Research articles for the 2019-05-15
SSRN
We examine the Centros decision through the lens of SB 826 â" the California statute mandating a minimum number of women on boards. SB 826, like the Centros decision, raises questions about the scope of the internal affairs doctrine and its role in encouraging regulatory competition. Despite the claim that US corporate law is characterized by regulatory competition, in the US, the internal affairs doctrine has led to less variation in corporate law than in Europe. We theorize that this is due to the shareholder primacy norm in US corporate law which results in the internal affairs doctrine focusing on matters of shareholder interest and, primarily, shareholder economic interest. We argue that the internal affairs doctrine should be understood within the context of the shareholder primacy norm and therefore directed to rules oriented to enhancing firm economic value. In contrast, EU corporate law has traditionally had broader stakeholder orientation. We posit that the limited impact of the Centros decision, an impact which differed significantly from its predicted revolutionary effect, can be attributed to the greater focus of EU corporate law on social ordering and extra-shareholder interests. This difference leads to a new understanding of SB 826 as reflecting a move toward more EU-style governance focused on social ordering. Ironically, Californiaâs adoption of SB 826 may portend a movement of the United States towards Centros-style governance. Under this analysis, we argue that SB 826 should not be viewed as inconsistent with the internal affairs doctrine since it involves social ordering rather than purely shareholder interests.
SSRN
For a Lévy process, in which asset prices are corrupted with microstructure noise, I derive the sampling distributions for the information-related and information-unrelated pricing error parameters as well as for the variance of the latent true price returns (a noise-robust estimate of realized variance). The resulting test statistics are standard normally distributed and simulation studies show that they display good properties. Joint tests as well as tests for time varying parameters follow Ï2 distributions. As an empirical example, the proposed statistical tests are taken to a high-frequency data sample of exchange rates, commodities, and index futures.
arXiv
Uncovering the structure of socioeconomic systems and timely estimation of socioeconomic status are significant for economic development. The understanding of socioeconomic processes provides foundations to quantify global economic development, to map regional industrial structure, and to infer individual socioeconomic status. In this review, we will make a brief manifesto about a new interdisciplinary research field named Computational Socioeconomics, followed by detailed introduction about data resources, computational tools, data-driven methods, theoretical models and novel applications at multiple resolutions, including the quantification of global economic inequality and complexity, the map of regional industrial structure and urban perception, the estimation of individual socioeconomic status and demographic, and the real-time monitoring of emergent events. This review, together with pioneering works we have highlighted, will draw increasing interdisciplinary attentions and induce a methodological shift in future socioeconomic studies.
SSRN
We conduct firm and industry level examinations of key market risk exposures deemed material by managers over the period 2002â"2016. We find that risk exposures have expanded in line with firmsâ growth and globalization and that managers strategically select disclosure formats in recognition of firmsâ demand for capital market access and need to protect proprietary information. Currency derivatives use has surpassed that of interest rate derivatives and, conditioned on a firm having the associated risk exposure, commodity derivatives use is the highest. Finally, we find large increases in risk exposures concurrent with the initiation of derivatives use.
arXiv
The econometric challenge of finding sparse mean reverting portfolios based on a subset of a large number of assets is well known. Many current state-of-the-art approaches fall into the field of co-integration theory, where the problem is phrased in terms of an eigenvector problem with sparsity constraint. Although a number of approximate solutions have been proposed to solve this NP-hard problem, all are based on relatively simple models and are limited in their scalability. In this paper we leverage information obtained from a heterogeneous simultaneous graphical dynamic linear model (H-SGDLM) and propose a novel formulation of the mean reversion problem, which is phrased in terms of a quasi-convex minimisation with a normalisation constraint. This new formulation allows us to employ a cyclical coordinate descent algorithm for efficiently computing an exact sparse solution, even in a large universe of assets, while the use of H-SGDLM data allows us to easily control the required level of sparsity. We demonstrate the flexibility, speed and scalability of the proposed approach on S\&P$500$, FX and ETF futures data.
