robust findings, which are in line with the results of similar studies for the US and the UK.

This study is motivated in part by the fact that the unfolding 2022 bear market, which has reached the −25% drawdown, has not been preceded by the inverted 10Y-3 m spread or an inverted near-term forward spread.

The authors develop a three-factor probit model to predict/explain the deep stock market drawdowns, which the authors define as the drawdowns in excess of 20%.

The study results show that (1) the rising credit risk predicts a deep drawdown about a year in advance and (2) the monetary policy easing precedes an imminent drawdown below the 20% threshold.

This study three-factor probit model shows adaptability beyond the typical recessionary bear market and predicts/explains the liquidity-based selloffs, like the 2022 and possibly the 1987 deep drawdowns.

This study examines co-movements between global Islamic index and heterogeneous rated/maturity sukuk. It tests the impact of financial uncertainty on these movements.

Firstly, we conduct a bivariate wavelet analysis to assess the co-movements between stocks and sukuk indexes. Secondly, we use General dynamic factor model and stochastic volatility to construct financial uncertainty index from Islamic stock indexes. Finally, we run regression analysis to determine the impact of uncertainty on the obtained correlations.

Our results suggest the absence of flight to quality phenomenon since correlations are positive especially at a short investment horizon. There is evidence of contagion phenomena across assets. Financial uncertainty may be considered as a determinant of stock-sukuk co-movements. Our results show that a rise in financial uncertainty induces correlation to move in the opposite direction in the short term, (exception for correlation with AA-Rated sukuk). However, the sign of stock market uncertainty becomes positive in the long term, which leads sukuk and stocks to move in the same direction (exception for 1–3 Year and AA Rated sukuk).

Investors may combine sukuk with 1–3 Year maturity and AA Rated when considering long holding periods. Further, all sukuk categories provide diversification benefit in time high financial uncertainty expectation for AA Rated sukuk when considering short holding periods.

To the best of our best knowledge, our study is the first investigation of the impact of financial uncertainty on Stock-sukuk co-movements and provides recommendation considering sukuk with different characteristics.

To date there is little understanding of the factors that impact the survival of foreign IPOs after they list on US stock exchanges. In this study, we examine how foreign IPO survival is contingent on institutional factors associated with the firm’s home country. We also explore how corporate governance and organizational identity influence the survival of foreign IPOs in the United States. Results suggest that the US institutional environment supports foreign firms with more independent and professional leadership, and that knowledge-intense organizations have higher chances of long-term success after listing on US exchanges.

The purpose of this paper is to investigate the risk and economic policy uncertainty (EPU) shocks on China’s equity markets while controlling for changes in sentiments and liquidity.

The GED-TARCH(1,1)-M procedure is used in estimations to deal with the heteroscedasticity problem.

Evidence shows that stock returns are positively correlated with predictable volatility and lagged downside risk. This study indicates that the stock returns are negatively correlated with both local and global uncertainty innovations. The test results are robust across different measures of stock returns and model specifications. The global EPU innovations have more profound impact on stock returns than that of Chinese EPU.

The findings are based on the data in the China’s stock market, other global markets may be considered in the future research.

Evidence indicates that a rise in EPU produces a negative effect on stock returns at the time news hits a market; however, investors will be rewarded by a premium as prices rebound in the subsequent period for compensating the investment decision made at a high uncertainty period.

The excess stock returns are negatively related to the EPU innovations, regardless of whether EPU originates from a domestic source or external sources.

Past research suggests that a financial crisis event has a dual and ambiguous effect on the exporting strategy of subsidiaries of multinational firms in a value chain and offshoring perspective. From a total volume perspective exports are expected to contract due to a decline in demand (demand shock) from other subsidiaries downstream in the value chain. While in a comparative perspective multinational subsidiaries are found to perform relatively better than local firms that are integrated differently (arms’ length) in global production networks (e.g., offshoring outsourcing). This chapter tries to reconcile these findings by testing a number of hypothesis about global integration strategies in the context of the Global Financial Crisis (GFC) and how it affected exporting among multinational subsidiaries operating out of Turkey. Controlling for the impact that exchange rate depreciations and volatility has on firm-level exports the study shows that the particular global event studied had no additional impact on individual firms’ exports. Since multinational subsidiaries are more insulated from these effects they are able to expand rather than contract their global integration strategies throughout the course of the GFC.

The Indian stock market can be tricky when there's trouble in the world, like wars or big conflicts. It's like trying to read a secret message. We want to figure out what makes investors nervous or happy, because their feelings often affect how they buy and sell stocks. We're building a tool to make prediction that uses both numbers and people's opinions.

Hybrid approach leverages Twitter sentiment, market data, volatility index (VIX) and momentum indicators like moving average convergence divergence (MACD) and relative strength index (RSI) to deliver accurate market insights for informed investment decisions during uncertainty.

Our study reveals that geopolitical tensions' impact on stock markets is fleeting and confined to the short term. Capitalizing on this insight, we built a ground-breaking predictive model with an impressive 98.47% accuracy in forecasting stock market values during such events.

To the best of the authors' knowledge, this model's originality lies in its focus on short-term impact, novel data fusion and high accuracy. Focus on short-term impact: Our model uniquely identifies and quantifies the fleeting effects of geopolitical tensions on market behavior, a previously under-researched area. Novel data fusion: Combining sentiment analysis with established market indicators like VIX and momentum offers a comprehensive and dynamic approach to predicting market movements during volatile periods. Advanced predictive accuracy: Achieving the prediction accuracy (98.47%) sets this model apart from existing solutions, making it a valuable tool for informed decision-making.