Javier Perote

• Professor
• Professor (Assistant) at University of Salamanca

Identifying the effects of quantitative easing (QE) on asset return correlations is critical to assessing such policies’ impact across financial markets. In this paper, we use a dynamic conditional correlation model that allows us to measure the impact of unconventional monetary policy on time-varying correlations. Our results suggest that QE signi...

Predicting carbon and oil prices is recently gaining relevance in the climate change literature. This is due to the fact that conventional energy market analysis and the design of mechanisms for climate change mitigation constitute key variables for artificial carbon markets. Yet, modelling non‐linear effects in time series remains a major challeng...

Real options analysis is an adequate tool with which to value companies and projects under investment uncertainty. Nevertheless, the estimation of the volatility to be employed in the valuation procedure is a challenging task. The volatility parameter not only affects the investment value, but is also important in strategic decision-making. The aim...

Purpose: This paper investigates the potential influence of managers on sustainability assurance. When the quality of sustainability reporting is questionable due to subsequent restatements, we explore whether assurance is used to enhance its credibility, as a legitimization tool, or as an impression management strategy. Additionally, we analyze ho...

This paper proposes new risk measures by accurately estimating the components of solvency risk and focusing on prudential policy implementation. We use semi‐nonparametric statistics to model the stylised facts of the probability density functions, particularly the higher‐order moments of three variables: the solvency decline rate, the tier decline...

The increasing volatility experienced in financial and commodity markets has motivated the search of frequency functions with more complex attributes to characterize their asset returns distribution. In this research, two semi-nonparametric distributions are proposed and compared, the Gram-Charlier expansion and a novel Edgeworth expansion for the...

Purpose This paper aims to analyze the volatility transmission between an energy stock index and a financial stock index in emerging markets during recent high instability periods. The study considers the impact of both the period under analysis and the data frequency on the direction and intensity of the contagion, as well as the effect of the pot...

Electricity production in highly hydrological‐dependent systems is determined by different weather phenomena, which strongly impact spot prices. To account for such stylized facts, we propose a stochastic process with a mean reversion and switching regime component to represent the dynamics of the spot price. The short‐term movements are represente...

This study examines how green bonds and environmental, social and governance (ESG) stock market returns have reacted to the COVID-19 crisis in the US. Unlike the Standard and Poor's (S&P) 500 index, the response of green bonds and ESG markets to pandemic progress is nonlinear: A low (large) level of confirmed new cases of COVID-19 has a positive (n...

Whenever a crisis hits, it is likely to spread simultaneously among stock markets due to their interconnection. This phenomenon, known in the literature as financial contagion, may have a long-lasting effect and manifest itself in herd behavior. A sample of worldwide MSCI (Morgan Stanley Capital International) indices covering the subprime, Europea...

This paper introduces the effect of the crossed products of Hermite polynomials on Gram-Charlier densities. This allows to capture the impact of the interaction between skewness and kurtosis and evaluate this new parameter as an additional source of information for risk management. We show that our modified Gram-Charlier density presents an improve...

This paper introduces a new risk measure for portfolio choice and compares its performance with two related metrics, namely the behavioral variance and the modified variance by using a Taylor’s expansion. The methodology for our proposal naturally incorporates investor attitudes to risk related to skewness and kurtosis by assuming a Gram-Charlier r...

This paper implements a procedure for dynamically selecting the Gram–Charlier approximation that best fits the empirical distribution of cryptocurrency returns at any point in time. The endogenous selection of the Gram–Charlier expansion length exploits its property for approximating frequency distributions through a flexible number of parameters t...

This paper adopts a real options approach to investigate the effects of economic policy uncertainty (EPU) and monetary policy on R&D investment. Using a panel of U.S. firms over the period 2000-2019, we show that higher (lower) EPU and contractionary (expansionary) monetary policy exert a positive (negative) and significant influence on R&D investm...

This article proposes a methodology to calculate the effect of moral hazard on short term credit (working capital) to small and medium-sized enterprises (SMEs). The methodology incorporates four categories of moral hazard ratio defined in a previous study, which are employed to determine probability of default based on a logit model. To this end, a...

This paper establishes a brand-new perspective of analyzing the risk of crypto assets through a semi-nonparametric approach, discussing its theoretical advantages and testing its performance compared to parametric approaches and in terms of backtesting techniques and different risk measures: Value-at-Risk, Expected Shortfall and Median Shortfall. O...

