Research articles for the 2019-06-20
arXiv
Competing firms can increase profits by setting prices collectively, imposing significant costs on consumers. Such groups of firms are known as cartels and because this behavior is illegal, their operations are secretive and difficult to detect. Cartels feel a significant internal obstacle: members feel short-run incentives to cheat. Here we present a network-based framework to detect potential cartels in bidding markets based on the idea that the chance a group of firms can overcome this obstacle and sustain cooperation depends on the patterns of its interactions. We create a network of firms based on their co-bidding behavior, detect interacting groups, and measure their cohesion and exclusivity, two group-level features of their collective behavior. Applied to a market for school milk, our method detects a known cartel and calculates that it has high cohesion and exclusivity. In a comprehensive set of nearly 150,000 public contracts awarded by the Republic of Georgia from 2011 to 2016, detected groups with high cohesion and exclusivity are significantly more likely to display traditional markers of cartel behavior. We replicate this relationship between group topology and the emergence of cooperation in a simulation model. Our method presents a scalable, unsupervised method to find groups of firms in bidding markets ideally positioned to form lasting cartels.
SSRN
A detailed treatment of aggregation and capital heterogeneity substantially improves the performance of the investment CAPM. Firm-level predicted returns are constructed from firm-level accounting variables and aggregated to the portfolio level to match with portfolio-level stock returns. Working capital forms a separate productive input besides physical capital. The model fits well the value, momentum, investment, and profitability premiums simultaneously and partially explains positive stock-fundamental return correlations, the procyclical and short-term dynamics of the momentum and profitability premiums, as well as the countercyclical and long-term dynamics of the value and investment premiums. However, the model falls short in explaining momentum crashes.
SSRN
Designing a financial market that works well is very important for developing and maintaining an advanced economy, but is not easy because changing detailed rules, even ones that seem trivial, sometimes causes unexpected large impacts and side effects. A computer simulation using an agent-based model can directly treat and clearly explain such complex systems where micro processes and macro phenomena interact. Many effective agent-based models investigating human behavior have already been developed. Recently, an artificial market model, which is an agent-based model for a financial market, has started to contribute to discussions on rules and regulations of actual financial markets. I introduce an artificial market model to design financial markets that work well and describe a previous study investigating tick size reduction. I hope that more artificial market models will contribute to designing financial markets that work well to further develop and maintain advanced economies.
SSRN
Cryptocurrencies employ different consensus protocols to verify transactions. While the Proof-of-Work consensus protocol is the most energy consuming protocol, Proof-of-Stake and Hybrid consensus protocols have been introduced which consume considerably less energy. We employ portfolio analysis to explore whether energy is a fundamental economic factor affecting cryptocurrency prices. Surprisingly, our results suggest that, on average, cryptocurrencies employing Proof-of-Work consensus protocols do not generate returns that are significantly different from those that incorporate Proof-of-Stake consensus protocols. Even more surprising is that our results show that cryptocurrencies that incorporate Hybrid consensus protocols generated significantly higher average return than the other groups. A possible explanation for that phenomenon may be that investorsâ demand for cryptocurrencies that they perceive as offering more trust is larger than for those that carry potential risks of blockchain manipulation.
SSRN
This paper examines whether a randomized auction ending time reduces market manipulation. Using the random auction ending rule implemented on the Singapore Exchange, we examine changes in indicators of market manipulation and market efficiency. We find that end of day price swings and price dislocation probability both declined, suggesting a lower risk of market manipulation. In addition, the variance ratio and market-adjusted return volatility measures have decreased indicating a more efficient and less volatile price discovery process. We do note that there are still telltale signs of manipulation in the pre-auction opening and pre-closing phase suggesting that the length of time of this phase is important. Overall, our results indicate that the randomized auction ending can curb market manipulation and improve price efficiency.
