Research articles for the 2019-12-11
SSRN
We study a principal-agent problem of two general S-shaped utilities, where the two parties have different reference points. It turns out to be a non-concave and non-smooth optimization problem of a special double S-shaped utility. The main difficulty is to deal with the double S-shaped utility without explicit expressions and study the existence of the possible solution. We investigate the double S-shaped utility thoroughly by concavification techniques to solve the optimization problem, and introduce a concept of local asymptotic elasticity to strictly prove existence of the solution. The key technique is to analyze limiting behaviors of two featured tangent lines of the double S-shaped utility. The optimal final wealth can be classified into two cases: (a) One-side-loss Case in which either both parties suffer liquidation, or one gains and the other loses, or both make profit; (b) Option Case in which either both parties suffer liquidation or both make profit. We finally demonstrate the classification of optimal wealths by numerical examples.
SSRN
[enter Abstract Body]Industry 4.0 revolution find a real interest of entrepreneurs but in the case of frontier and emerging markets it is difficult to find a reliable source of long-term financing. The decoupling of the technological evolution from the evolution of the access to financing capacities must be analysed from different point of view (financial, legislative, socio- technical). In Romania, as a frontier market there are only few alternative investment solutions capable to respond to the long-term financing demand of performant projects. The main interest is to understand the strategies for adaptation of venture capital fund (VCF) at real conditions. Venture capital funds (VCF) represents a particular form of private equity investments, scale down and more focused on innovative start-up (or even expansions on technology or markets) projects (the typical value is 10 mil Euro). This form of investments is a personalized response to the general problem related to the actors that do not have tangible assets for collaterals and / or cannot demonstrate the ability to make a profit. In the case of VCF, as a vehicle oriented on innovation and technology, the business plan represents the main element for project portfolio selection in the context of matching the interests of investors with the interests of financed firmâs managers. This contribution is especially important for the case of frontier and emerging markets characterized by additional restrictions (access to strategies, liquidity problems, and agency costs beyond a simple monitoring). For Romania, it is essential to adapt VCF investors' objectives to all phases (selection, evaluation, contract signing and restructuring, progress monitoring, stimulating value-added and, especially, closing the VCF cycle) to real conditions and considering the performance indicators balancing with the value creation mechanisms specific of industry 4.0.
SSRN
This note extends the CAPM to situations where a subset of investors is not mean-variance optimizers. We show that a CAPM relation holds when suitably adjusting beta to the presence of such investors. The adjusted CAPM can be used to reveal which non-mean-variance behavior is needed to explain so-called CAPM anomalies. For example, the adjusted CAPM explains the low-beta anomaly if non-mean-variance investors overweight (underweight) high-beta (low-beta) assets. Our empirical analysis reveals that one needs two thirds of investors to depart from mean-variance analysis in order to explain the low beta anomaly.
SSRN
Firms in information and communication (ICT) sector are often considered as an important element of business innovation performance in the economy. This paper is focused on examining their share on innovation and total research and development (R&D) expenditure in selected European countries. Moreover, our goal is to test the potential effect of R&D expenditure on selected business performance indicators. We used panel macro-level data from 24 countries during the years 2008-2016. Based on the results of panel regression analysis we found empirical evidence for the positive effect of R&D expenditure on value-added and apparent labour productivity in the ICT sector. This fact could be to some extent attributed to the innovation of products and processes. The highest share of business R&D expenditure in ICT is present in Nordic countries such as Island, Norway and Finland. Firms in ICT appear to be more above-average innovative and represent a significant share of total business R&D expenditure.
SSRN
Warrant is normally priced on the basis of Black and Scholes' model, which refers to calculations in a risk neutral world. Hence, it neither captures the market expectation nor being a good reference for the risk management process. This study examines a new way of pricing warrants under the real world probability by utilizing the recovered Vacisek short rate model. Applying Carr and Yu's recovery model, an extended version of Ross Recovery Theorem, we managed to recover the Vasisek process. Then, suppose that the economy is driven by this recovered Vacisek process, we point out a valuation model for the warrant of an underlying stock. We deduce that by applying the recovered Vacisek model we can derive the warrant price under the real world probability without the assumption of the market price of risk as in the risk neutral model.
arXiv
We present three models of stock price with time-dependent interest rate, dividend yield, and volatility, respectively, that allow for explicit forms of the optimal exercise boundary of the American put option. The optimal exercise boundary satisfies nonlinear integral equation of Volterra type. We choose time-dependent parameters of the model so that the integral equation for the exercise boundary can be solved in the closed form. We also define the contracts of put type with time-dependent strike price that support the explicit optimal exercise boundary. All these results can be used as approximations to the standard model with constant parameters, i.e., geometric Brownian motion process.