This paper studies the distribution of the firm size for the Colombian economy showing evidence against the Gibrat’s law, which assumes a stable lognormal distribution. On the contrary, we propose a lognormal expansion that captures deviations from the lognormal distribution with additional terms that allow a better fit at the upper distribution ta...

Energy transactions in liberalized markets are subject to price and quantity uncertainty. This paper considers the spot price and energy generation to follow a bivariate semi-nonparametric distribution defined in terms of the Gram–Charlier expansion. This distribution allows us to jointly model not only mean, variance, and correlation but also skew...

This paper investigates the impact of monetary policy on firm-level investment in contexts of economic turmoil. Using a panel of US public firms for the period 2000–2019, we show that policy-rate-based transmission mechanisms are undermined when uncertainty spikes. Furthermore, we find evidence of the existence of asymmetries at the firm level. In...

The semi-nonparametric (SNP) modeling of the return distribution has been proved to be a flexible and accurate methodology for portfolio risk management that allows two-step estimation of the dynamic conditional correlation (DCC) matrix. For this SNP-DCC model, we propose a stepwise procedure to compute pairwise conditional correlations under bivar...

The semi-nonparametric (SNP) modeling of the return distribution has been proved to be a flexible and accurate methodology for portfolio risk management that allows two-step estimation of the dynamic conditional correlation (DCC) matrix. For this SNP-DCC model, we propose a stepwise procedure to compute pairwise conditional correlations under bivar...

Different economic studies have been concentrated on specific and/or isolated factors to explain public debt evolution. In this article we have developed an integrated viewpoint based on financial, social and governance or institutional factors. Under our dynamic econometric assessment for the last two decades (i.e., since the Euro currency incepti...

This paper analyses risk quantification for three main stock market index exchange‐traded funds in world financial markets. We compare the relative performance of a set of parametric and semi‐nonparametric models in terms of both value‐at‐risk and expected shortfall backtesting techniques. To this end, we explore the result of the jointly elicitabi...

https://authors.elsevier.com/c/1bFcC3mS~2EHGf

The transition from traditional energy to cleaner energy sources has raised concerns from companies and investors regarding, among other things, the impact on financial downside risk. This article implements backtesting techniques to estimate and validate the value-at-risk (VaR) and expected shortfall (ES) in order to compare their performance amon...

This paper introduces a semi-nonparametric approach for modeling Bitcoin risk relatively to other parametric distributions and volatility models. Model performance is assessed through different backtesting techniques, including multinomial test, for three risk measures: Value-at-Risk, Expected Shortfall and Median Shortfall. Our results show that t...

This paper investigates on the alpha-stable distribution capacity to capture the probability of market crashes by means of the dynamic forecasting of its alpha and beta parameters. On the basis of the GARCH-stable model, we design a market crash forecasting methodology that involves three-stepwise procedure: (i) Recursively estimation the GARCH-sta...

Recent regulation is becoming more oriented to a cleaner world energy market, bringing concerns on traditional energy companies and investors regarding consequences of transition and financial downside risks. This article implements techniques to estimate and validate the two main financial risk measures of four renewable energy stocks and four tra...

This paper introduces a semi-nonparametric (SNP) methodology for the modeling of skewness, leptokurtosis and high-order moments in electricity markets. We highlight the importance of accurately measuring these features in many contexts (e.g. design of power plants with different technologies, fuel prices, and energy demand) and the need for using f...

In this paper, we analyse the demand for real money balances in the United States for the period 1990Q1–2017Q2 using a novel Divisia monetary aggregate developed by Barnett et al. (2013). Unlike simple-sum aggregates, Divisia aggregates take into account the different degrees of ‘moneyness’ of each monetary asset. In addition, Divisia aggregates ha...

This article implements backtesting techniques to estimate and validate the Value-at-Risk (VaR) and expected shortfall (ES) of four renewable energy stocks and four traditional energy stocks for the period 2005-2016. The models used to estimate VaR and ES are AR(1)-GARCH(1,1), AR(1)-EGARCH(1,1) and AR(1)-APARCH(1,1), all of them under either normal...

Since 2010, Bitcoin has shown high price volatility, spurring a debate regarding the underlying reasons that lead economic agents to demand it. This paper analyzes the demand for Bitcoin in order to determine whether it stems from Bitcoin's utility as a medium of exchange, a speculative asset, or as a safe-haven commodity. We examine Bitcoin from a...

