German Stock Index Research Articles

The Quality of Blume and Vasicek Betas for forecasting systematic risk: Evidence from a German stock portfolio

Abstract In both practical applications and empirical capital market research the beta factor is often estimated for the future period using an OLS regression analysis based on historical data. However, these betas are often not reliable for the future. For this reason, methods have been developed to correct or adjust the (raw) beta. The aim of this study is to find out to what extent the forecasting quality of a stock beta can be improved by Blume Beta, Vasicek Beta and a simple variant of Blume Beta ("Adjusted Beta"). For this purpose, an empirical analysis is carried out on the basis of 10 stocks included in the German stock index DAX. For the entire period under review, it can be observed that all three adjustment methods tend to improve the forecast quality compared to the raw beta, with the simple “Adjusted beta” leading to the best values. The examination of two subperiods, one covering the financial and economic crisis of 2008/2009 and the other the Corona pandemic, shows that the forecasting quality tends to be lower when looking at individual stocks compared with the overall period. However, according to the values (i.e. averages of all stocks) of the forecasting quality measures used in this paper, the adjustment procedures mostly produce better values than raw beta in both subperiods. JEL classification numbers: G11. Keywords: Adjusted beta, Blume beta, Vasicek beta, Mean Squared Error.

Measures of stochastic non-dominance in portfolio optimization

Stochastic dominance rules are well-characterized and widely used. This work aims to describe and better understand the situations when they do not hold by developing measures of stochastic non-dominance. They quantify the error caused by assuming that one random variable dominates another one when it does not. To calculate them, we search for a hypothetical random variable that satisfies the stochastic dominance relationship and is as close to the original one as possible. The Wasserstein distance between the optimal hypothetical random variable and the original one is considered as the measure of stochastic non-dominance. Depending on the conditions imposed on the probability distribution of the hypothetical random variable, we distinguish between general and specific measures of stochastic non-dominance. We derive their exact values for random variables with uniform, normal, and exponential distributions. We present relations to almost first-order stochastic dominance and to tractable almost stochastic dominance. Using monthly returns of twelve assets captured by the German stock index DAX, we solve portfolio optimization problems with the first-order and second-order stochastic dominance constraints. The measures of stochastic non-dominance allow us to compare the optimal portfolios with respect to different orders of stochastic dominance from a new angle. We also defined the closest dominating and closest approximately dominating portfolios. They brought a better understanding of the relationship between the two types of optimal portfolios. Using moving window analysis, the relationship of the in-sample measure of stochastic non-dominance to out-of-sample performance was studied, too.

Testing the goodness-of-fit of the stable distributions with applications to German stock index data and Bitcoin cryptocurrency data

Testing the goodness-of-fit of the stable distributions with applications to German stock index data and Bitcoin cryptocurrency data

The role of female leadership in times of financial crisis – an analysis during the COVID-19 pandemic

In 2020 the new COVID-19-virus brought an external shock to the stock markets. In this situation effective leadership was essential to bring companies through the crisis.
 Political observation showed that countries led by women managed the pandemic situation more effectively than those led by men. Therefore, the research objective of this article is to examine whether female leaders were also more successful to guide companies through the pandemic. Success in this study is defined as financial performance based on stock prices.
 To find out whether female managers showed a better financial performance during this crisis, this study examined all companies listed on the German Stock Exchange, which have at least 50 % women in the board. To compare this female managed companies to firms managed mainly by male managers, a market value weighted index for the female managed companies was conducted and compared to the German Stock Index DAX by looking at several financial key figures.
 The analysis of these key figures shows that female managed companies outperformed male managed companies in terms of return as well as risk in the year of the COVID-pandemic but were not able to keep their overperformance in the subsequent years. This may be an indicator that women are superior in leading a company through a crisis but suffer in terms of performance when times have calmed down.

