Research articles for the 2021-07-07
arXiv
We use the aggregate information from individual-to-firm and firm-to-firm in Garanti BBVA Bank transactions to mimic domestic private demand. Particularly, we replicate the quarterly national accounts aggregate consumption and investment (gross fixed capital formation) and its bigger components (Machinery and Equipment and Construction) in real time for the case of Turkey. In order to validate the usefulness of the information derived from these indicators we test the nowcasting ability of both indicators to nowcast the Turkish GDP using different nowcasting models. The results are successful and confirm the usefulness of Consumption and Investment Banking transactions for nowcasting purposes. The value of the Big data information is more relevant at the beginning of the nowcasting process, when the traditional hard data information is scarce. This makes this information specially relevant for those countries where statistical release lags are longer like the Emerging Markets.
arXiv
How crypto flows among Bitcoin users is an important question for understanding the structure and dynamics of the cryptoasset at a global scale. We compiled all the blockchain data of Bitcoin from its genesis to the year 2020, identified users from anonymous addresses of wallets, and constructed monthly snapshots of networks by focusing on regular users as big players. We apply the methods of bow-tie structure and Hodge decomposition in order to locate the users in the upstream, downstream, and core of the entire crypto flow. Additionally, we reveal principal components hidden in the flow by using non-negative matrix factorization, which we interpret as a probabilistic model. We show that the model is equivalent to a probabilistic latent semantic analysis in natural language processing, enabling us to estimate the number of such hidden components. Moreover, we find that the bow-tie structure and the principal components are quite stable among those big players. This study can be a solid basis on which one can further investigate the temporal change of crypto flow, entry and exit of big players, and so forth.
SSRN
Few blockchain centric projects have gone beyond their white paper or proofs-of-concept. While many have fallen below expectations and failed to address the fundamental issues of scalability, privacy, and trust distribution, there are a few “imperfect†projects that are making an impact on society. We describe the lessons learned from three projects and highlight their “improvisions†in achieving their vision of serving the underserved, and identify areas of possible improvements. Our research has shown that mass adoption of blockchain technology will accelerate in financial industry and supply chain with private permissioned blockchains, but these e-inclusion projects using “Inclusive†Blockchain will take a longer time with OnChain/OffChain complexities. A long-term view is needed to build a Noah’s Ark as the rush to build the Tower of Babel to harness short term gain may not bring net benefits to the economy and society.
SSRN
What is now called the judgment-based approach to entrepreneurship (JBA) has a rich pedigree in Austrian economics and continues to grow rapidly in that tradition as well as in various research fields in business and management. The JBA has also attracted some criticisms. Frédéric Sautet’s recent review essay is an example. Sautet’s main concern is that the JBA rejects Israel Kirzner’s alertness/discovery approach which, in Sautet’s view, provides a more compelling basis for theorizing. Unfortunately, we do not find Sautet’s criticisms of the JBA convincing. They frequently ignore our arguments about entrepreneurial judgment and its manifestation in the business firm, fail to address our criticisms of the alertness/discovery approach, and are rooted in a flawed understanding of the history of economic thought.
SSRN
The computation of Greeks is a fundamental task for risk managing of financial instruments. The standard approach to their numerical evaluation is via finite differences. Most exotic derivatives are priced via Monte Carlo simulation: in these cases, it is hard to find a fast and accurate approximation of Greeks, mainly because of the need of a tradeoff between bias and variance. Recent improvements in Greeks computation, such as Adjoint Algorithmic Differentiation, are unfortunately uneffective on second order Greeks (such as Gamma), which are plagued by the most significant instabilities, so that a viable alternative to standard finite differences is still lacking. We apply Chebyshev interpolation techniques to the computation of spot Greeks, showing how to improve the stability of finite difference Greeks of arbitrary order, in a simple and general way. The increased performance of the proposed technique is analyzed for a number of real payoffs commonly traded by financial institutions.
