Research articles for the 2021-03-17
SSRN
Optimal investment strategies for enhanced indexation problems have attracted considerable attentions over the last decades in the field of fund management. In this paper, a featured difference from the existing literature is that our main concern of the investigation is the development of a sparse enhanced indexation model to describe the process of assets selection by introducing a sparse L1/2 regularization instead of binary variables, which is expected to avoid the over-fitting and promote a better out-of-sample performance for the resulting tracking portfolio to some extent. An Alternating Quadratic Penalty (AQP) method is proposed to solve the corresponding nonconvex optimization problem, into which the Block Coordinate Descent (BCD) algorithm is integrated to solve a sequence of penalty subproblems. Under some suitable assumptions, we establish that any accumulation point of the sequence generated by the AQP method is a KKT point of the proposed model. Computational results on five typical data sets are reported to verify the efficiency of the proposed AQP method, including the superiority of the sparse L1/2 model with the AQP method over one cardinality constrained quadratic programming model with one of its solution methods in terms of computational costs, out-of-sample performances, and the consistency between in-sample and out-of-sample performances of the resulting tracking portfolios.
arXiv
The prediction of stock and foreign exchange (Forex) had always been a hot and profitable area of study. Deep learning application had proven to yields better accuracy and return in the field of financial prediction and forecasting. In this survey we selected papers from the DBLP database for comparison and analysis. We classified papers according to different deep learning methods, which included: Convolutional neural network (CNN), Long Short-Term Memory (LSTM), Deep neural network (DNN), Recurrent Neural Network (RNN), Reinforcement Learning, and other deep learning methods such as HAN, NLP, and Wavenet. Furthermore, this paper reviewed the dataset, variable, model, and results of each article. The survey presented the results through the most used performance metrics: RMSE, MAPE, MAE, MSE, accuracy, Sharpe ratio, and return rate. We identified that recent models that combined LSTM with other methods, for example, DNN, are widely researched. Reinforcement learning and other deep learning method yielded great returns and performances. We conclude that in recent years the trend of using deep-learning based method for financial modeling is exponentially rising.
SSRN
We study the degree and determinants of capital allocation efficiency across firms, using comprehensive firm-level survey data that covers a broad spectrum of developing countries. As measured by the dispersion in firms’ marginal revenue product of capital, we document that capital misallocation is pervasive in firms within the same industry in a country. We find that limited access to finance, bureaucracy, information asymmetry, and gender inequality play essential roles in impeding the most efficient allocation of capital across firms in developing countries. By employing the quantile regression technique, we show these factors exert more significant effects on firms that are already highly distorted (i.e., have too little capital). The results have direct policy implications; in particular, governments could achieve a more efficient allocation of capital by eliminating these distortions to enhance economic performance.
SSRN
In this paper, we propose and analyze Adaptive Projected Gradient Thresholding (APGT) methods for finding sparse solutions of the underdetermined linear system with equality and box constrains. The general convergence will be demonstrated, and in addition the bound of the number of iterations is established in some special cases. Under suitable assumptions, it is proved that any accumulation point of the sequence generated by the APGT methods is a local minimizer of the underdetermined linear system. Moreover, the APGT methods, under certain conditions, can find all s-sparse solutions for accurate measurement cases and guarantee the stability and robustness for awed measurement cases. Numerical examples are presented to show the accordance with theoretical results in compressed sensing and verify high out-of-sample performance in index tracking.
SSRN
We construct a monthly Presidential Economic Approval Rating (PEAR) index from 1981 to 2019, by averaging ratings on president’s handling of the economy across various national polls. In the cross-section, stocks with high betas to changes in the PEAR index significantly under-perform those with low betas by 0.9% per month in the future, on a risk adjusted basis. The low-PEAR-beta premium persists up to one year, and is present in various sub-samples (based on industries, presidential cycles, transitions, and tenures) and even in other G7 countries. It is also robust to different risk adjustment models and controls for other related return predictors. Since the PEAR index is negatively correlated with measures of aggregate risk aversion, a simple risk model would predict the low PEAR-beta stocks to earn lower (not higher) expected returns. Contrary to the sentiment-induced overpricing, the premium does not come primarily from the short leg following high sentiment periods. Instead, the premium could be driven by a novel sentiment towards presidential alignment.