IPO Fund Raising and Chinese Markets IPO Suspension

During the period spanning from 2007 to 2021, China had substantial increase in its Gross Domestic Production (GDP). However, it is noteworthy that this rise was not mirrored by a commensurate expansion in China's A-share market. When examining the performance of China's stock market in relation to other major global economies within the same time frame, it becomes evident that the overall returns of China's stock market are comparatively lower. For example, Standard & Poors 500 increased 236.11%, Nasdaq Composite Index increased 547.75%, the German Stock Index 30 increased 109.99%, and Nikkei Stock Average (Nikkei 225) increased 66.21%, whereas Shanghai Stock Exchange Composite Index increased 33.41%. Based on the monthly Initial Public Offering (IPO) proceeds of China's stock market from 2007 to 2021, this paper comprehensively examines the impact of IPO activities on China's stock market, including the correlation coefficients among IPO fundraised, index amplitude, index return, and GDP. By studying the correlation between the Chinese All-securities Index (CSI) data and IPO fundraising, as well as exploring the impact of policy changes on the market, it can be concluded that IPO fundraising itself has a limited impact on market returns. The low yield in China's country's stock market might be due to corporate information asymmetry, corporate information fraud, and imperfect supervision. The contributions of this paper include the summary and interpretation of China's IPO and related data, the interpretation of China's IPO reform and other policy actions, and the suggestions for the future development direction of China's market.

Selected Methods of optimized Sampling for Index Tracking – Evidence from German Stocks

Abstract The aim of this study is to verify the tracking quality of four different optimization approaches used for approximate replication (sampling) of a stock index. These approaches include relative optimization, optimization according to Markowitz, the use of regression methods and linear optimization. To test the tracking qualities of these strategies, an empirical analysis of portfolios of 10 stocks included in the German stock index DAX is used to determine the in-sample and out-of-sample results. In addition, a portfolio composition based on market capitalization and an equally weighted portfolio are considered. The analysis shows that the in-sample results are quite similar for all index tracking methods used in this study. Considering the out-of-sample results, it can be stated that all four index tracking methods lead to a portfolio that initially shows a high degree of similarity to the benchmark. However, it is surprising that the equally weighted portfolio leads to the best overall results. Therefore, the analysis presented here gives the impression that the uncomplicated equal weighting is preferable to the more sophisticated index tracking methods considered in this study. JEL classification number: G11. Keywords: Index tracking, Sampling, Optimization, Tracking error, Residual risk.

A Statistical Recurrent Stochastic Volatility Model for Stock Markets

The stochastic volatility (SV) model and its variants are widely used in the financial sector, while recurrent neural network (RNN) models are successfully used in many large-scale industrial applications of deep learning. We combine these two methods in a nontrivial way and propose a model, which we call the statistical recurrent stochastic volatility (SR-SV) model, to capture the dynamics of stochastic volatility. The proposed model is able to capture complex volatility effects, for example, nonlinearity and long-memory auto-dependence, overlooked by the conventional SV models, is statistically interpretable and has an impressive out-of-sample forecast performance. These properties are carefully discussed and illustrated through extensive simulation studies and applications to five international stock index datasets: the German stock index DAX30, the Hong Kong stock index HSI50, the France market index CAC40, the U.S. stock market index SP500 and the Canada market index TSX250. An user-friendly software package together with the examples reported in the article are available at https://github.com/vbayeslab.

Out-of-sample performance of the Black-Litterman model

The aim of this paper is to test the out-of-sample performance of the Black Litterman (BL) model for a German stock portfolio compared to the traditional mean-variance optimized (MV) portfolio, the German stock index DAX, a reference portfolio, and an equally weighted portfolio. The BL model was developed as an alternative approach to portfolio optimization many years ago and has gained attention in practical portfolio management. However, in the literature, there are not many studies that analyze the out-of-sample performance of the model in comparison to other asset allocation strategies. The BL model combines implied returns and subjective return forecasts. In this study, for each stock, sample means of historical returns are employed as subjective return forecasts. The empirical analysis shows that the BL portfolio performs significantly better than the DAX, the reference portfolio and the equally weighted portfolio. However, overall, it is slightly outperformed by the MV portfolio. Nevertheless, the BL portfolio may be of greater interest to investors because -according to this study, where the subjective return forecasts are based on historical returns of a rather long past period of time-it could lead in most cases to lower absolute (normalized) values for the stock weights and for all stocks to smaller fluctuations in the (normalized) weights compared to the MV portfolio. JEL classification numbers: C61, G11. Keywords: Black-Litterman, Mean-variance, Portfolio optimization, Performance.

