Research articles for the 2021-05-23
arXiv
I demonstrate that with the market return determined by the equilibrium returns of the CAPM, expected returns of an asset are affected by the risks of all assets jointly. Another implication is that the range of feasible market returns will be limited and dependent on the distribution of weights in the market portfolio. A large and well diversified market with no dominating asset will only return zero while a market dominated by a small number of assets will only return the risk-free rate. In the limiting case of atomistic assets, we recover the properties of the standard CAPM.
arXiv
It is a difficult task for both professional investors and individual traders continuously making profit in stock market. With the development of computer science and deep reinforcement learning, Buy\&Hold (B\&H) has been oversteped by many artificial intelligence trading algorithms. However, the information and process are not enough, which limit the performance of reinforcement learning algorithms. Thus, we propose a parallel-network continuous quantitative trading model with GARCH and PPO to enrich the basical deep reinforcement learning model, where the deep learning parallel network layers deal with 3 different frequencies data (including GARCH information) and proximal policy optimization (PPO) algorithm interacts actions and rewards with stock trading environment. Experiments in 5 stocks from Chinese stock market show our method achieves more extra profit comparing with basical reinforcement learning methods and bench models.
RePEC
Bookmakers sell claims to bettors that depend on the outcomes of professional sports events. Like other financial assets, the wisdom of crowds could help sellers to price these claims more efficiently. We use the Wikipedia profile page views of professional tennis players involved in over ten thousand singles matches to construct a buzz factor. This measures the difference between players in their pre-match views relative to the usual numbers they received over the previous year. The buzz factor significantly predicts mispricing by bookmakers. Using this fact to forecast match outcomes, we demonstrate that a strategy of betting on players who received more pre-match buzz than their opponents can generate substantial profits. These results imply that sportsbooks could price outcomes more efficiently by listening to the buzz.
SSRN
Potential investors examine governance characteristics prior to an initial public offering (IPO) to assess the quality and prospects of the issuing firm. One important governance characteristic is board financial expertise, as it provides directors with the relevant knowledge for an IPO process and is valuable for the boardâs monitoring duties. Therefore, the purpose of this paper is to examine whether and how board financial expertise affects IPO outcomes. To do so, I employ a sample of 414 completed and 85 withdrawn IPOs that were filed from 2014â"2017 at NYSE or NASDAQ. I document that the ratio of directors with financial expertise on the board is negatively associated with the level of underpricing and the probability of IPO withdrawal. The results suggest that particularly outside directors with financial expertise have a positive signaling effect and help to reduce information asymmetry around initial public offerings. Above that, using quantile regression, I find that director financial expertise is most valuable for issuances with high levels of investor uncertainty. Therefore, this study makes important contributions to the corporate governance and IPO literature by providing a comprehensive analysis of the effects of board financial expertise on IPO outcomes.
SSRN
This paper examines whether the presence of foreign board members leads to higher dividend yield in top Egyptian listed companies. Using a sample of the top 50 firms listed on the Egyptian Exchange between 2005 and 2014, I found that there is a significant positive relationship between board national diversity and dividend yield. This paper contributes to the literature by investigating a novel board diversity variable's relationship with dividend policies.
arXiv
A large proportion of market making models derive from the seminal model of Avellaneda and Stoikov. The numerical approximation of the value function and the optimal quotes in these models remains a challenge when the number of assets is large. In this article, we propose closed-form approximations for the value functions of many multi-asset extensions of the Avellaneda-Stoikov model. These approximations or proxies can be used (i) as heuristic evaluation functions, (ii) as initial value functions in reinforcement learning algorithms, and/or (iii) directly to design quoting strategies through a greedy approach. Regarding the latter, our results lead to new and easily interpretable closed-form approximations for the optimal quotes, both in the finite-horizon case and in the asymptotic (ergodic) regime.