SSRN
Over the last decade, the volume of market-on-close orders has increased to more than 10% of the entire day's trading volume. This paper investigates this rise and documents four stylized facts: (i) passive investing leads to greater usage of market-on-close orders, consistent with passive fundâs motivation for minimizing tracking error; (ii) the price impact from large market-on-close order imbalances is economically large and transitory, leading to short-term price reversal; (iii) a long/short trading strategy exploiting this reversal results in a significant risk-adjusted return of 13.2 basis points per day, consistent with the hypothesis that investors are compensated by providing liquidity to passive funds; and (iv) informed traders also use market-on-close orders, consistent with Admati and Pfleiderer's (1988) prediction that liquidity trades attract informed trades. Overall, the set of findings demonstrates market-on-close order as an important trading channel through which passive investing affects underlying stocks.
SSRN
Commodity-exporting economies display procyclicality with the price of commodity exports. However, the evidence for the relative importance of commodity price shocks for aggregate fluctuations remains inconclusive. Using Russian data from 2001 -2018 we estimate a small open economy New Keynesian model with a banking system and leveraged domestic firms who default on their unsecured domestic debt. Default rates vary endogenously over the business cycle and amplify the estimated contribution of commodity price shocks. As the effect of macroprudential policies depends on the type of the shock, optimal combinations of policy tools depend on the estimated relative importance of shocks.
SSRN
We examine whether components of the earnings-to-price (EP) ratio can be used to extract incremental information to better estimate future returns in the cross-section of country-industry indexes. We demonstrate that the EP components such as lagged EP, changes in earnings, short-term momentum and long-term reversal in prices increase the accuracy of return forecasts. The EP decomposition matters in developed markets, as well as in North America, Europe, Asia, and MENA, but is pointless in emerging countries, as well as in South America and Japan. Decomposing EP into its components is a worthwhile effort in the majority of industries examined. The results are robust to modifications in the methodology, sub-period analyses, the use of an alternative sample and remain unchanged after controlling for net share issuance and size effects.
SSRN
Using a unique data set, this paper studies the governance of anti-money laundering supervisors known as Financial Intelligence Units (FIUs). Starting from a theoretical framework that highlights four key properties of FIU governance â" financial powers, law enforcement features, independence and accountability â" we build the first quantitative index of FIU governance. The proposed metrics are then applied in an analysis of 71 countries that explores the drivers of FIU governance properties. Our results show that FIUsâ financial powers tend to be weaker in bank-based economies and stronger in countries with more affiliations with international anti-money laundering organizations. FIU independence and FIU accountability are stronger in countries with higher-quality governments and less opacity in the fiscal and legal systems. With regards to the nexus between country fundamentals and our overall FIU Governance Index, the index generally appears stronger for richer and more transparent countries. It is also stronger for countries with civil (rather than common) law. Finally, given the distinction between administrative FIUs and law enforcement FIUs, we find that overall FIU governance as well as independence and accountability are all weaker in countries with law enforcement FIUs.
SSRN
Using the 2008-09 Global financial crisis and the 2012 Euro area sovereign debt crisis as natural experiments, we investigate the effects of contractions in credit supply on R&D spending in a large sample of European firms. Our identification strategy exploits differences in financial constraints across firms, as well as the cross-industry variation in dependence on external finance, to identify a causal effect of bank credit supply on firm investment in innovation. We show that firms that are more likely financially constrained, in industries more dependent on external finance, have a disproportionally lower growth rate of R&D spending, as well as lower R&D intensity and share of R&D investment in total investment during periods of tight credit supply. These results are robust to different proxies of financial constraints, model specifications and fixed-effects identification strategies.
SSRN
This paper discusses the possibility of a financial value chain with CG as the trigger that generates and transmits value till it reaches market. The study explores the nature and function of CG in value creation. The main goal is to expose the role of CG in the financial value chain that culminates in market value addition. Main attention was paid to identifying financial leading indicators for Current Operations Value, Future Growth Value, Tobinâs q and Shareholder Value Added that remains as anchors for complete value materialization process .This topic was chosen because when corporate failures happen, the blame is on the CG, hence all actions aiming at strengthening of CG practices are deemed as assurance on firm performance and firm value. The major findings of the paper is the identification of a value chain that originates at CGPI. CGPI activates COV and FGV which in turn leads to EV, which in turn produces SVA. SVA in turn amplifies q. The q generates MVA and WAI. The above findings suggest that CG instigates value creation.