In this paper we show that flexible probability distribution functions, in addition to being able to capture stylized facts of financial returns, can be used to identify pure higher-order effects of investors' optimizing behavior. We employ the five-parameter weighted generalized beta of the second kind distribution—and other density functions nest...

This paper studies the risk assessment of semi-nonparametric (SNP) distributions for leveraged exchange trade funds, (L)ETFs. We applied the SNP model with dynamic conditional correlations (DCC) and EGARCH innovations, and implement recent techniques to backtest Expected Shortfall (ES) to portfolios formed by bivariate combinations of major (L)ETFs...

This paper contributes to the literature on the estimation of the Risk Neutral Density (RND) function by proposing a log-semi-nonparametric (log-SNP) distribution as the implicit RND when the Gram-Charlier model is used for option pricing. The performance of the model is compared to the lognormal (Black Scholes) benchmark for a sample of option pri...

This research studies how incentives to cooperation and sustainability through up-front pay mechanisms can impact teamwork. For this purpose, we carry out certain laboratory experiments on the two-player Minimum Effort Game. First, we compare two treatments: one with “free play teams”, against teams forced to make a non-refundable up-front payment...

This paper uses panel data estimation under the assumptions of the agency theory of insider trading to identify the factors enhancing bank insider trading. We conclude that the more entrenched the directors, the less prestigious the bank, the bigger the firm and the lower the charter values for high levels of ownership, the higher the intensity of...

This paper calibrates risk assessment of alternative methods for modeling commodity ETFs. We implement recently proposed backtesting techniques for both value-at-risk (VaR) and expected shortfall (ES) under parametric and semi-nonparametric techniques. Our results indicate that skewed-t and Gram-Charlier distributional assumptions present the best...

This paper examines the failure of small- and medium-sized enterprises (SMEs) by considering both traditional financial ratios and other ratios proposed to capture 'moral hazard effects' in the presence of collateral, which lie in the principal-agent relationship between lender and borrower under conditions of asymmetric information. With a new Col...

We propose a novel semi-nonparametric distribution that is feasibly parameterized to represent the non-Gaussianities of the asset return distributions. Our Moments Expansion (ME) density presents gains in simplicity attributable to its innovative polynomials, which are defined by the difference between the nth power of the random variable and the n...

This article proposes a three-step procedure to estimate portfolio return distributions under the multivariate Gram–Charlier (MGC) distribution. The method combines quasi maximum likelihood (QML) estimation for conditional means and variances and the method of moments (MM) estimation for the rest of the density parameters, including the correlation...

The Lazarillo of Tormes’ picaresque novel introduces a story where two subjects sequentially extract (one, two or three) tokens from a common pool in an asymmetric information framework (the first player cannot observe her partners’ actions). By introducing a reward for both subjects in case that in every period at least one subject had taken one s...

Experimental data. Data obtained from the experiment. (ZIP)

In this article, we propose a new methodology based on a (log) semi-nonparametric (log-SNP) distribution that nests the lognormal and enables better fits in the upper tail of the distribution through the introduction of new parameters. We test the performance of the lognormal and log-SNP distributions capturing firm size, measured through a sample...

The paper proposes a semi-nonparametric methodology consistent with dynamic conditional correlations and high-order moments to jointly estimate transmissions in volatility, skewness and kurtosis in highly volatile scenarios among developed and emerging markets. As a by-product of the SNP-VSK model, we measure co-movements between conditional correl...

This paper studies the performance of the high-order moment CAPM market models in emerging markets. We apply the cubic market model (4-moment CAPM) to sixteen emerging market stock indices ranging from January, 2010 to September, 2015. Performance of the model is evaluated through the Fama and MacBeth’s two-step regression and through different cor...

This paper studies the impact of different types of parental involvement on the students’ performance on both reading and mathematics. We analyze the results of PISA surveys for the 9 countries that implemented the PISA parental questionnaire in 2009 (reading) and 2012 (mathematics). We find that daily parental involvement in academic homework is a...

Research productivity distributions exhibit heavy tails because it is common for a few researchers to accumulate the majority of the top publications and their corresponding citations. Measurements of this productivity are very sensitive to the field being analyzed and the distribution used. In particular, distributions such as the lognormal distri...

