European Equity Research Articles

Assessing the Impact of the ECB’s Unconventional Monetary Policy on the European Stock Markets

This study assesses the effects of the European Central Bank’s (ECB) unconventional monetary policy (UMP) on the prices of selected European stock market indices during the European sovereign debt (2010–2012) and the COVID-19 pandemic (2020–2022) crises interventions. This research employs the instrumental variables (IV) two-stage least squares (2SLS) model approach to evaluate the effects of changes in the size of the ECB’s balance sheet on the pricing of key equity market indices in Europe. The results of this study suggest that the ECB’s asset value expansion had the opposite statistically significant effects on the European stock market indices’ prices between the interventions. That is, an increase in the ECB’s balance sheet size was associated with a decrease in the prices of the indices during the sovereign debt crisis and with a rise during the COVID-19 pandemic. This research pinpoints the price sensitivity of each of the European equity indices to the ECB’s UMP and determines the different outcomes of the ECB’s quantitative easing policy between the interventions.

Herding in equity crowdfunding

AbstractWe build a model of equity crowdfunding that incorporates the two major funding models: all‐or‐nothing (AoN) and keep‐it‐all (KIA). Both informed and uninformed investors arrive sequentially and rationally choose whether and how much to invest. The KIA solution turns out to be a reduced version of AoN without signalling. We test predictions using data from a leading European equity crowdfunding platform and find support. Results are consistent with rational information aggregation. However, negative information cascades may still appear. The AoN crowdfunding mechanism might therefore fail to finance a nonnegligible percentage of positive NPV projects.

ESG dynamics in real estate: temporal patterns and financial implications for REITs returns

PurposeThis paper aims to explore the dynamic relationship between ESG scores and REITS returns. The overarching goal is to provide a better understanding of how ESG considerations impact financial performance across different temporal contexts.Design/methodology/approachUsing a sample of 175 European Equity REITs, this analysis combines numerical ESG scores with the Fama-French model, employing both random and fixed effects methods. It integrates individual REIT data and the HESGL (High ESG Scores Minus Low ESG Scores) factors to assess their impact on REIT returns.FindingsThe findings highlight divergent patterns between the numerical ESG score and the HESGL factor concerning REIT returns. While the numerical ESG score displays a negative impact in later periods, the HESGL factor demonstrates a positive effect during prosperous times but loses significance during crises.Originality/valueThis research contributes original insights by emphasizing the importance of temporal segmentation in understanding the nuanced and evolving nature of the relationship between ESG scores and REITs’ returns. The study provides a comprehensive analysis and highlights divergent outcomes that are essential for a better interpretation of ESG impacts on real estate investments.

Interplay of crises: Unpacking intraday spillovers in oil and European equities in the shadow of the COVID-19 and the Ukraine-Russia war

This study investigates the time-varying frequency of spillovers between European stock markets and oil during the COVID-19 pandemic and the Russia-Ukraine war. Using the spillover index by Diebold & Yilmaz, 2012 and Baruník & Křehlík, 2018, we analyze high-frequency data at a 5-min interval to analyze the interplay between crude oil market returns and the Stoxx 600 index returns, including sectors such as auto, basic material, banks, chemicals, food and beverage, health, industrials, insurance, oil and gas, retail, real estate, technology (tech), telecommunication (telecom), and utilities. The sample period is January 3, 2022, to March 25, 2022. Our findings reveal a substantial degree of connectedness within this financial network, with specific sectors—auto, chemicals, food, industrials, insurance, real estate, retail, tech, and telecom—acting as net transmitters of shocks, while other sectors assume the role of net receivers. The Russia-Ukraine war is a significant driver of these interconnected dynamics. Spillovers are most prevalent in the medium-term horizon, with the time dimension affecting the role of sectors and oil. Furthermore, our research highlights the potential benefits of adding oil assets to portfolios, enhancing risk-adjusted performance. However, ongoing risk management remains crucial due to the dynamic hedge ratios. This study offers practical insights for investors and policy makers, aiding risk management and investment strategies in turbulent markets.