SSRN
There has been scant empirical evidence on how government involvement affects the investor demand for firm-specific information. We fill the void by testing how investor responses to risk-factor disclosures in Initial Public Offerings (IPO) prospectuses in China, which is characterized as a state-controlled economy. In such an economy, state-controlled firms receive superior perks and benefits, as well as implicit insurance, from the government. Consistent with the theoretical conjecture that more risk-factor disclosures reduce cost of equity, our results indicate that high-quality risk-factor disclosures are associated with less IPO underpricing and lower post-IPO stock return volatility among non-state-controlled IPO firms. However, we find an insignificant association between risk-factor disclosure quality and IPO underpricing (or post-IPO stock return volatility) among state-controlled firms. Our findings suggest that state-offered implicit insurance is the predominant consideration when investors value IPO shares of state-controlled firms, thereby weakening the investor demand for high-quality risk-factor disclosures. We further rule out other potential explanations (e.g., different firm-specific risks, different investor bases, or heterogeneity across state-controlled and non-state-controlled firms). Our study extends the prior risk disclosure literature by considering the state control effect, which renders the high-quality risk disclosures ineffective for state-controlled firms in economies with significant government involvement.
SSRN
In recent years, numerous countries around the globe have adopted macroprudential policies. However, the understanding of these policies and how exactly they impact the banking industry remains limited. Using a sample of 1,534 banks from 57 countries, we examine whether and how macroprudential and monetary policies interact in shaping bank stability. The results show that the positive impact of macroprudential policies on bank stability is enhanced in countries with higher central bank policy rates. Additional analysis reveals that this result is driven by financial institution-targeted instruments rather than borrower-targeted ones. These findings are robust to the use of various bank-level and country-level control variables, alternative indicators of bank-risk, and methodological approaches.
arXiv
We theoretically study a general family of economic geography models that features endogenous agglomeration. In many-region settings, the spatial scale---global or local---of the dispersion force(s) in a model plays a key role in determining the resulting endogenous spatial patterns and comparative statics. A global dispersion force accrues from competition between different locations and leads to the formation of multiple economic clusters, or cities. A local dispersion force is caused by crowding effects within each location and induces the flattening of each city. By distinguishing local and global dispersion forces, we can reduce a wide variety of extant models into only three prototypical classes that are qualitatively different in implications. Our framework adds consistent interpretations to the empirical literature and also provides general predictions on treatment effects in structural economic geography models.
SSRN
This paper discusses the challenges facing the IRS as it seeks to enforce taxpayer compliance regarding cryptocurrency transactions. For a proper analysis of these issues, we must look from the perspective of economic policy, as well as tax policy, including both domestic and global. The first part of addressing non-compliance is to abandon the idea that cryptocurrency is only a currency. Instead, I will use âcryptoassetsâ to describe all types of digital and virtual currency. This broader term will allow us to think beyond contemporary perspective and policy regarding cryptoasset and blockchain technology. Through that, the analysis will compare cryptoassets to other investments and securities, discuss the high potential for crime and fraud, examine the IRSâs current characterization of cryptoassets as property, and explore how other nations are implementing their own regulatory and tax policies for cryptoassets.Finally, this paper will argue that in order to successfully enhance taxpayer compliance with taxable cryptoasset events in the United States, there will need to be a dual regulatory and policy shift, which can be accomplished on two fronts. First by creating a regulatory foundation that incentivizes taxpayers to comply with tax law, and second by carving out a special tax characterization for cryptoassets and taxable transactions related to cryptoassets
SSRN
This paper discusses the influence of Corporate Governance (CG) on Cost of Capital (CoC). The study revolves on the hypothesis that optimum capital structure at minimum cost is also an agenda item of CG. Thus this study explores the influence of CG on overall cost of capital as well as at its components level. The main goal is to prove that with improvement in CG performance, leads to reduction in information asymmetry among principal and agents, enabling agency cost to decline resulting in resetting guidance for required returns for equity and debt to a lower level. Main attention was paid to nature of correlation and OLS based econometric modelling of WACC to identify the lead indicators CG should influence to create an impact. This topic was chosen on the assumption that CG has a role to play in enabling financial competitiveness for the firm to fuel its ambitious growth path. The major findings of the paper are, there exist no statistically significant differences existing among the means for CoC among the CG categories, and with rise in CG, and required return on equity and required return on debt are declining by the direction of correlation. However, in CGPI category 1, study finds required return on debt rising as a possible outcome of corporate strategies in those companies. The above findings suggest that the implications on the CoC on the whole is an outcome of the strategy implementation which is a byproduct of CG performance. Overall, study concludes that there is a reduction in CoC with rise in CG performance.
arXiv
Machine learning (especially reinforcement learning) methods for trading are increasingly reliant on simulation for agent training and testing. Furthermore, simulation is important for validation of hand-coded trading strategies and for testing hypotheses about market structure. A challenge, however, concerns the robustness of policies validated in simulation because the simulations lack fidelity. In fact, researchers have shown that many market simulation approaches fail to reproduce statistics and stylized facts seen in real markets. As a step towards addressing this we surveyed the literature to collect a set of reference metrics and applied them to real market data and simulation output. Our paper provides a comprehensive catalog of these metrics including mathematical formulations where appropriate. Our results show that there are still significant discrepancies between simulated markets and real ones. However, this work serves as a benchmark against which we can measure future improvement.
