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The relationship between risk and expected returns has been investigated extensively in the financial economics literature. Theoretical models generally predict a positive relation between the two. Nevertheless, the empirical findings so... more
The relationship between risk and expected returns has been investigated extensively in the financial economics literature. Theoretical models generally predict a positive relation between the two. Nevertheless, the empirical findings so far have been inconclusive. Using a generalization of the analytical framework developed by Theodossiou and Savva (2016) along with time-varying asymmetry, linked to the upside and downside uncertainty, the risk–return puzzle is investigated across international stock markets. The investigation reveals that the contradictory findings are the result of ignoring the impact of skewness on the total price of risk. That is, in the absence of skewness the relationship between risk and return is positive as depicted by finance theory. However, negative skewness results in lowering the total price of risk and in some cases reverting its sign from positive to negative.
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DESCRIPTION
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Research Interests: Business, Economics, Applied Economics, Probit, Insolvency, and 3 moreCreditor, Logit, and Probit Model
Research Interests: Economics, Econometrics, Social Sciences, Financial management, Extreme Value Theory, and 13 moreValue at Risk, Economics and Business, Reinsurance, Normal Distribution, Time varying, Performance Test, Generalized Pareto Distribution, Distribution Function, Generalization Error, Finance and Investment Banking, extreme value distribution, Generalized extreme value distribution , and Risk measure
We study an equilibrium risk and return model to explore the effects of the coronavirus crisis and associated skewness on the market price of risk. We derive the moment and equilibrium equations, specifying skewness price of risk as an... more
We study an equilibrium risk and return model to explore the effects of the coronavirus crisis and associated skewness on the market price of risk. We derive the moment and equilibrium equations, specifying skewness price of risk as an additive component of the effect of variance on mean expected return. We estimate our model using the flexible skewed generalized error distribution, for which we derive the distribution of returns and the likelihood function. Using S&P 500 Index returns from January 1980 to mid-October 2020, our results show that the coronavirus crisis generated a deeply negative reaction in the skewness and total market price of risk, more negative even than the subprime and the October 1987 crises.
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The stochastic behaviour of stock prices on the Athens Stock Exchange in Greece is investigated. The methodology employed is Nelson's (1991) exponential GARCH-M model, which allows shocks... more
The stochastic behaviour of stock prices on the Athens Stock Exchange in Greece is investigated. The methodology employed is Nelson's (1991) exponential GARCH-M model, which allows shocks to have an asymmetric impact on volatility. The findings suggest that both the first and the second moments of the distribution of returns are time-dependent, and as such cannot be modelled as white-noise
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This paper makes specifics contributions in the methodology of event studies. First, it develops a financial econometrics framework for understanding, measuring and testing the impact of outlier returns on the estimated parameters of... more
This paper makes specifics contributions in the methodology of event studies. First, it develops a financial econometrics framework for understanding, measuring and testing the impact of outlier returns on the estimated parameters of stock return models. Second, it presents a maximum likelihood robust estimation method that enables the decomposition of a firm’s stock returns into regular and outlier returns for the purpose of computing robust or outlier resistant CAR statistics. Third, it presents analytical results on how outliers in the estimation sample affect OLS-CAR statistics. Results based on extensive Monte Carlo and actual data simulations, depict that outliers in the estimation sample affect adversely and significantly the performance of the OLS-CAR statistics in event studies. Outliers, however, do not impair the forecasting ability of the robust-CAR statistics introduced in this paper.
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The impact of the cognitive biases of overconfidence, underconfidence and anchoring on the distribution of errors of forecasting models is analyzed using an analytical framework based on a flexible two-piece generalized distribution. The... more
The impact of the cognitive biases of overconfidence, underconfidence and anchoring on the distribution of errors of forecasting models is analyzed using an analytical framework based on a flexible two-piece generalized distribution. The total forecasting bias, measured by the expected value of a model’s errors, is decomposed to an anchoring bias and a skewness bias. An examination of BEA’s preliminary estimates of the final GDP growth rates reveals that the underprediction present is to a large extent the result of negative skewness bias and to a lesser extent of negative anchoring bias. The latter are attributes of underconfident forecasters.
