Research articles for the 2019-03-12
SSRN
We provide first empirical evidence of the long-term realized performance of alternative beta strategies. Despite diversified risk premia portfolios achieving satisfactory Sharpe ratios of 0.80 â" 1.07 over the past decade, we show that up to two thirds of the performance can be explained by exposure to traditional benchmarks. We find no evidence of positive alpha in the aggregate industry returns, and document a pattern of time-varying, asymmetric, and statistically significant betas to global equities and bonds. We highlight the sensitivity of the results to strategy fees and identify an economically meaningful survivorship bias in publicly available strategy data.
SSRN
Using a unique data set on provincial net factor income flows disaggregated across the three asset classes of debt, equity and FDI reinvested earnings in Korea, we investigated how these asset channels impacted consumption risk sharing during the Global Financial Crisis and the European sovereign debt crisis. Adopting spatial panel methods, this study found that net receipts of debt, equity and FDI retained earnings have all contributed favorably to consumption risk sharing during these crises episodes, with FDI retained earnings robustly positive in its contribution in buffering shocks to consumption. We also found suggestive evidence that net equity receipts rather than net debt receipts contributed more to risk sharing during these episodes. Overall, our results indicate that different asset channels can provide the insurance needed to cushion the economy against adverse shocks.
arXiv
We introduce a Cox-type model for relative intensities of orders flows in a limit order book. The model assumes that all intensities share a common baseline intensity, which may for example represent the global market activity. Parameters can be estimated by quasi likelihood maximization, without any interference from the baseline intensity. Consistency and asymptotic behavior of the estimators are given in several frameworks, and model selection is discussed with information criteria and penalization. The model is well-suited for high-frequency financial data: fitted models using easily interpretable covariates show an excellent agreement with empirical data. Extensive investigation on tick data consequently helps identifying trading signals and important factors determining the limit order book dynamics. We also illustrate the potential use of the framework for out-of-sample predictions.
SSRN
This study exploits a new long-run data set of daily bid and offered exchange rates in spot and forward markets from 1919 to the present to analyze carry returns in fixed and floating currency regimes. We first find that outsized carry returns occur exclusively in the floating regime, being zero in the fixed regime. Second, we show that fixed-to-floating regime shifts are associated with negative returns to a carry strategy implemented only on floating currencies, robust to the inclusion of volatility risks. These shifts are typically characterized by global flight-to-safety events that represent bad times for carry traders.
SSRN
We demonstrate theoretically and empirically that financial development of the destination country is as important as that of the origin country in shaping bilateral trade patterns, on both the extensive margin and the intensive margin of trade.
SSRN
We find that the threat of takeover has a negative relation with default risk. The result is robust to alternative estimation methods, different measures of default, exclusion of the financial crisis period and over a number of sub-periods. We identify improvement in performance and earnings quality in response to the threat of takeover as channels underlying our main result. We find that the threat of takeover on default risk is more pronounced for firms with low information asymmetry and institutional ownership. Our findings provide important insights for the market for corporate control as a disciplining mechanism in reducing default risk.
arXiv
In the last five years, the financial industry has been impacted by the emergence of digitalization and machine learning. In this article, we explore two methods that have undergone rapid development in recent years: Gaussian processes and Bayesian optimization. Gaussian processes can be seen as a generalization of Gaussian random vectors and are associated with the development of kernel methods. Bayesian optimization is an approach for performing derivative-free global optimization in a small dimension, and uses Gaussian processes to locate the global maximum of a black-box function. The first part of the article reviews these two tools and shows how they are connected. In particular, we focus on the Gaussian process regression, which is the core of Bayesian machine learning, and the issue of hyperparameter selection. The second part is dedicated to two financial applications. We first consider the modeling of the term structure of interest rates. More precisely, we test the fitting method and compare the GP prediction and the random walk model. The second application is the construction of trend-following strategies, in particular the online estimation of trend and covariance windows.