SSRN
We study the dynamics of sovereign risk spillovers from (and between) Spain and Italy, before and after the ECB's announcement of the OMT program. We identify domestic Italian and Spanish sovereign risk shocks through an intraday event study. The shocks are used as external instruments in bilateral, daily, local projection regressions. Prior to the announcement of the OMT, changes in the Spanish and, to a lesser extent, Italian spread spilled over to many other euro area member states, and also affected the euro-dollar exchange rate. Peak effects generally materialized after 2-3 days. Since the OMT announcement, spillovers to non-crisis, non-safe haven countries have disappeared. Some spillovers among crisis countries persist, but are smaller and shorter-lived than before. Overall, our results are consistent with the view that the OMT, through eliminating equilibrium multiplicity, has largely stopped contagion.
SSRN
Considerable effort has been devoted by economists to understand the aggregate impact of debt finance. Despite the lack of similar attention to equity, we show empirically that equity finance plays a leading role in corporate asset growth. An extra dollar of equity issuance is associated with $0.93 more real assets, while an extra dollar of debt is associated with an extra $0.14 of real assets. We find a typical financing-growth sequence in which equity finance comes first, then real assets grow, and after that debt increases while equity is repurchased. To explain this process we provide a model in which debt is tax-preferred, but it requires collateral. In the model, firms initially issue equity to finance investments. After they obtain assets that can be pledged to lenders, firms substitute debt for equity to benefit from interest tax deductions. We use the model to evaluate: 1) the 1996 National Securities Markets Improvement Act that facilitated equity financing, 2) a government policy to limit corporate debt, and 3) a government policy to limit share buybacks.
SSRN
Using household-level survey and housing transaction data, we detect the flight to safety vis-a-vis housing in China: Great economic uncertainty causes the prices of housing assets to soar, especially those of good quality. To stabilize housing prices, China has imposed purchase restrictions on the housing market. In this paper, we study the aggregate and distributional effects of this housing policy by developing a two-sector macroeconomic model with heterogeneous households. An uncertainty shock generates a countercyclical housing boom by shifting outward households' demand for housing as a store of value. A vibrant housing sector then leads to an economic recession by crowding out resources that could have been allocated to the real sector. Our quantitative analysis suggests that the policy limiting housing purchases effectively curbs surging housing prices. However, the policy restricts households' access to housing that can be used to buffer idiosyncratic uncertainties, creating a larger consumption dispersion. Consequently, the housing policy creates a trade-off between macro-level stability and micro-level consumption risk sharing.
arXiv
In the present paper, a decomposition formula for the call price due to Al\`{o}s is transformed into a Taylor type formula containing an infinite series with stochastic terms. The new decomposition may be considered as an alternative to the decomposition of the call price found in a recent paper of Al\`{o}s, Gatheral and Radoi\v{c}i\'{c}. We use the new decomposition to obtain various approximations to the call price in the Heston model with sharper estimates of the error term than in the previously known approximations. One of the formulas obtained in the present paper has five significant terms and an error estimate of the form $O(\nu^{3}(\left|\rho\right|+\nu))$, where $\nu$ is the vol-vol parameter, and $\rho$ is the correlation coefficient between the price and the volatility in the Heston model. Another approximation formula contains seven more terms and the error estimate is of the form $O(\nu^4(1+|\rho|)$. For the uncorrelated Hestom model ($\rho=0$), we obtain a formula with four significant terms and an error estimate $O(\nu^6)$. Numerical experiments show that the new approximations to the call price perform especially well in the high volatility mode.
arXiv
We study two-dimensional stochastic differential equations (SDEs) of McKean--Vlasov type in which the conditional distribution of the second component of the solution given the first enters the equation for the first component of the solution. Such SDEs arise when one tries to invert the Markovian projection developed by Gy\"ongy (1986), typically to produce an It\^o process with the fixed-time marginal distributions of a given one-dimensional diffusion but richer dynamical features. We prove the strong existence of stationary solutions for these SDEs, as well as their strong uniqueness in an important special case. Variants of the SDEs discussed in this paper enjoy frequent application in the calibration of local stochastic volatility models in finance, despite the very limited theoretical understanding.
