Research articles for the 2019-07-15
arXiv
Presidential debates are thought to provide an important public good by revealing information on candidates to voters. However, this may not always be the case. We consider an endogenous model of presidential debates in which an incumbent and a contender (who is privately informed about her own quality) publicly announce whether they are willing to participate in a public debate, after taking into account that a voter's choice of candidate depends on her beliefs regarding the candidates' qualities and on the state of nature. Surprisingly, it is found that in equilibrium a debate occurs or does not occur independently of the contender's quality or the sequence of the candidates' announcements to participate and therefore the announcements are uninformative.
arXiv
We develop an agent-based simulation of the catastrophe insurance and reinsurance industry and use it to study the problem of risk model homogeneity. The model simulates the balance sheets of insurance firms, who collect premiums from clients in return for ensuring them against intermittent, heavy-tailed risks. Firms manage their capital and pay dividends to their investors, and use either reinsurance contracts or cat bonds to hedge their tail risk. The model generates plausible time series of profits and losses and recovers stylized facts, such as the insurance cycle and the emergence of asymmetric, long tailed firm size distributions. We use the model to investigate the problem of risk model homogeneity. Under Solvency II, insurance companies are required to use only certified risk models. This has led to a situation in which only a few firms provide risk models, creating a systemic fragility to the errors in these models. We demonstrate that using too few models increases the risk of nonpayment and default while lowering profits for the industry as a whole. The presence of the reinsurance industry ameliorates the problem but does not remove it. Our results suggest that it would be valuable for regulators to incentivize model diversity. The framework we develop here provides a first step toward a simulation model of the insurance industry for testing policies and strategies for better capital management.
SSRN
This paper examines the relationship between managerial ownership and cash holdings of non-financial firms in Thailand over the period 2011 to 2015. The results indicate that higher managerial ownership is associated with lower cash holdings, suggesting that managers of Thai firms do not hoard cash for taking private benefits. The findings therefore lend support to the incentive-alignment hypothesis. In addition, the evidence indicates that board size has a negative impact on cash holdings while board independence does not play a significant role. Further, it is found that profitability, firm size, growth opportunities and cash flow have positive effects on cash holdings whereas leverage has a nonlinear impact on cash reserves.
SSRN
Crowdfunding has the potential to democratize access to financing, especially among women entrepreneurs. This paper examines whether social media activity provides an advantage for women entrepreneurs in raising funding from crowds. The results of our study, based on tracking the daily fundraising and social media activity for a sample of 11409 campaigns launched in Kickstarter, show that by diffusing electronic word-of-mouth information and signaling popularity, social media is beneficial in high search-cost situations such as crowdfunding efforts for all entrepreneurs, even more so for women entrepreneurs. Our theoretical discussions implicitly attribute this finding to the role of social media in altering investorsâ perceptions about legitimacy of women entrepreneurs, which views entrepreneurship as a masculine-typed endeavor that women are incapable of successfully undertaking. The broader implications of this research are to address the influence of social media in helping mobilize resources for entrepreneurs, especially those imbued with greater initially-perceived legitimacy concerns.
SSRN
An extensive list of risks relative to big data frameworks and their use through models of artificial intelligence is provided along with measurements and implementable solutions. Bias, interpretability and ethics are studied in depth, with several interpretations from the point of view of developers, companies and regulators. Reflexions suggest that fragmented frameworks increase the risks of models misspecification, opacity and bias in the result. Domain experts and statisticians need to be involved in the whole process as the business objective must drive each decision from the data extraction step to the final activatable prediction. We propose an holistic and original approach to take into account the risks encountered all along the implementation of systems using artificial intelligence from the choice of the data and the selection of the algorithm, to the decision making.
arXiv
Many existing jobs are prone to automation, but since new technologies also create new jobs it is crucial to understand job transitions. Based on empirical data we construct an occupational mobility network where nodes are occupations and edges represent the likelihood of job transitions. To study the effects of automation we develop a labour market model. At the macro level our model reproduces the Beveridge curve. At the micro level we analyze occupation-specific unemployment in response to an automation-related reallocation of labour demand. The network structure plays an important role: workers in occupations with a similar automation level often face different outcomes, both in the short term and in the long term, due to the fact that some occupations offer little opportunity for transition. Our work underscores the importance of directing retraining schemes towards workers in occupations with limited transition possibilities.