Correlation between the ECB Pandemic Policy and the STOXX Europe 600 Sector Performance Sensitivity

In 2022 European equity markets lost some of their value, led by high-growth sectors, which generally have a significantly higher growth rate. The prevailing academic opinion is that the European Central Bank's monetary policy during the COVID-19 pandemic is a key reason and the financial and the technology sectors are defined to be particularly sensitive to interest rates. In this context, a performance sensitivity analysis for the STOXX Euro 600 sectors on European Central Bank interest rates from 2020 to 2022 will be investigated based on the assumption of a significant interest rate sensitivity. The objective is achieved with a Pearson correlation and linear regression. The results confirm a correlation for the selected sectors, indicating a potential general sensitivity for the entire investigation period. On this basis, further research on sectors and variables such as inflation and a comparison with Fed interest rates and the S&P 500 is recommended.

An Empirical Study of the Impact of the Euro on Cross-Country Diversification

The euro was launched, on 1 January 1999, as a common currency for members of the European Union that complied with the Maastricht Treaty. The Maastricht Treaty calls for the coordination of major macroeconomic policies, such as inflation, budget balance, public debt, and long-term interest rates. Theoretically, the coordination of these policy issues and the launch of a common currency will increase the degree of market integration among member countries. This paper empirically tests the impact of the euro on the degree of market integration by looking at the comovement of the European equity markets and a sample of OECD equity markets. Weekly stock market indices for the period covering seven years before the euro and seven years after the euro was implemented was used. The results show that cross-country divergences in stock markets continued after the euro. There is no evidence of cointegration after the adoption of the euro. Cross-country portfolio diversification continues to be beneficial even among euro countries.

European equity markets volatility spillover: Destabilizing energy risk is the new normal

AbstractWhile energy risk is increasingly recognized as a systemic risk, there is limited comprehensive analysis of the risk propagation in regional contexts. In this study, we examine oil and natural gas price changes and shocks in relation to equity market returns and volatility for 24 European Economic Area (EEA) countries. In addition to traditional panel regressions, we also deploy the Diebold‐Yilmaz (2014) spillover index for a closed network analysis. We differentiate in the cross‐section across the core EU block, PIIGS countries, EU enlargement countries joining after 2004, and other non‐EU countries, to provide insights into the ongoing debates on the European energy market stability. While we find evidence of the manifestation of energy risk throughout the sample period, we find that until 2019 the primary sources of volatility spillover in the EEA economic network arose from economic or political uncertainty. Energy risks, measured by large crude oil and natural gas price shocks also significantly contributed to equity market volatility, with increasing volatility risk arising from natural gas, a green labelled energy source after 2019. Last, we show that CEEC equity markets are more sensitive to oil and natural gas price shocks when domestic currencies depreciate against the Euro.

Does team size and tenure matter for European pension funds?

ABSTRACT Pension funds are investment vehicles quite different from mutual funds, because they are specifically designed to provide retirement benefits. We examine the effect of management team size and experience on the ability to capture flows, generate performance (returns and alphas), and risk (value at risk) in a sample of European equity pension funds. To achieve this objective, we resort to cointegration econometric methodology. After analysing the stationarity of the series, we estimate four different proposed relationships to lower the short-run and long-run effects of team size and manager experience on different metrics of pension funds. Our findings reveal a negative short-term effect of team size on pension fund flows and returns, but not on risk-adjusted performance (alpha). Additionally, team size shows a relationship with value at risk (VaR), leading to decreased expected losses as team size increases. Conversely, manager experience positively influences flows in the long run but has negative effects on alpha, not impacting returns.

Market crises and benchmark-adjusted fund alphas in a small market context

Most mutual fund performance evaluation studies interpret fund alphas as the incremental performance of managers in relation to passive benchmark indices, which should exhibit statistically insignificant alphas. However, if these indices present significant non-zero alphas, standard (non-adjusted) fund alphas are biased. This paper investigates the impact of using benchmark-adjusted alphas to assess the performance of Portuguese-based mutual funds, investing in domestic and European equities. For the period 2000-2020, our results show that fund benchmarks exhibit significantly negative alphas, which lead to an underestimation of mutual fund performance when employing standard models. As a result, benchmark-adjusted alphas are significantly higher than unadjusted alphas for both fund categories, though the differences are larger for domestic than for European funds. We have also found that the impact of the benchmark-adjustment procedure depends on the state of markets. The domestic (European) benchmark exhibits considerably lower (higher) alphas during crisis than during non-crisis periods. During market crises, the differences between pre- and post-adjustment alphas are statistically significant only for domestic funds, whereas during non-crisis periods, both fund categories exhibit significant performance improvements. Our findings suggest that the benchmark-adjustment procedure has a higher impact when benchmark indices exhibit higher concentration.