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ABSTRACT
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ABSTRACT EGARCH-M models based on a daily, weekly, and monthly S&P–500 returns over the period October 1934–September 1994 reveal that higher margins have a much stronger negative relation to subsequent volatility in bull markets... more
ABSTRACT EGARCH-M models based on a daily, weekly, and monthly S&P–500 returns over the period October 1934–September 1994 reveal that higher margins have a much stronger negative relation to subsequent volatility in bull markets than in bear markets. Higher margins are also negatively related to subsequent conditional stock returns, apparently because they reduce systemic risk. These empirical regularities are consistent with the pyramiding-depyramiding framework of stock prices that US Congress had in mind when it instituted margin regulation in 1934, and suggest that a prudential rule for setting margins over time would be to raise them during periods of unwarranted price increases and to lower them immediately after large declines in stock prices.
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This paper proposes a conditional technique for the estimation of VaR and expected shortfall measures based on the skewed generalized t (SGT) distribution. The estimation of the conditional mean and conditional variance of returns is... more
This paper proposes a conditional technique for the estimation of VaR and expected shortfall measures based on the skewed generalized t (SGT) distribution. The estimation of the conditional mean and conditional variance of returns is based on ten popular variations of the GARCH model. The results indicate that the TS-GARCH and EGARCH models have the best overall performance. The remaining GARCH specifications, except in a few cases, produce acceptable results. An unconditional SGT-VaR performs well on an in-sample evaluation and fails the tests on an out-of-sample evaluation. The latter indicates the need to incorporate time-varying mean and volatility estimates in the computation of VaR and expected shortfall measures.
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Using a flexible statistical framework that accounts for time-varying skewness and leptokurtosis, we examine the stochastic behavior of Bitcoin in comparison to five major currencies. The empirical findings reveal that the distribution of... more
Using a flexible statistical framework that accounts for time-varying skewness and leptokurtosis, we examine the stochastic behavior of Bitcoin in comparison to five major currencies. The empirical findings reveal that the distribution of all series is leptokurtic. Once the effect of skewness-kurtosis is considered, the true price of risk is obtained, with implications on policymakers’ and investors’ strategies.
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The econometric framework of the contemporaneous asset pricing model used by Theodossiou and Savva and Savva and Theodossiou to investigate the relationship between risk and expected returns in fin...
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This paper presents a unified framework for the popular Skewed Generalized t (SGT) distribution and its special cases the Skewed Generalized Error Distribution (SGED), the skewed student’s t, the skewed Laplace and skewed normal... more
This paper presents a unified framework for the popular Skewed Generalized t (SGT) distribution and its special cases the Skewed Generalized Error Distribution (SGED), the skewed student’s t, the skewed Laplace and skewed normal distributions. The analytical moment equations presented can be useful to researchers in statistics, finance and econometrics working in the areas of estimation, asset pricing and risk management. The unified framework presented helps avoid confusions related to the interpretation of their parameters and results.
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Stock returns are decomposed into their regular and outlier components using a maximum likelihood outlier-resistant estimation method. Analytical results depicting the impact of outliers on the ordinary least square (OLS) estimated models... more
Stock returns are decomposed into their regular and outlier components using a maximum likelihood outlier-resistant estimation method. Analytical results depicting the impact of outliers on the ordinary least square (OLS) estimated models and cumulative abnormal return (CAR) statistics are derived and validated using Monte Carlo simulations. The implications of outliers for past event studies are investigated using samples drawn randomly from the universe of stocks in the CRSP database. The OLS-CAR statistics fail to forecast about 37% of the negative-impact and 43% of the positive-impact events. These results raise serious concerns about the validity of conclusions of past event studies, especially those that rejected the hypothesis of significant-impact events.