SSRN
Blockchain, as a decentralised ledger technology with characteristics of transparent, secure, permanent and immutable, has been applied in many fields such as cryptocurrency, equity financing and corporate governance. However, the blockchain technology is in the experimental stage and has several problems to be solved including limited data processing capacity, information confidentiality and regulatory difficulties. This study sheds light on the potential application of blockchain technology in financial accounting and its possible impacts. We argue that in the short run the public blockchain could be used as a platform for firms to voluntarily disclose information. In the long run, the application could effectively reduce errors in disclosure and earnings management, increase the quality of accounting information and mitigate information asymmetry. We also discuss potential impacts that the application will have on independent auditors and financial accountants.
arXiv
Data providers such as government statistical agencies perform a balancing act: maximising information published to inform decision-making and research, while simultaneously protecting privacy. The emergence of identified administrative datasets with the potential for sharing (and thus linking) offers huge potential benefits but significant additional risks. This article introduces the principles and methods of linking data across different sources and points in time, focusing on potential areas of risk. We then consider confidentiality risk, focusing in particular on the "intruder" problem central to the area, and looking at both risks from data producer outputs and from the release of micro-data for further analysis. Finally, we briefly consider potential solutions to micro-data release, both the statistical solutions considered in other contributed articles and non-statistical solutions.
SSRN
This study aims to test and analyse the determinants of internal stock returns with annual data observation used from 2014â"2015. Following are the types of quantitative research employed in this study. The population of 41 companies with their capitalisation is listed on the Indonesia Stock Exchange (IDX), and their capitalisations report have been consistent for two years. The non-probability sampling technique is purposive sampling. A data analysis using a regression regarding the fixed-panel effect has an R-squared value of 71.6% compared with other models. The results showed that the return on assets, return on equity, debt-to-equity ratio, firm size and growth simultaneously and significantly influence stock returns. Partially, all independent variables have a positive and significant effect on stock returns. Hence, it is advisable to add external factor variables, using sample companies within other industries.
SSRN
This paper examines the impact of business diversification of banks on their risk, with efficiency taken into consideration as a conduit. Using bank-level data from more than 1000 commercial banks in 39 emerging economies during the period of 2000-2016, we find that increased business diversification exerts two competing effects on bank risk. The direct effect of increased diversification bolsters the stability of banks, but it is offset by the indirect effect whereby lowered efficiency, which is resulted from higher diversification, increases the riskiness of banks. In addition, we also find some evidence that the diversification-risk nexus is heterogeneous on the size, market power and ownership of banks.
SSRN
We introduce the concept of fraud morality, validate such conceptualization by prior studies in economics and criminology as well as by our own independent tests, and explore the relationship of fraud morality with numerous cultural attributes using data from the World Values Survey. Applying partial least squares path modeling, we find that people with stronger self-enhancing (self-transcending) values exhibit lower (higher) fraud morality. Further, respondents who believe in the importance of hard work exhibit higher fraud morality, and such beliefs mediate the relationship between locus of control and fraud morality. Finally, we find that people prone to traditional gender stereotypes demonstrate lower fraud morality and document subtle differences in the influence of these cultural attributes across age and gender groups. Our study contributes to research on the fraud triangle, accounting ethics, and corporate governance.
SSRN
We examine the influence of financial literacy and perceptions of financial knowledge on households' financial risk-taking. Greater literacy and self-belief in one's literacy positively relate to equity ownership. However, self-awareness of illiteracy reduces participation by about 5%. We find that financial self-awareness is impacted by innate traits and environmental elements. Specifically, it is reduced by risk-seeking preferences and rising income but increases with income uncertainty.