SSRN
We derive optimal hedging ratios for interest rate risk under different assumptions that underpin the relationship between the forward rate and the expected future spot rate. In some instances, full hedging is optimal, and the conditions for the optimality of a partial hedge are identified. Less hedging is more optimal under the liquidity preference model than under the unbiased expectations hypothesis. This indicates that in times of higher preference for liquidity less hedging is optimal. Higher preference for liquidity correlates with larger term spreads (a steeper yield curve) and periods of monetary easing. Comparison of the analytical results with historical data indicates that partial hedging for interest rate risk is generally preferable over full hedging strategies with some exceptions. Lastly, the paper shows the role of market timing on hedging decisions.
arXiv
We develop an alternative theory to the aggregate matching function in which workers search for jobs through a network of firms: the labor flow network. The lack of an edge between two companies indicates the impossibility of labor flows between them due to high frictions. In equilibrium, firms' hiring behavior correlates through the network, generating highly disaggregated local unemployment. Hence, aggregation depends on the topology of the network in non-trivial ways. This theory provides new micro-foundations for the Beveridge curve, wage dispersion, and the employer-size premium. We apply our model to employer-employee matched records and find that network topologies with Pareto-distributed connections cause disproportionately large changes on aggregate unemployment under high labor supply elasticity.
SSRN
We use unique firm level data from Mexico to document that non-financial corporations engage in carry trades by borrowing in foreign currency and lending in domestic currency, largely to related partners (trade credit), accumulating currency risk in the process. The interest rate differential between local and foreign currency borrowing largely drives this behavior at a quarterly frequency, inducing an expansion in gross trade credit and sales. Firms that were active in carry-trade have decreased investment following a large depreciation, independent of currency exposure levels and export status, but maintain their supply of trade credit.
SSRN
We analyze the underlying source of gender differences in earnings estimates on a crowd-sourcing platform with low barriers to entry. This platform allows us to examine gender differences within earnings estimates among a sample of non-professional analysts in an effort to better understand the development of analyst ability. Estimates made by females are more accurate than those made by males. We eliminate explanations of more talented females joining the platform, an innate ability of females to process information, females utilizing more up-to-date information, superior stock selection among females, and survivor ship bias. Rather, our evidence is consistent with females learning faster and males exhibiting greater overconfidence. Our findings provide new insight into the mechanisms behind the increase in accuracy documented among professional female analysts. Finally, we observe a positive market response when females provide more optimistic estimates.
arXiv
This tutorial provides a gentle introduction to the particle Metropolis-Hastings (PMH) algorithm for parameter inference in nonlinear state-space models together with a software implementation in the statistical programming language R. We employ a step-by-step approach to develop an implementation of the PMH algorithm (and the particle filter within) together with the reader. This final implementation is also available as the package pmhtutorial in the CRAN repository. Throughout the tutorial, we provide some intuition as to how the algorithm operates and discuss some solutions to problems that might occur in practice. To illustrate the use of PMH, we consider parameter inference in a linear Gaussian state-space model with synthetic data and a nonlinear stochastic volatility model with real-world data.
SSRN
Initial coin offerings (ICOs) have been a prominent focus of legal and economic studies in recent years, which analyze their characteristics and determinants of their success. In this paper, we review these studies and identify key ICO success factors. We then compare the results with the empirical literature on initial public offerings (IPOs) and crowdfunding and offer theoretical explanations for the differences found. The results of this comparison are important for two reasons. Firstly, because there is no single formal data source, and there is evidence of inconsistencies across the different data sources available. Secondly, our results show in what circumstances ICO investors and initiators behave like IPO investors and initiators, and hence contribute to the literature on tokens as securities. Subsequently, we identify market frictions in ICOs, with a focus on information asymmetry and investor sentiment and biases. Finally, we discuss the regulatory implications of our findings.
SSRN
This paper examines the behaviour of stock and bond markets across four major international countries. The results confirm the view that same asset-cross country return correlations and spillovers increase over time. However, the same in not true with variance and covariance behaviour. Volatility spillovers across countries exhibit a substantial amount of time-variation, however, there is no evidence of trending in any direction. Equally, cross asset-same country correlations exhibit both negative and positive values. Further, we report an inverse relation between same asset-cross country return correlations and cross asset-same country return correlations i.e., the stock return correlation across countries increases at the same time the stock and bond return correlation within each country declines. Moreover, results show that the stock and bond return correlations exhibit commonality across countries. Results also demonstrate that stock returns lead movement in bond returns, while US stock and bond returns have predictive power other country stock and bond returns. In terms of the markets analysed, Japan exhibit a distinct nature compared with those of Germany, the UK and the US. The results presented here provide a detailed characterisation of how asset interact both with each other and cross countries and should be of interest to portfolio managers, policy-makers and those interested in modelling cross market behaviour.