SSRN
The hedge fund industry has grown from $200 billion in assets under management around the turn of the millennium to now over $3 trillion. Many reports have criticized hedge funds for poor performance, particularly since the 2008 global financial crisis (GFC). In this paper, I seek to demystify hedge fund strategies by evaluating fund performance that can be attributed to the markets as well as other well-known systematic factors with an emphasis on outcomes prior to and following the 2008 GFC. When adjusted for risk to stock/bond markets, the evidence shows that, after fees and costs, hedge fund managers as a group have shown a marked decline in risk-adjusted alpha in the 10 years following the GFC. To aid in a better understanding of the decline in alpha, I further investigate equity hedge fund returns against a suite of well-known systematic risk/return factors documented in the literature beyond traditional market factors. In all, the model explains around 90 percent of the variation in returns. Equity hedge funds show meaningful and consistent exposures to many of these factors over time, but whether intended or otherwise, significant changes also occurred (including a significant decline in active risk) following the GFC, in turn influencing their performance. Armed with this information, investors are better positioned to make more informed decisions in deciding manager allocations.
SSRN
We present evidence that human capital outflow can lead to a higher likelihood of stock price crashes. Our test exploit US state courtsâ staggered rejection of the inevitable disclosure doctrine (IDD), which improves employeesâ ability to switch employers. We find that after the rejection of IDD, firms headquartered in these states experience a significant increase in stock price crash risk relative to unaffected firms. This effect is stronger for firms under server financial distress, facing fierce industry competition, and relying heavily on human capitals. Overall, our results support the view that losing key talents is an important determinant for stock price crashes.
SSRN
This paper studies the effect of mandatory information disclosure on stock price crash risk using data on listed firmsâ private in-house meetings in the Chinese stock market. Utilizing the regulation implemented by the Shenzhen Stock Exchange in 2012, we use a difference-in-difference approach and find that the treated group exhibits significantly lower crash risk comparing to the control group listed on the Shanghai Stock Exchange, following the regulation. This finding suggests that improving transparency may reduce crash risk, and have implications to both academic and policymakers.
arXiv
When the in-sample Sharpe ratio is obtained by optimizing over a k-dimensional parameter space, it is a biased estimator for what can be expected on unseen data (out-of-sample). We derive (1) an unbiased estimator adjusting for both sources of bias: noise fit and estimation error. We then show (2) how to use the adjusted Sharpe ratio as model selection criterion analogously to the Akaike Information Criterion (AIC). Selecting a model with the highest adjusted Sharpe ratio selects the model with the highest estimated out-of-sample Sharpe ratio in the same way as selection by AIC does for the log-likelihood as measure of fit.
arXiv
In this paper, Malliavin calculus is applied to arrive at exact formulas for the difference between the volatility swap strike and the zero vanna implied volatility for volatilities driven by fractional noise. To the best of our knowledge, our estimate is the rst to show the rigorous relationship between the zero vanna implied volatility and the volatility swap strike. In particular, we will see that the zero vanna implied volatility has a higher rate of convergence than the at-the-money (ATM) implied volatility for both zero and non-zero correlation and for all values of the Hurst parameter.
SSRN
This is the Online Appendix for: Is the Behavior of Sellers with Expected Gains and Losses Relevant to Cycles in House Prices?Appendix 1 provides support for using assessed value to mitigate unobserved quality.Appendix 2 describes the calculation of normalized assessed value (NAV) and summarizes results of leave-one-out (LOO) cross-validation.Appendix 3 summarizes the analytical framework.Appendix 4 displays our sample construction process.Appendix 5 reports the first-stage hedonic regression results.Appendix 6 shows the comparison between repeat sales index (based on repeat sales pairs), loss index and gain index.Appendix 7 provides additional summary statistics that supplement Table 2.Appendix 8 summarizes double results using asking price.Appendix 9 summarizes results using an alternative house price cycle.Appendix 10 reports additional robustness tests. ⢠A10.1 report robustness tests with various combinations of spatial and temporal fixed effects.⢠A10.2 report robustness tests by restricting to the repeat sale sample only.⢠A10.3 report results using asking price as the dependent variable.⢠A10.4 reports robustness tests by adding the loan-to-value ratio.Appendix 11 summarizes Clapp and Zhou (2019)âs method for correcting unobserved quality and report results using their method.Appendix 12 presents and discusses contrast-relative analyses holding loss/gain coefficients constant.