SSRN
This paper proposes a novel approach to understand contagion of financial distress in the banking system, which takes into account the spatial nature of the phenomena. We use a Bayesian spatial autoregressive model that treats the likelihood of default of each bank as endogenous, and dependent on the network formed by all the other banks. Identification is achieved by controlling for bank fundamentals, latent macrofinancial and bank specific shocks that have similar consequences to contagion and act as confounding factors. Through the lens of a simulations exercise we study the importance of the structure of financial networks for financial stability, shedding light on the empirical adherence of important theoretical propositions that remain untested.
SSRN
This paper tests a theory conjecturing that cross-listing can insulate firms from potential hostile takeovers due to the increased cost concern of bidders. We find a significant and positive relation between the corporate control threat and the likelihood that firms cross-list in a foreign country. Firms facing takeover threats are more likely to choose hosting countries with greater accounting differences from the US GAAP. Cross-sectional evidence suggests that cross-listing is more likely to be used as an antitakeover device if firms have foreign market exposure or when all-cash offers are less likely. Tests based on quasi-natural experiments provide further support.
SSRN
We use a novel dataset that links audit-firm and client-firm financial statement information from the U.K.âs largest audit firms to examine drivers of audit-firm profitability and its implications for audit outcomes conveyed by Key Audit Matter (KAM) disclosures. We first explore the determinants of audit-firm profitability and conclude that Big-4 and non-Big-4 audit firms have fundamentally different profitability structures. Big-4 firms earn higher profit margins than non-Big-4 firms. Furthermore, Big-4 profitability increases with client size and complexity, while non-Big-4 profitability is higher for smaller clients and clients with losses. Next, we examine the relation between audit-firm profitability and KAM reporting. We find that more profitable audit firms address more KAMs. However, audit-firm profitability is less likely to affect audit outcomes for loss-making clients (i.e., when auditors are exposed to more litigation risk). Our results are robust to several endogeneity controls such as controlling for client-firm and/or audit-firm fixed effects, employing changes specifications, and using an instrumental variables approach, as well as to examining the external validity of our findings and using alternative outcome measures. Our study presents evidence consistent with theoretical models in economics and empirical evidence in management sciences suggesting that firm profitability positively affects product/service quality.
SSRN
Dynastic-controlled firms are led by founding family CEOs while the family owns an insignificant share of equity (defined as less than five percent). They represent 7.4% of listed firms in post-war Japan, include well-known firms such as Casio, Suzuki and Toyota, and are often grouped with widely-held firms in the literature. These firms differ in key performance measures from both traditional family firms and non-family firms, and evolve from the former as equity-financed growth dilutes the founding familyâs ownership over time. In turn, the transition from dynastic control to non-family status is driven by a diminution of strategic family resources.
arXiv
The performance of a cross-sectional currency strategy depends crucially on accurately ranking instruments prior to portfolio construction. While this ranking step is traditionally performed using heuristics, or by sorting outputs produced by pointwise regression or classification models, Learning to Rank algorithms have recently presented themselves as competitive and viable alternatives. Despite improving ranking accuracy on average however, these techniques do not account for the possibility that assets positioned at the extreme ends of the ranked list -- which are ultimately used to construct the long/short portfolios -- can assume different distributions in the input space, and thus lead to sub-optimal strategy performance. Drawing from research in Information Retrieval that demonstrates the utility of contextual information embedded within top-ranked documents to learn the query's characteristics to improve ranking, we propose an analogous approach: exploiting the features of both out- and under-performing instruments to learn a model for refining the original ranked list. Under a re-ranking framework, we adapt the Transformer architecture to encode the features of extreme assets for refining our selection of long/short instruments obtained with an initial retrieval. Backtesting on a set of 31 currencies, our proposed methodology significantly boosts Sharpe ratios -- by approximately 20% over the original LTR algorithms and double that of traditional baselines.
