Research In Financial Economics Research Articles

Parallel computing in finance for estimating risk-neutral densities through option prices

Option pricing is one of the most active Financial Economics research fields. Black-Scholes-Merton option pricing theory states that risk-neutral density is lognormal. However, markets' pieces of evidence do not support that assumption. More realistic assumptions impose substantial computational burdens to calculate option pricing functions. Risk-neutral density is a pivotal element to price derivative assets, which can be estimated through nonparametric kernel methods. A significant computational challenge exists for determining optimal kernel bandwidths, addressed in this study through a parallel computing algorithm performed using Graphical Processing Units. The paper proposes a tailor-made Cross-Validation criterion function used to define optimal bandwidths. The selection of optimal bandwidths is crucial for nonparametric estimation and is also the most computationally intensive. We tested the developed algorithms through two data sets related to intraday data for VIX and S&P500 indexes.

Is the development of the stock market a barometer of China's economy?

The rise of China and the five-fold increase in the expanse of its stock market over the previous decade has spurred a rising body of research in financial economics on the marketplace. The link between the development of the Chinese stock market and China’s economy has always been an eternal topic. The existing literature has rarely systematically analyzed whether the stock market development is a barometric measure of China's economy. To this end, this paper examines the role of using the Chinese stock market’s development as a barometer of China's economy by studying the relationship between stock price changes in the stock market and China's Industrial Development Index.

The COVID-19 Crisis and the Allocation of Capital

AbstractWe summarize and synthesize the results of the articles in this symposium issue on research in financial economics related to the COVID-19 pandemic. We argue that the articles, taken together, present evidence that the pandemic resulted in a distributional shock to capital allocation. The underlying mechanisms include accelerating technological shifts, government stimulus programs, and heterogeneous responses of investors and firms. We augment these articles with evidence on the heterogeneous effects of the pandemic on profitability, payout, investment, employment, and productivity across sectors.

New developments in financial economics

PurposeThis study aims to critically review recent contributions to the methodology of financial economics and discuss how they relate to one another and directions for further research.Design/methodology/approachA critical review of recent literature on new methodologies for financial economics.FindingsRecent books have made important contributions to the study of financial economics. They suggest new approaches that include an emphasis on radical uncertainty, adaptive markets, agent-based modeling and narrative economics, as well as extensions of behavioral finance to include concepts such as diagnostic expectations. Many of these contributions can be seen more as complements than substitutes and provide fruitful directions for further research. Efficient markets can be seen as holding under particular circumstances. A major them of most of these contributions is that the study of financial crises and other aspects of financial economics requires the use of multiple theories and approaches. No one approach will be sufficient.Research limitations/implicationsThere are great opportunities for further research in financial economics making use of these new approaches.Practical implicationsThese recent contributions can be quite useful for improved analysis by researchers, private participants in the financial sector and macroeconomic and regulatory officials.Originality/valueProvides an introduction to these new approaches and highlights fruitful areas for their extensions and applications.

Study on the relationship between the IVol-BR and the future returns of the Brazilian stock market,

ABSTRACT In 2015, the Financial Economics Research Center (NEFIN) of the University of São Paulo proposed an implicit volatility index for the Brazilian stock market based on the daily prices of options for the Bovespa index (Ibovespa) and that measures the expected volatility of the Ibovespa in the next two months. The aim of this study is to determine whether this implicit volatility index can be considered an antecedent indicator of future returns of the Brazilian stock market, given that it represents the expected volatility of the Ibovespa two months into the future. This study contributes to the literature on the implicit volatility index for the Brazilian stock market, which has been scarce until now. This happens due to the recent establishment of the index and due to the fact that there is not an official one published by the B3 S.A. - Brasil, Bolsa, Balcão (B3). Given the relationship found between the Brazilian implicit volatility index and the future returns of the Ibovespa, investors could anticipate instabilities in the Brazilian market by putting together strategies to protect their investment portfolios, as well as identifying opportunities to enter and exit the market. This research corroborates in disclosing the Brazilian implicit volatility index in order for it to become more widely used in academia and in the Brazilian financial market. The increase in studies on this index may also incentivize the launch of an official implicit volatility index by the B3. The relationship between the Brazilian implicit volatility index and the future returns of the Ibovespa is examined using least squares and quantile regressions. The implicit volatility index for the Brazilian stock market could help in predicting the future returns of the Ibovespa, especially for 20-, 60-, 120-, and 250-day future returns.