SSRN
We examine the decision of wealthy business owners to protect their holdings from expropriation and arbitrary taxation through proxies, shell companies, and offshore firms. Our theoretical framework emphasizes the role of political connections in decisions to obfuscate. Linking information from investigative journalists on Ukrainian oligarchs with firm-level administrative data on formal ownership ties, we observe obfuscation among more than two-thirds of oligarch-controlled firms, but such behavior is much less common for connected oligarchs. Further exploiting the abrupt shock to political connections that accompanied the Orange Revolution, we find a sharp rise in obfuscation among previously connected oligarchs.
arXiv
We examine how extreme market risks are priced in the cross-section of asset returns at various horizons. Based on the decomposition of covariance between indicator functions capturing fluctuations of different parts of return distributions over various frequencies, we define a \textit{quantile spectral} beta representation that characterizes asset's risk generally. Nesting the traditional frameworks, the new representation explains \textit{tail}-specific as well as horizon-, or frequency-specific \textit{spectral} risks. Further, we work with two notions of frequency-specific extreme market risks. First, we define tail market risk that captures dependence between extremely low market and asset returns. Second, extreme market volatility risk is characterized by dependence between extremely high increments of market volatility and extremely low asset return. Empirical findings based on the datasets with long enough history, 30 Fama-French Industry portfolios, and 25 Fama-French portfolios sorted on size and book-to-market support our intuition. We reach the same conclusion using stock-level data as well as daily data. These results suggest that both frequency-specific tail market risk and extreme volatility risk are priced and our final model provides significant improvement over specifications considered by previous literature.
SSRN
Acknowledging the importance and role of corporate reputation as a unique intangible and specific organizational resource, in this paper, we analyze its role and importance for the market success of contemporary banks. Furthermore, the paper provides an overview of the existing research regarding bank reputation in the Republic of Croatia. As corporate social responsibility aspect of a business is one of the most widely studied aspects of corporate reputation, we investigate the corporate social responsibility practice of two major banks in Croatia. By using publicly available data, we analyse the internal and external dimensions of their CSR and their relation to a bankâs reputation.
arXiv
At the zero lower bound, the New Keynesian model predicts that output and inflation collapse to implausibly low levels, and that government spending and forward guidance have implausibly large effects. To resolve these anomalies, we introduce wealth into the utility function; the justification is that wealth is a marker of social status, and people value status. Since people partly save to accrue social status, the Euler equation is modified. As a result, when the marginal utility of wealth is sufficiently large, the dynamical system representing the zero-lower-bound equilibrium transforms from a saddle to a source---which resolves all the anomalies.
arXiv
Among all the emerging markets, the cryptocurrency market is considered the most controversial and simultaneously the most interesting one. The visibly significant market capitalization of cryptos motivates modern financial instruments such as futures and options. Those will depend on the dynamics, volatility, or even the jumps of cryptos. In this paper, the risk characteristics for Bitcoin are analyzed from a realized volatility dynamics view. The realized variance is estimated with the corrected threshold jump components, realized semi-variance, and signed jumps. Our empirical results show that the BTC is far riskier than any of the other developed financial markets. Up to 68% of the days are identified to be entangled with jumps. However, the discontinuities do not contribute to the variance significantly. The full-sample fitting suggests that future realized variance has a positive relationship with downside risk and a negative relationship with the positive jump. The rolling-window out-of-sample forecasting results reveal that the forecasting horizon plays an important role in choosing forecasting models. For the long horizon risk forecast, explicitly modeling jumps and signed estimators improve forecasting accuracy and give extra utility up to 19 bps annually, while the HAR model without accounting jumps or signed estimators suits the short horizon case best. Lastly, a simple equal-weighted portfolio of BTC not only significantly reduces the size and quantity of jumps but also gives investors higher utility in short horizon case.
SSRN
This paper investigates whether family ownership affects selling, general and administrative cost behavior. We find that family firms exhibit anti-sticky cost behavior, as opposed to non-family firms that demonstrate cost stickiness. This result is robust to alternative definitions of family firms. The results are also preserved for a subsample of firms that switched ownership status (i.e., from family owned to non-family owned and vice versa). Further inquiry reveals that anti-sticky cost behavior is focused in family firms with active family involvement, that is, where the family member serves as an officer or chairperson of the firm. Finally, we test the effect of other known determinants of asymmetric cost behavior and find that managersâ optimism mitigates anti-sticky cost behavior and that successive sales decrease does not affect this behavior.
SSRN
A comparison of the most 30 influential cryptocurrencies has been made, based on the "CoinMarketCap" web page. Over the last few years, an increasing number of the world's population is investing in the cryptocurrency market. The emphasis is placed on Bitcoin, which is the absolute leader on this market. The difference between electronic money and virtual currency is explained, followed by the history of crypto values. Finally, the statistical analysis of the most influential cryptocurrencies, during the last year, will be presented.