АНАЛІЗ ВЗАЄМОЗВ’ЯЗКУ БІТКОЇНА З ФОНДОВИМИ ІНДЕКСАМИ, ТОВАРАМИ ТА ЦІННИМИ ПАПЕРАМИ

The article analyzes the impact of 44 different factors on the change in the price of bitcoin, such as: yields on US one-year bonds, prices for futures on palladium, platinum, gold, silver, copper, Chinese stock indices, German stock index DAX, French index CAC 40, stock indices of South Africa, India, Mauritius, England, Switzerland, Sweden, South Korea, etc. The most influential factors were selected, with the help of which two regression models were built. The presence of insignificant factors in the first model led to the need to consider the second one, which is much better. The second model lacks multicollinearity, but there are autocorrelation of residues and heteroscedasticity. There was an attempt to eliminate autocorrelation of residues, but it led to a significant reduction in the coefficient of determination to 22%. An attempt to explain the causality of the Bitcoin exchange rate to the KOSPRI index has been made. South Korea is a country, which actively cooperates with two main leaders in Bitcoin mining, namely China, where 65 % of new bitcoins are created, and the United States – 23 % of new bitcoins. Modern economic leaders actively influence not only the economy of their country, but also other economies. Korean companies are actively penetrating both the Chinese economy and the US national economy, which determines their impact on Bitcoin mining, as a large amount of necessary electronics is produced by South Korean companies such as SK hynix Inc. As for the palladium futures rate, palladium is a metal which is actively used in production of the electronics needed to mine bitcoin. Prospects for further research depend on trends in the price of bitcoin. It is possible that the price of the cryptocurrency Bitcoin will gradually rise, as some corporations begin to recognize Bitcoin as a means of payment for goods and services. This will increase demand and, as a result, prices. The confidence of large companies in Bitcoin will indicate the reliability of the cryptocurrency, which in turn will give confidence to minority investors in the need to add cryptocurrency to investment portfolios. The rise in prices will indicate the need to study the impact of various factors on changes in the price of Bitcoin. If the popularity of cryptocurrency begins to wane, it will lead to a rapid loss of its price. This development option will indicate the inexpediency of continuing to study the relationship of this cryptocurrency with these factors and the need to find other ones.

Sleep disturbances, fear, and generalized anxiety during the COVID-19 shut down phase in Germany: relation to infection rates, deaths, and German stock index DAX

BackgroundThe COVID-19 pandemic impacts the whole world. So far, nothing is known about the course of psychological disturbances, such as fear, anxiety, and sleep disturbances of this pandemic over time in Europe. MethodsAim of this web-based survey was to assess the mental health burden of the German public over a period of 50 days after the COVID-19 outbreak. 16,245 individuals responded regarding sleep disturbances, COVID-19-fear, and generalized anxiety disorder (GAD-7). Data were put in relation to infection rates, number of deaths and the German stock index. ResultsThe specific fear increased rapidly in concordance with infection numbers. However, no relation to the number of deaths was found, COVID-19-fear developed reversed to the stock index. Initially, 13.5% of the respondents reported a reduced sleep quality, and 7.2% a moderate generalized anxiety; proceeding simultaneously with high peaks. Finally, more than twice as many respondents showed psychological burdens. ConclusionThe COVID-19-fear decreased within six weeks to the level before the shutdown, indicating a habituation to the threatening situation. However, generalized anxiety remained elevated over time. Sleep disturbances, generalized anxiety as well as economical stock alterations develop in advance to infectiological trends which demands consequent and comprehensible information policies.

Which is the Correct Discount Rate? Arithmetic Versus Geometric Mean

The paper revisits the two major concepts for average historical returns, i. e., the arithmetic mean and the geometric mean, in order to clarify which approach must be used for which application. Conducting a rigorous derivation with a geometric Brownian motion, we can explain that the appropriate discount rate refers to the mean discrete return and, therefore, to the arithmetic mean rather than the often wrongly applied geometric mean. Likewise, the prominent CAPM relationship between the expected asset return and the expected market return is only valid for the arithmetic mean rather than the geometric mean. Using historical data for the German stock index, we illustrate that an inconsistent application can cause severe deviations from the meaningful ex-ante expected performance of an asset, the true discount rate, the true CAPM risk-adjusted return, and the intended performance scenarios of packaged retail and insurance-based investment products (PRIIPs) within the key information documents (KIDs).