SSRN
This study examines the effect of capitalizing acquired in-process research and development (IPR&D) on information asymmetry under Statement of Financial Accounting Standard No. 141 (R). SFAS 141R requires acquirers to fully recognize IPR&D at fair value as an indefinite-lived intangible asset until completion or discontinuation of the project. Prior research suggests IPR&D capitalization will result in an improvement in the information environment. In contrast, we find no evidence that capitalizing IPR&D improved the information environment for IPR&D acquirers. Instead, most of our results suggest no significant change in information asymmetry for IPR&D acquirers during the post-SFAS 141R period, relative to the concurrent changes for non-IPR&D acquirers. In cases in which the results suggest a statistically significant increase, the economic magnitudes are relatively small. In addition, we find no evidence that IPR&D acquirers engaged in increased classification shifting between IPR&D and goodwill during the post-SFAS 141R period, as critics of capitalization had feared.
SSRN
This paper studies the spread of losses and defaults in financial networks with two important features: collateral requirements and alternative contract termination rules in bankruptcy. When collateral is committed to a firm's counterparties, a solvent firm may default if it lacks sufficient liquid assets to meet its payment obligations. Collateral requirements can thus increase defaults and payment shortfalls. Moreover, one firm may benefit from the failure of another if the failure frees collateral committed by the surviving firm, giving it additional resources to make other payments. Contract termination at default may also improve the ability of other firms to meet their obligations. As a consequence of these features, the timing of payments and collateral liquidation must be carefully specified, and establishing the existence of payments that clear the network becomes more complex. Using this framework, we study the consequences of illiquid collateral for the spread of losses through fire sales; we compare networks with and without selective contract termination; and we analyze the impact of alternative bankruptcy stay rules that limit the seizure of collateral at default. Under an upper bound on derivatives leverage, full termination reduces payment shortfalls compared with selective termination.
SSRN
In this paper, we analyze the welfare effects of bailout policies when banks compete with switching costs. We compare no-bailout policies to systematic bailouts. We argue that no-bailout policies increase the interest rates paid by borrowers ex ante (i.e., before a shock), whereas they may reduce the interest rates paid by consumers who are not credit constrained ex post. Such policies increase social welfare ex post if borrowers can easily switch banks and if the credit constraints are not too severe.
SSRN
Corporate debt maturity is a concave function of financial leverage when the debt has restrictive asset-based covenants attached. This concavity kicks in earlier with increasing covenant tightness and is absent when firms have no restrictive asset-based covenants. We argue that this concavity is suboptimal for equityholders and will arise if managers' prioritize maintaining firm control over reducing the firm's cost of capital. Managers of highly levered firm choose shorter-term debt (at a higher cost) to reduce the probability of covenant violation. We also find that maturity-leverage concavity is reduced when executive remuneration contracts better align managers and owners' interests.
SSRN
We investigate determinants of voluntary administration (VA) and deed of company arrangement (DOCA) durations for Australian firms using unconditional quantile regression (UQR). Larger firms have longer VA durations across the VA duration distribution, older (expert insolvency) firms have longer (shorter) VA durations at longer (shorter) durations. Firms with serious accounting issues, firms with longer audit lags and those with credit committees are associated with longer DOCAs around the middle of the DOCA duration distribution, and firms with larger investing cashlows and the existence of a private equity provider are negatively associated with DOCA duration across its distribution and good economic periods are negatively associated with DOCA duration at shorter durations.
SSRN
Boards of directors play their role in corporate governance by advising and/or monitoring managers. In the corporate disclosure literature, prior research has documented directorsâ monitoring role, yet empirical evidence on directorsâ advising role is limited. Since the advising role often entails information transfer, we examine directors who concurrently serve as directors or executives in the firmsâ related industries (DRIs) and hence possess valuable information about the firmsâ external operating environment. We hypothesize and find that more DRIs on boards are associated with more accurate management forecasts. This association is stronger when firms face greater uncertainty, and holds in settings where DRIs are unlikely to monitor managers, suggesting a distinct advising role of DRIs. Our study highlights directorsâ role as information suppliers and advisors who help shape corporate voluntary disclosure.
