nep-fmk New Economics Papers
on Financial Markets
Issue of 2023‒05‒08
fifteen papers chosen by
Kwang Soo Cheong
Johns Hopkins University

  1. Asset management as creator of market inefficiency By Vayanos, Dimitri; Woolley, Paul
  2. Analyst Bias and Mispricing By Mark Grinblatt; Gergana Jostova; Alexander Philipov
  3. The Elasticity of Quantitative Investment By Carter Davis
  4. Statistical properties of volume in the Bitcoin/USD market By Roberto Mota Navarro; Francois Leyvraz; Hern\'an Larralde
  5. FOUR FACTS ABOUT ESG BELIEFS AND INVESTOR PORTFOLIOS By Giglio, Stefano; Maggiori, Matteo; Stroebel, Johannes; Tan, Zhenhao; Utkus, Stephen; Xu, Xiao
  6. Dark Matter in (Volatility and) Equity Option Risk Premiums By Gurdip Bakshi; John Crosby; Xiaohui Gao
  7. Risk-Taking Behavior during Downturn: Evidence of Loss-Chasing and Realization Effect in the Cryptocurrency Market By Voraprapa Nakavachara; Roongkiat Ratanabanchuen; Kanis Saengchote; Thitiphong Amonthumniyom; Pongsathon Parinyavuttichai; Polpatt Vinaibodee
  8. The Market-Based Statistics of “Actual” Returns of Investors By Olkhov, Victor
  9. Equilibrium bitcoin pricing By Bruno Biais; Christophe Bisière; Matthieu Bouvard; Catherine Casamatta; Albert J. Menkveld
  10. Bank Ownership Around the World By Ugo Panizza
  11. Institutional Blockholders and Corporate Innovation By Bing Guo; Dennis C. Hutschenreiter; David Pérez-Castrillo; Anna Toldrà-Simats
  12. Model-free and Model-based Learning as Joint Drivers of Investor Behavior By Nicholas C. Barberis; Lawrence J. Jin
  13. Global Risk, Non-Bank Financial Intermediation, and Emerging Market Vulnerabilities By Anusha Chari
  14. Dissecting the explanatory power of ESG features on equity returns by sector, capitalization, and year with interpretable machine learning By Jérémi Assael; Laurent Carlier; Damien Challet
  15. Finding Anomalies in China By Hou, Kewei; Qiao, Fang; Zhang, Xiaoyan

  1. By: Vayanos, Dimitri; Woolley, Paul
    Abstract: In this paper, we describe how agency frictions in asset management can generate prime violations of the Efficient Markets Hypothesis, such as momentum, value and an inverted risk-return relationship. Momentum in our theory is associated with procyclical fund flows and price over-reaction, and is more pronounced for overvalued assets. The investors who generate the momentum and who are losing from it are those requiring their asset managers to keep their portfolios close to benchmark indices. Our theory suggests a rethinking of asset management contracts. Contracts should employ measures of long-run risk and return, and benchmark indices that emphasize asset fundamentals. There should also be greater transparency on managers’ choice of strategies.
    Keywords: financial markets; asset management; agency frictions; momentum; benchmarking; Springer deal
    JEL: G12 G14 G23 E44
    Date: 2023–04–19
  2. By: Mark Grinblatt; Gergana Jostova; Alexander Philipov
    Abstract: Cross-sectional forecasts of conservative and optimistic biases in analyst earnings estimates predict a stock's future returns, especially for firms that are hard to value. Trading strategies—whether based on the component of analyst bias that is correlated with major return anomalies or the component that is orthogonal to these anomalies—earn abnormal profits. The prevalence of optimistic analyst earnings estimates and rarity of conservative estimates emerges as a common link between anomaly-generating firm characteristics and subsequent negative alphas. For the vast majority of anomaly strategies, profitability disappears once we control for analyst bias.
    JEL: G12 G13 G14 G24 G41
    Date: 2023–03
  3. By: Carter Davis
    Abstract: What is the price elasticity of demand for canonical portfolio choice methods in financial economics? Twelve models from the literature exhibit strikingly inelastic demand, in contrast to classical models. This is due to the difficulty of trading against price changes in practice, and is consistent with demand elasticity estimates. This provides a novel answer to the inelastic markets hypothesis, raises important concerns for the use of strongly elastic investors in theory models, and quantifies the difficulty of trading against potential mispricing aside from the standard limits to arbitrage frictions. Counterfactual experiments with these demand functions exhibit large and persistent alpha.