Stock Market Return and Stagflation Under Two Control Variables: International Evidence

The study investigated the impact of stagflation on stock market returns under two Control variables that economic policies and the characteristics of the stock market. The study included nine countries (Brazil, Egypt, Indonesia, Korea, Malaysia, Pakistan, Singapore, South Africa, and Turkey) during the period from 2005 to 2018. We found that for the economic policies within the lag period under stagflation, the characteristics of each economy and stock market within and outside of the lag period were between 25.74% and 16.20% of the returns of stock markets, respectively. The current study explains the different results according to the different methods of study, in particular with regard to the use of the lag period, which was beneficial for the economic policy but not beneficial with stagflation. In addition, the different abilities of each economy created value-added from production factors with the different levels of efficiency of the stock exchanges. Finally, rational investment in stock exchanges requires the ability to classify the policies and economic variables and determine the extent of their time contributions to caret stock return within/outside the lag period. This area is a fertile field in financial economics research, particularly to develop theories and models.

Climate Disaster Risks—Empirics and a Multi-Phase Dynamic Model

Recent research in financial economics has shown that rare large disasters have the potential to disrupt financial sectors via the destruction of capital stocks and jumps in risk premia. These disruptions often entail negative feedback effects on the macroeconomy. Research on disaster risks has also actively been pursued in the macroeconomic models of climate change. Our paper uses insights from the former work to study disaster risks in the macroeconomics of climate change and to spell out policy needs. Empirically, the link between carbon dioxide emission and the frequency of climate related disaster is investigated using a panel data approach. The modeling part then uses a multi-phase dynamic macro model to explore the effects of rare large disasters resulting in capital losses and rising risk premia. Our proposed multi-phase dynamic model, incorporating climate-related disaster shocks and their aftermath as a distressed phase, is suitable for studying mitigation and adaptation policies as well as recovery policies.

Climate Disaster Risks – Empirics and a Multi-Phase Dynamic Model

Recent research in financial economics has shown that rare large disasters have the potential to disrupt financial sectors via the destruction of capital stocks and jumps in risk premia. These disruptions often entail negative feedback e?ects on the macroecon-omy. Research on disaster risks has also actively been pursued in the macroeconomic models of climate change. Our paper uses insights from the former work to study disaster risks in the macroeconomics of climate change and to spell out policy needs. Empirically the link between carbon dioxide emission and the frequency of climate re-lated disaster is investigated using cross-sectional and panel data. The modeling part then uses a multi-phase dynamic macro model to explore this causal nexus and the e?ects of rare large disasters resulting in capital losses and rising risk premia. Our proposed multi-phase dynamic model, incorporating climate-related disaster shocks and their aftermath as one phase, is suitable for studying mitigation and adaptation policies.

Climate Disaster Risks - Empirics and a Multi-Phase Dynamic Model

Recent research in financial economics has shown that rare large disasters have the potential to disrupt financial sectors via the destruction of capital stocks and jumps in risk premia. These disruptions often entail negative feedback effects on the macroeconomy. Research on disaster risks has also actively been pursued in the macroeconomic models of climate change. Our paper uses insights from the former work to study disaster risks in the macroeconomics of climate change and to spell out policy needs. Empirically the link between carbon dioxide emission and the frequency of climate related disaster is investigated using cross-sectional and panel data. The modeling part then uses a multi-phase dynamic macro model to explore this causal nexus and the effects of rare large disasters resulting in capital losses and rising risk premia. Our proposed multi-phase dynamic model, incorporating climate-related disaster shocks and their aftermath as one phase, is suitable for studying mitigation and adaptation policies.