SSRN
I investigate influences of unemployment insurance benefits on the cost of bank loans by exploiting changes in state unemployment insurance laws as a source of variation in labor unemployment costs. The evidence shows that the cost of bank loans is significantly lower for firms headquartered in states with more generous unemployment insurance benefits. I also find that higher unemployment insurance benefits reduce the loan spreads particularly for labor intensive and unionized firms. Empirical results are robust to controlling for loan characteristics, macroeconomic conditions and borrower characteristics. Overall, results suggest that credit markets respond to workersâ unemployment costs while approving and pricing loan contracts.
SSRN
This paper documents empirically that increases in the book-to-market spread predict larger market premiums in sample and larger size, value, and investment premiums (also) out of sample. In addition, increases in the investment (or profitability) spread exclusively predict larger investment (or profitability) premiums. This predictability generates âfactor timingâ strategies that deliver substantial economic gains out of sample. I argue theoretically that the book-to-market spread is a price of risk proxy, while the investment and profitability spreads are factor risk proxies. The evidence confirms standard theoretical predictions in the macro-finance literature and contradicts the hypothesis of constant factor risks.
SSRN
We look at managerial activism through collective action in the corporate sector. Activist managers spend considerable resources on lobbying, lawsuits and public statements to pursue pro-business as well as pro-manager issues. While managerial activism is valuable in following pro-business strategies, pro-manager agendas may exacerbate agency problems. We find evidence more towards the pro-business role of managerial activism. Specifically, operating performance improves with managerial activism, and this improvement is observed primarily in firms that are government dependent, produce differentiated products, operate in concentrated industries or have more intangible assets. Corporate governance of firms with activist managers is comparable to other firms. While market differentiates managerial activism pursued for pro-manager agendas and responds unfavorably to such activism, in the overall, managerial activism adds value to firms, especially when information dissemination is more essential due to firm characteristics.
SSRN
We textually analyze 10-K texts from EDGAR during 1995-2009 to score firmsâ investment opportunity sets on multiple dimensions. We identify 646 unique key words that predict future investments and group them into 62 factors. Industry-specific factors include Bio-Pharmaceutical, Banking, Information Technology, Oil & Gas and Semi-conductor, while more general factors include Impairment, Debt Intensity, Executive Changes, Preferred Stock Buyback and Capital Seeking. Our multi-dimensional measures of firmsâ investment opportunities outperform Tobinâs Q and/or industry-fixed effects, in predicting out-of-sample future (2010-15) investments and related corporate policies, and even inform incrementally over lagged dependent variables. Our IOS factors outperform Tobinâs Q more in subsamples with less efficient market prices, i.e., when Tobinâs Q is a noisier signal of investment opportunities.
SSRN
This paper examines factors that affect the profitability of momentum returns for the US, the UK, Japan, and Germany, for the period 1998-2018. More specifically, the paper examines the impact of factors that have been largely neglected in the relevant literature, such as energy price changes and economic policy uncertainty, along with macroeconomic and risk factors on the profitability of professional momentum portfolios that are often used as benchmarks in the institutional investor industry. The results indicate that, since the financial crises in the US and the EU, energy prices and economic-policy uncertainty have become important return determinants, along with market-related uncertainty that seems to have a stable impact overtime, especially for the US and UK portfolios. For example, between 2007 and 2018, oil price variance accounts for 20.80% of US momentum return variance while natural gas price variance explains a further 10.57% of momentum return variance in the US.
SSRN
We study momentum and its predictability within equities listed at the London Stock Exchange (1820-1930). At the time, this was the largest and most liquid stock market and it was thinly regulated, making for a good laboratory to perform out-of-sample tests. Cross-sectionally, we find that the size and market factors are highly profitable, while long-term reversals are not. Momentum is the most profitable and volatile factor. Its returns resemble an echo: they are high in long-term formation portfolios, and vanish in short-term ones. We uncover momentum in dividends as well. When controlling for dividend momentum, price momentum loses significance and profitability. In the time-series, despite the presence of a few momentum crashes, dynamically hedged portfolios do not improve the performance of static momentum. We conclude that momentum returns are not predictable in our sample, which casts some doubt on the success of dynamic hedging strategies.