The current paper produces the very first experiment on the relationship between insider trading and earnings management in an unregulated scenario, where the decision of misreporting only depends on ethical considerations. Using a price formation model based upon the excess of supply/demand, but also on the difference between the reported and real...

The paper proposes a semi-nonparametric (SNP) methodology consistent with dynamic conditional correlations (DCC) and high-order moments to jointly estimate transmissions in volatility, skewness and kurtosis among different stock markets. As a by-product of the so-called SNP-VSK model, we measure the co-movements between conditional correlations and...

In this study, we propose a new semi-nonparametric (SNP) density model for describing the density of portfolio returns. This distribution, which we refer to as the multivariate moments expansion (MME), admits any non-Gaussian (multivariate) distribution as its basis because it is specified directly in terms of the basis density’s moments. To obtain...

This article discusses the implementation and advantages of classroom experiments for teaching and learning about economic and entrepreneurial decisions. We argue that this methodology is not only appealing from the students’ perspective but also is consistent with the European Higher Education Area philosophy. Particularly, classroom experiments c...

We derive the conditions for the optimal portfolio choice within a constant relative risk aversion type of utility function considering alternative probability distributions that are able to capture the asymmetric and leptokurtic features of asset returns. We illustrate the role —beyond risk aversion— played by higher-order moments in the optimal d...

We study experimentally in the laboratory the situation when individuals have to report their private information about a (dependent) variable to a public authority that then makes inference about the true values given a known (independent) variable using a regression technique. It is assumed that individuals prefer this predicted value to be as cl...

Highly volatile scenarios, such as those provoked by the recent subprime and sovereign debt crises, have questioned the accuracy of current risk forecasting methods. This paper adds fuel to this debate by comparing the performance of alternative specifications for modeling the returns filtered by an ARMA-GARCH: Parametric distributions (Student’s t...

The need to provide accurate value-at-risk (VaR) forecasting measures has triggered an important literature in econophysics. Although these accurate VaR models and methodologies are particularly demanded for hedge fund managers, there exist few articles specifically devoted to implement new techniques in hedge fund returns VaR forecasting. This art...

We design a laboratory experiment to study the relation between earnings management and insider trading and their effects on the stock markets. The experiment simulates a market where one insider and three outsiders trade on the stocks of a company. We show that if the insider affects the stock price with her earnings announcements, then she will u...

This paper compares two alternative estimation methods for estimating the density underlying financial returns specified in terms of a finite Gram–Charlier (GC) expansion. Maximum likelihood (ML) is the most widely employed method despite the fact that it is only consistent under the Gaussian or the true density, and usually involves convergence pr...

This article presents a new semi-nonparametric (SNP) density function, named Positive Edgeworth-Sargan (PES). We show that this distribution belongs to the family of (positive) Gram-Charlier (GC) densities and thus it preserves all the good properties of this type of SNP distributions but with a much simpler structure. The in-and out-of-sample perf...

This paper proposes multivariate Semi-Nonparametric distributions (SNP) based on the General Moments Expansion (GME) to model portfolio returns distribution. The multivariate GME is as exible as other multivariate SNP distributions based on Gram-Charlier series and thus is capable of capturing salient empirical regularities of …nancial data but it...

Growth models under uncertainty and constant relative risk aversion (CRRA) utility are fragile in explaining consumers’ choice, as equilibrium consumption is dependent on distributional assumptions. We show that, under semi-nonparametric distributions, general equilibrium models are stable, as the existence of expected utility is guaranteed.

This article proposes the Method of Moments (MM) as a straightforward and accurate method to estimate financial returns densities when the Gram-Charlier asymptotic expansion is assumed as the data generating process. We show that MM provides very similar outcomes than Maximum Likelihood (ML) and overcomes both theoretical and empirical drawbacks of...

This paper generalizes the Dynamic Conditional Correlation (DCC) model of Engle (2002), incorporating a flexible non-Gaussian distribution based on Gram-Charlier expansions. The resulting semi-nonparametric-DCC (SNP-DCC) model allows estimation in two stages and deals with the negativity problem which is inherent in truncated SNP densities. We test...

Economic growth models under uncertainty and rational agents with CRRA utility have been shown to provide quite fragile explanations of consumers.choice as equlib- rium comsumption paths (expected utility) are drastically dependant on distributional assumptions. We show that assuming a SNP distribution for random consumption provides stability to g...