SSRN
We provide new evidence on the role of bank lending in corporate innovation by exploiting the implementation of SFAS 166/167, which removed the off--balance sheet status of certain securitized assets of banks. The regulation affects bank lending and thus represents a credit supply shock to borrowing firms. We find that affected banks raise spreads and cut loan amounts after the regulation. Firms that borrow from affected banks reduce R&D investment and the number and quality of the patents they generate. The reduction is concentrated among firms whose banks experience more downward pressure on capital ratios and greater market discipline, and firms that are more dependent on external financing. Additional analyses reveal that information asymmetry between incumbent banks and outsiders with respect to borrowing firms prevent them from switching. The overall findings suggest that bank lending promotes borrowing firms' innovation activities.
SSRN
This study investigates the determinants of banking sector profitability in South Africa, Nigeria and the United States. The findings reveal that cost efficiency, the size of non-performing loans and overhead cost ratio are significant determinants of the banking sector profitability. In the comparative analysis, the findings from South Africa show that the cost efficiency ratio, overhead cost to total asset ratio and non-performing loans are significant determinants of banking sector profitability. In the United States, capital adequacy ratio and the size of non-performing loans are significant determinants of banking sector profitability. In Nigeria, the overhead cost to total asset ratio and cost efficiency ratio are significant determinants of the banking sector profitability. The descriptive analysis reveal that bank net interest margin and return on asset are higher in Nigeria and lowest in the United States which suggests that the Nigerian banking sector is more profitable than the US banking sector. Return on equity is higher in South Africa and lowest in the United States.
SSRN
Bitcoin trading on an Australian Cryptocurrency Exchange using an Australian bank means that transactions of A$10,000 or more are automatically reported to AUSTRAC. This analysis, of six years of Bitcoin trading on BTC Markets, finds that there is a propensity to keep trades just below the automatic reporting threshold. Unless these transactions arouse the suspicions of the exchange or financial institution then these trades go unreported. This may not be money laundering but there are traders who do not wish to draw attention to their Bitcoin transactions. The implication is that AUSTRAC’s AML/CTF regulation does have an impact on Bitcoin trading on an Australian exchange pointing to significant amounts, in this case A$23,750,000, going unreported over a six year period, as traders keep their transactions a fraction under A$10,000. A quick analysis of January 2021 indicates that this pattern continues with a significant amount of trading just below the reporting threshold.
SSRN
Enhanced-index-funds have attracted considerable attention from investors over the last decade, which aims at outperforming a benchmark index while maintaining a similar risk level. In this paper, we investigate an enhanced indexation methodology using Conditional Value-at-Risk (CVaR). In particular, we adopt CVaR of excess returns as risk measurement subject to cardinality constraint for controlling the tracking portfolio scale precisely, and tunable short-selling constraints for adjusting the margin of each risky asset adaptively within the budget of short-selling. As the resulted model is a mixed 0-1 binary program, we propose an improved hybrid heuristic method, where a customized relax-round-polish is embedded to improve the quality of the iterative population. Computational results on five standard data sets from OR-library show that our proposed method is generally superior to the naive portfolio strategy and the CVaR-LASSO method in terms of the out-of-sample excess return, Sharpe ratio, and maximum drawdown of the portfolio.
SSRN
Sensitivities are the core inputs to the Standardized Approach of the Fundamental Review of the Trading Book (FRTB) and are costly to implement and calculate for large portfolios and complex products. The internally calculated sensitivities by institutions may not be directly applicable for FRTB purpose due to different choices of risk factors. This paper introduces a new framework of defining and deriving FRTB sensitivities from the internally calculated sensitivities while keeping consistent risk measurement under the Standardized Approach framework, which will significantly improve efficiency of implementation, validation and model risk management for FRTB Standardized Approach and other similar regulatory programs, including SA-CVA (Credit Valuation Adjustment) VaR and ISDA-Standard Initial Margin Model (SIMM) etc.