SSRN
We adapt simple tools from computational linguistics to construct a new measure of political risk faced by individual US firms: the share of their quarterly earnings conference calls that they devote to political risks. We validate our measure by showing it correctly identifies calls containing extensive conversations on risks that are political in nature, that it varies intuitively over time and across sectors, and that it correlates with the firmâs actions and stock market volatility in a manner that is highly indicative of political risk. Firms exposed to political risk retrench hiring and investment and actively lobby and donate to politicians. These results continue to hold after controlling for news about the mean (as opposed to the variance) of political shocks. Interestingly, the vast majority of the variation in our measure is at the firm level rather than at the aggregate or sector level, in the sense that it is neither captured by the interaction of sector and time fixed effects, nor by heterogeneous exposure of individual firms to aggregate political risk. The dispersion of this firm-level political risk increases significantly at times with high aggregate political risk. Decomposing our measure of political risk by topic, we find that firms that devote more time to discussing risks associated with a given political topic tend to increase lobbying on that topic, but not on other topics, in the following quarter.
arXiv
Using microscopic price models based on Hawkes processes, it has been shown that under some no-arbitrage condition, the high degree of endogeneity of markets together with the phenomenon of metaorders splitting generate rough Heston-type volatility at the macroscopic scale. One additional important feature of financial dynamics, at the heart of several influential works in econophysics, is the so-called feedback or Zumbach effect. This essentially means that past trends in returns convey significant information on future volatility. A natural way to reproduce this property in microstructure modeling is to use quadratic versions of Hawkes processes. We show that after suitable rescaling, the long term limits of these processes are refined versions of rough Heston models where the volatility coefficient is enhanced compared to the square root characterizing Heston-type dynamics. Furthermore the Zumbach effect remains explicit in these limiting rough volatility models.
SSRN
We conduct a detailed analysis of investors in successful initial coin offerings (ICOs). The average ICO has 4,700 contributors. The median participant contributes small amounts and many investors sell their tokens before the underlying product is developed. Large presale investors obtain tokens at a discount and flip part of their allocation shortly after the ICO. ICO contributors lack the protections traditionally afforded to investors in early stage financing. Nevertheless, returns nine months after the ICO are positive on average, driven mostly by an increase in the value of the Ethereum cryptocurrency.
SSRN
We show that tax enforcement benefits US firms that borrow from banks. Using data on syndicated loans over the 1993-2017 period, we find that higher IRS audit probabilities exert a negative and significant effect on the cost of loans. The baseline estimates show that a one standard deviation increase in the IRS audit probability decreases the cost of bank credit by around 9 basis points (or $1.55 million interest for the average loan). In further analysis we find that the negative effect of IRS tax enforcement on the cost of syndicated loans is more evident when the presence of external monitors, other than the IRS, is weaker and for loans issued by lead banks that are less reputed and less experienced with borrowing firms and their sector or region. IRS tax enforcement decreases also the probability that loans will contain covenants. The results are robust to several tests that address endogeneity and other concerns. These findings indicate that banks perceive the IRS as a useful external monitoring mechanism that alleviates information asymmetry in the syndicated loan market. This study informs the public policy debate about the IRS by showing that it exerts a positive spillover to the US economy in the form of lower costs of corporate financing through the banking system.
SSRN
This study examines whether microfinance is an effective poverty-reduction intervention tool and the link between access to microfinance and poverty reduction in northern Ethiopia. The study tests the hypothesis that access to/ or participation in microfinance eradicates poverty reduction and /or improving the living standards of the poorest population are positively related. Key questions we attempted to answer in this study are: Is microfinance an effective anti-poverty program intervention tool to obliterate poverty? Do the living standards of microfinance clients improve and become less poor after they get the microfinance service/they borrow the money and have access to micro-credits? Whether microfinance stimulated the poor to develop enterprises and contributed significantly to alleviating poverty? In this study, we used propensity score matching to estimate the impact of microfinance unidimensional poverty indicators on approximately 400 Ethiopian households randomly selected from four tibias. Estimation results reveal that DECSI has a significant (at 1% level of significance) impact on school-age children expenditure on education materials in the radius and stratified matching methods. Likewise, MFIs have significant (at a 10% level of significance) impact on householdsâ productive and fixed assets (with and without the house) in the nearest neighbour matching method; household assets in the stratified and nearest neighbour matching methods at (10% and 5% level of significance). Equally important, we find MFIs to have a significant effect on household expenditure on food, non-food items and poverty severity in the stratified matching method at 5% level of significance. In conclusion, our view is that microfinance keeps borrowers from even greater catastrophes, but only rarely does it enable them to climb out of poverty? However, we should not consider micro-credit as a panacea to all multiple overlapping deprivation and poverty experienced by poor people. Even though microfinance helps the poor to tread water and just keeps them from drowning; However, we should not expect micro-credit alone to help get the poor out of poverty.