arXiv
Calcium (Ca) requirement increases tenfold upon parturition in dairy cows & buffaloes and its deficiency leads to a condition called milk fever (MF). Estimation of losses is necessary to understand the depth of the problem and design preventive measures. How much is the economic loss due to MF? What will be the efficiency gain if MF is prevented at the advent of a technology? We answer these questions using survey data and official statistics employing economic surplus model. MF incidence in sample buffaloes and cows was 19% and 28%, respectively. Total economic losses were calculated as a sum total of losses from milk production, mortality of animals and treatment costs. Yearly economic loss due to MF was estimated to be INR 1000 crores (US$ 137 million) in Haryana. Value of milk lost had the highest share in total economic losses (58%), followed by losses due to mortality (29%) and treatment costs (13%). Despite lower MF incidence, losses were higher in buffaloes due to higher milk prices and market value of animals. The efficiency gain accruing to producers if MF is prevented, resulting from increased milk production at decreased costs was estimated at INR 10990 crores (US$ 1.5 billion). As the potential gain if prevented is around 10 times the economic losses, this study calls for the use of preventive technology against MF.
SSRN
Starting in October 2013, auditors of premium-listed firms in the United Kingdom are mandated to prepare an expanded auditorâs report that provides details on audit procedures, risks of material misstatement (RMMs), and materiality thresholds. This regulatory change is important to study, because it aims to increase the informational value of the traditional, highly standardized, pass-or-fail auditorâs report. We examine whether the disclosures in the expanded auditorâs report provide information that is relevant for adopting firmsâ loan contracting terms in the post-adoption period. Our results indicate that the introduction of the expanded auditorâs report is associated with reduced loan spread and longer maturity for loan facilities of adopting firms relative to non-adopting UK firms. When we focus on adopting firms in the post-adoption period, we find that the number of âunique RMMsâ mentioned in the auditorâs report, but not in the audit committee report, are positively associated with loan spread but are not associated either with loan maturity or the number of lenders in the loan syndicate. Additional tests show that the benefits, in terms of a reduced spread, of having a lower number of âunique RMMsâ accrue mostly to adopters with a poor information environment. Taken together, our results provide preliminary evidence that the expanded auditorâs report disclosures contain relevant information for loan contracting in the United Kingdom. This study highlights the unique role of the expanded auditorâs report in providing information relevant to lenders and supports standard settersâ efforts to enrich its informational content.
SSRN
We create an alternative, simpler definition of analyst forecast timeliness leaders based on their response after the corporate quarterly earnings announcements, examining if these analystsâ forecasts are superior in informativeness and accuracy. Our Earnings Announcement Date Leader classification method of leaders and followers is able to identify superior analysts who provide forecasts of higher quality in all three properties, timeliness, informativeness and accuracy, contrary to prior definitions of timeliness. Furthermore, prior forecast accuracy is positively associated to the forecast informativeness of both leaders and followers, being more important for the former. Our findings are important for investors and other market participants, because they can use the EAD Leader classification to identify superior analysts and, consequently, more informative and accurate forecasts.
SSRN
In this paper we show that the MSCI ACWI Metals and Mining Index has the ability to predict base metal prices. We use both in-sample and out-of-sample exercises to conduct such examination. The theoretical underpinning of these results relies on the present-value model for stock-price determination. This model has the implication of Granger causality from stock prices to their key determinants. In the case of metal and mining producers, one of the key elements determining the value of these firms is the price of the commodity they produce and export. Our results are consistent with this theoretical framework, as forecasts based on a model including the MSCI index outperform, in terms of Mean Squared Prediction Error, forecasts that do not use the information contained in that index.
arXiv
We study the effects of stochastic resetting on geometric Brownian motion (GBM), a canonical stochastic multiplicative process for non-stationary and non-ergodic dynamics. Resetting is a sudden interruption of a process, which consecutively renews its dynamics. We show that, although resetting renders GBM stationary, the resulting process remains non-ergodic. Quite surprisingly, the effect of resetting is pivotal in manifesting the non-ergodic behavior. In particular, we observe three different long-time regimes: a quenched state, an unstable and a stable annealed state depending on the resetting strength. Notably, in the last regime, the system is self-averaging and thus the sample average will always mimic ergodic behavior establishing a stand alone feature for GBM under resetting. Crucially, the above-mentioned regimes are well separated by a self-averaging time period which can be minimized by an optimal resetting rate. Our results can be useful to interpret data emanating from stock market collapse or reconstitution of investment portfolios.