SSRN
This paper studies a stylized economy in which the central bank can hold either treasuries or risky securities against central bank digital currency (CBDC) deposits. The key mechanism driving the results is the reduction in bank deposits that follows the introduction of a CBDC and its impact on the banking sector. With CBDC funds invested in treasuries, the central bank channels funds back to the banking sector via open market operations and the introduction of a CBDC is neutral, consistently with the equivalence theorem of Brunnermeier and Niepelt (2019). However, it is not neutral when accounting for liquidity requirements, quantitative easing, or for CBDC deposits held against risky securities. We reach two main conclusions. First, current monetary policy regimes do matter for CBDC equilibrium effects. Second, there is a trade-off between bank lending to the economy and taxes, as holding risky assets against CBDC deposits leads to lower expected taxes and lower bank lending.
SSRN
Using a dataset of cross-border mergers and acquisitions (M&A) entailing U.S. acquirers over the period 1990-2013, we document detailed descriptive statistics and find that the operating efficiency of the acquirers decreases around the acquisition, and up to three years after. However, contrary to findings in some of the extant literature, the announcement-period acquirer abnormal stock-price return is not significantly associated with acquirer’s operating efficiency post-acquisition. Therefore, investors should be careful interpreting the announcement-period stock-price reaction in cross-border mergers and acquisitions as indicative of merger efficiency gains. We find that target nation’s religiosity and governance features are also not significantly associated with the acquirer’s operating efficiency post acquisition; however, the acquirer’s financial features and the target nation’s macroeconomic features are.
SSRN
Do people behave consistently when it comes to sustainability? Based on financially-incentivized choices, we study non-investment related sustainable behavior of customers of three German robo advisors and relate it to their investment decisions. We find that sustainability awareness translates into a higher likelihood to choose an automatically-managed portfolio following a sustainable investment strategy among the customers of a digital wealth manager that offers both conventional and sustainable investments. Sustainability awareness also translates into a particularly strong interest in the launch of sustainable investment strategies among the customers of a so-far conventional robo advisor. We note that the provision of sustainable investment strategies can, next to performance and costs, be a selling point for a digital wealth manager. Our results provide guidance to practitioners in the financial industry regarding the identification of investors with a potential interest in sustainable investments.
arXiv
In this paper we perform a rigorous mathematical analysis of the word2vec model, especially when it is equipped with the Skip-gram learning scheme. Our goal is to explain how embeddings, that are now widely used in NLP (Natural Language Processing), are influenced by the distribution of terms in the documents of the considered corpus. We use a mathematical formulation to shed light on how the decision to use such a model makes implicit assumptions on the structure of the language. We show how Markovian assumptions, that we discuss, lead to a very clear theoretical understanding of the formation of embeddings, and in particular the way it captures what we call frequentist synonyms. These assumptions allow to produce generative models and to conduct an explicit analysis of the loss function commonly used by these NLP techniques. Moreover, we produce synthetic corpora with different levels of structure and show empirically how the word2vec algorithm succeed, or not, to learn them. It leads us to empirically assess the capability of such models to capture structures on a corpus of around 42 millions of financial News covering 12 years. That for, we rely on the Loughran-McDonald Sentiment Word Lists largely used on financial texts and we show that embeddings are exposed to mixing terms with opposite polarity, because of the way they can treat antonyms as frequentist synonyms. Beside we study the non-stationarity of such a financial corpus, that has surprisingly not be documented in the literature. We do it via time series of cosine similarity between groups of polarized words or company names, and show that embedding are indeed capturing a mix of English semantics and joined distribution of words that is difficult to disentangle.
