Research articles for the 2020-09-03
SSRN
The Dodd-Frank Act allows the SEC to choose either an internal administrative proceeding or a federal district court as an enforcement venue for resolving violations of federal securities laws. I first document that the SEC increased the use of administrative proceedings after Dodd-Frank. I next examine the determinants and consequences of the SECâs choice of enforcement venue after the Dodd-Frank Act. Results show that more material cases are 28% to 35% more likely to be assigned to federal courts, and politically connected defendants are about 14% more likely to be routed to administrative proceedings. While monetary penalties by venue are statistically indifferent, politically connected defendants in administrative proceedings are associated with lower penalties. Additionally, I find that administrative proceedings process cases 27 times faster than federal courts. This study suggests that the SECâs private incentives affect its enforcement venue selection and possibly enforcement outcomes. When the political and economic costs (benefits) are greater, the SEC is more likely to use administrative proceedings (federal courts).
arXiv
We study large and moderate deviations for a life insurance portfolio, without assuming identically distributed losses. The crucial assumption is that losses are bounded, and that variances are bounded below. From a standard large deviations upper bound, we get an exponential bound for the probability of the average loss exceeding a threshold. A counterexample shows that a full large deviation principle does not follow from our assumptions.
arXiv
This paper compares mathematical models for automated market makers including logarithmic market scoring rule (LMSR), liquidity sensitive LMSR (LS-LMSR), constant product/mean/sum, and others. It is shown that though LMSR may not be a good model for Decentralized Finance (DeFi) applications, LS-LMSR has several advantages over constant product/mean based automated market makers. However, LS-LMSR requires complicated computation (i.e., logarithm and exponentiation) and the cost function curve is concave. In certain DeFi applications, it is preferred to have computationally efficient cost functions with convex curves to conform with the principle of supply and demand. This paper proposes and analyzes constant circle/ellipse based cost functions for automated market makers. It is shown that the proposed cost functions are computationally efficient (only requires multiplication and square root calculation) and have several advantages over widely deployed constant product cost functions.
arXiv
This paper examines the dynamic interaction between falling and rising markets for both the real and the financial sectors of the largest economy in the world using asymmetric causality tests. These tests require that each underlying variable in the model be transformed into partial sums of the positive and negative components. The positive components represent the rising markets and the negative components embody the falling markets. The sample period covers some part of the COVID19 pandemic. Since the data is non normal and the volatility is time varying, the bootstrap simulations with leverage adjustments are used in order to create reliable critical values when causality tests are conducted. The results of the asymmetric causality tests disclose that the bear markets are causing the recessions as well as the bull markets are causing the economic expansions. The causal effect of bull markets on economic expansions is higher compared to the causal effect of bear markets on economic recessions. In addition, it is found that economic expansions cause bull markets but recessions do not cause bear markets. Thus, the policies that remedy the falling financial markets can also help the economy when it is in a recession.
SSRN
Machine learning techniques have gained enormously in popularity in recent years, but so far only to a very limited extent in fixed income research. In this paper we therefore like to do some pioneering work and apply Boosted Regression Trees to Equity Momentum in the corporate bond market. We report large performance gains to investors using these machine learning driven forecasts, roughly doubling the alpha and information ratio to industry standard Equity Momentum factors. The most important variables within our model framework are the most recent equity performance, liquidity and size.
SSRN
The objective of this study is to explore the impact of commodity price volatility on the governmentsâ fiscal balance. Using a dynamic panel data model for 108 countries from 1993 to 2018, this study finds that governmentsâ fiscal balance deteriorates with commodity price volatility. A one standard deviation increase in commodity price volatility leads to a reduction of approximately 0.04 units in the fiscal balance as a percentage of gross domestic product. In addition, we examine the role of real interest rates in influencing the relationship between commodity price volatility and fiscal balance. The empirical results suggest that the negative impact of commodity price volatility on fiscal balance can be mitigated with lower real interest rate.