SSRN
This monograph reviews the academic literature on market outcomes, reporting practices and the political economy behind the global use of International Financial Reporting Standards (IFRS). We start with a conceptual discussion of expected benefits and costs of an international harmonization of accounting regulation and explain why predictions on possible outcomes are ambiguous. Our first main section discusses the characteristics of an âidealâ IFRS experiment that would allow to draw causal inferences on the effects of IFRS adoption. We offer a comprehensive overview of research on the impact of IFRS on capital markets, particularly around firsttime adoption and during the global financial crisis. In our second main section, we describe current IFRS reporting practices, including digital reporting (XBRL), and benchmark the availability, accessibility, and processing of IFRS financial information against the information environment in the United States. We complement this discussion by evidence on the use of IFRS reporting choices such as the different fair value options. The third main section provides information about important institutional features of IFRS standard setting and how political powers affect decisions on IFRS adoption, standard setting, and enforcement. The monograph concludes with an assessment of the impact of IFRS research and outlines emerging trends that provide opportunities for future research. Overall, this monograph offers a summary of research findings and methods that are relevant for the analysis of future regulatory innovations, such as the international standardization of sustainability (or ESG) reporting.
arXiv
This exercise offers an innovative learning mechanism to model economic agent's decision making process using a deep reinforcement learning algorithm. In particular, this AI agent has limited or no information on the underlying economic structure and its own preference. I model how the AI agent learns in terms of how it collects and processes information. It is able to learn in real time through constantly interacting with the environment and adjusting its actions accordingly. I illustrate that the economic agent under deep reinforcement learning is adaptive to changes in a given environment in real time. AI agents differ in their ways of collecting and processing information, and this leads to different learning behaviours and welfare distinctions. The chosen economic structure can be generalised to other decision making processes and economic models.
arXiv
We design multi-horizon forecasting models for limit order book (LOB) data by using deep learning techniques. Unlike standard structures where a single prediction is made, we adopt encoder-decoder models with sequence-to-sequence and Attention mechanisms, to generate a forecasting path. Our methods achieve comparable performance to state-of-art algorithms at short prediction horizons. Importantly, they outperform when generating predictions over long horizons by leveraging the multi-horizon setup. Given that encoder-decoder models rely on recurrent neural layers, they generally suffer from a slow training process. To remedy this, we experiment with utilising novel hardware, so-called Intelligent Processing Units (IPUs) produced by Graphcore. IPUs are specifically designed for machine intelligence workload with the aim to speed up the computation process. We show that in our setup this leads to significantly faster training times when compared to training models with GPUs.
arXiv
Transition probability densities are fundamental to option pricing. Advancing recent work in deep learning, we develop novel transition density function generators through solving backward Kolmogorov equations in parametric space for cumulative probability functions, using neural networks to obtain accurate approximations of transition probability densities, creating ultra-fast transition density function generators offline that can be trained for any underlying. These are 'single solve' , so they do not require recalculation when parameters are changed (e.g. recalibration of volatility) and are portable to other option pricing setups as well as to less powerful computers, where they can be accessed as quickly as closed-form solutions. We demonstrate the range of application for one-dimensional cases, exemplified by the Black-Scholes-Merton model, two-dimensional cases, exemplified by the Heston process, and finally for a modified Heston model with time-dependent parameters that has no closed-form solution.