SSRN
We examine the effect of the common ownership relation between brokerage houses and the firms covered by their analysts (referred to as co-owned brokerage houses, co-owned firms, and connected analysts, respectively) on analyst forecast performance. Common ownership can help the connected analysts to have better access to co-owned firms, leading to higher quality analyst research. However, common owners have incentives for higher valuation for the co-owned firms, and thus can exert pressure on the connected analysts to issue optimistically biased research reports for these firms. We find that common ownership improves analyst forecast accuracy. This result is robust to a difference-in-differences design that exploits exogenous shocks to common ownership. The effects vary systematically with the quality of alternative sources of information that analysts can access for the co-owned firms. Overall, our paper contributes to the literature by documenting that common ownership can facilitate information communication.
arXiv
We use a controlled laboratory experiment to study the causal impact of income decreases within a time period on redistribution decisions at the end of that period, in an environment where we keep fixed the sum of incomes over the period. First, we investigate the effect of a negative income trend (intra-personal decrease), which means a decreasing income compared to one's recent past. Second, we investigate the effect ofa negative income trend relative to the income trend of another person (inter-personal decrease). If intra-personal or inter-personal decreases create dissatisfaction for an individual, that person may become more selfish to obtain compensation. We formal-ize both effects in a multi-period model augmenting a standard model of inequality aversion. Overall, conditional on exhibiting sufficiently-strong social preferences, we find that individuals indeed behave more selfishly when they experience decreasing incomes. While many studies examine the effect of income inequality on redistribution decisions, we delve into the history behind one's income to isolate the effect of income changes.
arXiv
In this work we provide a simple setting that connects the structural modelling approach of Gai-Kapadia interbank networks with the mean-field approach to default contagion. To accomplish this we make two key contributions. First, we propose a dynamic default contagion model with endogenous early defaults for a finite set of banks, generalising the Gai-Kapadia framework. Second, we reformulate this system as a stochastic particle system leading to a limiting mean-field problem. We study the existence of these clearing systems and, for the mean-field problem, the continuity of the system response.
SSRN
Due to their long-term horizons, pension funds face enhanced exposures to the long-lived effects of many ESG risks. Moreover, given the potential consequences of being underfunded, pension funds are particularly exposed to ESG-related downside risks, especially those related to climate change. We discuss the implications of these risks and provide evidence on institutional investors’ perspectives on climate-related downside risks and how these risks are priced in financial markets. We also document how institutional investors address climate risks in the investment process, with a focus on the role of engagement versus divestment.
arXiv
The authors of the article have reviewed the scientific literature on the development of the Russian-Chinese cooperation in the field of combining economic and logistics projects of the Eurasian Economic Union and the Silk Road Economic Belt. The opinions of not only Russian, but also Chinese experts on these projects are indicated, which provides the expansion of the vision of the concept of the New Silk Road in both countries.
SSRN
We ask whether epidemic exposure leads to a shift in financial technology usage within and across countries and if so who participates in this shift. We exploit a dataset combining Gallup World Polls and Global Findex surveys for some 250,000 individuals in 140 countries, merging them with information on the incidence of epidemics and local 3G internet infrastructure. Epidemic exposure is associated with an increase in remote-access (online/mobile) banking and substitution from bank branch-based to ATM-based activity. Using a machine-learning algorithm, we show that heterogeneity in this response centers on the age, income and employment of respondents. Young, high-income earners in full-time employment have the greatest propensity to shift to online/mobile transactions in response to epidemics. These effects are larger for individuals in subnational regions with better ex ante 3G signal coverage, highlighting the role of the digital divide in adaption to new technologies necessitated by adverse external shocks.
arXiv
Global concern regarding ultrafine particles (UFPs), which are particulate matter (PM) with a diameter of less than 100nm, is increasing. These particles-with more serious health effects than PM less than 2.5 micrometers (PM2.5)-are difficult to measure using the current methods because their characteristics are different from those of other air pollutants. Therefore, a new monitoring system is required to obtain accurate UFPs information, which will raise the financial burden of the government and people. In this study, we estimated the economic value of UFPs information by evaluating the willingness-to-pay (WTP) for the UFPs monitoring and reporting system. We used the contingent valuation method (CVM) and the one-and-one-half-bounded dichotomous choice (OOHBDC) spike model. We analyzed how the respondents' socio-economic variables, as well as their cognition level of PM, affected their WTP. Therefore, we collected WTP data of 1,040 Korean respondents through an online survey. The estimated mean WTP for building a UFPs monitoring and reporting system is KRW 6,958.55-7,222.55 (USD 6.22-6.45) per household per year. We found that people satisfied with the current air pollutant information, and generally possessing relatively greater knowledge of UFPs, have higher WTP for a UFPs monitoring and reporting system. The results can be used to establish new policies response to PM including UFPs.