SSRN
We develop a model under which the allocation of control rights between shareholders and managers is irrelevant to firm value. In our model, multiple firms buy resources for their business activities in a competitive market. Shareholders deduce from decisions made by managers, who differ in their integrity, whether a manager should be retained or fired. The allocation of control rights allowing a shareholder to fire a manager can either be easy ("strong governance") or impossible ("weak governance").The model shows that independent governance choices of individual firms are interrelated through the feedback from resources markets. In a competitive equilibrium, which is socially efficient, the universe of firms splits between strong and weak governance firms, with all of them having the same value. No firm can improve its value by changing from weak to strong governance or vice versa. The governance structure is irrelevant.The irrelevance result has important implications for the study of corporate governance. First, since shareholders with market power violate the irrelevance conditions, the model provides insights into the consequences of common ownership. It shows that, by pushing more public firms toward strong governance, institutional investors with common ownership create a monopsony power, with negative consequences to the labor market, the inputs market, the investment level in the economy, and the number of firms traded on public markets. Second, the model illuminates the need for empirical studies to specify the conditions under which strong governance is assumed to consistently be better than weak governance.
SSRN
We examine whether and how lending banks around the world respond to borrowersâ carbon emissions â" the major contributors to global warming â" in their lending decisions. We find that banks charge a higher loan spread and apply stricter non-price terms to borrowing firms with larger direct carbon emissions, but not to those with indirect emissions. We conduct two novel natural experiments using, as exogenous shocks, climate legislations around the globe and staggered adoptions of environment-related principles in the banking industry. The results of these experiments confirm that it is emerging carbon concerns that bring about the observed changes in loan contracting terms. Experience of extreme climate events strengthens the sensitivity of loan terms to carbon emissions. Moreover, if borrowers have emission mitigation schemes and better governance of climate change risks, the relation between carbon emissions and loan terms becomes weaker. Carbon emissionsâ influence on bank loans also has real effect in promoting borrowersâ future carbon reduction plans. Carbon-intensive firms are associated with deteriorated profitability and heightened regulatory and bankruptcy risks, which potentially explain the tougher loan terms they face.
SSRN
We dissect the pricing implications of both market left- and right-tail risks for the cross-section of stock returns with portfolio trading strategies that load on one factor but are orthogonal to the other. The resulting time series of factors estimated from daily Standard & Poor's 500 index option data are forward-looking, and show low correlations with other known risk factors. Stocks with high sensitivity toward innovations in market left-tail (right-tail) risk exhibit low (high) returns on average. The market right-tail risk premium is statistically and economically significant and cannot be explained by other common risk factors or firm characteristics, while the premium for left-tail risk is partially absorbed by the right-tail risk premium. The large effect of right-tail risk on cross-sectional stock returns stands in contrast to the less significant impact of market upward jumps on aggregate market returns.
SSRN
Individual investorsâ demand for trading activity will vary over time according to their availability and desire to trade. Academic research has primarily investigated market wide trading activity, showing low trading activity on Mondays and high activity at the start and end of each day. It remains unknown whether individual investorsâ trading behavior mimics these market patterns. Instead research on individual investors shows that they overtrade in general and are less likely to trade losses. We research trading activity for 7 200 UK investors, finding these investors actually prefer trading on Mondays and trade in a W-shaped intraday pattern. Further investigation revealed that investors increased their selling of losses on Monday mornings, suggesting investors utilise spare time to process difficult trading decisions.
arXiv
Sublinear functionals of random variables are known as sublinear expectations; they are convex homogeneous functionals on infinite-dimensional linear spaces. We extend this concept for set-valued functionals defined on measurable set-valued functions (which form a nonlinear space), equivalently, on random closed sets. This calls for a separate study of sublinear and superlinear expectations, since a change of sign does not convert one to the other in the set-valued setting. We identify the extremal expectations as those arising from the primal and dual representations of them. Several general construction methods for nonlinear expectations are presented and the corresponding duality representation results are obtained. On the application side, sublinear expectations are naturally related to depth trimming of multivariate samples, while superlinear ones can be used to assess utilities of multiasset portfolios.