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This article examines the usefulness of an active portfolio strategy that uses time-varying parameters produced by a GARCH methodology. The results suggest that such a strategy outperforms alternative buy-and-hold strategies. When... more
This article examines the usefulness of an active portfolio strategy that uses time-varying parameters produced by a GARCH methodology. The results suggest that such a strategy outperforms alternative buy-and-hold strategies. When transaction costs are extended to include the bid-ask spread, investors can profit from adding low-cost levered positions, such as futures indexes, to their portfolios of equities.
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Research Interests: Economics, Econometrics, Financial Accounting, Time Series, Financial Distress, and 12 moreLogistic Regression, Discriminant Analysis, Social Science Research Network, Mathematical Sciences, CUSUM, Financial Ratios, Logit, Serial Correlation, Logit Model, Cumulant, Linear discriminate analysis, and Statistical Method
The distributions of stock returns and capital asset pricing model (CAPM) regression residuals are typically characterized by skewness and kurtosis. We apply four flexible probability density functions (pdfs) to model possible skewness... more
The distributions of stock returns and capital asset pricing model (CAPM) regression residuals are typically characterized by skewness and kurtosis. We apply four flexible probability density functions (pdfs) to model possible skewness and kurtosis in estimating the parameters of the CAPM and compare the corresponding estimates with ordinary least squares (OLS) and other symmetric distribution estimates. Estimation using the flexible
Research Interests: Economics, Econometrics, Quantitative Finance, Beta, Capital Asset Pricing Model, and 14 moreMathematical Sciences, Estimation, Cost of Capital, Kurtosis, Ordinary Least Squares, Public Utilities, Skewness, Estimator, Probability Density Function, Parametric Statistics, Stock Returns, Distributed Estimation, Robust estimator, and Ordinary Least Square
We study an equilibrium risk and return model to explore the effects of the coronavirus crisis and associated skewness on the market price of risk. We derive the moment and equilibrium equations, specifying skewness price of risk as an... more
We study an equilibrium risk and return model to explore the effects of the coronavirus crisis and associated skewness on the market price of risk. We derive the moment and equilibrium equations, specifying skewness price of risk as an additive component of the effect of variance on mean expected return. We estimate our model using the flexible skewed generalized error distribution, for which we derive the distribution of returns and the likelihood function. Using S&P 500 Index returns from January 1980 to mid-October 2020, our results show that the coronavirus crisis generated a deeply negative reaction in the skewness and total market price of risk, more negative even than the subprime and the October 1987 crises.
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This paper presents a unified framework for the popular Skewed Generalized t (SGT) distribution and its special cases the Skewed Generalized Error Distribution (SGED), the skewed student’s t, the skewed Laplace and skewed normal... more
This paper presents a unified framework for the popular Skewed Generalized t (SGT) distribution and its special cases the Skewed Generalized Error Distribution (SGED), the skewed student’s t, the skewed Laplace and skewed normal distributions. The analytical moment equations presented can be useful to researchers in statistics, finance and econometrics working in the areas of estimation, asset pricing and risk management. The unified framework presented helps avoid confusions related to the interpretation of their parameters and results.
Research Interests:
This paper makes specifics contributions in the methodology of event studies. First, it develops a financial econometrics framework for understanding, measuring and testing the impact of outlier returns on the estimated parameters of... more
This paper makes specifics contributions in the methodology of event studies. First, it develops a financial econometrics framework for understanding, measuring and testing the impact of outlier returns on the estimated parameters of stock return models. Second, it presents a maximum likelihood robust estimation method that enables the decomposition of a firm’s stock returns into regular and outlier returns for the purpose of computing robust or outlier resistant CAR statistics. Third, it presents analytical results on how outliers in the estimation sample affect OLS-CAR statistics. Results based on extensive Monte Carlo and actual data simulations, depict that outliers in the estimation sample affect adversely and significantly the performance of the OLS-CAR statistics in event studies. Outliers, however, do not impair the forecasting ability of the robust-CAR statistics introduced in this paper.
