Real Effects of Financial Conditions: How Does Provider Financial Health Affect Opioid Prescription?
Ma Pengfei (SKBI) | January 2025 |
We examine how healthcare providers’ financial health affects their opioid prescription decisions, using changes in house prices in providers’ residential neighborhoods as shocks to their wealth. We find that providers increase opioid prescriptions when experiencing adverse financial conditions: a one-standard-deviation decrease in house price growth leads to a 3% increase in opioid prescriptions. Results are robust to including provider office–year fixed effect and using the subsample of providers who live far away from their offices, which largely rules out a patient–demand explanation. Providers living in zip codes with price changes in the bottom half during 2007–2009 increased their opioid prescriptions by approximately 16% more in 2010–2012 than others. The effect is stronger among providers with greater home equity, those in competitive markets, and those serving vulnerable populations. Our findings reveal a previously undocumented channel through which providers’ financial incentives affect opioid prescriptions.
Applications of vector autoregressions in their scalar autoregressive component form
Leo Krippner (SKBI) | November 2024 |
The eigenvalue/eigenvector structure underlying a standard N-variable P-lag vector autoregression (VAR) may be transformed into a system of NP scalar AR1 processes, each with an eigenvalue as its coefficient. This perspective allows a VAR to be assessed, analyzed, and manipulated using the mathematical convenience of elementary AR1 processes. Illustrative empirical applications demonstrate the inherent benefits: (1) the persistence of a VAR's dynamics is interpreted from its AR1 processes; (2) closed-form VAR forecasts are obtained from AR1 forecasts; (3) equality or zero constraints on selected AR1 coefficients are tested and imposed for VAR parsimony; (4) a median-unbiased estimate of the largest AR1 coefficient is generated and imposed to produce a more persistent VAR; (5) a unit root for the largest AR1 coefficient is tested and imposed to produce a cointegrated VAR, which also produces an estimate of the associated cointegrating vector.
Price Discovery on Decentralised Exchanges
Shihao Yu (SMU) | July 2024 |
Decentralized exchanges (DEXs) allow traders to express their willingness to pay for quick execution through a public priority fee bidding mechanism. This influences the trading strategy of informed traders and creates a distinct price discovery process on DEXs compared to centralized exchanges. We present empirical evidence that high-fee DEX trades contain more private information. Informed traders bid high fees not only to avoid execution risk from blockchain congestion, but also to compete for execution priority. Using a dataset of Ethereum mempool orders, we demonstrate that informed traders employ a “jump bidding” strategy, placing high initial bids to deter potential competitors.
Retail Investors' Activity and Climate Disasters
Marinela Adriana Finta (SKBI) | June 2024 |
We analyze the effects of climate disasters on retail investors’ trading activity. Results show that retail investors trade significantly less during and around climate disasters, and retail buyers exhibit higher returns than sellers. Climate disasters weaken the positive return predictability of the past month’s order imbalances while strengthening it for the past six month’s order imbalances. In the short run, firms within climate disaster counties with retail net buying underperform those with negative imbalances. Instead, in the long run, firms within and outside climate disaster counties with positive order flows outperform those with negative order flows. Finally, the estimates on the return and order imbalance comovement around climate disasters are consistent with the main findings.
Specifying and Estimating Vector Autoregressions using their Eigensystem Representation
Leo Krippner (SKBI) | May 2024 |
This article introduces the principles and mechanics of the eigensystem vector autoregression (EVAR) framework, where a VAR may be specified and estimated directly via its eigenvalue and eigenvector parameters. Using explicit constraints on the eigensystem permits control of a VARs allowable dynamics, which is illustrated empirically with standard and time-varying VAR estimations specified to be always non-explosive.
Are Investors Better Off Doing Nothing during Exchange Traded Fund Closures
Ekkehart Boehmer (SMU), Marinela Adriana Finta (SKBI) | Nov 2023 |
We investigate a sample of several Exchange-Traded Funds (ETFs) that closed between 2012 and 2019. Our findings show that ETFs close after positive returns and flows. Moreover, both returns and flows are good predictors of the ETFs’ decision to close. In general, we also find that small ETFs earn greater daily returns on average than larger ETFs with the same investment objective. We finally highlight that after the closure announcement, in normal circumstances (e.g., without exposure to extra fees), investors are better off keeping calm and doing nothing while waiting to receive shares’ cash at the NAV from the ETF issuer.