SSRN
Portfolio diversification of firms' controlling owners influences their firms' capital investment. Empirically, the effect of owners' portfolio diversification on their firms' investment levels is positive for publicly-traded firms and tends to be negative for privately-held ones. These findings are consistent with predictions of a model in which a risk-averse investor simultaneously chooses her portfolio structure, and the level and riskiness of capital investment of the firm she controls, and in which the firm can be potentially constrained in its capital investment choices. Overall, our results indicate that owners' portfolio underdiversification and firms' financial constraints can impact firms' resource allocation.
arXiv
Despite decades of research, the relationship between the quality of science and the value of inventions has remained unclear. We present the result of a large-scale matching exercise between the universes of 4.8 million patent families and 43 million publication records. We find a strong positive relationship between quality of scientific contributions referenced in patents and the value of the respective inventions. We rank patents by the quality of the science they are linked to. Strikingly, patents in the top decile are twice as valuable as patents in the bottom decile, which in turn are about as valuable as patents with no direct science link. We show this core result for various measures of science quality and patent value. The effect of science quality on patent value remains relevant even when science is linked indirectly, i.e., through other patents. Our findings imply that what is considered "excellent" within the science sector also leads to outstanding outcomes in the technological or commercial realm.
SSRN
This paper shows how price leadership bans imposed, as part of the European Commissionâ s State aid control, on all main mortgage providers but the largest bank shifted the Dutch mortgage market from a competitive to a collusive price leadership equilibrium. In May 2009, mortgage rates in The Netherlands suddenly rose against the decreasing funding cost trend to almost a full percentage point above the Eurozone average. We derive equilibrium best-response functions, identify the price leader, and estimate response adjustments in cointegrating equations on a large data set of daily mortgage rates 2004-2012. Consistent with the full coordination equilibrium, we find structural decreases in the leaderâs cost pass-through and H-statistic, suggesting monopoly power, as well as much closer following of the leaderâs price and strongly reduced transmission of common cost changes in to price followers mortgage rates. All the structural breaks are around the Spring of 2009, when the price leadership bans were negotiated. Predicted over charges are 125 basis points or 26% on average.
SSRN
This paper finds that in Nasdaq Helsinki where brokers can voluntarily reveal or conceal identities, unsophisticated traders are less willing to trade after anonymous trades than non-anonymous trades. Using intraday order and trade data of large-cap stocks to which the voluntary anonymity model applies, I find that on earnings announcement days, the duration-until-next-unsophisticated-order (DUNUO) â" a novel unsophisticated liquidity measure â" following an anonymous trade is 21 seconds longer than that following a non-anonymous trade before announcements. However, this difference reduces to 8 seconds when earnings information is disclosed, implying a reduction in the negative impact of anonymity caused by lower information asymmetry. Moreover, unsophisticated traders are found to be increasingly unwilling to trade as the degree of anonymity â" whether the preceding trade is non-, half-, or fully anonymous â" increases.
SSRN
In this article, we study two negative events that can happen to newly public stocks: (1) the price drops at least 50% from the closing price on the first trading date within one year after the initial public offering (IPO) (initial failure) and (2) the firm is delisted for negative reasons within three years after the IPO (final failure). We find that high investor sentiment at the time of IPO can lead to both initial failure and final failure of IPO firms, whereas monitoring by external professionals plays a more important role in averting final failure than initial failure. Exploring the roles of different types of institutional investors, we find that transient (i.e., short-term trading) institutions sell before initial failure. In contrast, dedicated (i.e., monitoring) institutions focus on long-term performance and may stay with stocks suffering temporary initial failure, but their selling typically signals the imminent final failure of newly public firms.