This paper analyzes the out-of-sample ability of different parametric and semi-parametric GARCH-type models to forecast the conditional variance and the condi-tional and unconditional kurtosis of three types of financial assets (stock index, ex-change rate and Treasury Note). For this purpose, we consider the Gaussian and Student-t GARCH models by...

This paper proposes a semi-nonparametric (SNP) methodology for computing portfolio value-at-risk (VaR) that is more accurate than both the traditional Gaussian-assumption-based methods implemented in the software packages used by risk analysts (Risk Metrics), and alternative heavy-tailed distributions that seem to be very rigid to incorporate jumps...

This paper generalizes the Dynamic Conditional Correlation (DCC) model of Engle (2002) to incorporate a flexible non-Gaussian distribution based on Gram-Charlier expansions. The resulting semi-nonparametric (SNP)-DCC model admits a separate estimation of, in a first stage, the individual conditional variances under a Gaussian distribution and, in t...

This paper introduces a new family of multivariate distributions based on Gram-Charlier and Edgeworth expansions. This family encompasses many of the univariate semi-non-parametric densities proposed in financial econometrics as marginal of its different formulations. Within this family, we focus on the analysis of the specifications that guarantee...

In the recent literature, several competing hypotheses have been advanced to explain the stylized fact of declining contributions in repeated public goods experiments. We present results of an experiment that has been designed to evaluate these hypotheses. The experiment elicits individual beliefs about the contributions of the partners in the repe...

Experimental research on first price sealed bid auctions has usually involved repeated settings with information feedback on winning bids and payoffs after each auction round. Relative to the risk neutral Nash equilibrium, significantly higher bidding has been reported. The present paper reports the results of experimental first price auctions with...

The current research examines the capacity of the Edgeworth-Sargan density on forecasting market crashes. Focusing on the 1987 stock market crash the performance of this distribution is compared to the Student’s t concluding that the latter overestimates the risk. In contrast, and due to its flexible parametric structure, the Edgeworth-Sargan densi...

No evidence exists so far on the causality between insider trading and stock returns for the banking industry. This paper provides the first evidence on the casual relationship between both variables both at the aggregate and at the firm level. We find that bank insiders are able to predict future returns at firm level, but no relationship is found...

This paper examines the causal relationship between directors' dealings and monthly stock returns in the Spanish market for the first time for the banking industry. At the firm level, we conclude that bank insiders are able to predict future returns. At the aggregate level, no relationship is found between both series, indicating that the stock mis...

This paper examines the causal relationship between directors' dealings and monthly stock returns in the Spanish market for the first time for the banking industry. At the firm level, we conclude that bank insiders are able to predict future returns. At the aggregate level, no relationship is found between both series, indicating that the stock mis...

This study analyses the factors triggering insider trading profitability. Since there is not much evidence on this topic in the continental-European context, we focus on the Spanish stock market. Our findings show that the main relevant factors (the timing ability of the insider, the transparency of the transaction and the level of free cash flow o...

We report the results of an experiment on a continuous version of the minimum effort coordination game. The introduction of within-team competition significantly increases effort levels relative to a baseline with no competition and increases coordination relative to a secure treatment where the pay-off-dominant equilibrium strategy weakly dominate...

This paper develops both univariate and multivariate distributions based on Gram-Charlier and Edgeworth expansions, attempting to ensure non negativity by exploiting the orthogonal properties of the Hermite polynomials. The article motivates the problems underlying some specifications (in particular those involving other conditional moments beyond...

Previous studies have cast doubts on the effectiveness of corporate governance codes in Continental- European countries, due to their Anglo-Saxon orientation. We chose a Continental-European country with an Anglo-Saxon orientated code, such as Spain, and analyse the effects of the recommendations proposed in the Spanish Olivencia Code on the value...

This article reports the results of a market experiment designed to test the predictions of the constant relative risk aversion model and to study the importance of information feedback in repeated first-price sealed-bid auctions. The data reveal that introduction of price information feedback implies a significant change of individual behavior. Wi...

In this paper we introduce a transformation of the Edgeworth-Sargan series expansion of the Gaussian distribution, that we call Positive Edgeworth-Sargan (PES). The main advantage of this new density is that it is well defined for all values in the parameter space, as well as it integrates up to one. We include an illustrative empirical application...