When do investors go green? Evidence from a time-varying asset-pricing model

This study employs individual stock returns to examine the evolution of the greenium, which is the risk premium linked to firms’ carbon emissions and environmental transparency. We estimate an asset-pricing model with time-varying risk premia, in which the greenium is associated with a priced ‘greenness and transparency’ factor. We show that investors in the European equity market tend to accept lower returns, ceteris paribus, and hold greener and more transparent assets when economic shifts toward low carbon become more credible. This occurred after the Paris Agreement, the first global climate strike, and the announcement of the EU Green Deal. Opposite signals, such as increases in the prices of oil or critical minerals for the low-carbon transition, are associated with increases in the greenium; that is, more polluting firms are perceived as less risky.

Scale and skills in European active management: Impact of a new regulatory context

This study examines the impact of a new regulatory context on the dynamics and nature of returns to scale in European active management. Using a sample of 1325 actively managed European equity funds and following Pastor, Stambaugh, and Taylor’s model from 2015, we find strong evidence of industry-level decreasing returns to scale. We also find that the new regulatory context creates structural breaks in the optimal scale that significantly change the size-performance relationship. We find strong support that emerging and small-cap funds allow increasing returns to scale. We find evidence that fund families play a moderating role in decreasing returns to scale. Further, the results show a significant upward trend in fund skills evolution.

Symbolic Encoding Methods with Entropy-Based Applications to Financial Time Series Analyses.

Symbolic encoding of information is the foundation of Shannon's mathematical theory of communication. The concept of the informational efficiency of capital markets is closely related to the issue of information processing by equity market participants. Therefore, the aim of this comprehensive research is to examine and compare a battery of methods based on symbolic coding with thresholds and the modified Shannon entropy in the context of stock market efficiency. As these methods are especially useful in assessing the market efficiency in terms of sequential regularity in financial time series during extreme events, two turbulent periods are analyzed: (1) the COVID-19 pandemic outbreak and (2) the period of war in Ukraine. Selected European equity markets are investigated. The findings of empirical experiments document that the encoding method with two 5% and 95% quantile thresholds seems to be the most effective and precise procedure in recognizing the dynamic patterns in time series of stock market indices. Moreover, the Shannon entropy results obtained with the use of this symbolic encoding method are homogenous for all investigated markets and unambiguously confirm that the market informational efficiency measured by the entropy of index returns decreases during extreme event periods. Therefore, we can recommend the use of this STSA method for financial time series analyses.

The low-magnitude and high-magnitude asymmetries in tail dependence structures in international equity markets and the role of bilateral exchange rate

This paper introduces a new Markov-switching mixture copula model with a GAS mechanism in the weighting process to investigate the structures of the upper-tail dependence and lower-tail dependence in a low-magnitude asymmetry state and a high-magnitude asymmetry state for international equity markets. Three important findings arise. First, there are obvious low-magnitude and high-magnitude asymmetries in the tail dependence between equity markets of the U.S. and four nations (Canada, France, Germany, and the U.K.). Second, the difference between the upper-tail dependence and lower-tail dependence increases substantially around after 2000. In general, the importance of the lower-tail dependence is stronger than that of the upper-tail dependence in the high-magnitude asymmetry state. However, the Brexit panic does not change the importance of the tail dependence for the U.S. and European equity markets. Third, the evidence for the impact of the bilateral exchange rate on the tail dependence appears only for some international equity markets during the period of a high-magnitude asymmetry state. The bilateral exchange rate has a significant asymmetric impact on the upper-tail dependence and lower-tail dependence for the U.S. and Canadian equity markets. There is weak evidence of an asymmetric effect of the bilateral exchange rate for the U.S. and U.K. equity markets.