    Date: 2023–03
  4. By: Roberto Mota Navarro; Francois Leyvraz; Hern\'an Larralde
    Abstract: Several studies have shown that just as there are some quite non-trivial statistical properties in the time series of financial asset returns, the volumes of transactions and of orders entered into the order book also display interesting and complex statistical properties. For instance, a recurring observation in the literature has been that the sizes of volumes, both of incoming orders and of realized transactions, can take on many different values across several orders of magnitude, with a marked preference for whole numbers like 5, 10, 100 and so on. Another common finding is that the time series of volumes present long lived autocorrelations, with decay rates that can be well approximated by power laws. These studies have focused their attention on the volume of incoming orders or on the volume of registered transactions, but there is another source of data relevant for a deeper understanding of market dynamics: the volume stored at the best ask and best bid. The present work is a study of the statistical properties of volume stored at the best orders. We measured both properties that do not have a dependence on the passage of time (e.g. probability distributions), as well as properties that directly depend on time (e.g. autocorrelation functions).
    Date: 2023–04
  5. By: Giglio, Stefano; Maggiori, Matteo; Stroebel, Johannes; Tan, Zhenhao; Utkus, Stephen; Xu, Xiao
    Abstract: We analyze survey data on ESG beliefs and preferences in a large panel of retail investors linked to administrative data on their investment portfolios. The survey elicits investors' expectations of long-term ESG equity returns and asks about their motivations, if any, to invest in ESG assets. We document four facts. First, investors generally expected ESG investments to underperform the market. Between mid-2021 and late-2022, the average expected 10-year annualized return of ESG investments relative to the overall stock market was $-1.4\%$. Second, there is substantial heterogeneity across investors in their ESG return expectations and their motives for ESG investing: 45\% of survey respondents do not see any reason to invest in ESG, 25\% are primarily motivated by ethical considerations, 22\% are driven by climate hedging motives, and 7\% are motivated by return expectations. Third, there is a link between individuals' reported ESG investment motives and their actual investment behaviors, with the highest ESG portfolio holdings among individuals who report ethics-driven investment motives. Fourth, financial considerations matter independently of other investment motives: we find meaningful ESG holdings only for investors who expect these investments to outperform the market, even among those investors who reported that their most important ESG investment motives were ethical or hedging reasons.
    Date: 2023–04–03
  6. By: Gurdip Bakshi; John Crosby; Xiaohui Gao
    Abstract: Emphasizing the statistics of jumps crossing the strike and local time, we develop a decomposition of equity option risk premiums. Operationalizing this theoretical treatment, we equip the pricing kernel process with unspanned risks, embed (unspanned) jump risks, and allow equity return volatility to contain unspanned risks. Unspanned risks are consistent with negative risk premiums for jumps crossing the strike and local time and imply negative risk premiums for out-of-the-money call options and straddles. The empirical evidence from weekly and farther-dated index options is supportive of our theory of economically relevant unspanned risks and reveals ``dark matter" in option risk premiums.
    Date: 2023–03
  7. By: Voraprapa Nakavachara; Roongkiat Ratanabanchuen; Kanis Saengchote; Thitiphong Amonthumniyom; Pongsathon Parinyavuttichai; Polpatt Vinaibodee
    Abstract: Psychologists and economists have both explored how past outcomes influence subsequent risktaking behavior. However, psychologists traditionally focused on gambling, while economists mainly looked at investors’ decisions under uncertainty. As a result, the two fields arrived at different conclusions. Psychology literature identified loss-chasing behavior among casino gamblers and labeled it “compulsive gambling, †a disorder requiring treatment. Economists, on the other hand, introduced a concept of the “realization effect, †suggesting that risk-taking may increase after an unrealized loss but decrease after a realized loss (Imas, 2016). This paper aims to reconcile these two perspectives using empirical evidence from the cryptocurrency market, where gamblers and investors coexist. We find that high-risk individuals increase risk-taking after both unrealized and realized losses. In the most severe case, a one-standard-deviation increase in loss would raise risk-taking, as measured by portfolio volatility, by 58.72%. Thus, high-risk individuals in the cryptocurrency market behave like casino gamblers observed in Psychology literature. On the other hand, low-risk individuals increase risk-taking only after unrealized losses and avoid risks after realized losses. Thus, low-risk individuals in the cryptocurrency market behave like investors facing risky choices, which can be explained by the “realization effect†in Economics literature.