SSRN
Credit unions compete directly with for-profit commercial banks in markets for consumer financial services yet receive an exemption from federal corporate income tax. Commercial banks claim that credit unions are no different than for-profit banks and that the credit union tax exemption represents an unfair competitive advantage. Credit unions counter that while they offer similar products and services, they differ from commercial banks in terms of structure and mission, given their not-for-profit, cooperative status. In this paper, we test for substantive differences in the objective functions of for-profit commercial banks and nonprofit credit unions by comparing CEO compensation structures. We use a stylized principal-agent model and provide several arguments to support the hypotheses that credit union boards of directors establish lower-powered incentive contracts with their CEOs relative to similarly-sized commercial banks, and lower overall expected compensation. We find that credit union CEOs receive approximately two-and-a-half times less performance-based compensation relative to CEOs of similarly-sized âcommunityâ banks. Bank CEOs also earn approximately 10% to 20% more total compensation on average, depending on the measure. The results are generally robust to controlling for CEO characteristics (gender, tenure and retirement income), institution-level variables (asset size, growth, earnings, risk, complexity, competition and market share), and local economic conditions (housing price levels, housing price growth and unemployment). The findings suggest important differences in incentive structures and objectives between banks and credit unions and serve as a foundation for further research.
SSRN
Azerbaijani Abstract: MÉqalÉdÉ kapital bazarlarının sÉmÉrÉli fÉaliyyÉtini tÉmin Effektiv Bazar Hipotezi haqqında ÉvvÉlcÉ qısa mÉlumat verilmiÅ, daha sonra hipotezin inkiÅafına töhvÉ verÉn elmi tÉdqiqatların xronikası verilmiÅdir. Burada, bu hipotezin rüÅeymi sayılan tÉsadüfi yürüŠnÉzÉriyyÉsindÉn baÅlayaraq hipotezin tam bir elmi konsepsiya kimi formalaÅmasına qÉdÉr olan tÉdqiqatlar, hipotezi dÉstÉklÉyÉn vÉ tÉnqid elÉn Én vacib tÉdqiqat vÉ mÉqalÉlÉr qeyd edilmiÅdir.English Abstract: In this paper we firstly give brief information about Efficient Market Hypothesis, then chronologically order researches that contributed development of the hypothesis. Here we noted important studies that support and criticize the market efficincy, starting from seed of the hypothesis â" random walk up to hypotheis as a completed financial concept.
SSRN
We examine gender differences in investment risk tolerance, knowledge, confidence, and portfolio cash allocations among a sample of advised and self-directed wealthy individuals. Our results demonstrate that gender effects are more complicated than previously assumed. First, while even wealthy women consider themselves more conservative and hold more cash than men, previous findings of lower confidence and knowledge do not extend to our sample wealthy women. Second, having an advisor matters. Advised investors perceive themselves to have a higher risk tolerance and hold 15% points less cash than self-directed investors. Finally, the investor-advisor gender combination matters, but only for female investors. Women with male advisors are more risk averse, and feel less knowledgeable and less confident about investments. They also hold 11% more cash than women with female advisors. Indeed, female investors advised by women report the highest risk tolerance and make the lowest portfolio allocation to risk-free assets across the full sample, including men.
SSRN
How do primary and secondary mortgage markets interact? This paper shows that funding shocks to mortgage originators interact with the degree of local credit market competition to increase lending growth. Specifically, I use a shift-share approach to estimate the causal effect of the growth in private-label securitization related funding. This effect is stronger in more competitive mortgage markets; with less-regulated non-bank lenders being most responsive to this competition channel. The results emphasize the interaction between the two layers of the mortgage market and document how credit market structure can amplify, or dampen, shocks to the economy.