SSRN
Mutual funds are structurally different from other corporations. The corporation or trust is controlled by an external entity: an investment management firm that profits from fees charged to manage the fundâs portfolio. Recognizing this fundamental conflict of interest, in 1970 Congress made investment management firms fiduciaries with respect to fees charged their captive funds. In the nearly fifty years since then, the courts have interpreted their fiduciary duty so narrowly that no plaintiff has met the judicially established fiduciary standard. This paper presents and analyzes empirical evidence on advisory and sub-advisory fees and shows how the courts and the Securities and Exchange Commission can better enforce the fiduciary duty imposed on investment management firms.
SSRN
This paper provides new evidence on the effect of housing wealth on consumption by focusing on the impact of home-equity extraction. We develop a household consumption decision model to illustrate the differential effect of home-equity extraction, relative to net home equity, on consumption. The home-equity extraction channel is also shown to vary with household-lever borrowing constraints. Based on U.S. household survey data and an instrumental-variables approach, our empirical results validate model predictions. We find that the marginal propensity to consume is two times higher for the home-equity extraction channel relative to the conventional housing wealth effect. The consumption effect of home-equity extraction is more than 2.5 times greater for liquidity-constrained households than for unconstrained households. These results are even more pronounced in the case of durable goods consumption for constrained borrowers.
SSRN
Within a standard risk-based asset pricing framework with rational expectations, realized returns have two components: Predictable risk premiums and unpredictable shocks. In bad times, the price of risk increases. Hence, the predictable fraction of returns -- and predictability -- increases. "Disagreement" (dispersion in analyst forecasts) also grows in bad times if (i) analysts report risk-neutral expectations weighted by state prices, which become more volatile, or (ii) dividend volatility changes with the price of risk, for example because consumption volatility changes. In both cases, individual analysts produce unbiased forecasts based on partial information.
arXiv
Electricity accounts for 25% of global greenhouse gas emissions. Reducing emissions related to electricity consumption requires accurate measurements readily available to consumers, regulators and investors. In this case study, we propose a new real-time consumption-based accounting approach based on flow tracing. This method traces power flows from producer to consumer thereby representing the underlying physics of the electricity system, in contrast to the traditional input-output models of carbon accounting. With this method we explore the hourly structure of electricity trade across Europe in 2017, and find substantial differences between production and consumption intensities. This emphasizes the importance of considering cross-border flows for increased transparency regarding carbon emission accounting of electricity.
arXiv
We formulate banks' capital optimization problem as a classic mean variance optimization, by leveraging an accurate linear approximation to the Shapely or Constrained Aumann-Shapley (CAS) allocation of max or nested max cost functions. This reduced form formulation admits an analytical solution, to the optimal leveraged balance sheet (LBS) and risk weighted assets (RWA) target of banks' business units for achieving the best return on capital.
SSRN
Nick Szabo defined smart contracts as, ââ¦.a set of promises, specified in digital form, including protocols within which the parties perform on the other promises.â The essence of a smart contract is that it is self-executing and has a protocol to effect this, i.e. the mechanism for communicating with the smart contract. In addition, Szabo distilled four basic objectives of any contract that should be fulfilled by smart contracts. Two of these, verifiability and enforceability, are given more attention in this paper. Szabo, however, did not address what types of contracts would be most suited to be executed as smart contracts.This paper describes first the unique aspects of financial contracts that make them the most promising candidates for implementation as smart contracts. Secondly, we analyze the conditions under which the use of distributed ledgers and smart financial contracts are most likely to prove successful. This analysis concludes that unless a distributed ledger is combined with an algorithmic financial contract standard and a standard protocol, the potential benefits of smart contracts will not be realized. The corollary to this conclusion is that it is essential for FinTech to adopt such a standard in order to be able to realize its promise of a paradigm shift in finance. The combination of distributed ledger technology and an open, well documented and well tested algorithmic financial contract standard is the next logical step in the development of FinTech.