    Keywords: Cryptocurrency; Realization Effect; Loss-Chasing; Behavioral Finance
    JEL: D81 G11 G41
    Date: 2023–04
  8. By: Olkhov, Victor
    Abstract: The paper presents the unified theoretical description of three levels of the market-based statistical moments of “actual” returns, which Investors gain within their market sales. The market-based statistics of “actual” returns takes into account the size of the trade sale values, purchased values and volumes of stocks and that differs it from conventional regular statistics based on frequency analysis of returns time-series. We start with description of statistical moments of returns, which Investor gains via a single sale due to his multiple purchases in the past. The second level describes statistics of returns, which Investor gains performing numerous market sales during the “trading day”. The third level describes statistics of returns that different Investors gain during the “trading day”. We derive dependence of statistical moments of returns on statistical moments of market sale values, purchased values and volumes of stocks. In its turn, statistical moments of trade values and volumes for finite number of market trades during the “trading day” are assessed via regular frequency-based probability.
    Keywords: asset pricing, stock returns, volatility, correlations, probability, market trades
    JEL: C0 C80 G1 G11 G12
    Date: 2023–04–02
  9. By: Bruno Biais (TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, CNRS - Centre National de la Recherche Scientifique); Christophe Bisière (TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Matthieu Bouvard (TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Catherine Casamatta (TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Albert J. Menkveld (Unknown)
    Abstract: We offer an overlapping generations equilibrium model of cryptocurrency pricing and confront it to new data on bitcoin transactional benefits and costs. The model emphasizes that the fundamental value of the cryptocurrency is the stream of net transactional benefits it will provide, which depend on its future prices. The link between future and present prices implies that returns can exhibit large volatility unrelated to fundamentals. We construct an index measuring the ease with which bitcoins can be used to purchase goods and services, and we also measure costs incurred by bitcoin owners. Consistent with the model, estimated transactional net benefits explain a statistically significant fraction of bitcoin returns.
    Date: 2023–01–19
  10. By: Ugo Panizza (IHEID, Graduate Institute of International and Development Studies, Geneva)
    Abstract: This paper builds a dataset on bank ownership that covers more than 6, 500 banks in 181 countries (59 low-income economies, 72 middle-income economies, and 50 high-income economies) over 1995-2020. I show that until 2010, there was a reduction in state-ownership of banks and an increase foreign ownership. However, the Global Financial Crisis interrupted or reversed these trends. At the country level, the relationship between bank ownership and each of GDP growth and financial depth is mixed- regressions with country fixed effects indicate that the presence of foreign-owned banks is positively associated with future economic growth and state-ownership is negatively but not robustly associated with future financial depth. Bank-level regressions show that state-owned banks are less profitable and have a higher share of non-performing loans than their private (domestic or foreign) counterparts. State-owned and foreign-owned banks located in developing economies pay and charge lower interest rates than their domestic private counterparts. There is also evidence that state-owned banks stabilize credit in the presence of domestic shocks while foreign banks amplify external shocks. In terms of domestic shocks, foreign banks are not significantly different from their domestic private counterparts.
    Keywords: State-owned banks; Foreign-owned banks; Economic growth; Financial depth; Non-performing loans; Credit cyclicality
    JEL: G21 G28 G32 F21 F36 O16
    Date: 2023–04–18
  11. By: Bing Guo; Dennis C. Hutschenreiter; David Pérez-Castrillo; Anna Toldrà-Simats
    Abstract: Institutional investors’ ownership in public firms has become increasingly concentrated in the last decades. We study the heterogeneous effects of large versus more dispersed institutional owners on firms’ innovation strategies and their innovation output. We find that large institutional investors induce managers to increase spending in internal R&D by reducing short-term pressure. However, to avoid empire building and dilution, large institutional investors prevent acquisitions, which reduces firms’ investment in external innovation. The overall effect on firms’ future patents and citations is negative. By acquiring less innovation from external sources, firms reduce the returns of their investment in internal R&D, jeopardizing their total innovation output. We use the mergers of financial institutions as exogenous shocks on firms’ institutional ownership concentration. Our findings complement the previously found positive effects of institutional ownership on firm innovation and indicate that the effects become negative when institutional investors become large owners.