SSRN
We develop a unique dataset of 24 thousand U.S. finance patents granted over last two decades to explore the evolution and production of financial innovation. We use machine learning to identify the financial patents and extensively audit the results to ensure their reasonableness. We find that patented financial innovation is substantial and economically important, with the number of annual grants expanding from a few dozen in the 1990s to over 2000 in the 2010s. The subject matter of financial patents has changed, consistent with the industry’s shift in revenue and value-added towards household investors and borrowers. The surge in financial patenting was driven by information technology firms and others outside of financial sector, which collectively accounted for 69% of the awards. The location of innovation has shifted, with banks moving this activity from regions with tight financial regulation to more permissive ones. High-tech regions have attracted financial innovation by payments, IT, and other non-financial firms. Turning to the source of these ideas, while academic knowledge remained associated with more valuable patents, citations in finance patents to academic papers, especially in those by banks, fell sharply.
SSRN
Following the 2008 financial crisis, mortgage credit tightened and banks lost significant mortgage market share to nonbank lenders, including to fintech firms recently. Have fintech firms expanded credit access, or are their customers similar to those of traditional lenders? Unlike in small business and unsecured consumers lending, fintech mortgage lenders do not have the same incentives or flexibility to use alternative data for credit decisions because of stringent mortgage origination requirements. Fintech loans are broadly similar to those made by traditional lenders, despite innovations in the marketing and the application process. However, nonbanks market to consumers with weaker credit scores than do banks, and fintech lenders have greater market shares in areas with lower credit scores and higher mortgage denial rates.
SSRN
Using matched microdata for the UK, I estimate two distinct channels via which credit supply shocks affect mortgage debt: one that operates through price conditions in credit markets; and another that operates through non-price credit conditions and affects the quantity of credit supplied by lenders. I find substantial heterogeneity in the different channels by age, financial situation, borrower type and income. Young households and home-owners respond exclusively to non-price credit conditions, in particular to changes in the supply of riskier lending. First-time buyers, middle-income households and middle-aged borrowers increase debt following shocks to either type of credit conditions. Debt responses of financially constrained borrowers are amplified by a simultaneous loosening in mortgage spreads and in credit availability at high loan to value or high loan to income ratios. In aggregate, household leverage responds more strongly to supply shocks that change the quantity of credit, as they affect households across the distribution, both at the intensive and at the extensive margin. But a loosening in price and non-price credit conditions simultaneously or a contraction in multiple price indicators at a time can also fuel rapid credit growth.
SSRN
We show that mutual funds are more likely to hold and significantly overweight stocks of their broker banks. Correspondingly, funds’ proxy voting is biased towards management of their brokers in contentious proposals. Such voting bias has a material impact on voting outcomes. In return, client mutual funds with greater portfolio overweighting and voting support receive larger allocations of underpriced IPOs from connected broker banks. Our study not only uncovers a new mechanismâ€"being brokers’ friendly shareholdersâ€"through which the two parties maintain their quid pro quo relationships, it also raises a broader concern on shareholder monitoring of important financial institutions.
SSRN
Exploiting the staggered introductions and lifting of COVID-19 lockdowns across different regions in China, we study how lockdowns affect the investment decisions of venture capital (VC) investors. China provides a unique setting that allows us to examine VC investment decisions after the pandemic is under control and lockdowns are lifted. Contrary to the conventional wisdom that VCs tend to invest in local ventures during lockdowns, we find that they invest in remote ventures during lockdowns and such effects persist even after lockdowns are lifted. Such lockdown effects are stronger when there is better internet infrastructure, when the level of information asymmetry between VCs and entrepreneurs is lower, when VCs are more experienced, and when ventures are in the early stages of development. The lockdown effects can be explained by the advancement of remote communication technology as a response to the social distancing requirements. As VCs invest in remote ventures, the regional inequality of entrepreneurial access to VC financing has been reduced. Our findings uncover how VC investors adapt to the pandemic and such changes can have long-lasting effects in the post-pandemic era.