SSRN
In this paper we investigate whether herding by actively managed equity funds affects their performances and flows over the 1980-2013 period. We show that during the herding quarter, on average, funds that trade with the herd benefit from this behavior. Although this does not directly translate into a positive association between the extent to which funds herd and their subsequent performance, we find that the funds that follow the herd earn negative abnormal returns whereas the ones that lead earn no abnormal returns. Our results also indicate that investors react adversely to follower funds while they are neutral towards the leader funds.
SSRN
In a rapidly changing world, older data is not as informative as the most recent data. This is known as a concept drift problem in statistics and machine learning. How does a firm adapt in such an environment? To address this research question, we propose a generalized revealed preference approach. We argue that by observing a firmâs choices, we can recover the way the firm uses the past data to make business decisions. We apply this approach to study how Prosper Marketplace, an online P2P lending platform, adapts in order to address the concept drift problem. More specifically, we develop a two-sided market model, where Prosper uses the past data and machine learning techniques to assess borrowersâ and lendersâ preferences, borrowersâ risks, and then set interest rate for their loans to maximize his expected profits. By observing his interest rate choices over time and using this structural model, we infer that Prosper assigns different weights to past data points depending on how close the economic environments that generate the data are to the current environment. In the counterfactual, we demonstrate that Prosper may not be using the past data optimally, and it could improve its revenue by changing the way it uses data.
SSRN
We provide a comprehensive analysis of incentive compensation design--the link of compensation to operating performance--in insurance companies and banks and compare it to that in non-fi nancial fi rms. Top executives in financial fi rms are paid less (20% less in banks and 52% less in insurance companies) than their counterparts in non-fi nancial fi rms of similar size and performance. Banks (and insurance fi rms) link a larger fraction of top executive pay to short-term accounting metrics like ROE and EPS and a smaller fraction to (long-term) stock price. Performance targets for bankers are not related to the risk of the bank. Better corporate governance and greater post-crisis regulatory oversight over bankers' compensation encourage an increase in performance-based pay, but not a decrease in bonuses tied to ROE. There is evidence of rent-seeking by bank managers as ROE targets drop when leverage drops, but do not increase with leverage.
arXiv
In the IEEE Investment ranking challenge 2018, participants were asked to build a model which would identify the best performing stocks based on their returns over a forward six months window. Anonymized financial predictors and semi-annual returns were provided for a group of anonymized stocks from 1996 to 2017, which were divided into 42 non-overlapping six months period. The second half of 2017 was used as an out-of-sample test of the model's performance. Metrics used were Spearman's Rank Correlation Coefficient and Normalized Discounted Cumulative Gain (NDCG) of the top 20% of a model's predicted rankings. The top six participants were invited to describe their approach. The solutions used were varied and were based on selecting a subset of data to train, combination of deep and shallow neural networks, different boosting algorithms, different models with different sets of features, linear support vector machine, combination of convoltional neural network (CNN) and Long short term memory (LSTM).
SSRN
I document new details on the timing and nature of the recent boom and bust in the home mortgage market. The boom began in the 1990s, not the mid-2000s, and was indeed pronounced among low-income and high-minority neighborhoods. The relative increase in lending to these neighborhoods was not the result of special lending programs targeting them. It was due to something much less precise, such as a relaxation of underwriting standards that would benefit all neighborhoods but disproportionately benefit neighborhoods with lower incomes and higher minority concentrations. I suggest affordable housing policies as an explanation for the boom and bust.
arXiv
Since the 2007-2009 financial crisis, substantial academic effort has been dedicated to improving our understanding of interbank lending networks (ILNs). Because of data limitations or by choice, the literature largely lacks multiple loan maturities. We employ a complete interbank loan contract dataset to investigate whether maturity details are informative of the network structure. Applying the layered stochastic block model of Peixoto (2015) and other tools from network science on a time series of bilateral loans with multiple maturity layers in the Russian ILN, we find that collapsing all such layers consistently obscures mesoscale structure. The optimal maturity granularity lies between completely collapsing and completely separating the maturity layers and depends on the development phase of the interbank market, with a more developed market requiring more layers for optimal description. Closer inspection of the inferred maturity bins associated with the optimal maturity granularity reveals specific economic functions, from liquidity intermediation to financing. Collapsing a network with multiple underlying maturity layers or extracting one such layer, common in economic research, is therefore not only an incomplete representation of the ILN's mesoscale structure, but also conceals existing economic functions. This holds important insights and opportunities for theoretical and empirical studies on interbank market functioning, contagion, stability, and on the desirable level of regulatory data disclosure.