SSRN
This paper contributes a shred of quantitative evidence to the embryonic literature as well as existing empirical evidence regarding spillover risks among cryptocurrency markets. By using VAR (Vector Autoregressive Model)-SVAR (Structural Vector Autoregressive Model) Granger causality and Studentâs-t Copulas, we find that Ethereum is likely to be the independent coin in this market, while Bitcoin tends to be the spillover effect recipient. Our study sheds further light on investigating the contagion risks among cryptocurrencies by employing Studentâs-t Copulas for joint distribution. This result suggests that all coins negatively change in terms of extreme value. The investors are advised to pay more attention to âbad newsâ and moving patterns in order to make timely decisions on three types (buy, hold, and sell).
SSRN
We employ a recursive econometric technique to identify and date multiple financial bubbles in five countries, the US, UK, France, Germany, and Japan. We identify multiple bubbles in each country except Germany for the period, 1973-March 2018. These bubbles are classified into three groups, each clustered around a significant financial event. The results show that if there is no synchronicity in the timing of bubbles, overall annualized returns are positive even after the bubbles burst. However, during the subprime mortgage crisis bubble, all nations experienced simultaneous, short bubbles with returns falling sharply in all countries. Thus, one can conclude that if bubbles do not coincide investors are better off riding out the bubble.
arXiv
We introduce a new tool for predicting the evolution of an option for the cases where at some specific time, there is a high-degree of uncertainty for identifying its price. We work over the special case where we can predict the evolution of the system by joining a single price for the Option, defined at some specific time with a pair of prices defined at another instant. This is achieved by describing the evolution of the system through a financial Hamiltonian. The extension to the case of multiple prices at a given instant is straightforward. We also explain how to apply these results in real situations.
SSRN
A large literature debates the link between news and investor decision making. Relying on unique U.S. firm-level news data between 1979 and 2016, we document the cross-sectional difference in the speed of diffusion of the information contained in news. We distinguish news articles as being either slowly or quickly incorporated into contemporaneous stock prices. The return spread between these two types of news yields a statistically significant profitability (94 basis points per month) and this effect cannot be explained by other well-known risk factors. By employing novel attention data (Google Search Volume Index and Bloomberg News Readerships Index), we find that this news-induced anomaly can be attributed to limited-attention theory where firm-specific news is not read by investors. Our research refines the role of news regarding information dissemination in the financial markets.
SSRN
Tontines are useful vehicles for providing retirement income. Their payouts, however, will necessarily vary as a function of investment returns and the mortality experience of the membership pool. Retirees who place a high value on income stability will desire to minimize the variability of these payouts. This can be accomplished via a large membership pool to minimize the effect of mortality experience volatility and by using immunizing cash-flow matching techniques to minimize the effect of investment volatility. A structured bond ladder can achieve this quite effectively.
arXiv
Management of systemic risk in financial markets is traditionally associated with setting (higher) capital requirements for market participants. There are indications that while equity ratios have been increased massively since the financial crisis, systemic risk levels might not have lowered, but even increased. It has been shown that systemic risk is to a large extent related to the underlying network topology of financial exposures. A natural question arising is how much systemic risk can be eliminated by optimally rearranging these networks and without increasing capital requirements. Overlapping portfolios with minimized systemic risk which provide the same market functionality as empirical ones have been studied by [pichler2018]. Here we propose a similar method for direct exposure networks, and apply it to cross-sectional interbank loan networks, consisting of 10 quarterly observations of the Austrian interbank market. We show that the suggested framework rearranges the network topology, such that systemic risk is reduced by a factor of approximately 3.5, and leaves the relevant economic features of the optimized network and its agents unchanged. The presented optimization procedure is not intended to actually re-configure interbank markets, but to demonstrate the huge potential for systemic risk management through rearranging exposure networks, in contrast to increasing capital requirements that were shown to have only marginal effects on systemic risk [poledna2017]. Ways to actually incentivize a self-organized formation toward optimal network configurations were introduced in [thurner2013] and [poledna2016]. For regulatory policies concerning financial market stability the knowledge of minimal systemic risk for a given economic environment can serve as a benchmark for monitoring actual systemic risk in markets.