A reconsideration of operating-financial leverage tradeoff hypothesis

PurposeThis paper aims to attempt to perform a test of the operating leverage-financial leverage tradeoff hypothesis that is more methodologically consistent with the logical framing of the hypothesis appearing in the Mandelker and Rhee (1984) paper.Design/methodology/approachThe paper uses a sample of firms from the manufacturing industry to estimate their degree of operating leverage and degree of financial leverage coefficients. The switching regression methodology is then used to perform the empirical test of the tradeoff hypothesis.FindingsThe results suggest that firms tradeoff their operating and financial leverage during good economic times, but do not engage in the tradeoff behavior during recessionary times.Originality/valueThis paper refines the empirical testing of the tradeoff hypothesis using the innovative switching regression methodology. The paper also has important implications for the impact of firms’ risk on the capital markets as well as the economy as a whole, and for academic researchers in financial economics examining the relationships between operating and financial leverage and various firm-specific variables.

Finance and Corporate Innovation: A Survey

AbstractCorporate innovation is an increasingly important topic that has attracted great attention from academic researchers in financial economics in recent years. Although the top three finance journals (i.e. the Journal of Finance, the Journal of Financial Economics, and the Review of Financial Studies) together published a total of only five papers on corporate innovation from 2000 to 2008, the number of such papers published by these three journals skyrocketed to 56 from 2009 to the third quarter of 2017. The purpose of this survey is to provide a synthetic and evaluative monograph of academic papers that examine the drivers and financing sources of corporate innovation.

GARCH volatilities applied to an asset selection algorithm: the case of fixed income markets

This paper introduces an empirical analysis of a selective model for the impact on various sources of financial risk, with particular focus on credit risk. Practitioners in risk management are still strongly linked to value-at-risk as the most widely used methodology for the analysis and prediction of financial risk. Modern research in financial economics shows that this approach becomes misleading if we relax some constraints in order to get closer to the real world. The model tries to overtake the inadequacy of value-at-risk by introducing a selection algorithm.

GARCH volatilities applied to an asset selection algorithm: the case of fixed income markets

This paper introduces an empirical analysis of a selective model for the impact on various sources of financial risk, with particular focus on credit risk. Practitioners in risk management are still strongly linked to value-at-risk as the most widely used methodology for the analysis and prediction of financial risk. Modern research in financial economics shows that this approach becomes misleading if we relax some constraints in order to get closer to the real world. The model tries to overtake the inadequacy of value-at-risk by introducing a selection algorithm.

Finance and Corporate Innovation: A Survey

Corporate innovation is an increasingly important topic that has attracted great attention from academic researchers in financial economics in recent years. Although the top three finance journals (i.e. the Journal of Finance, the Journal of Financial Economics, and the Review of Financial Studies) together published a total of only five papers on corporate innovation from 2000 to 2008, the number of such papers published by these three journals skyrocketed to 56 from 2009 to the third quarter of 2017. The purpose of this survey is to provide a synthetic and evaluative monograph of academic papers that examine the drivers and financing sources of corporate innovation.

Future directions in international financial integration research - A crowdsourced perspective

This paper is the result of a crowdsourced effort to surface perspectives on the present and future direction of international finance. The authors are researchers in financial economics who attended the INFINITI 2017 conference in the University of Valencia in June 2017 and who participated in the crowdsourcing via the Overleaf platform. This paper highlights the actual state of scientific knowledge in a multitude of fields in finance and proposes different directions for future research.

Presidential Address: The Scientific Outlook in Financial Economics

ABSTRACTGiven the competition for top journal space, there is an incentive to produce “significant” results. With the combination of unreported tests, lack of adjustment for multiple tests, and direct and indirect p‐hacking, many of the results being published will fail to hold up in the future. In addition, there are basic issues with the interpretation of statistical significance. Increasing thresholds may be necessary, but still may not be sufficient: if the effect being studied is rare, even t > 3 will produce a large number of false positives. Here I explore the meaning and limitations of a p‐value. I offer a simple alternative (the minimum Bayes factor). I present guidelines for a robust, transparent research culture in financial economics. Finally, I offer some thoughts on the importance of risk‐taking (from the perspective of authors and editors) to advance our field.SUMMARY Empirical research in financial economics relies too much on p‐values, which are poorly understood in the first place. Journals want to publish papers with positive results and this incentivizes researchers to engage in data mining and “p‐hacking.” The outcome will likely be an embarrassing number of false positives—effects that will not be repeated in the future. The minimum Bayes factor (which is a function of the p‐value) combined with prior odds provides a simple solution that can be reported alongside the usual p‐value. The Bayesianized p‐value answers the question: What is the probability that the null is true? The same technique can be used to answer: What threshold of t‐statistic do I need so that there is only a 5% chance that the null is true? The threshold depends on the economic plausibility of the hypothesis.