Estimating and Applying Autoregression Models via their Eigensystem Representation
Leo Krippner (SKBI) | Oct 2023 |
This article introduces the eigensystem autoregression (EAR) framework, which allows an AR model to be specified, estimated, and applied directly in terms of its eigenvalues and eigenvectors. An EAR estimation can therefore impose various constraints on AR dynamics that would not be possible within standard linear estimation. Examples are restricting eigenvalue magnitudes to control the rate of mean reversion, additionally imposing that eigenvalues be real and positive to avoid pronounced oscillatory behaviour, and eliminating the possibility of explosive episodes in a time-varying AR. The EAR framework also produces closed-form AR forecasts and associated variances, and forecasts and data may be decomposed into components associated with the AR eigenvalues to provide additional diagnostics for assessing the model.
Bank Competition amid Digital Disruption: Implications for Financial Inclusion
Erica Xuewei Jiang (USC), Gloria Yang Yu (SMU) and Jinyuan Zhang (UCLA Anderson) | Aug 2023 |
Financial inclusion is presumed to have improved because of advances in FinTech over the last ten years. This paper shows that the effects of new technology on the market for banking services are not straightforward -- digital disruption alters competition among banks, which influences how the welfare effects from FinTech are distributed among consumers.
Air Pollution, Regulations on Emission and Firms’ Social Responsibility
Jun Myung Song (SKBI) | Jun 2023 |
This paper examines whether firms adjust their strategy in emission when air pollution is severe. Considering high PM 2.5 as severe air pollution across 65 countries, I show that firms from countries with severe air pollution have low emission score, suggesting that they put less effort in reducing emission. This is because if they improve emission strategy, firm performance deteriorates. However, such relationship disappears when the government’s environmental stringency is strong, suggesting that government’s intervention is crucial for sustainable environment. This paper concludes with analysis on the factors which can mediate the negative impact of air pollution on firms’ emission strategies.
Female CEOs and Investment Efficiency in the Vietnamese Market
Jun Myung Song (SKBI), Chune Young Chung (Chung-Ang University)| Jun 2023 |
This paper proposes female CEOs’ overconfidence and risky behaviour stem from gender stereotype threats. With two subsamples in Vietnam—firms in the Northern and Southern regions–we empirically show that female CEOs in the North, where there is less gender stereotype, tend to overinvest relative to male CEOs. However, in the South, they are indifferent. Additional analysis reinforces the main finding that female CEOs from the North tend to take more risks even when dealing with market volatility and uncertainty (e.g., the COVID-19 pandemic). Such risky behaviours of female CEOs in the North do not deteriorate firm value but instead, possibly improve firm performance.
This paper was published in Finance Research Letters, Volume 58, Part A, December 2023. Access the published paper.
E-DSGE model with endogenous capital utilization rate
Ying Tung Chan (Beijing Normal University), Maria Teresa Punzi (SKBI) | Jun 2023 |
Environmental policy research has increased due to stricter policies aligned with climate goals. However, to achieve the goal of net-zero emissions, the adoption of even stronger policies and increased carbon taxes is necessary, with transition risk becoming a major concern for companies. Even though governments worldwide have been employing a range of methods such as carbon tax, cap-and-trade, and intensity targets to mitigate the impact of climate change, a pivotal debate around determining the optimal policy that reduces emissions without harming the economy continues. Our paper delves into the environmental policy assessment emphasizing the role of endogenous capital utilization rates, which have hitherto been largely disregarded in literature. We study how endogenous capital utilization rate affects the transmission mechanism of economic shocks and the optimal environmental policy choice. To evaluate the quantitative impact of the transmission mechanism, we introduce distinct features to the E-DSGE framework, including endogenous capital utilization, time-varying depreciation of capital, and environment quality shocks. We find that the complementarity between energy and capital leads to an amplification effect of the conventional transmission mechanism. Our model with these ingredients ranks any carbon tax below 25% as the best policy in terms of welfare improvement.
