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González Sánchez, Mariano

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0000-0002-8255-9478
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González Sánchez
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Mariano
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2019 - 201912020 - 202421
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Mostrando 1 - 10 de 22
  • Miniatura
    Publicación
    The Role of Assumptions in Ohlson Model Performance: Lessons for Improving Equity-Value Modeling
    (MDPI, 2021) Fullana, Olga; Toscano, David; González Sánchez, Mariano
    In this paper, we test whether the short-run econometric conditions for the basic assumptions of the Ohlson valuation model hold, and then we relate these results with the fulfillment of the short-run econometric conditions for this model to be effective. Better future modeling motivated us to analyze to what extent the assumptions involved in this seminal model are not good enough approximations to solve the firm valuation problem, causing poor model performance. The model is based on the well-known dividend discount model and the residual income valuation model, and it adds a linear information model, which is a time series model by nature. Therefore, we adopt the time series approach. In the presence of non-stationary variables, we focus our research on US-listed firms for which more than forty years of data with the required cointegration properties to use error correction models are available. The results show that the clean surplus relation assumption has no impact on model performance, while the unbiased accounting property assumption has an important effect on it. The results also emphasize the uselessness of forcing valuation models to match the value displacement property of dividends.
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    Sectoral composition of GDP and greenhouse gas emissions: an empirical analysis in EU27
    (Springer, 2023) Martín Ortega, Juan Luis; González Sánchez, Mariano
    Understanding the relationship between economic growth and GHG emissions is crucial for achieving sustainable development and the Paris Agreement decarbonization goals. The objective of this paper is to analyse the long-term relationship between sectoral Gross Domestic Product (GDP) and greenhouse gas (GHG) emissions in the EU27 under the framework of the Environmental Kuznets Curve (EKC) theory. Previous research has yielded inconclusive results and presented various drawbacks, such as the omission of sectoral economic growth, poor data quality, and the use of methods that did not enable hypothesis testing. In contrast, this research applies the Autoregressive Distributed Lag (ARDL) method to assess the EKC in the long-term for the industrial, service, and agriculture components of GDP for EU27 countries from 1990 to 2018 using audited data from the United Nations Framework Convention on Climate Change. Despite a wide body of literature, this is the first research to investigate the EKC’s nature in sectoral GDP in the EU-27. The EKC theory has been confirmed statistically in only five countries. Nevertheless, the results imply that economic growth has a lowering impact on the environment in more than half of the EU-27, as the EKC theorizes. A high impact on GHG emissions is observed in the service sector of those countries that combined a high share of services in the national economy with weak energy efficiency performance in the transport and building sectors. Likewise, countries with major employment in carbon-intensive industry branches tend to show a long-term impact on GHG emissions.
  • Miniatura
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    Factorial asset pricing models using statistical anomalies
    (Elsevier, 2022) González Sánchez, Mariano
    Although up to seven factors market, size, earnings, profitability, investment, momentum, and quality are used to explain asset returns mainly due to anomalies, there is no consensus in the financial literature on the suitability of the factors to include in asset pricing models. Empirical research has found that investors’ responses to market movements up and down are not symmetric. We show a new type of anomaly, statistical anomalies, resulting from decomposing asset returns into three independent time series: positive outliers (the good), negative outliers (the bad), and the remainder or Gaussian returns (the usual). Using a sample consisting of 49 equalweighted US industrial portfolios with daily and monthly frequencies from 1969 to 2020, we find evidence that the good-usual-bad factor model exhibits fewer anomalies, better explanatory power, and greater robustness than the “magnificent seven” factors model. Our results are relevant to investors trading at less than monthly frequencies.
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    Board of Directors’ Remuneration, Employee Costs, and Layoffs: Evidence from Spain
    (MDPI, 2021-07) González Sánchez, Mariano; Ibáñez Jiménez, Eva María; Segovia San Juan, Ana Isabel
    Most of the empirical studies on board remuneration have focused on finding explanatory performance measures. There are studies that analyze if the compensation contracts of directors reward managers in such a way that they strive to maximize firm performance and shareholders’ wealth; however, there are few studies on the social aspect of corporate governance, or agent–employee and principal–employee relationships. Thus, in this study, our aim is to test whether there is a causal relationship between the remuneration of the board of directors of listed companies and the personnel policies of the companies, expressed through the cost of personnel and layoffs. For that, we used a sample of Spanish listed companies, and we found that two performance measures (return on equity and earnings per share on market price) have a greater effect on the growth rate of board remuneration when layoffs occur. Additionally, we found that the sales revenue and cash flow on total assets subsequently influenced personnel management.
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    Influence of Bloomberg’s Investor Sentiment Index: Evidence from European Union Financial Sector
    (MDPI, 2021) Morales de Vega, M. Encina; González Sánchez, Mariano
    A part of the financial literature has attempted to explain idiosyncratic asset shocks through investor behavior in response to company news and events. As a result, there has been an increase in the development of different investor sentiment measurements. This paper analyses whether the Bloomberg investor sentiment index has a causal relationship with the abnormal returns and volume shocks of major European Union (EU) financial companies through a sample of 85 financial institutions over 4 years (2014–2018) on a daily basis. The i.i.d. shocks are obtained from a factorial asset pricing model and ARMA-GARCH-type process; then we checked whether there is both individual and joint causality between the standardized residuals. The results show that the explanatory capacity of the shocks of the firm Bloomberg sentiment index is low, although there is empirical evidence that the effects correspond more to the situation of the financial subsector (banks, real estate, financial services and insurance) than to the company itself, with which we conclude that the sentiment index analyzed reflects a sectorial effect more than individual one.