SSRN
We study the effect of discrimination against Jewish managers and owners on their firms' stock during the Third Reich. The stock of firms with Jewish managers underperformed by around 5% annually, with abnormal performance persisting on average for three years until firm "Aryanization." Firms with Jewish owners perform much like firms without any Jewish involvement. We identify harassment of Jewish-managed firms as the leading cause for the discount. Alternative explanations, such as brain drain and Jewish stigma, seem less relevant. We find that discriminating against a minority can have a negative effect on an entire economy.
arXiv
Computing risk measures of a financial portfolio comprising thousands of options is a challenging problem because (a) it involves a nested expectation requiring multiple evaluations of the loss of the financial portfolio for different risk scenarios and (b) evaluating the loss of the portfolio is expensive and the cost increases with its size. In this work, we look at applying Multilevel Monte Carlo (MLMC) with adaptive inner sampling to this problem and discuss several practical considerations. In particular, we discuss a sub-sampling strategy that results in a method whose computational complexity does not increase with the size of the portfolio. We also discuss several control variates that significantly improve the efficiency of MLMC in our setting.
arXiv
The latest financial crisis has painfully revealed the dangers arising from a globally interconnected financial system. Conventional approaches based on the notion of the existence of equilibrium and those which rely on statistical forecasting have seen to be inadequate to describe financial systems in any reasonable way. A more natural approach is to treat financial systems as complex networks of claims and obligations between various financial institutions present in an economy. The generic framework of complex networks has been successfully applied across several disciplines, e.g., explaining cascading failures in power transmission systems and epidemic spreading. Here we review various network models addressing financial contagion via direct inter-bank contracts and indirectly via overlapping portfolios of financial institutions. In particular, we discuss the implications of the "robust-yet-fragile" nature of financial networks for cost-effective regulation of systemic risk.
SSRN
The purpose of this paper is to contribute to the existing literature on experiential learning in finance by discussing the instructional design of an undergraduate derivatives course. Moreover, we advocate for the use of Bloomberg Terminals as an experiential learning tool, providing students with real-life experiences. This paper proposes and describes two learning products designed to enhance the experiential learning benefits of this course: a customized instructional manual and a simulation for option trading strategies. To measure the effectiveness of this experiential teaching approach, we rely on pre- and post-class surveys, as well as a recent graduate survey. Our findings suggest that integrating Bloomberg in the classroom has both short term and long term implications: In the short run, it improves students learning outcomes. In the long run, the results of the survey suggest that learning how to use Bloomberg in the classroom provided a boost to recent graduates, both during their job search and during the first weeks after they start.
SSRN
Predicting long-term equity market returns is of great importance for investors to strategically allocate their assets. We apply machine learning methods to forecast 10-year-ahead U.S. stock returns and compare the results to traditional Shiller regression-based forecasts more commonly used in the asset-management industry. Machine-learning forecasts have similar forecast errors to a traditional return forecast model based on lagged CAPE ratios. However, machine-learning forecasts have higher forecast errors than the regression-based, two-step approach of Davis et al [2018] that forecasts the CAPE ratio based on macroeconomic variables and then imputes stock returns. When we combine our two-step approach with machine learning to forecast CAPE ratios (a hybrid ML-VAR approach), U.S. stock return forecasts are statistically and economically more accurate than all other approaches. We discuss why and conclude with some best practices for both data scientists and economists in making real-world investment return forecasts.
SSRN
The Italian insolvency and pre-insolvency frameworks have been reformed recently (2019). This paper recalls the intense period of reforms in Italian insolvency law, started in 2005 and culminated with the new âCode of enterprise crisis and of insolvencyâ. The Code introduces new rules for court-confirmed debt restructuring agreements (similar to schemes of arrangement) and judicial composition with creditors, as well as with regard to new rules for insolvency of groups, international jurisdiction and directorsâ liability. The paper addresses these novelties pointing out some unresolved issues. Finally, the paper touches upon the compatibility of the new law with the Directive on restructuring and insolvency.
SSRN
We examine how the Jumpstart Our Business Startup Act (JOBS Act) affect mergers and acquisitions. We find that U.S. private targets are valued higher after the JOBS Act relative to public targets acquired by US acquirers. The announcement returns of acquirers who acquired US private targets after the JOBS Act are lower. Consistent with the argument that the JOBS Act affects firms with higher disclosure costs more, we find that the effect is more pronounced for firms with higher disclosure costs.