The Scientific Outlook in Financial Economics

It is time that we reassess how we approach our empirical research in financial economics. Given the competition for top journal space, there is an incentive to produce “significant” results. With the combination of: unreported tests, lack of adjustment for multiple tests, direct and indirect p-hacking, many of the research results that we are publishing will fail to hold up in the future. In addition, there are some fundamental issues with the interpretation of statistical significance. Increasing thresholds, such as t > 3, may be necessary but such a rule is not sufficient. If the effect being studied is rare, even a rule like t > 3 will produce a large number of false positives. I take a step back and explore the meaning of a p-value and detail its limitations. I offer a simple alternative approach known as the minimum Bayes factor which delivers a Bayesian p-value. I present a list of guidelines that are designed to provide a foundation for a robust, transparent research culture in financial economics. Finally, I offer some thoughts on the importance of risk taking (both from the perspective of both authors and editors) to advance our field.The transcript and presentation slides are available here: http://ssrn.com/abstract=2895842.

Volatility Spillover Effects Between Stock Prices and Exchange Rates in Emerging Economies: Evidence from Turkey

Volatility spillover effects between stock prices and exchange rates in emerging countries are a critical focus in the financial economics research arena. This paper focused to investigate the volatility spillover effects between stock prices and exchange rates of Istanbul stock exchange (ISE) by employing an exponential generalized autoregressive condition heteroskedasticity (EGARCH) model. The period of study covered 11 years (i.e. 2005 to 2015) inclusive a period of the global financial crises (i.e. from 2005 to 2009) which resulted out from subprime mortgage in United States of America (USA).Our results suggest an existence of short run relationship between stock prices and exchange rates in Istanbul stock exchange (ISE).This empirical evidence suggest that there is symmetric volatility spillover between stock prices and exchange rates of Istanbul stock exchange (ISE) for full sample employed as a result good and bad news has got a balanced effect to the market. The findings of the significant volatility spillover effects between exchange rates and stock prices suggest that, the markets are informationally efficient and one market exchange rate has significant predictive power of equal weight to another in case of two markets. Our study recommends investors and multinational firm managers to consider the general behaviour of the financial market before making decision whether to invest in or not since there is existence of relationship and volatility spillover between stock prices and exchange rates meanwhile economic policy makers both in Turkey and outside Turkey should consider these findings in their policy as one of the determinant to economic growth, as macroeconomic variable should be stable like exchange rates. Furthermore, this study may be extended after including of other variables which were not considered in this study like interest rate, inflation and agency theory.

Design and Construction of a Historical Financial Database of the Italian Stock Market 1973--2011

This article presents the technical aspects of designing and building a historical database of the Italian Stock Market. The database contains daily market data from 1973 to 2011 and is constructed by merging two main digital sources and several other hand-collected data sources. We analyzed and developed semiautomatic tools to deal with problems related to time-series matchings, quality of data, and numerical errors. We also developed a concatenation structure to allow the handling of company name changes, mergers, and spin-offs without artificially altering numerical series. At the same time, we maintained the transparency of the historical information on each individual company listed. Thanks to the overlapping of digital and hand-collected data, the completed database has a very high level of detail and accuracy. The dataset is particularly suited for any empirical research in financial economics and for more practically oriented numerical applications and forecasting simulations.

Recent topics in Applied Financial Economics

This note discusses topics concerning recent evolutions in financial economics research. It focuses in particular on the progress of quantitative finance and applied economics in the context of the global financial crisis. To this end, I examine various important topics in Economics and Finance and discuss several empirical studies on the statistical properties of macroeconomic and financial data through the application of different econometric methodologies. I analyse their empirical findings and discuss their conclusions.