arXiv
Pravuil is a robust, secure, and scalable consensus protocol for a permissionless blockchain suitable for deployment in an adversarial environment such as the Internet. Pravuil circumvents previous shortcomings of other blockchains:
- Bitcoin's limited adoption problem: as transaction demand grows, payment confirmation times grow much lower than other PoW blockchains
- higher transaction security at a lower cost
- more decentralisation than other permissionless blockchains
- impossibility of full decentralisation and the blockchain scalability trilemma: decentralisation, scalability, and security can be achieved simultaneously
- Sybil-resistance for free implementing the social optimum
- Pravuil goes beyond the economic limits of Bitcoin or other PoW/PoS blockchains, leading to a more valuable and stable crypto-currency
SSRN
This paper investigates how banks and finance companies operate in business groups. Using uniquely detailed ownership data from Thailand, we find that the controlling share- holders extensively use pyramids to control banks and finance companies and assign different lending strategies across pyramidal tiers. Lower-tier banks tend to extend loans more aggressively and perform more poorly, while upper tier banks carry out more profitable investments. After the crisis hit, upper-tier banks survived and almost all lower-tier banks went bankrupt. Our results suggest that the multilayer organisational structure of bank ownership can affect a bankâs lending behavior and its resistance to economic shocks.
arXiv
In order to study the phenomenon of regional economic development and urban expansion from the perspective of night-light remote sensing images, researchers use NOAA-provided night-light remote sensing image data (data from 1992 to 2013) along with ArcGIS software to process image information, obtain the basic pixel information data of specific areas of the image, and analyze these data from the space-time domain for presentation of the trend of regional economic development in China in recent years, and tries to explore the urbanization effect brought by the rapid development of China's economy. Through the analysis and study of the data, the results show that the urbanization development speed in China is still at its peak, and has great development potential and space. But at the same time, people also need to pay attention to the imbalance of regional development.
arXiv
Using Forbes 400 data together with historical data on tax rates and macroeconomic indicators, we study the relationship between the maximum marginal income tax rate and wealth inequality. We find through a novel tail regression model that a higher maximum tax rate is associated with a higher wealth Pareto exponent. Setting the maximum rate to 0.30-0.40 (as in U.S. currently) leads to an exponent of 1.5-1.8, while counterfactually setting it to 0.8 (as suggested by Piketty, 2014) would lead to an exponent of 2.6. We present a simple economic model that explains these findings and discuss the welfare implications of taxation.
SSRN
This paper provides an overview of rules for taxation and dividend distributions for EU and UK listed entities in EU regulated markets. Empirical research on IFRS application typically considers IFRS as informative about future cash flows. However, taxes and distributable dividends are based on national rules different from IFRS in all EU countries prior to Brexit. To analyze these differences, researchers need to know about 1) how taxable and distributable income are determined in different EU countries mandating IFRS for most listed firms; 2) the differences between IFRS and the national rules on taxable and distributable income. Regarding Question 1), we analyze and classify the EU countriesâ regulations about tax and income distributions and whether and how the are legally linked to IFRS. To address Question 2), we develop an ordinal measure of the de jure differences between IFRS income and taxable income on the one hand and IFRS income and distributable income on the other. Our study contributes to empirical research on the informativeness of IFRS by providing measures of book-tax and book-dividend conformity within the EU and the UK. By comparing the national rules to IFRS, we enhance the understanding of the relevance of IFRS reporting.
SSRN
The ability of oil investment vehicles to perfectly track spot oil has always been challenging, however recently many vehicles have underperformed spot oil. We study the behavior of oil futures and exchange-traded products that invest in oil futures to document and understand the source of this tracking error. The primary reason that oil investment vehicles have underperformed spot oil is due to an increase in contango in oil futures markets that we find might be related to investment crowding and the financialization of commodity markets. We show that from 2006 to 2017 oil futures investing underperformed spot oil and the market was in contango most of the time. Proxies for crowding, such as the concentration of major oil investors and changes in assets under management and fund flows of major oil exchange-traded products are associated with contango in the futures markets and the divergence between futures and spot returns. We also provide evidence of an impact of the financialization on oil futures prices.