SSRN
We present a structured portfolio optimization framework with sparse inverse covariance estimation and an attention-based LSTM network that exploits machine learning (deep learning) techniques. We shrink Wishart volatility towards a Graphical Lasso initial covariance estimator and solve the portfolio optimization using a fast coordinate descent algorithm with regularization determined using a genetic algorithm. We further introduce a novel portfolio shrinkage rule using an attention-based Long-Short-Term-Memory (LSTM) network, allowing a formal selection of reference portfolios where the network forecasts future performance based on predetermined out-of-sample monthly certainty equivalent return. We reduce the dimension of successful candidates and then linearly combine them. When nested within a minimum-variance, Bayes-Stein shrinkage, Black-Litterman portfolio framework with four types of weight constraints based on no-short-selling, upper, lower-generalized variance-based restrictions, our approach delivers a clear improvement over the baseline sample-based minimum-variance portfolio and claims superiority over 11 GARCH models used to forecast covariances, as well as a minimum-variance combination of all dynamic optimization models. We provide an illustrative example based on optimal diversification across hedge fund strategies. Robustness checks show our application of sparse covariance dominates the use of a dimension reduction algorithm for Wishart covariance forecasting.
SSRN
Sparse optimization has attracted increasing attention in numerous areas such as compressed sensing, financial optimization and image processing. In this paper, we first consider a special class of l0 constrained optimization problems, which involves box constraints and a singly linear constraint. An efficient approach is provided for calculating the projection over the feasibility set after a careful analysis on the projection subproblem. Then we present several types of projected gradient methods for a general class of l0 constrained optimization problems. Global convergence of the methods are established under suitable assumptions. Finally, we illustrate some applications of the proposed methods for signal recovery and index tracking. Especially for index tracking, we propose a new model subject to an adaptive upper bound on the sparse portfolio weights. The computational results demonstrate that the proposed projected gradient methods are efficient in terms of solution quality.
arXiv
Why do people engage in certain behavior. What are the effects of social expectations and perceptions of community behavior and beliefs on own behavior. Given that proper infant feeding practices are observable and have significant health impacts, we explore the relevance of these questions in the context of exclusive infant breastfeeding behavior using social norms theory. We make use of a primary survey of mothers of children below the age of two years in the Kayes and Sikasso region of Mali, which have a historically lower prevalence of exclusive breastfeeding. The findings from regression estimations, controlling for a host of potential confounding factors, indicate that expectations about the behavior of other community members can strongly predict individual exclusive breastfeeding. Beliefs about approval of the infant feeding behavior of the community though are found to be only modestly associated with it. In addition, mothers who hold false but positive beliefs about the community are found to exclusively breastfeed their kids. Further, using responses from randomly assigned vignettes where we experimentally manipulated the levels of social expectations, our data reveal a strong relationship between perceived prevalence of community level exclusive breastfeeding and individual behavior. This result indicates the existence of a potential causal relationship. We argue that our findings represent an important foundation for the design of policy interventions aimed at altering social expectations, and thus effecting a measurable change in individual behaviors. This type of intervention, by using social norm messaging to end negative behavior, avoids the use of coercive measures to effect behavior change in a cost-effective and efficient way.
SSRN
We develop three complementary tests to examine how adverse selection affects the design of executive compensation contracts: First, we show that externally-hired CEOs receive higher total pay and have fewer equity incentives relative to internally-promoted CEOs, consistent with their ability to extract larger information rents due to greater private information. These differences are more pronounced when less is known about the prospective CEO, but quickly dissipate over time. Second, we show that external CEOs’ initial contracts differ more from those of their firm’s incumbent senior managers than do those of internal CEOsâ€"particularly in terms of accounting performance metrics and equity-based pay, in line with the use of these features to elicit private information. Third, we find that following an unanticipated change in option vesting schedules prompted by SFAS 123R, newly appointed executives do not increase their option exercises and share salesâ€"despite their newfound ability to do soâ€"while longer-tenured executives do, consistent with contracts initially being designed to screen for certain types of managers before shifting to encourage certain behaviors. Combined, our evidence supports the distinct role of adverse selection in the design of executive compensation contracts.