This paper was published in Journal of Cleaner Production, Volume 414, 15 August 2023, 137640. Access the published paper.
Does Abstract Thinking Facilitate Information Processing? Evidence from Financial Analysts
Zuben Jin (Southwestern University of Finance and Economics), Frank Weikai Li (SMU), Rong Wang (SMU), and Gloria Yang Yu (SMU) | Dec 2022 |
We study whether abstract thinking – an essential cognitive trait established by psychological and neuroscientific studies – facilitates analysts’ information processing. Exploiting analysts’ questions during earnings calls, we construct an Abstract Thinking Index (ATI) that measures their tendency to involve abstract words, logical reasoning, broader topics, and future outlooks. We find that abstract thinking improves analysts’ forecast accuracy and recommendation informativeness. Consistent with abstract thinking featuring identifying central characteristics and comprehending intangible things, ATI has stronger effects for firms with fundamentals comoving more with peers and less tangible information. Additional analyses suggest that ATI captures analysts’ cognitive traits rather than information access.
The Just Transition Transaction (JTT) in Southeast Asia
Bharat Gangwani (SMU), Gireesh Shrimali (University of Oxford; Stanford University; SKBI) and Rajiv B Lall (SKBI) | Sep 2022 |
The Just Transition Transaction (JTT) was developed for South Africa to support its coal retirement and greening of its national utility, ESKOM. We first use South Africa as a reference case study to deconstruct the JTT and develop a framework of necessary and conducive features for its application to other countries. We then use this framework to evaluate the JTT’s suitability for supporting a green transition in key South-East Asian countries, specifically Indonesia, Vietnam, and the Philippines. We find that, while the JTT is suitable for Indonesia and Vietnam, it is not as suitable for the Philippines. Finally, we present a tiered JTT as a model to encourage a green transition at a supranational level and propose avenues for specific research to apply the JTT to Indonesia and Vietnam.
Quantum Machine Learning for Credit Scoring
Nikolaos Schetakis (ALMA Sistemi Srl) , Davit Aghamalyan (A*STAR) , Michael Boguslavsky (Tradeteq), Agieszka Rees (Tradeteq), Marc Rakotomalala (SKBI), Paul Robert Griffin (SMU) | Jul 2022 |
This paper explores combining quantum circuits with classical neural networks to improve credit scoring for small- and medium-sized enterprises (SMEs). We introduce a hybrid quantum–classical model, focusing on the synergy between quantum and classical rather than comparing the performance of separate quantum and classical models. The model integrates a quantum layer into a traditional neural network, resulting in significantly reduced training time. Applying this approach to a real-world Singapore SME credit dataset, we find that the hybrid model achieves efficient training with notably fewer epochs compared to its classical counterpart, while maintaining similar predictive accuracy. However, we observe decreases in performance with larger quantum components. The study also addresses challenges in deploying such models on quantum simulators and actual quantum computers. Despite scalability limitations and practical challenges with current technology, the hybrid model for credit scoring reveals its potential in industry.
This paper was published in the Special Issue of Quantum Computing Algorithms and Quantum Computing Simulators, May 2024. Access the published paper.
Weak Identification of Long Memory with Implications for Inference
Jia Li (SMU), Peter C. B. Phillips (Yale University), Shuping Shi (Macquarie University) and Jun Yu (SMU) | Jun 2022 |
This paper explores weak identification issues arising in commonly used models of economic and financial time series. Two highly popular configurations are shown to be asymptotically observationally equivalent: one with long memory and weak autore-gressive dynamics, the other with antipersistent shocks and a near-unit autoregressive root. We develop a data-driven semiparametric and identification-robust approach to inference that reveals such ambiguities and documents the prevalence of weak identifi-cation in many realized volatility and trading volume series. The identification-robust empirical evidence generally favors long memory dynamics in volatility and volume, a conclusion that is corroborated using social-media news flow data.