The Value of Speaking for \u201cUs\u201d: the Relationship Between CEOs\u2019 Use of I- and We-Referencing Language and Subsequent Organizational Performance

CEOs have been argued to play a critical role for organizational performance. However, CEOs cannot achieve success singlehandedly. They rely on other organizational members to execute and implement their agenda and to contribute to organizational success. In the present research, we propose that CEOs serve as identity leaders of their organization who are able to enhance organizational performance by representing and cultivating a sense of shared collective identity (“us”) with those they lead. One way for leaders to do so is through the use of we-referencing (as opposed to I-referencing) language. We examine this idea in a pre-registered study of organizations listed in the DAX (i.e., leading German stock index) between 2000 and 2016, assessing the impact of CEOs’ use of we- and I-referencing language in letters to the stakeholders (N = 378) on objective indicators of organizational financial performance. In line with hypotheses, results show a positive relationship between CEOs’ use of we-referencing language and key indicators of financial performance: return on assets and sales per employee (while there was no evidence of an association with return on sales). At the same time, results indicate that the use of I-referencing language was unrelated to organizational performance. These findings advance the literature on strategic leadership and on the social identity approach to leadership by suggesting that CEOs’ thinking and acting in collective terms is associated with greater organizational financial performance.

Is Bad News Difficult to Read? A Readability Analysis of Differently Connoted Passages in the Annual Reports of the 30 DAX Companies

This study examines the strategic use of readability to obfuscate negative news in a German financial communication context. Combining a manual and an automated content analysis, the authors assess the tone and readability of three parts (chairman’s address, share-price development, and development in the fiscal year) of the 2014 annual reports of the 30 companies listed in the German stock index DAX. The results indicate that positively connoted passages in annual reports are not necessarily easier to read than negatively connoted passages. Furthermore, the readability of the annual report varies depending on the part and its function within the report.

The Impact of Macroeconomic Factors on the German Stock Market: Evidence for the Crisis, Pre- and Post-Crisis Periods

Today we live in a post-truth and highly digitalized era characterized by a flow of (mis-) information around the world. Identifying the impact of this information on stock markets and forecasting stock returns and volatilities has become a much more difficult task, perhaps almost impossible. This paper investigates the impact of macroeconomic factors, German government bond yields, sentiment and other leading indicators on the main German stock index, namely the DAX30, for the time period from 1991 to 2018. Using a dataset on 24 factors and over a timeframe of about 27 years, we found evidence that across most subsamples, the Composite Leading Indicator (OECD), the Institute for Economic Research (ifo) Export Expectations index, the ifo Export Climate index, exports, the Consumer Price Index CPI, as well as 3 y German government bonds yields show delayed impacts on stock returns. We further found that the delayed impact of the constituents of the monetary aggregate M2 on stock returns changed direction between the crisis and post-crisis periods. Overall, the results illustrate that in the crisis period a larger number of factors and economic indicators had significant impacts on the stock returns compared to the pre- and post-crisis periods. This implies that in the post-crisis period a macro-driven market prevails.

The conservatism as a cultural value that underlies the financial reporting: Empirical evidence from listed companies in European regulated markets

This paper intends to assess the existence of confirmatory variables of conservatism based on the disclosures made in the financial report. Data were collected from the annual accounts for 2013 and 2014 disclosed by 137 listed entities (non-financial groups) in the European Union (EU) stock indexes: Portuguese Stock Index (PSI)-20, Iberian Index (IBEX)-35, Financial Times Stock Exchange (FTSE)- 100, German Stock Index (DAX)-30 e Stockholm Stock Exchange (OMX)-S30. The content analysis was used as a methodology. After applying multiple linear regression models, the findings indicate that the assessment of the conservatism based on relevance is consistent with the associations suggested in the literature. One of the main contributions of this research is the consideration of the impact of culture on financial reporting, namely through the proposal of a new proxy for the measurement of conservatism based on the financial report.

TINGKAT INTEGRASI PASAR MODAL INDONESIA DENGAN PASAR MODAL GLOBAL

This study aims to determine the level of capital market interation Indonesia (Jakarta Composite Index) with American capital markets (Dow Jones Industrial Average), England (FTSE 100 Index), German (Deutsche Borse AG German Stock Index), Hongkong (Hang Seng) and Japan (Nikkei 225). The result of this study expected to become an information for investment actors in deciding to invest at the stockmarket. These variables include the Indonesian capital market as the dependent variable and the global capital markets as an independent variable. Analysis tool is the correlation coefficient and t test. It is used to determine the significance of the correlation coefficient between independent variables and the dependent variable. Based on the calculation of the correlation coefficient is exemplified that the market index Indonesian capital market and the five major global capital markets has been integrated on various classification levels of relationships or different integration. The level of integration between Indonesian capital market and capital markets of America and Japan are very strong level of integration, the German stock market has stronglevel integration, and England and Hong Kong capital market has low level integration.