SSRN
This article examines how the issuance of a Digital Currency by a non-bank operator impacts competition between banks in a cashless society. I analyze how the fee charged for the digital currency impacts the interest rates on loans and the fees charged by banks to depositors for paying by card and opening an account in a bank. I derive the conditions under which consumers use the digital currency to pay.
arXiv
The Hicks induced innovation hypothesis states that a price increase of a production factor is a spur to invention. We propose an alternative hypothesis restating that a spur to invention require not only an increase of one factor but also a decrease of at least one other factor to offset the companies' cost. We illustrate the need for our alternative hypothesis in a historical example of the industrial revolution in the United Kingdom. Furthermore, we econometrically evaluate both hypotheses in a case study of research and development (R&D) in 29 OECD countries from 2003 to 2017. Specifically, we investigate dependence of investments to R&D on economic environment represented by average wages and oil prices using panel regression. We find that our alternative hypothesis is supported for R&D funded and/or performed by business enterprises while the original Hicks hypothesis holds for R&D funded by the government and R&D performed by universities. Our results reflect that business sector is significantly influenced by market conditions, unlike the government and higher education sectors.
arXiv
This paper considers how to elicit information from sensitive survey questions. First we thoroughly evaluate list experiments (LE), a leading method in the experimental literature on sensitive questions. Our empirical results demonstrate that the assumptions required to identify sensitive information in LE are violated for the majority of surveys. Next we propose a novel survey method, called Multiple Response Technique (MRT), for eliciting information from sensitive questions. We require all of the respondents to answer three questions related to the sensitive information. This technique recovers sensitive information at a disaggregated level while still allowing arbitrary misreporting in survey responses. An application of the MRT provides novel empirical evidence on sexual orientation and Lesbian, Gay, Bisexual, and Transgender (LGBT)-related sentiment.
SSRN
This paper deals with the problem of capital allocation for a peculiar class of risk measures, namely the Haezendonck-Goovaerts (HG) ones. We generalize the capital allocation rule (CAR) introduced by Xun et al. for Orlicz risk premia, using firstly an approach based on Orlicz quantiles and secondly a more general one based on the, here introduced, concept of linking functions. Further on, we use the same construction of to extend the CARs previously introduced to HG risk measures. We therefore study the properties of different CARs for HG risk measures, both in the quantile-based setting and in the linking one. Finally, we provide robust versions of the introduced CARs, both considering the case of ambiguity over the probabilistic model and the one of multiple Young functions, following the scheme of.
SSRN
The COVID-19 pandemic is impacting global markets through unprecedented circumstances. Fears surrounding such novel virus has led to dramatic market turbulence and massive tumbles in stock prices. In this paper, we explore the impact of COVID-19 on a comprehensive sample of 45 emerging countries. We track the performance of each of the markets during the outbreak using its major stock index and we compute the volatilities using a GARCH (1,1) model. Moreover, we report conventional and Islamic bond issuances and assess investors' perceptions towards credit risk by examining the premiums on sovereign credit default swaps. We then compare the results to the global financial crisis period. We find that indeed COVID-19 has harshly struck the emerging countries driving sharp declines in stock market indices, causing an escalation in volatility levels, and widening the premiums on sovereign credit default swaps. However, such upheavals did not yet reach the global financial crisis levels. We finally examine the reactions of the IMF and local governments and central banks in response to such crisis.
SSRN
Investors have a lot of investment avenues to park their savings. The risk and returns available from each of these investment avenues differ from one avenue to another. The investors expect more returns with relatively lesser risks. In this regard, the financial advisors and consultants offer various suggestions to the investors. The available literature relating to the investors' attitude towards investment avenues is very little and failed to provide a lot of information. An attempt has been made in this study to find out the main objective of the investors in Coimbatore District towards making investments and to assess the investors' attitude towards the investment avenues. The demographic variables and objectives of the investors have been obtained from the respondents and the relationship between these variables and objectives has been computed. The attitude of the respondents towards the select investment avenues has been ranked. The study also offers suggestions to the investors to make investments.
SSRN
We provide a comprehensive overview of the role of institutional investors in corporate governance with three main components. First, we provide a detailed characterization of key aspects of the legal and regulatory setting within which institutional investors govern portfolio firms. Second, we establish new stylized facts documenting the evolution and importance of institutional ownership. Third, we synthesize the evolving âresponseâ of the recent theoretical and empirical academic literature in finance to the emergence of institutional investors in corporate governance. We highlight how the defining aspect of institutional investors â" the fact that they are financial intermediaries â" differentiates them in their governance role from standard principal block-holders. Further, not all institutional investors are identical, and we pay close attention to heterogeneity amongst institutional investors as block-holders.