Commodity Return Predictability: Evidence from Implied Variance, Skewness and their Risk Premia
Marinela Adriana Finta (SKBI) and José Renato Haas Ornelas (Banco Central do Brasil) | Apr 2022 |
This paper investigates the role of realized and implied moments and their risk premia (variance and skewness) for commodities’ future returns. We estimate these moments from high frequency and commodity futures option data that results in forward-looking measures. Risk premia are computed as the difference between implied and realized moments. We highlight, from a cross-sectional and time-series perspective, the strong positive relation between commodity returns and implied skewness. Moreover, we emphasize the high performance of skewness risk premium. Additionally, we show that their portfolios exhibit the best risk-return tradeoff. Most of our results are robust to other factors such as the momentum and roll yield.
This paper was published in Journal of International Financial Markets, Institutions and Money, Volume 79, July 2022. Access the published paper.
Higher-Order Risk Premium and Return Spillovers between Commodity and Stock Markets
Marinela Adriana Finta (SKBI) | Mar 2022 |
This study examines the spillovers between risk premia and returns of commodity (grain, metal, and energy sectors) and equity markets (the U.S., U.K., Germany, and Japan). Risk premia are defined as the difference between implied volatility, skewness, and kurtosis and their realized moments. Our results show that cross-market and cross-moment spillovers vary over time, and various announcements explain this variation. We uncover the substantial effects of equity markets for commodity markets, and as those of returns for the risk premia. Moreover, we highlight the prominent influence of the metal sector for the other commodity sectors and equity market, and that of skewness risk premia for the returns.
Is Carbon Risk Priced in the Cross-Section of Corporate Bond Returns?
Tinghua Duan (IESEG School of Management), Frank Weikai Li (SMU) and Quan Wen (Georgetown University) | Feb 2022 |
The ‘carbon risk premium’ hypothesis says that bonds of more carbon-intensive firms should earn significantly higher returns, but this paper fails to find evidence supporting this view. The dominant explanation is that investors under-appreciate the negative relation between a firm's carbon intensity and its fundamental performance and creditworthiness.
Volatility Puzzle
Jun Yu (SMU), Shuping Shi (Macquarie University) | Jan 2022 |
Market volatility can help us understand other financial variables and macroeconomic conditions. But volatility is often regarded as an imperfect measure of market risk or anxiety. Nevertheless, this paper helps practitioners and academics strive for a rigorous empirical volatility model that more accurately describes current market behaviour and the interactions among market participants.
Outsourcing Climate Change
Rui Dai (University of Pennsylvania), Rui Duan (WU), Hao Liang (SMU), Lilian Ng (York University) | Jan 2022 |
This paper examines whether and how firms combat climate change. Our study provides robust evidence that firms outsource part of their carbon emissions to foreign suppliers and shows how internal and external stakeholders significantly shape firms’ environmental policies. Furthermore, firms tend to seek a foreign supplier and decrease their emission abatement efforts as pressure to reduce domestic emissions intensifies. These firms are also less incentivized to develop green technologies. Finally, we find that outsourcing emissions has real and economic consequences, with investors demanding a higher carbon premium for their exposures to carbon risks associated with increased outsourced emissions.
Does The Institutional Environment Affect the Value of Analyst Recommendations Around the World?
Wanyi Yang (SKBI) and Jun Ma (University of Auckland) | Aug 2021 |
This paper investigates whether the value of analyst recommendations varies across countries and whether this difference is associated with a country’s institutional environment. Using recommendations from a sample of 32 countries from 1994 to 2015, we found that stock prices react to analysts significantly differently across countries. In particular, recommendation announcements in countries with higher accounting standards, more effective security law enforcement, better earnings quality, common law origins, and better protection of private property are associated with significantly higher price reactions. The results are robust using alternative research settings. The institutional environment affects the value of recommendation revisions across countries as well.