SSRN
The last decade has challenged the paradigm of the hedge fund industry as a unique performer. We identify three main factors that have affected the operation of hedge funds: competition from mutual funds, the market environment, and tighter regulation. Recent trends in the financial industry have moved asset managers closer to hedge funds by introducing similar underlying strategies, such as liquid alternative funds, to directly compete with hedge funds. We find that such strategies can achieve performance similar to that of hedge funds, thus introducing more competition for hedge funds. Moreover, we find that several hedge fund styles that have traditionally worked well in crisis timesâ"even in the last decadeâ"are also strategies that can be replicated by liquid alternatives. Together with tighter regulation and a strong market environment, these developments continue to put pressure on the hedge fund industry. Our empirical findings add to the existing debate on the performance of hedge funds and the direct competition from liquid alternatives.
SSRN
In 2018, the Insurance Distribution Directive (IDD) was fully implemented by all EU member states. It intends to harmonize the insurance market, provide the right incentives for the agents and protect the consumers. But why? The core business of the banking sector makes it necessary for a prudential authority to intervene and monitor. The question arises if the latest changes in the insurance business require these limitations and monitoring. This paper offers a literature review by compiling findings and setting up profound arguments, why the regulation of insurance companies is relevant. The main arguments for a strong prudential regulation are transparency, information asymmetry and agency problems, wrong incentives, a representation of the policyholder and the inversion of the production cycle. These findings make it necessary to regulate the companies and protect the policyholders. Further research should focus on case studies of insurance companies implementing the changes of IDD into daily business.
SSRN
Sticky costs materialize when costs increase more with rising an activity than they decrease with falling of the very same amount of the activity. Over time a silent diffusion of sticky costs can be observed in the HoReCa (HOtel/REstaurant/CAtering) industry. In sticky costs literature the cost behaviour is evaluated by correlating the current growth in Selling, General and Administrative costs â" often referred to overhead - with current revenue growth. Recently, research identified several attributes affecting the hysteresis (Greek: remaining even if the cause is no longer there) of cost. Managerial oversight, external regulatory conditions and company culture are an example of such attributes. First insights indicate that the dependence of a system on its history is the driving force to determine the severance of cost stickiness. It depends for different sizes of corporations on the corporate governance model and on the successful variabilization of costs. This paper presents the most important attributes affecting sticky cost. Further, the various implementations in real managerial decision-making processes in the HoReCa industry are described on the example of the region of Opatija, Croatia. A qualitative research using ATLAS.ti as Computer Assisted Qualitative Data Analysis Software (CAQDAS) is the chosen approach for unveiling the desired findings.
SSRN
English Abstract: The workshop Media Texts of Social and Economic Discourse and the Specifics of their Translation from English into Russian and from Russian into English is for those who are interested in the problems and difficulties translators face when dealing with these types of texts. Irina G. Ignateva will talk about the specifics of translating this type of discourse from English into Russian, while Marina Ye. Korovkina will focus on translating from Russian into English. The key difficulty in translating from English into Russian is understanding the meaning and sense. Interference being a minor challenge in this case, it may still result in various stylistic mistakes. It is much more difficult to avoid interference when translating from Russian into English, as the world-view of the mother tongue has a much greater impact on the translator. Anyway, in both cases the challenge is to break away from the literal or word-for-word translation. That is why the translator needs to be well-versed in translation transformations and devices and to be able to use them consciously. All this and much more to be discussed and trained during our workshop!Russian Abstract: ÐаÑÑеÑ-клаÑÑ "ТекÑÑÑ Ð¿Ð¾Ð»Ð¸ÑиÑеÑкой и ÑоÑиалÑно-ÑкономиÑеÑкой напÑавленноÑÑи: оÑобенноÑÑи пеÑевода пÑблиÑиÑÑики в паÑе английÑкий-ÑÑÑÑкий ÑзÑки" пÑедназнаÑен Ð´Ð»Ñ ÑÐµÑ , кÑо Ñ Ð¾ÑÐµÑ Ð¿Ð¾Ð·Ð½Ð°ÐºÐ¾Ð¼Ð¸ÑÑÑÑ Ñ Ð¿Ñоблемами, возникаÑÑими пÑи пеÑеводе данного Ñипа ÑекÑÑов Ñ Ð°Ð½Ð³Ð»Ð¸Ð¹Ñкого и Ñ ÑÑÑÑкого ÑзÑков и ÑпоÑобами Ð¸Ñ Ð¿ÑеодолениÑ. Ð.