SSRN
This paper argues leasing is a risk-sharing mechanism: risk-tolerant lessors (capital owners) provide insurance to financially constrained risk-averse lessees (capital borrowers) against systematic capital price fluctuations. We provide strong empirical evidence to support this novel risk premium channel. Among financially constrained stocks, firms with a high leased capital ratio earn average returns 7.35% lower than firms with a low leased capital ratio, which we call it the negative leased capital premium. We develop a general equilibrium model with heterogeneous firms and financial frictions to quantify this channel. Our study also provides a caveat to the recent leasing accounting change of IFRS 16: lease induced liability and financial debt should not be treated equally on firms' balance sheet, as their implications for firms' equity risks and cost of equity are opposite.
arXiv
We study the \emph{multi-level order-flow imbalance (MLOFI)}, which measures the net flow of buy and sell orders at different price levels in a limit order book (LOB). Using a recent, high-quality data set for 6 liquid stocks on Nasdaq, we use Ridge regression to fit a simple, linear relationship between MLOFI and the contemporaneous change in mid-price. For all 6 stocks that we study, we find that the goodness-of-fit of the relationship improves with each additional price level that we include in the MLOFI vector. Our results underline how the complex order-flow activity deep into the LOB can influence the price-formation process.
arXiv
The pricing of Bermudan options amounts to solving a dynamic programming principle , in which the main difficulty, especially in large dimension, comes from the computation of the conditional expectation involved in the continuation value. These conditional expectations are classically computed by regression techniques on a finite dimensional vector space. In this work, we study neural networks approximation of conditional expectations. We prove the convergence of the well-known Longstaff and Schwartz algorithm when the standard least-square regression is replaced by a neural network approximation.
SSRN
Weld, Michaely, Thaler, and Benartzi (2009) find that the average nominal U.S. stock price has been approximately $25 since the Great Depression. They report that this ânominal price fixation is primarily a U.S. or North American phenomenon.â Using a larger data set from 38 countries, we show that this nominal price fixation is a global phenomenon. We exploit the introduction of the Euro in 1999 to show that stock splits maintain these nominal stock price anchors. Generally, firms in countries with larger drops in nominal prices had fewer stock splits after stock prices are displayed in Euros.
arXiv
As the rental housing market moves online, the Internet offers divergent possible futures: either the promise of more-equal access to information for previously marginalized homeseekers, or a reproduction of longstanding information inequalities. Biases in online listings' representativeness could impact different communities' access to housing search information, reinforcing traditional information segregation patterns through a digital divide. They could also circumscribe housing practitioners' and researchers' ability to draw broad market insights from listings to understand rental supply and affordability. This study examines millions of Craigslist rental listings across the US and finds that they spatially concentrate and over-represent whiter, wealthier, and better-educated communities. Other significant demographic differences exist in age, language, college enrollment, rent, poverty rate, and household size. Most cities' online housing markets are digitally segregated by race and class, and we discuss various implications for residential mobility, community legibility, gentrification, displacement, housing voucher utilization, and automated monitoring and analytics in the smart cities paradigm. While Craigslist contains valuable crowdsourced data to better understand affordability and available rental supply in real-time, it does not evenly represent all market segments. The Internet promises information democratization, and online listings can reduce housing search costs and increase choice sets. However, technology access/preferences and information channel segregation can concentrate such information-broadcasting benefits in already-advantaged communities, reproducing traditional inequalities and reinforcing residential sorting and segregation dynamics. Technology platforms construct new institutions with the power to shape spatial economies and human interactions.