Greenwashing: Evidence from Hedge Funds
Hao Liang (SMU LKCSB), Melvyn Teo (SMU LKCSB) and Lin Sun (Fudan University) | Aug 2021 |
We find that a non-trivial number of hedge funds that endorse the United Nations Principles for Responsible Investment indulge in greenwashing. Hedge funds that greenwash underperform both genuinely green and nongreen funds after adjusting for risk. Consistent with an agency explanation, greenwashers (i) underperform more when incentive alignment is poor, (ii) trigger more regulatory violations, and (iii) report more suspicious returns. By exploiting regulatory reforms that aim to enhance stewardship and curb greenwashing, we provide causal evidence that relates agency problems to greenwashing and fund underperformance. Investors, however, do not appear to discriminate between greenwashers and genuinely green funds.
Japanese Monetary Policy and Its Impact on Stock Market Implied Volatility During Pleasant and Unpleasant Weather
Marinela Adriana Finta (SKBI) | Mar 2021 |
We investigate the effect of Japan’s Monetary Policy Meeting releases on the intraday dynamics of the Nikkei Stock Average Volatility Index and its futures during pleasant and unpleasant weather. We show that at the time of a monetary policy release when the temperature is pleasant, there is a significant decline in Japanese equities’ implied volatility and futures, which lasts for about 10 minutes and 5 minutes, respectively. This decline is longer and exhibits a greater variation when releases occur during cold days. Finally, we emphasize the achievable economic profits and losses, given the reaction of Nikkei VI futures to the Japanese monetary policy releases during pleasant and unpleasant weather days, respectively. In particular, taking a short position at the start of the trading day on pleasant days and closing this position at the end of the trading day generates an average annual return of 5.6%.
This paper was published in the Pacific-Basin Finance Journal, Volume 67, Jun 2021. Access the published paper.
Corporate Social Responsibility and Sustainable Finance: A Review of the Literature
Hao Liang (SMU), Luc Renneboog (Tilburg University) | Sep 2020 |
Corporate Social Responsibility (CSR) refers to the incorporation of Environmental, Social, and Governance (ESG) considerations into corporate management, financial decision making, and investors’ portfolio decisions. Socially responsible firms are expected to internalize the externalities (e.g. pollution) they create, and are willing to be accountable to shareholders as well as a broader group of stakeholders (employees, customers, suppliers, local communities,…). Over the past two decades, various rating agencies developed firm-level measures of ESG performance, which are widely used in the literature. A problem for past and a challenge for future research is that these ratings show inconsistencies, which depend on the rating agencies’ preferences, weights of the constituting factors, and rating methodology.
Forthcoming in Oxford Research Encyclopedia of Economics and Finance.
Decentralizing Money: Bitcoin Prices and Blockchain Security
Emiliano Pagnotta (SKBI) | Nov 2020 |
This paper studies the equilibrium determination of bitcoin prices and its blockchain security. Complementarities between users and miners lead to multiple equilibria: the same blockchain technology is consistent with different price-security levels. Bitcoin’s design embeds price volatility amplification of demand shocks and is prone to exhibit seemingly irrational price jumps. The results clarify when bitcoin demand strengthens against conventional currencies.
This paper was published in The Review of Financial Studies, Volume 35, Issue 2, Feb 2022, Pages 866–907. Access the published paper.
Risk Premium Spillovers Among Stock Markets: Evidence from Higher-Order Moments
Marinela Adriana Finta (SKBI) and Sofiane Abourab (University of Paris XIII) | Jun 2017 |
This paper investigates the volatility, skewness and kurtosis risk premium spillovers among U.S., U.K., German and Japanese stock markets. We define risk premia as the difference between risk-neutral and realized moments. Our findings highlight that during periods of stress and after 2014, cross-market and cross-moment spillovers increase, and this is mirrored by a decrease in within spillovers. We document strong bi-directional spillovers between skewness and kurtosis risk premia and emphasize the prominent role played by the volatility risk premium. Finally, we show that several macroeconomic and financial factors increase with the intensity of risk premium spillovers.
This paper was published in the Journal of Financial Markets, Volume 49, Jun 2020. Access the published paper.