SSRN
Before completing an M&A transaction, acquiring firms conduct due diligence. This process provides acquiring firms with a more informed assessment of the expected costs, benefits, and risks of an acquisition and offers one last opportunity to renegotiate or terminate an M&A transaction. However, acquiring firms must trade off the costs and benefits of performing additional due diligence versus completing the acquisition. Based on an analysis of the time to negotiate the acquisition agreement and complete the transaction, I predict and find that competitive pressures, short-term financial reporting incentives, and agency problems are associated with less due diligence. I also find that less due diligence is associated with lower post-acquisition profitability, a higher probability of acquisition-related goodwill impairments, and lower quality fair value estimates for the acquired assets and liabilities. These findings highlight due diligence as an important factor explaining cross-sectional variation in post-acquisition performance and financial reporting for business combinations.
RePEC
This paper investigates the long-run and the short-run relationship between oil prices (international oil price), US exchange rates and the Amman Stock Exchange as measured by MSCI stock market index in Jordan. The data used in this paper are monthly time series data from M1 2005 to M12 2015. To meet this ambitious objective, we use VECM method. Our results show that the Jordan stock market prices have a relationship with two macroeconomic variables. Nevertheless, oil prices have significantly long and short-run negative effect on stock prices contrary to the US exchange rate that has a significant negative effect on stock prices only in the short term.
SSRN
We formulate a generalization of the traditional medium-of-exchange function of money in contexts where there is imperfect competition in the intermediation of credit, settlement, or payment services used to conduct transactions. We find that the option to settle transactions directly with money strengthens the stance of sellers of goods and services vis-a-vis intermediaries. We show this mechanism is operative even for sellers who never exercise the option to sell for cash, and that these latent money demand considerations imply monetary policy remains effective through medium-of-exchange channels even if the share of monetary transactions is arbitrarily small.
arXiv
Pairwise comparisons are used in a wide variety of decision situations when the importance of different alternatives should be measured by numerical weights. One popular method to derive these priorities is based on the right eigenvector of a multiplicative pairwise comparison matrix. We introduce an axiom called monotonicity: increasing an arbitrary entry of a pairwise comparison matrix should increase the weight of the favoured alternative (which is in the corresponding row) by the greatest factor and should decrease the weight of the favoured alternative (which is in the corresponding column) by the greatest factor. It is proved that the eigenvector method violates this natural requirement. We also investigate the relationship between non-monotonicity and the Saaty inconsistency index. It turns out that the violation of monotonicity is not a problem in the case of nearly consistent matrices. On the other hand, the eigenvector method remains a dubious choice for inherently inconsistent large matrices such as the ones that emerge in sports applications.
arXiv
This paper is concerned with an optimal reinsurance and investment problem for an insurance firm under the criterion of mean-variance. The driving Brownian motion and the rate in return of the risky asset price dynamic equation cannot be directly observed. And the short-selling of stocks is prohibited. The problem is formulated as a stochastic linear-quadratic (LQ) optimal control problem where the control variables are constrained. Based on the separation principle and stochastic filtering theory, the partial information problem is solved. Efficient strategies and efficient frontier are presented in closed forms via solutions to two extended stochastic Riccati equations. As a comparison, the efficient strategies and efficient frontier are given by the viscosity solution for the Hamilton-Jacobi-Bellman (HJB) equation in the full information case. Some numerical illustrations are also provided.