Ð". ÐгнаÑÑева ÑаÑÑÐºÐ°Ð¶ÐµÑ Ð¾ ÑпеÑиÑике пеÑевода Ñ Ð°Ð½Ð³Ð»Ð¸Ð¹Ñкого на ÑÑÑÑкий, а Ð.Ð. ÐоÑовкина о пеÑеводе Ñ ÑÑÑÑкого ÑзÑка на английÑкий. ÐÑи пеÑеводе Ñ Ð°Ð½Ð³Ð»Ð¸Ð¹Ñкого ÑзÑка оÑÐ½Ð¾Ð²Ð½Ð°Ñ ÑÑÑдноÑÑÑ â" понимание ÑмÑÑла, пÑи ÑÑом пеÑеводÑÐ¸ÐºÑ Ð»ÐµÐ³Ñе ÑпÑавлÑÑÑÑÑ Ñ Ð¸Ð½ÑеÑÑеÑенÑией английÑкого ÑзÑка, коÑоÑаÑ, Ñем не менее, пÑоÑвлÑеÑÑÑ Ð² ÑазнообÑазнÑÑ Ð½Ð°ÑÑÑениÑÑ ÑÑилиÑÑиÑеÑÐºÐ¸Ñ Ð½Ð¾Ñм ÑÑÑÑкого ÑзÑка. ÐÑи пеÑеводе Ñ ÑÑÑÑкого ÑзÑка понимание как Ñаковое оÑобой ÑÑÑдноÑÑи не пÑедÑÑавлÑеÑ, но пÑи ÑÑом пеÑеводÑик в болÑÑей ÑÑепени подвеÑгаеÑÑÑ Ð²Ð»Ð¸ÑÐ½Ð¸Ñ Ð¸Ð½ÑеÑÑеÑенÑии Ñо ÑÑоÑÐ¾Ð½Ñ Ñодного ÑзÑка и каÑÑÐ¸Ð½Ñ Ð¼Ð¸Ñа, ÑÑо пÑÐ¸Ð²Ð¾Ð´Ð¸Ñ Ðº «ÑÑÑÑÐºÐ¾Ð¼Ñ Ð°Ð½Ð³Ð»Ð¸Ð¹ÑкомÑ». ÐÐµÐ¾Ð±Ñ Ð¾Ð´Ð¸Ð¼Ð¾ ÑÑиÑÑÑÑ Ð¾Ñознанно иÑполÑзоваÑÑ Ð¿ÐµÑеводÑеÑкие ÑÑанÑÑоÑмаÑии и пÑÐ¸ÐµÐ¼Ñ Ð¿ÐµÑевода, позволÑÑÑие избегаÑÑ Ð´Ð¾Ñловного пеÑевода и ÑÑÑÑкÑÑÑно-ÑеманÑиÑеÑÐºÐ¸Ñ Ð±Ñквализмов, ÑÑо и бÑÐ´ÐµÑ Ð¿Ð¾ÐºÐ°Ð·Ð°Ð½Ð¾ на пÑакÑике ÑÑаÑÑникам маÑÑеÑ-клаÑÑа.
arXiv
We compare the revenue of the optimal third-degree price discrimination policy against a uniform pricing policy. A uniform pricing policy offers the same price to all segments of the market. Our main result establishes that for a broad class of third-degree price discrimination problems with concave revenue functions and common support, a uniform price is guaranteed to achieve one half of the optimal monopoly profits. This revenue bound obtains for any arbitrary number of segments and prices that the seller would use in case he would engage in third-degree price discrimination. We further establish that these conditions are tight, and that a weakening of common support or concavity leads to arbitrarily poor revenue comparisons.
SSRN
Cryptocurrencies embodied or represented in a âsmart contractâ, at first glance may be a new asset class, where depending on the internal method of classification and use different frameworks may be applicable. Although, most concepts are not necessarily new (inventive). As the digitalization of databases, information and systems do not change, the underlying object. It is analyzed, in particular, the case of payments tokens (contrasting with other forms of - public - money, in a narrow sense, so as with the hybrid cases, so-called âstable coinsâ), across jurisdictions, namely Switzerland, the UK, Germany and the US (as having most of the regulatory response or litigation), besides Portugal. It is broken down from the micro-level (token) to its exchange (as a means of exchange in a given contract) and infrastructure (messages, communications and infrastructure). There is a need to go beyond the formal representation (and dimensions) of a given entity, or the problem of knowledge representation and the need of (actual) systematic approach, to access function (rather than formal representation) and governance of the blockchain infrastructure.
SSRN
Firms seem to care a lot about "risk management'': the practice of hedging risks whether they are correlated with market risk or not. The standard reasons why widely held corporations might be averse to idiosyncratic risk are based on the principal-agent problem, bankruptcy costs, external finance, and tax convexity. This paper offers a different reason: idiosyncratic risk makes business decisions more difficult. Risk can increase the value of investment projects because of option value. We must distinguish, however, between risk over the expected value of profits ("value risk'') and risk over the volatility of cash flows ("cash-flow noise''). Value risk is good because an unprofitable policy can be abandoned. Cash-flow noise is bad because it makes learning when to abandon more difficult. This distinction is unrelated to Knightian risk or ambiguity aversion, and it matters even if the firm's agents are risk neutral.