SSRN
We use search queries with the word âCORONAVIRUSâ in Google Trends as a proxy for investorsâ attention and track its impact on the stock markets and sovereign risk. By using daily data of 41 countries for the period of January-June 2020, it is found that increased coronavirus related search is negatively linked with stock market returns and positively linked with country risk. Further, stock market returns are depressed, and sovereign risk is higher in developed countries than emerging countries in response to rising concern about the spread of COVID-19.
SSRN
I show that rising temperatures can detrimentally affect the sovereign creditworthiness of emerging economies. To this end, I collect long-term monthly temperature data of 54 emerging countries. I calculate a country's temperature deviation from its historical average, which approximates present day climate change trends. Running regressions from 1994m1-2018m12, I find that higher temperature anomalies lower sovereign bond performances (i.e. increase sovereign risk) significantly for countries that are warmer on average and have lower seasonality. The estimated magnitudes suggest that affected countries likely face significant increases in their sovereign borrowing costs if temperatures continue to rise due to climate change. However, results indicate that stronger institutions can make a country more resilient towards temperature shocks, which holds independent of a country's climate.
arXiv
In this paper we propose an efficient pricing-hedging framework for volatility derivatives which simultaneously takes into account path roughness and jumps. Instead of dealing with log-volatility, we directly model the instantaneous variance of a risky asset in terms of a fractional Ornstein-Uhlenbeck process driven by an infinite-activity L\'{e}vy subordinator, which is shown to exhibit roughness under suitable conditions and also eludes the need for an independent Brownian component. This structure renders the characteristic function of forward variance obtainable at least in semi-closed form, subject to a generic integrable kernel. To analyze financial derivatives, primarily swaps and European-style options, on average forward volatility, we introduce a general class of power-type derivatives on the average forward variance, which also provide a way of adjusting the option investor's risk exposure. Pricing formulae are based on numerical inverse Fourier transform and, as illustrated by an empirical study on VIX options, permit stable and efficient model calibration once specified.
SSRN
We propose and find that enhanced regulatory transparency facilitates alignment between private and public enforcement. Utilizing the SECâs 2004 decision to publicly disclose its comment letters, we explore the actions of a public enforcer (the SEC) and a private enforcer (shareholder litigants). The two partiesâ enforcement targets are more aligned in the post-public-disclosure period. The increased alignment is attributable to two channels. First, SECâs actions are subject to greater public scrutiny, enhancing regulator incentives and reducing regulatory capture. Second, shareholder plaintiffs gain information previously accessible only by regulators, enabling litigants to identify cases with âmerit,â reducing nuisance suits and earning larger settlements.
SSRN
Social inflation refers to steeply rising insurance rates due to social factors such as large jury awards and broader definitions of liability. This paper is the first to study the risk of social inflation and its economic consequences. Using a novel, hand-matched dataset that spans verdicts, financial statements, and insurance rate filings for commercial auto liability, I find that the number of verdicts and settlements exceeding $50 million has increased almost threefold from 2011 to 2019. To highlight the role of these nuclear awards in insurance pricing, I build a model of social inflation and show that social inflation risk has a âdouble kickâ effect on insurance price through increased effective marginal cost and heightened required reserves. I then use both a case study and a triple-difference framework to illustrate the causal impact of social inflation risk on insurance rates. Finally, I discuss implications for insurers during the COVID-19 pandemic facing social inflation: the risks of retroactive modification and extended interpretation of existing insurance policies. Ultimately, I uncover an important new source of aggregate risk that affects the stability of the insurance sector and the economic activities that depend on it.
arXiv
We consider optimal stopping problems with finite-time horizon and state-dependent discounting. The underlying process is a one-dimensional linear diffusion and the gain function is time-homogeneous and difference of two convex functions. Under mild technical assumptions with local nature we prove fine regularity properties of the optimal stopping boundary including its continuity and strict monotonicity. The latter was never proven with probabilistic arguments. We also show that atoms in the signed measure associated with the second order spatial derivative of the gain function induce geometric properties of the continuation/stopping set that cannot be observed with smoother gain functions (we call them \emph{continuation bays} and \emph{stopping spikes}). The value function is continuously differentiable in time without any requirement on the smoothness of the gain function.