How Can We Interpret the Estimates of the Full BEKK Model with Asymmetry? The Case of French and German Stock Returns

This study conducts careful interpretations of the model parameters from the full Baba-Engle-Kraft-Kroner (BEKK) model with asymmetric effects. This study also includes a case study, in which we interpret the full BEKK model parameter estimates from the empirical examinations using French and German stock index returns. More concretely, in this paper, we firstly examine the model formula and obtain general interpretations of the full BEKK model parameters. This shall be particularly helpful to understand not only the structure of the full BEKK model but also the mechanisms of similar multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) models. After the above general considerations, this study also interprets the case results, in which the full BEKK model is applied to French and German stock index returns. The concrete illustrations demonstrated in this case study shall be also very useful for future related research.

Implied volatility and state price density estimation: arbitrage analysis

This paper deals with implied volatility (IV) estimation using no-arbitrage techniques. The current market practice is to obtain IV of liquid options as based on Black–Scholes (BS type hereafter) models. Such volatility is subsequently used to price illiquid or even exotic options. Therefore, it follows that the BS model can be related simultaneously to the whole set of IVs as given by maturity/moneyness relation of tradable options. Then, it is possible to get IV curve or surface (a so called smile or smirk). Since the moneyness and maturity of IV often do not match the data of valuated options, some sort of estimating and local smoothing is necessary. However, it can lead to arbitrage opportunity if no-arbitrage conditions on state price density (SPD) are ignored. In this paper, using option data on DAX index, we aim to analyse the behavior of IV and SPD with respect to different choices of bandwidth parameter h, time to maturity and kernel function. A set of bandwidths which violates no-arbitrage conditions is identified. We document that the change of h implies interesting changes in the violation interval of moneyness. We also perform the analysis after removing outliers, in order to show that not only outliers cause the violation of no-arbitrage conditions. Moreover, we propose a new measure of arbitrage which can be considered either for the SPD curve (arbitrage area measure) or for the SPD surface (arbitrage volume measure). We highlight the impact of h on the proposed measures considering the options on a German stock index. Finally, we propose an extension of the IV and SPD estimation for the case of options on a dividend-paying stock.

Improving stock index forecasts by using a new weighted fuzzy-trend time series method

We propose using new weighted operators in fuzzy time series to forecast the future performance of stock market indices. Based on the chronological sequence of weights associated with the original fuzzy logical relationships, we define both chronological-order and trend-order weights, and incorporate our proposals for the ex-post forecast into the classical modeling approach of fuzzy time series. These modifications for the assignation of weights affect the forecasting process, because we use jumps as technical indicators to predict stock trends, and additionally, they provide a trapezoidal fuzzy number as a forecast of the future performance of the stock index value. Working with trapezoidal fuzzy numbers allows us to analyze both the expected value and the ambiguity of the future behavior of the stock index, using a possibilistic interval-valued mean approach. Therefore, using fuzzy logic more useful information is provided to the decision analyst, which should be appropriate in a financial context. We analyze the effectiveness of our approach with respect to other weighted fuzzy time series methods using trading data sets from the Taiwan Stock Index (TAIEX), the Japanese NIKKEI Index, the German Stock Index (DAX) and the Spanish Stock Index (IBEX35). The comparative results indicate the better accuracy of our procedure for point-wise one-step ahead forecasts.

Predicting European carbon emission price movements

ABSTRACTThe European carbon emission trading market is critical in achieving planned carbon emission reduction for global sustainable growth. This paper investigates various statistical methods in forecasting the European carbon emission (CO2 hereafter) price movements. The paper builds a predictive regression model of CO2 price movements with past returns of various commodities and financial products. In the paper, 22 functional forms of five different classifiers are employed and CO2 price movements are forecast. Results indicate that the past returns of Brent crude futures, natural gas (NG), Financial Times Stock Exchange 100 (FTSE100), Deutscher Aktienindex (German stock index) 30 (DAX30), Cotation Assistée en Continu (French stock index) 40 (CAC40) and Standard & Poor's 500 (S&P500) are statistically significant in forecasting the current CO2 price movements. The authors also found that the bagged decision tree of the ensemble classifier best forecasts the CO2 price movements. The result should be relevant to firms that wish to trade European carbon emissions.