SSRN
We examine the extent to which deferred vesting of stock and option grants (deferred pay) helps firms retain executives. To the extent an executive forfeits all deferred pay if they leave the firm, deferred vesting will increase the cost (to the executive) of an early exit. The impact of deferred pay on executive retention, a key ingredient for firms to create shareholder value, is hence an important empirical issue. Using pay duration proposed in Gopalan et al. (2014) as a measure of the extent of deferred equity, we find that CEOs and non-CEO executives with longer pay duration are less likely to leave the firm voluntarily. The talent retention role of deferred pay is mitigated by performance-vesting provisions and signing bonuses offered by industry peers. Moreover, we also find that voluntary turnover is less sensitive to pay duration for executives who are perceived to be more talented and have more firm-specific skills. Overall, our study highlights a strong link between compensation design and turnover of top executives. It suggests that firms take into account the need for retaining managerial talent in designing executive compensation.
arXiv
Telecom industry is significantly evolving all over the globe than ever. Mobile users number is increasing remarkably. Telecom operators are investing to get more users connected and to improve user experience, however, they are facing various challenges. Decrease of main revenue streams of voice calls, SMS (Short Message Service) and LDC (Long distance calls) with a significant increase in data traffic. In contrary, with free cost, OTT (Over the top) providers such as WhatsApp and Facebook communication services rendered over networks that built and owned by MNOs. Recently, OTT services gradually substituting the traditional MNOs` services and became ubiquitous with the help of the underlying data services provided by MNOs. The OTTs` services massive penetration into telecom industry is driving the MNOs to reconsider their strategies and revenue sources.
arXiv
The purpose of this study is to examine the impact of board member composition and board members' social media presence on the performance of startups. Using multiple sources, we compile a unique dataset of about 500 US-based technology startups. We find that startups with more venture capitalists on the board and whose board members are active on Twitter attract additional funding over the years, though they do not generate additional sales. By contrast, startups which have no venture capitalists on the board and whose board members are not on Twitter show an increased ability to translate assets into sales. Consistent with other research, our results indicate that startups potentially benefit from working with VCs because of the opportunity to access additional funding, although their presence does not necessarily translate into sales growth and operational efficiency. We use a number of control variables, including board gender representation and board members' position in the interlocking directorates' network.
SSRN
Using alternative measures of return correlations, we show that neither industry nor country correlations exhibit an ever-increasing trend. Instead, correlations jump during recessions with a tendency to revert in stable periods. This keeps international diversification still important despite the financial integration that might have increased correlations permanently. Moreover, the mean of industry correlations is statistically lower than that of country correlations, suggesting that cross-industry diversification is more efficient. Finally, diversifying through industries of emerging markets rather than those of developed markets reduces mean correlations more. These results are robust to several correlation definitions.
arXiv
In this paper, we study the behavior of information ratio (IR) as determined by the fundamental law of active investment management. We extend the classic relationship between IR and its two determinants (i.e., information coefficient and investment "breadth") by explicitly and simultaneously taking into account the volatility of IC and the cost from portfolio turnover. Through mathematical derivations and simulations, we show that - for both mean-variance and quintile portfolios - a turnover-adjusted IR is always lower than an IR that ignores the cost from turnover; more importantly, we find that, contrary to the implication from the fundamental low but consistent with available empirical evidence, investment managers may improve their investment performance or IR by limiting/optimizing trade or portfolio turnover.
SSRN
We document evidence that mutual funds designated as âSustainable Investment Overallâ by Morningstar (which we classify as ESG mutual funds) are no more likely than other mutual funds to support shareholder proposals. We find, however, that ESG mutual funds are more likely than non-ESG mutual funds to support environmental and social (ES) shareholder proposals. We also find that ESG mutual fund support for ES proposals is more pronounced in ESG index funds than in ESG active funds and in the ESG funds of small rather than large fund families. These results imply that mutual fund investment constraints and access to investor demand may shape how ESG mutual funds influence portfolio firmsâ environmental and social action choices.