SSRN
This article investigates the random walk behavior of CIVETS (Colombia, Indonesia, Vietnam, Egypt, Turkey and South Africa) foreign exchange rates against the US dollar using weekly data from February 2007 to April 2012. Using variance ratio tests, the results suggest that the nominal exchange rates of Vietnamese dong and Egyptian pounds violate the random walk hypothesis and do not follow a martingale process. However, the Colombian peso, Indonesian rupiah, Turkish lira and South African rand exchange rate markets are considered weak-form efficient.
SSRN
The purpose of this paper is to investigate the relationship between the share price volatility in Pakistan and their dividend policies which affect the share price. We use dividend yield and dividend payout as proxies of dividend policy, and regress these ratios together with other control variables. We model share price volatility as a function of dividend policy which is proxies through dividend yield and dividend payout ratios using data for the period 2010â"2019 collected from Karachi stock exchange. The variables involved in the study were Dividend yield, Price volatility Earning Volatility, Payout ratio, size were independent variables and Price volatility is dependent variables. The findings of this study are that the payout ratio and price volatility is significantly positively related. The size and debt are negatively related to share price volatility. This study proposed that dividend yield is a better and more important determinant factor in determining share price volatility in the KSE 100 index rather than payout ratio.
SSRN
Research summary: Drawing on the âvarieties of capitalismâ literature, we develop an actor-centered framework that explains firm-level corporate social performance (CSP) by emphasizing the importance of considering ownersâ and other stakeholdersâ motives towards CSP â" which can be instrumental, relational or moral â" and their salience in the national institutional setting. Results from an international panel show that investment company (government) ownership has a stronger negative (positive) relationship with CSP in liberal markets, in which owners are the key stakeholder, as compared to coordinated markets, which counterbalance the interests of multiple stakeholders. Family and company ownership have weaker links to CSP across institutional settings. We discuss implications for research and practice and argue that CSP policies may hold more relevance in liberal rather than coordinated market economies.Managerial summary: Existing debates focus on the impact of corporate social performance (CSP) on firm outcomes. Less is known about the motives and pressures behind CSP, which may explain its variability across firms and institutional settings. We argue that powerful ownersâ motives are important for explaining CSP in liberal markets, where shareholders are the most important stakeholder, as compared to coordinated markets, which confer prominence to multiple stakeholders. Ownersâ motives are not homogeneous and depending on the type of owners the link between ownership concentration and CSP can be negative (for investment companies) or positive (for governments). In coordinated markets, owners have a weaker impact on CSP, which is mostly attributable to their lower salience relative to stakeholders, rather than to a change in their motives.
SSRN
This paper examines the time and frequency dynamics of connectedness between oil price shocks (demand and supply), and energy, electricity, carbon and clean energy markets using the methodology developed by Diebold and Yilmaz (2012) and Barunik and Krehlik (2018). The empirical findings show that there is time-varying connectedness among all variables in the sample. We find increased connectedness during the global financial crisis as well as in the shale oil revolution period. The total connectedness is more significant and higher in the short-term compared to the long-term. Net pairwise directional connectedness become more important during the shale oil revolution among oil supply, oil demand and clean energy index. The findings of the static full sample and sub-samples (GFC and SOR) provide significant evidence of the electricity futures as diversifier and safe-haven asset for oil shocks. These results can have important implications for investors and policymakers with different time horizons.
arXiv
Earnings calls are hosted by management of public companies to discuss the company's financial performance with analysts and investors. Information disclosed during an earnings call is an essential source of data for analysts and investors to make investment decisions. Thus, we leverage earnings call transcripts to predict future stock price dynamics. We propose to model the language in transcripts using a deep learning framework, where an attention mechanism is applied to encode the text data into vectors for the discriminative network classifier to predict stock price movements. Our empirical experiments show that the proposed model is superior to the traditional machine learning baselines and earnings call information can boost the stock price prediction performance.
arXiv
We use a randomized experiment to compare a workforce training program to cash transfers in Rwanda. Conducted in a sample of poor and underemployed youth, this study measures the impact of the training program not only relative to a control group but relative to the counterfactual of simply disbursing the cost of the program directly to beneficiaries. While the training program was successful in improving a number of core outcomes (productive hours, assets, savings, and subjective well-being), cost-equivalent cash transfers move all these outcomes as well as consumption, income, and wealth. In the head-to-head costing comparison cash proves superior across a number of economic outcomes, while training outperforms cash only in the production of business knowledge. We find little evidence of complementarity between human and physical capital interventions, and no signs of heterogeneity or spillover effects.