SSRN
Why and when do firms optimally deviate from target cash? And why do we observe imperfect adjustment of cash? In this paper, we postulate and provide evidence that policy uncertainty induces financing frictions and adjustment costs which decelerate the speed of adjustment (SOA) of cash toward target. We also find that the effects of policy uncertainty on SOA are higher for firms that operate below target cash than for firms that operate above target cash. Firms that operate below target cash accelerate SOA while firms that operate above target cash decelerate SOA. Overall, the results suggest that in the face of policy uncertainty shocks, firms optimally deviate from target cash as the expected benefit of deviation is greater than the expected value of approaching the target.
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We examine whether politically active firms play a role in disseminating political information via their management guidance. We use multiple proxies based on campaign financing activity or the presence of a government affairs office to capture whether a firm is politically active. We find that politically active firms are more likely to issue management guidance overall, and especially when the government is a key customer of the firm. Further, relative to politically inactive firms, the guidance released by politically active firms is more likely to discuss government policies. In addition to using numerous econometric techniques to address self-selection concerns, we examine the timing of when guidance is issued. We find that politically active firms are more likely to issue guidance prior to the public revelation of government policy decisions. Collectively, these findings suggest that the privileged information firms obtain through their political activities is shared with investors through voluntary disclosures.
SSRN
This paper studies the portfolio choice of two large investors who act strategically because their trading affects expected stock returns. Each investor chooses her optimal portfolio conditional on the portfolio of the opponent. Equilibrium portfolios and their performance depend on the investor's characteristics, namely risk aversion and return impact, and on the characteristics of the opponent. Depending on the interplay among these characteristics, strategic interaction can i) increase or decrease risk taking incentives, as compared to the Merton-style portfolio, ii) induce the more risk-averse investor to invest relatively more in the risky asset and iii) generate a preference for high-volatility assets.
SSRN
Using U.S. data for 1986-2017, the paper focuses on the impacts of macroeconomic risk factors and leverage on the performance of the various types of real estate exposure (direct, non-listed, and listed). The response of core funds to economic risk factors is akin to that of direct investments; however, real estate fund and direct investment performance are less tightly related as more aggressive (i.e., value-added and opportunistic) strategies are envisaged. Only REIT performance is linked to that of the stock market. Leverage matters as it amplifies the responses to the economic factors and hence investment risk.
SSRN
This paper uses a simple binomial framework to explore trend following. It shows (by counter example) that the existence of positive profits from trend-following strategies, on its own, provides no prima facie evidence on the efficiency or inefficiency of markets. In addition, it explores the most important feature of time series momentum investment strategies: the return shaping impact of trend following through its dynamic positioning. In a stylized efficient market setting (with no transaction costs), the paper shows that the dynamic nature of trend following shapes when profits and losses occur compared to a buy-and-hold strategy. There is, however, a conservation of âmassâ in that gains and losses are shuffled across periods such that the unconditional distribution of profits is unaffected. In this sense, trend following, by construction, generates crisis alpha --- for crises where large losses occur over extended periods of time. Due to its ability to shape when profit and losses occur, trend following can provide significant portfolio diversification and hedging potential for those investors with strategic risk-on exposures.
SSRN
Understanding the pattern of stock market volatility is important to investors as well as for investment policy. Volatility is directly associated with risks and returns, higher the volatility the more financial market is unstable. The volatility of the Zimbabwean stock market is modeled using monthly return series consisting of 109 observations from January 2010 to January 2019. ARCH effects test confirmed the use of GARCH family models. Symmetric and asymmetric models were used namely: GARCH(1,1), GARCH-M(1,1), IGARCH(1,1) and EGARCH(1,1). Post-estimation test for further ARCH effects were done for each model to confirm its efficiency for policy. EGARCH(1,1) turned to be the best model using both the AIC and SIC criterions; with the presence of asymmetry found to be significant. The study concludes that positive and negative shocks have different effects on the stock market returns series. Bad and good news will increase volatility of stock market returns in different magnitude. This simply imply that investors on the Zimbabwean stock exchange react differently to information depending be it positive or negative in making investment decisions.