Research Interests:
The relationship between risk and expected returns has been investigated extensively in the financial economics literature. Theoretical models generally predict a positive relation between the two. Nevertheless, the empirical findings so... more
The relationship between risk and expected returns has been investigated extensively in the financial economics literature. Theoretical models generally predict a positive relation between the two. Nevertheless, the empirical findings so far have been inconclusive. Using a generalization of the analytical framework developed by Theodossiou and Savva (2016) along with time-varying asymmetry, linked to the upside and downside uncertainty, the risk–return puzzle is investigated across international stock markets. The investigation reveals that the contradictory findings are the result of ignoring the impact of skewness on the total price of risk. That is, in the absence of skewness the relationship between risk and return is positive as depicted by finance theory. However, negative skewness results in lowering the total price of risk and in some cases reverting its sign from positive to negative.
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The econometric framework of the contemporaneous asset pricing model used by Theodossiou and Savva and Savva and Theodossiou to investigate the relationship between risk and expected returns in fin...
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k Robust estimation techniques, such as least absolute deviations, M and L and quasi-maximum likelihood techniques based on symmetric probability density functions, such as student’s T, Laplace, generalized error and generalized T... more
k Robust estimation techniques, such as least absolute deviations, M and L and quasi-maximum likelihood techniques based on symmetric probability density functions, such as student’s T, Laplace, generalized error and generalized T distributions are often substituted for OLS to obtain more efficient regression parameters in thick-tail data. The empirical, theoretical, and simulation results presented in this paper show that when skewness is present in the data, symmetric robust estimation techniques used to replace OLS produce biased regression intercepts. Replacing OLS with robust methods that do not accommodate skewness as well as thick tails introduces a statistically and analytically significant bias to the intercept. Simulation results favor the student’s T and generalized T regression estimators in leptokurtic symmetric data and the skewed T and skewed generalized T regression estimators in skewed data. In normal and skewed data, the OLS estimators are preferred because of thei...
We study an equilibrium risk and return model to explore the effects of the coronavirus crisis and associated skewness. We derive the moment and equilibrium equations, specifying skew-ness price of risk as an additive component of the... more
We study an equilibrium risk and return model to explore the effects of the coronavirus crisis and associated skewness. We derive the moment and equilibrium equations, specifying skew-ness price of risk as an additive component of the effect of variance on mean expected return. We estimate our model using the flexible skewed generalized error distribution, for which we derive the distribution of returns and the likelihood function. Using S&P 500 Index returns from January 1990 to mid-May 2020, our results show that the coronavirus crisis generated the most negative reaction in the skewness price of risk, more negative even than the subprime crisis.
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Shipping freight rates are notoriously volatile and shipping investors are perceived to be risk-loving. This paper explores the stochastic properties of freight rates in the shipping industry and derives the analytical equations for their... more
Shipping freight rates are notoriously volatile and shipping investors are perceived to be risk-loving. This paper explores the stochastic properties of freight rates in the shipping industry and derives the analytical equations for their moments in downside and upside markets using a two-piece extension of the generalized error distribution (GED). Pricing equations developed, across shipping segments, show how conditional risk and conditional skewness are priced along with their risk spillover effects. Results reveal the existence of a positive-skewness premium, suggesting that shipping investors are willing to accept lower expected returns for the opportunity to earn high payoffs in the future.
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The economy of Cyprus was barely affected by the U.S. subprime mortgage debacle. The economic crisis in Cyprus was initially driven by fiscal mismanagement and subsequently by the failure of the government and its regulatory branches to... more
The economy of Cyprus was barely affected by the U.S. subprime mortgage debacle. The economic crisis in Cyprus was initially driven by fiscal mismanagement and subsequently by the failure of the government and its regulatory branches to monitor the imprudent behavior and risky investment actions of top executives in the banking sector. That is, banking executives run amok due to poor monitoring leading to severe agency problems in the Cypriot banking industry. The economic effects of the first capital-controlled bail-in in the EU in 2013 temporarily hobbled the real economy and the banking sector of Cyprus. Nevertheless, in less than five years, the economy of Cyprus recovered almost fully. This paper provides an economic analysis of the macroeconomic, banking and political events that led to the economic collapse in Cyprus. We also cover the interim period between collapse and recovery. The Cyprus case is an opportunity for European economic agents and regulators to learn how to av...