arXiv
This paper considers the problem of optimal liquidation of a position in a risky security in a financial market, where price evolution are risky and trades have an impact on price as well as uncertainty in the filling orders. The problem is formulated as a continuous time stochastic optimal control problem aiming at maximizing a generalized risk-adjusted profit and loss function. The expression of the risk adjustment is derived from the general theory of dynamic risk measures and is selected in the class of $g$-conditional risk measures. The resulting theoretical framework is nonclassical since the target function depends on backward components. We show that, under a quadratic specification of the driver of a backward stochastic differential equation, it is possible to find a closed form solution and an explicit expression of the optimal liquidation policies. In this way it is immediate to quantify the impact of risk-adjustment on the profit and loss and on the expression of the optimal liquidation policies.
arXiv
Oscillations in the complementary cumulative distribution function (CCDF) of individual income data have been found in the data of various countries studied by different authors at different time periods, but the dynamical origins of this behavior are currently unknown. Although these datasets can be fitted by different functions at different income ranges, the Tsallis distribution has recently been found capable of fitting the whole distribution by means of only two parameters. This procedure showed clearly such oscillatory feature in the entire income range feature, but made it particularly visible at the tail of the distribution. Although log-periodic functions fitted to the data are capable of describing this behavior, a different approach to naturally disclose such oscillatory characteristics is to allow the Tsallis $q$-parameter to become complex. In this paper we use this idea in order to describe the behavior of the CCDF of the Brazilian personal income recently studied empirically by Soares et al.\ (2016). Typical elements of periodic motion, such as amplitude and angular frequency coupled to this income analysis, were obtained by means of this approach. A highly non-linear function for the CCDF was obtained through this methodology and a numerical test showed it capable of recovering the main oscillatory feature of the original CCDF of the personal income data of Brazil.
arXiv
We generalize Quasi-Linear Means by restricting to the tail of the risk distribution and show that this can be a useful quantity in risk management since it comprises in its general form the Value at Risk, the Tail Value at Risk and the Entropic Risk Measure in a unified way. We then investigate the fundamental properties of the proposed measure and show its unique features and implications in the risk measurement process. Furthermore, we derive formulas for truncated elliptical models of losses and provide formulas for selected members of such models.
SSRN
This paper refines the approximate factor model of asset returns by dividing systematic factors into a) natural rate factors, whose sum of squared factor betas grow at the same rate as the number of assets, and b) semi-strong factors, whose sum of squared factor betas grow, but at a slower rate. We describe a methodology to estimate the cross-sectional mean and mean-square of semi-strong factor betas, and to differentiate them from natural rate factors. We apply the methodology to US equity returns using daily changes in exchange rates and commodity prices as semi-strong factors. We find that oil and gold price changes are significant factors while foreign exchange rate changes are only significant in more recent subperiods.
SSRN
One of main consequences of the Global Financial Crisis is stricter banking regulation. In fact, the black and white of the regulators' output misleads people to believe that there will be no more bailouts in the future. But history teaches us that this statement should not be taken too seriously. Therefore we may speak of 'spurious regulation'. To judge upon the degree to which implicit guarantees are pre-supposed by the credit and capital markets we investigate empirically whether there is a link between the creditworthiness of a country and the prospects of an investment in a bank's equity. Specifically, we check whether there is a significant impact of sovereign CDS spreads on stock returns using panel econometrics within a CAPM-type context. The findings are model-dependent: Using SUR we find eight cases, whereas using DCC we get only four. Hence, there might be some work to do for the regulators. Hence, using only SUR can be misleading.
SSRN
The paper proposes a framework for assessing the impact of system-wide and bank-level capital buffers. The assessment rests on a factor-augmented vector autoregression (FAVAR) model that relates individual bank adjustments to macroeconomic dynamics. We estimate FAVAR models individually for eleven euro area economies and identify structural shocks, which allow us to diagnose key vulnerabilities of national banking systems and estimate short-run economic costs of increasing banksâ capitalisation. On this basis, we run a fullyfledged cost-benefit assessment of an increase in capital buffers. The benefits are related to an increase in bank resilience to adverse shocks. Higher capitalisation allows banks to withstand negative shocks and moderates the reduction of credit to the real economy that ensues in adverse circumstances. The costs relate to transitory credit and output losses that are assessed both on an aggregate and bank level. An increase in capital ratios is shown to have a sharply different impact on credit and economic activity depending on the way banks adjust, i.e. via changes in assets or equity.