SSRN
In this paper I study the extent to which the nexus between concentration and interbank linkages affects ï¬nancial stability, using data for a sample of 19,689 banks in 69 countries from 1995 to 2014. I ï¬nd that high levels of interbank exposures decrease the probability of observing a systemic banking crisis, when the banking system is either highly concentrated or fragmented. The relationship between concentration and stability is found to be non-monotonic, as predicted by Martinez-Miera & Repullo (2010), although not U-shaped.
SSRN
Market efficiency has been analyzed through many studies using different linear methods. However, studies on financial econometrics reveal that financial time series exhibit nonlinear patterns because of various reasons. This paper examines market efficiency at Borsa Istanbul using a smooth transition autoregressive (STAR) type nonlinear model. I develop nonlinear ARCH and STAR models, a linear AR model and random walk model for 10 yearsâ weekly data and then out-of-sample forecast next 12 weeksâ return. Comparing forecast performance powers, I find that the STAR model outperforms random walk, that is Borsa Istanbul returns are predictable at the given period. The results show that the shareholders may earn abnormal return and identify the direction of the return change for the next week with at least 66% accuracy. Contrary to the linear level studies, these findings show that the Borsa Istanbul is not weak form efficient at nonlinear level within the studied period.
arXiv
We apply Geometric Arbitrage Theory to obtain results in Mathematical Finance, which do not need stochastic differential geometry in their formulation. First, for a generic market dynamics given by a multidimensional It\^o's process we specify and prove the equivalence between (NFLVR) and expected utility maximization. As a by-product we provide a geometric characterization of the (NUPBR) condition given by the zero curvature (ZC) condition. Finally, we extend the Black-Scholes PDE to markets allowing arbitrage.
SSRN
In response to current regulatory initiatives which aim to foster information acquisition and processing across countries, we develop an index model (CR-score) designed to capture the extent of regulated firm information disseminated via company register (CR) websites. In a unique sample of 137 countries, we find consistent evidence that countries with a relatively high level of Internet penetration, those that facilitate cross-border trading, and those with higher governance quality show higher CR-scores. Our findings are robust to several additional tests, including amendments of the index model, the independent variables, and the sample composition. The results are generally in line with theories of regulation and should be of particular interest to regulators and standard setters.
SSRN
We use information on new sovereign debt issues in the euro area to explore the drivers behind the debt maturity decisions of governments. We set up a theoretical model for the maturity structure that trades off preference for liquidity services of short-term debt, roll-over risk and price risk. The average debt maturity is negatively related to both the level and the slope of the yield curve. A panel VAR analysis shows that positive shocks to risk aversion, the probability of non-repayment and the demand for the liquidity services of short-term debt all have a positive effect on the yield curve level and slope, and a negative effect on the average maturity of new debt issues. These results are partially in line with our theory. A forecast error variance decomposition suggests that changes in non-repayment risk as captured by credit default spreads are the most important source of shocks.
SSRN
The standard shifted lognormal model, defined by just two parameters, provides a remarkably good fit to the market implied volatilities of VIX options.Inspired by an analytic approximation derived by Lee and Wang, we propose a simple, intuitive extension that provides better empirical fits while retaining analytical tractability.In essence, by introducing a third parameter that controls the tilt of the surface beyond the shifted lognormal baseline we can better control the behavior of the fit for large strikes. We call this extended model TSLL: tilted and shifted lognormal-like.Finally, we suggest an alternative parameterization in terms of the ATM volatility, volatility floor and tilt parameter that is better suited to help set cutoffs and to rule out arbitrage violations.
SSRN
Carr and Wu (2004), henceforth CW, developed a framework that encompasses almost all of the continuous-time models proposed in the option pricing literature. Their framework hinges on the stopping time property of the time changes. By analyzing the measurability of the time changes with respect to the underlying filtration, we show that all models CW proposed for the time changes fail to satisfy this assumption.