    Keywords: institutional ownership, blockholders, innovation, acquisitions
    JEL: G32 G24 O31
    Date: 2023–04
  12. By: Nicholas C. Barberis; Lawrence J. Jin
    Abstract: In the past decade, researchers in psychology and neuroscience studying human decision-making have increasingly adopted a framework that combines two systems, namely "model-free" and "model-based" learning. We import this framework into a simple financial setting, study its properties, and use it to account for a range of facts: facts about investor behavior, such as extrapolative demand and experience effects; facts about beliefs, such as overreaction in beliefs and the relationship between beliefs and stock market allocations; and facts about asset prices, such as excess volatility. More broadly, the framework offers a way of thinking about individual behavior that is grounded in recent evidence on the computations that the brain undertakes when estimating the value of a course of action.
    JEL: D03 G02 G11
    Date: 2023–03
  13. By: Anusha Chari
    Abstract: Over the last two decades, the unprecedented increase in non-bank financial intermediation, particularly open-end mutual funds and ETFs, accounts for nearly half of the external financing flows to emerging markets exceeding cross-border lending by global banks. Evidence suggests that investment fund flows enhance risk-sharing across borders and provide emerging markets access to more diverse forms of financing. However, a growing body of evidence also indicates that investment funds are inherently more vulnerable to liquidity and redemption risks during periods of global financial market stress, increasing the volatility of capital flows to emerging markets. Benchmark-driven investments, namely passive funds, appear particularly sensitive to global risk shocks such as tightening US dollar funding conditions relative to their active fund counterparts. The procyclicality of investment fund flows to emerging markets during times of global stress poses financial stability concerns with implications for the role of macroprudential policy.
    JEL: F21 F32 F36 F65 G11 G15 G23
    Date: 2023–04
  14. By: Jérémi Assael (BNPP CIB GM Lab - BNP Paribas CIB Global Markets Data & AI Lab, MICS - Mathématiques et Informatique pour la Complexité et les Systèmes - CentraleSupélec - Université Paris-Saclay); Laurent Carlier (BNPP CIB GM Lab - BNP Paribas CIB Global Markets Data & AI Lab); Damien Challet (MICS - Mathématiques et Informatique pour la Complexité et les Systèmes - CentraleSupélec - Université Paris-Saclay)
    Abstract: We systematically investigate the links between price returns and Environment, Social and Governance (ESG) features in the European market. We propose a cross-validation scheme with random company-wise validation to mitigate the relative initial lack of quantity and quality of ESG data, which allows us to use most of the latest and best data to both train and validate our models. Boosted trees successfully explain a part of annual price returns not accounted by the market factor. We check with benchmark features that ESG features do contain significantly more information than basic fundamental features alone. The most relevant sub-ESG feature encodes controversies. Finally, we find opposite effects of better ESG scores on the price returns of small and large capitalization companies: better ESG scores are generally associated with larger price returns for the latter, and reversely for the former.
    Keywords: ESG features, sustainable investing, interpretable machine learning, model selection, asset management, equity returns, ESG data
    Date: 2023–03
  15. By: Hou, Kewei (Ohio State U); Qiao, Fang (U of International Business and Economics, Beijing); Zhang, Xiaoyan (Tsinghua U)
    Abstract: To study the cross-section of returns in the Chinese stock market, we follow the anomaly literature and construct 454 strategies between 2000 and 2020, based on 208 firm-level trading and accounting signals. With the conventional single-testing t-statistic cutoff of 1.96, 101 strategies have significant value-weighted raw returns, and 20 remain significant after risk adjustments. To avoid false discoveries, we recalibrate the t-statistic cutoff to 2.85 to accommodate multiple testing. 36 strategies survive the higher hurdle rate in value-weighted raw returns, while none remains significant after risk adjustments. When we use machine learning techniques to combine information from multiple signals, the resulting composite strategies mostly have significant returns after risk adjustments, even with the higher t-statistic cutoff. We relate Chinese anomaly returns to aggregate economic conditions and find that they comove with financial market development, accounting quality, market liquidity, and government regulations.
    JEL: G1 G12
    Date: 2023–01

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