Hedging effectiveness of cryptocurrencies in the European stock market

The aim of the paper is twofold: first, to examine the hedging effectiveness of cryptocurrencies and cryptocurrency portfolios for European equities in bearish and bullish market conditions, and second, to contrast cryptocurrencies with gold as a safe haven asset. To this end, daily data from 2018 to 2022 were employed in a linear and nonlinear Autoregressive Distributed Lag (ARDL) framework. The findings have significant implications for investors, financial intermediaries and regulators.

A right kind of wrong: European equity market forecasting with custom feature engineering and loss functions

This study makes time-series-based predictions on future returns of the STOXX Europe 600 and the German DAX by adopting (in addition to a lagged and transformed version of the target series) a diversified set of predictors. Feature engineering expands further — from the initial raw group of variables, to extract knowledge of market conditions and demand for hedging. A penalisation factor is introduced with loss functions to learn a model from neural networks, in order to adapt a traditional machine learning regression framework to solve the equity forecasting problems in question. Architectures based on convolutional neural network are proposed, treating the obtained feature map similarly to an image. Experiments over different time periods demonstrate that trading strategies derived from the forecasts are more profitable than models based on efficient market assumptions. The temporal, non-stationary structure of financial data has a significant impact on the out of sample success of any model. It thus can be seen that different architectures exhibit different resilience to changing market conditions.

Dissecting the Explanatory Power of ESG Features on Equity Returns by Sector, Capitalization, and Year with Interpretable Machine Learning

We systematically investigate the links between price returns and Environment, Social and Governance (ESG) scores in the European equity market. Using interpretable machine learning, we examine whether ESG scores can explain the part of price returns not accounted for by classic equity factors, especially the market one. We propose a cross-validation scheme with random company-wise validation to mitigate the relative initial lack of quantity and quality of ESG data, which allows us to use most of the latest and best data to both train and validate our models. Gradient boosting models successfully explain the part of annual price returns not accounted for by the market factor. We check with benchmark features that ESG data explain significantly better price returns than basic fundamental features alone. The most relevant ESG score encodes controversies. Finally, we find the opposite effects of better ESG scores on the price returns of small and large capitalization companies: better ESG scores are generally associated with larger price returns for the latter and reversely for the former.

Connectedness structure of Pan-European Equity REITs

ABSTRACT This paper examines the interconnectedness among European equity REITs (Real Estate Investment Trusts) due to increased financialization of the real estate sector and European economic integration. It uses two models, Diebold and Yilmaz's generalised variance decomposition and Barunik and Krehlik's time-frequency dynamics framework. The study covers a sample of 42 Pan-European REITs over a 15-year period from 2004 to 2018 and finds that the connectedness among REITs is influenced by the geographical location and performance of commercial real estate sub-sectors. The dynamic analysis shows that the source of shocks does not determine the persistence, but rather how the markets interpret the shocks during high-frequency intervals. The paper concludes that the connectedness structure among REITs reflects uncertainty interaction, with some effects observed mainly at high frequency levels, and few unexpected shocks found in the long-term stability of REIT returns.

Regime-dependent drivers of the EUR/CHF exchange rate

We analyze drivers of the EUR/CHF exchange rate in different regimes between 2000 and 2020. Structural breaks between these subperiods are estimated in an integrated way together with the drivers that are relevant during these subperiods. Overall, the main drivers of the exchange rate include European equity and volatility indices, interest rate and term structure slope differentials, as well as monetary policy interventions. For the “peg period” September 2011–January 2015, in addition to the observed exchange rate we also analyze the drivers of the latent exchange rate that could have been observed in the absence of the peg. Interestingly, the SNB’s foreign currency investments became a significant driver of the EUR/CHF exchange rate only after the end of the peg period when there was no longer an officially communicated target rate.

Time series momentum: Evidence from the European equity market

This study empirically analyzes time series momentum (TSM) in the European equity market between 2000 & 2020. The study produces additional evidence on TSM where a significant and persistent market price anomaly enables investors to earn abnormal returns. To achieve this goal the present study implements a pooled autoregressive model to test the predictability power of European equity indices of future returns. The results indicate that strategies based on TSM are in line with the discussed literature and enable market agents to earn returns above the market (0.71% per month) by using a six-factor model.

Closing Mechanisms in European Equities

Closing Mechanisms in European Equities