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    The extreme temperature factor in asset pricing models: Evidence from Europe
    (ELSEVIER, 2024-08) González Sánchez, Mariano; Arguedas Sanz, Raquel; Segovia San Juan, Ana Isabel
    Growing concern about climate change has led to increased research into the effects of climate on markets. One of the weather variables studied is temperature. The previous studies considered that the temperature influences on asset returns through changes in investor mood. There are few studies that incorporate a risk factor to analyze the effects of temperature changes on asset returns. We extract positive and negative extreme temperature changes to design three temperature factors. By a cross-section asset pricing model, we find evidence that temperature shocks (hot and cold) show a significant monthly risk premium and skewness for temperature changes.
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    The influence of Google search index on stock markets: an analysis of causality in-mean and variance
    (Emerald Insight, 2021) González Sánchez, Mariano
    Purpose – This empirical work studies the influence of investors’ Internet searches on financial markets. Design/methodology/approach – In this study, an asset pricing model with six factors is used, and autoregression, heteroscedasticity and moving average are taken into account to extract the independent shocks of each variable. Subsequently, a causality in-mean and in-variance analysis is performed to test the influence of Google searches on financial market variables, specifically, to test whether there is an influence on the idiosyncratic returns of financial assets. Findings – Unlike most of the literature, the results show that Google searches on the name of listed companies have little influence on the trend and volatility of asset returns. On the contrary, these searches are shown to have a significant influence on trading volumes in the following week. Practical implications –When analyzing specific effects, such as the influence of Internet searches, on financial markets, it is necessary that the model must include financial properties (asset valuation models) and statistical characteristics (stylized facts); otherwise, the empirical results could be inconsistent, since, among other issues, statistical findingsmaynot be robust given autocorrelation and heteroscedasticity, and if an asset valuationmodel is not considered, the specific effect analyzed could simply be an indirect effect of a risk factor excluded from the model. Originality/value – The empirical evidence shows that individual investors using Google have a significant influence on volume only so that institutional investors using other sources of information drive market prices. This means that potential investors should only be interested in the Internet searches index if their interest is focused on trading volume
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    Earnings management in socially responsible firms around seasoned equity offerings: Evidence from France, Germany, Italy and Spain
    (Elsevier, 2023-04) González Sánchez, Mariano; Segovia San Juan, Ana Isabel; Ibáñez Jiménez, Eva María
    Earnings manipulation (EM) has been a matter of interest to researchers for decades. How this is measured or the motivations of managers to engage in such actions have been studied in detail. Some studies find that managers have incentives to manipulate the earnings that accompany financing activities such as seasoned equity offerings (SEO). Under the corporate social responsibility (CSR) approach, profit manipulation actions have been shown to be mitigated in socially responsible companies. To the best of our knowledge, there are no studies that analyse whether CSR mitigate EM actions in a SEO context. Our work contributes to filling this gap. We investigate whether socially responsible companies exhibit EM in periods prior to SEO. This study uses a panel data model of listed non-financial firms from countries with the same currency and similar accounting rules (France, Germany, Italy and Spain) between 2012 and 2020. Our results show that in all the countries analysed, except Spain, there is a manipulation of operating cash flows in the year prior to capital increases, and only in French companies is there a decrease in the management of this variable in companies with higher development of corporate social responsibility.
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    Market and Liquidity Risks Using Transaction-by-Transaction Information
    (MDPI, 2021-07) González Sánchez, Mariano; Ibáñez Jiménez, Eva María; Segovia San Juan, Ana Isabel
    The usual measures of market risk are based on the axiom of positive homogeneity while neglecting an important element of market information—liquidity. To analyze the effects of this omission, in the present study, we define the behavior of prices and volume via stochastic processes subordinated to the time elapsing between two consecutive transactions in the market. Using simulated data and market data from companies of different sizes and capitalization levels, we compare the results of measuring risk using prices compared to using both prices and volumes. The results indicate that traditional measures of market risk behave inversely to the degree of liquidity of the asset, thereby underestimating the risk of liquid assets and overestimating the risk of less liquid assets.
  • Miniatura
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    Asset pricing models in emerging markets: Factorial approaches vs. information stochastic discount factor
    (Elsevier, 2022) González Sánchez, Mariano
    The factorial asset pricing models generally performs poorly in emerging markets. This prediction bias implies anomalies. This study analyzes whether it is consequence of ignoring other source of risk. We apply a non-parametric approach (stochastic discount factor) to improve the forecasts of the usual factorial models. For a sample of 26 emerging equity markets, we find that the information portfolio built from the stochastic discount factor shows better goodness of fit of emerging market and, only the factor that accounts value stocks versus growth stocks is relevant to emerging equity markets, specifically, it is a sensitivity measure at risk.