SSRN
I conduct an experiment with senior executives (CEOs, CFOs, controllers) to examine how their risk disclosure quality, with respect to disclosure volume and specificity, is influenced by three factors: first, whether the disclosure behavior is framed internally by the firm as obtaining a gain or avoiding a loss from disclosure; second, whether the external disclosure regime mandates risk mitigation disclosures that explain how a risk is handled; and third, whether the risk under consideration for disclosure is weakly or strongly mitigated. This research question is important because high-quality risk disclosures are challenging to regulate and changing how disclosure behavior is framed could substitute for costly disclosure regulations. I predict and find that a gain frame prompts managers to make more detailed risk disclosures than a loss frame, regardless of the disclosure regime. I also predict and find that a loss frame leads to less detailed and more boilerplate disclosure of weakly mitigated risks when risk mitigation plans are mandated. Given that the SEC (2016) is considering mandating risk mitigation disclosures similar to the practice in other regimes, my findings provide insights on the limitations of mandating these disclosures. My results suggest that changing managers’ disclosure frame internally through firm initiatives could be more effective in prompting higher quality risk disclosures.
SSRN
We explore whether financial access explains persistent gender and racial imbalance in entrepreneurship. The 1979 NLSY overlaps with bank deregulation events between 1971 and 2001, permitting a difference in differences analysis of the propensity for young people to attempt entrepreneurship. We find that the movement away from local finance supported new entry by African American men into entrepreneurship, but not by women of any race. We show that financial access is an important determinant of the propensity of young adults to become entrepreneurs and provide new evidence about a mechanism through which the demographic gap in entrepreneurship might be closed.
SSRN
We examine the price discovery process of initial public offerings (IPO) from the offer price to first day’s open price. Stock exchanges have made major changes to the IPO preopening process, and introduced an open auction process in which all investors are able to enter orders and participate in price discovery. The time spent in preopening has increased for IPOs over the years with an average of 77.23 minutes in 2020. The same pattern is not found for SPACs. The percentage of the day’s volume executed in the IPO Cross is much higher at 15.3% than the approximately 1% for non-IPO stocks. Each phase of preopening contributes to incremental price discovery with almost all of the price adjustment occurrs during preopening. However, for “cold†IPOs half of the price adjustment takes place after the market opens. Even though participation by retail investors has increased during preopening, their role in price discovery is limited. Our results suggest that institutional investors use the IPO Cross to sell shares. We also find that underwriters take advantage of changes implemented after the Facebook IPO that gave them a bigger role in deciding when to release an IPO for trading.
SSRN
We characterise the large number of mortgage offers for which people qualify. Almost no one picks the cheapest option, nonetheless the one selected is not usually much more expensive. A few borrowers make very expensive choices. These big mistakes are most common when the menu they face has many expensive options, and are most likely for high loan to value and loan to income borrowers. Young people and first-time buyers are more mistake-prone. The dispersion in the mortgage menu is consistent with banks attempting to price discriminate for some borrowers who might pick poorly while competing for others who might shop more effectively.
arXiv
This paper applies a deep reinforcement learning approach to revisit the hedging problem of variable annuities. Instead of assuming actuarial and financial dual-market model a priori, the reinforcement learning agent learns how to hedge by collecting anchor-hedging reward signals through interactions with the market. By the recently advanced proximal policy optimization, the pseudo-model-free reinforcement learning agent performs equally well as the correct Delta, while outperforms the misspecified Deltas. The reinforcement learning agent is also integrated with online learning to demonstrate its full adaptive capability to the market.
arXiv
The relationship between set-valued risk measures for processes and vectors on the optional filtration is investigated. The equivalence of risk measures for processes and vectors and the equivalence of their penalty function formulations are provided. In contrast with scalar risk measures, this equivalence requires an augmentation of the set-valued risk measures for processes. We utilize this result to deduce a new dual representation for risk measures for processes in the set-valued framework. Finally, the equivalence of multiportfolio time consistency between set-valued risk measures for processes and vectors are provided; to accomplish this, an augmented definition for multiportfolio time consistency of set-valued risk measures for processes is proposed.