SSRN
An increasing share of firms' borrowing occurs through bond markets. We present high-frequency evidence from the Eurozone that bond-reliant firms are more responsive to monetary shocks: in contrast to standard bank lending channel predictions, unexpected ECB policy changes affect their stock prices by more, even conditional on total debt and industry fixed-effects. We develop an organizing framework to decompose the stock price, credit risk and investment response of large firms. We emphasize the role of corporate liquidity management: firms react to rate hikes by being prudent in good times, reducing investment in favor of hoarding liquid assets. Since bond financing is less flexible in bad times than relationship banking, this effect can rationalize why the mix of bank and bond financing matters for monetary transmission. A mitigating force is that bonds generally have longer duration and lower interest-rate pass-through relative to loans. Our findings suggest that the recent global growth in bond debt following quantitative easing could interact with conventional interest rate policy going forward.
SSRN
I develop a dynamic structural model to study the quantitative impact of the Dodd-Frank Act on small banks' operation costs. Banks in my model face a minimum capital requirement which constitutes a capacity constraint on lending for any given capital level. This constraint may be relaxed by raising capital financed by internal funds. Loosening the capacity constraint enables a bank to lend more and increase profits due to economies of scale associated with fixed costs. Exploiting the timing of Dodd-Frank's implementation in 2010, I structurally estimate its impact on all non-interest costs small U.S banks face, including entry costs that are not observable in data. I find that Dodd-Frank has heightened entry costs and compliance costs by 18% and 15% respectively. These increases induce a strong selection effect on small banks: less profitable banks exit in the short run while those who survive become 45% more profitable in the long run. As a result, small bank loan market concentration rises and total small bank lending drops by 13%.
SSRN
We investigate the impacts of the short-termism on multiple equilibria in a dynamic rational expectations equilibrium model. We find that short-termism is not the cause of equilibrium multiplicity but affects market quality of all equilibria. The liquidity, price efficiency and expected trading volume in high trading intensity equilibrium (HTIE) are higher than those in low trading intensity equilibrium (LTIE) no matter how myopic the informed traders are. As investorsâ myopia degree increases, this difference between HTIE and LTIE becomes larger. The LTIE is always stable but the speed of convergence to new equilibrium is negatively related to the myopia degree of traders when an unexpected shock moves the price away from equilibrium. The opposite happens in HTIE.
SSRN
There is no consensus in the literature regarding the financial consequences of megamergers in part due to the difficulty in establishing a good counterfactual. By comparing the performance of these deals to the performance of synthetic mergers constructed using a novel matching procedure, we find no significant changes in return on assets after megamergers. This apparent non-result is driven by merged firms subsidizing their increased operating inefficiencies with higher markups. We show that this cross-subsidization effect is stronger in larger deals and in more concentrated industries, suggesting that our findings are driven by market power and quiet life considerations.
arXiv
We develop an extended multifractal analysis based on the Legendre-Fenchel transform (sometimes referred to as Legendre multi-branched one) rather than the routinely used canonical Legendre transform. In our variant of coarse-graining pre-processing, the local detrending of time series has been replaced by an appropriate averaging over days combined with properly-suited detrending on a daily time scale. This new approach is devoid of troublesome artifacts in the form of innumerable faults of these local trends that can deform the hierarchy of fluctuations and hence the final multifractality. Notably, our analysis is sensitive to the change of time scale as it should be. This analysis has developed, e.g., for empirical time series of inter-event or waiting times, which are an essential element of the popular continuous-time random walk formalism. The core of this extended multifractal analysis is the non-monotonic behavior of the generalized Hurst exponent -- the fundamental exponent of the study -- and hence a multi-branched spectrum of dimensions, which for our case is additionally of the left-sided one. We examine the main thermodynamic consequences of the existence of this type of multifractality. They can be expressed directly in the language of thermally stable, metastable, and unstable phases, and phase transitions between them as well. These phase transitions are of the first and second orders according to the modified Ehrenfest classification, sometimes called the Mandelbrot one.