SSRN
This article looks at how numbers currently reported by the government can be modified to produce a âbetterâ CPI. Here CPIs are compared by examining their ability to produce time series data on real consumer loan rates and wages that forecast consumer borrowing and default data. Suggested changes focus on goods with little change in the consumer experience as well as changes to the housing stock over time. The top performing CPI alternatives produce long run tends in income growth and the poverty level reductions that indicate both have been understated by the official CPI.
SSRN
Technological advances are creating a shift in the information disclosure environment allowing more investors to interact with management. We examine three key levels of trader-management interaction to assess the accuracy of tradersâ market-tested value estimates and resulting market price. These data require an engaging experiment and a complex, contextually-rich asset, which we create by playing a popular gaming app before the experiment. Participants view financial information, ask management questions, estimate value, and trade. We find that receiving non-personalized question responses improves trader estimates of value and market price efficiency relative to when traders ask questions but do not expect a response. This occurs because traders exert more effort estimating value and trading. However, receiving personalized versus non-personalized responses harms value estimates and market efficiency. This occurs because traders receiving personalized responses fixate on the interaction with management, dividing their attention and diverting it away from valuing and trading the asset.
SSRN
In this article, we investigate the impact of truncating training data when fitting regression trees. We argue that training times can be curtailed by reducing the training sample without any loss in out-of-sample accuracy as long as the prediction model has been trained on the tails of the dependent variable, that is, when âaverageâ observations have been discarded from the training sample. Filtering instances has an impact on the features that are selected to yield the splits and can help reduce overfitting by favoring predictors with monotonous impacts on the dependent variable. We test this technique in an out-of-sample exercise of portfolio selection which shows its benefits. The implications of our results are decisive for time-consuming tasks such as hyperparameter tuning and validation.
SSRN
We investigate whether reviews of transactional filings by the SEC unexpectedly constrain SEC resources leading to lower quality comment letters for periodic reports. The Sarbanes Oxley Act requires the SEC to review periodic reports (e.g., 10-Ks) at least once every three years. However, the SEC also reviews transactional filings (e.g., IPOs and acquisitions), which are unpredictable and often occur in waves. We find comment letters for periodic reports are of lower quality (in terms of outputs, inputs, and firm responses) during periods of abnormally high transactional filings. We also find that comment letters issued during periods of abnormally high versus low transactional filings are associated with increased information asymmetry and lower earnings response coefficients in the quarter after the resolution of the comment letter. Overall, our results suggest that unexpected resource constraints affect the quality of SEC oversight of periodic reports.
SSRN
This paper uses loan application-level data from a Chinese peer-to-peer lending platform to study the risk-taking channel of monetary policy. By employing a direct ex-ante measure of risk-taking and estimating the simultaneous equations of loan approval and loan amount, we are the first to provide quantitative evidence of the impact of monetary policy on the risk-taking of nonbank financial institution. We find that the search-for-yield is the main workhorse of the risk-taking effect, while we do not observe consistent findings of risk-shifting from the liquidity change. Monetary policy easing is associated with a higher probability of granting loans to risky borrowers and a greater riskiness of credit allocation, but these changes do not necessarily relate to a larger loan amount on average.
SSRN
Geometric Arbitrage Theory reformulates a generic asset model possibly allowing for arbitrage by packaging all assets and their forwards dynamics into a stochastic principal fibre bundle, with a connection whose parallel transport encodes discounting and portfolio rebalancing, and whose curvature measures, in this geometric language, the ''instantaneous arbitrage capability'' generated by the market itself.The asset and market portfolio dynamics have a quantum mechanical description, which is constructed by quantizing the deterministic version of the stochastic Lagrangian system describing a market allowing for arbitrage.Results, obtained by solving explicitly the Schrödinger equations by means of spectral decomposition of the Hamilton operator, coincides with those obtained by solving the stochastic Euler Lagrange equations derived by a variational principle and providing therefore consistency. Arbitrage bubbles are computed.