SSRN
This paper studies how demand for labor reacts to financial technology (fintech) shocks based on comprehensive databases of fintech patents and firm job postings in the U.S. during the past decade. We first develop a measure of fintech exposure at the occupation level by intersecting the textual information in job task descriptions and fintech patents. We then document a significant decline of job postings in the most exposed occupations, and an increase in the industry as well as the geographical concentration of these occupations. Firms resort to an upskilling strategy in face of the fintech disruption, requiring "combo" (finance and software) skills, higher education attainments, and longer work experiences in the hiring of fintech-exposed jobs. Financial firms and those with high innovation outputs are able to offset the disruptive effect from the fintech shock. Among innovating firms, however, only inventors (but not acquisition-driven innovators) experience growth in hiring, sales, investment, and enjoy better returns on assets.
SSRN
FinTech is inducing changes in how financial services (FS) are perceived, developed, promoted, delivered and consumed. Future of FinTech, however, is rooted in deliberate integrated actions to improve framework conditions related to consumer trust, regulation and scalability. Building on limited scholarship, this paper identifies the building blocks for the future of FinTech and provides prescriptive areas of focus to guide research, policy and practice. In sum, the purpose of the paper is to serve as a catalyst and a call for an integrative approach in developing a common understanding and interpretation of FinTech as a socially-constructed phenomenon at the intersection of research and technology management.
SSRN
Bank-created money, shadow-bank money, and Treasury bonds all satisfy investor's demand for a liquid transaction medium and safe store of value. We measure the quantity of these three forms of liquidity and their corresponding liquidity premium over a sample from 1926 to 2016. We empirically examine the links between these different assets, estimating the extent to which they are substitutes, and the amount of liquidity per-unit-of-asset delivered by each asset. We construct a new broad monetary aggregate based on our analysis and show that it helps resolves the money-demand instability and missing-money puzzles of the monetary economics literature. Our empirical results inform models of the monetary transmission mechanism running through shifts in asset supplies, such as quantitative easing policies. Our results on the substitutability of bank and shadow-bank money also inform analyses of the coexistence of the shadow-banking and regulated banking system.
SSRN
Historically, foreign investment policies have been a fiercely contested issue for the international trade regime. The launch of discussions on investment facilitation under WTO auspices suggests greater willingness among some WTO members to discuss investment issues. The China-EU Comprehensive Agreement on Investment (CAI) provides a possible basis for negotiating investment policy disciplines in the WTO on a plurilateral basis. While the prospects for ratification of the CAI by the EU are uncertain, the CAI provides a baseline for possible investment rules in the WTO. Investment rules anchored both against the CAI outcomes and structured on a plurilateral basis are a logical part of a WTO resuscitation strategy.
SSRN
We analyze fintechs and their impact on the traditional financial system from a functional perspective. Following the approach suggested by Merton (1995) [A Functional Perspective of Financial Intermediation, Financial Management 24(2), 23â€"41], we show how the six core functions of financial intermediation are affected by the technological developments. This analysis provides a new perspective on the future of financial services and their regulation.
SSRN
The recent Financial Action Task Force (FATF) Recommendations define virtual assets and virtual asset service providers (VASPs), and require under the Travel Rule that originating VASPs obtain and hold the required and accurate originator information and the required beneficiary information on virtual asset transfers. In this paper, we discuss the notion of key ownership evidence as a core part of originator and beneficiary information required by the FATF Recommendations. We discuss the approaches to securely communicate the originator and beneficiary information between VASPs, and review the existing standards for public-key certificates as applied to VASPs and virtual asset transfers. We propose the notion of a trust network of VASPs in which originator and beneficiary information, including key ownership information, can be exchanged securely off-chain while observing the individual privacy requirements.