SSRN
In recent years the external government debt has been reviewed and analysed in terms of the European debt crisis and due to the high debt levels in leading economies worldwide. The EU Member States external debt is discussed in the paper as the focus is on Bulgaria and Romania and two main issues are presented in more details: 1. The EU Member States debt levels for the last decade; and 2. The private versus public debt and major challenges in their management.
SSRN
Women are less financially literate than men. It is unclear whether this gap reflects a lack of knowledge or, rather, a lack of confidence. Our survey experiment shows that women tend to disproportionately respond “do not know†to questions measuring financial knowledge, but when this response option is unavailable, they often choose the correct answer. We estimate a latent class model and predict the probability that respondents truly know the correct answers. We find that about one-third of the financial literacy gender gap can be explained by women’s lower confidence levels. Both financial knowledge and confidence explain stock market participation.
SSRN
Using data across European corporate boards, we investigate the effects of quota-induced female representation on firm value and operations, under minimal identification assumptions. We consider sharp increases in the share of women on boards that arise due to rounding whenever percentage-based regulation applies to a small group of people. We find that having more women on corporate boards has large positive effects on Tobin´s Q and buy-and-hold returns. This result is in stark contrast with previous empirical work that finds large negative effects. The reason for this discrepancy is that these papers considered firms with different pre-quota shares of women to be good counterfactuals to each other. In our data, we see that such firms had grown differently already before the regulation. Thus, assuming they are good comparables would result in a negatively biased estimate of the effect. Instead, we use quasi-random assignment induced by rounding and find that promoting gender equality is aligned with shareholder interests. This positive effect is not explained by increased risk-taking or changes in board composition, but rather by scaling down inefficient operations and empire-“demolishing“.
SSRN
Using data across European corporate boards, we investigate the effects of quota-induced female representation on firm value and operations. We use quasi-random assignment induced by rounding and find that promoting gender equality is aligned with shareholder interests. This result is in stark contrast with previous work finding large negative effects of women on firm value. This discrepancy arises because these papers considered firms with different pre-quota shares of women to be good counterfactuals to each other. In our data, we see that such firms grew differently already before the regulation, resulting in a negatively biased estimate of the effect. We overcome this bias by considering sharp increases that arise whenever percentage-based regulation applies to a small group of people. We further show that these large positive effects of female directors are not explained by increased risk-taking or changes in board characteristics, but rather by scaling down inefficient operations and empire-"demolishing".
SSRN
This paper finds that CEO incentive horizon, proxied by their pay duration, has a positive influence on the engagement in corporate social responsibility (CSR), especially when firms face a higher risk of reputation loss, need more stakeholder support, and maintain more effective corporate governance practices. CSR, when practiced by CEOs with longer-horizon incentives, benefits both stakeholders and shareholders in the long run. Further tests suggest that endogenous factors are unlikely to drive our conclusions and inferences. Taken together, our evidence suggests that the instrumental perspective on CSR prevails and long incentive horizon helps align stakeholders’ interests with shareholder value.
SSRN
This study (i) examines how the within-group power structure in a unique setting modulates the impact of gender diversity on collective financial risk-taking and (ii) evaluates the external implications of the findings for corporate board gender diversity/-diversification, risk-attitudes, and financial performance. Specifically, using hand-collected data from over 12,000 minutes of the multiple Emmy Award-winning television game show, Cash Cab, I find that on average, the presence (or addition) of one influential female in (or to) a small previously homogeneous male group significantly reduces the group’s willingness to take financial risks. If, however, a group (of at least three persons) consists of one such female, adding more females does not significantly alter the group's risk-taking behavior. These findings and the key features of the Cash Cab setting suggest that the within-group power/influence distributions impact whether gender tendencies manifest in small group settings. Using difference-in-differences estimation on board and financial data (for publicly listed U.S. companies) spanning nearly 20 years, I provide strong external evidence supporting the latter. Overall, my results appear to effectively reconcile the mixed extant empirical evidence on the impact of board gender diversity on firms’ financial performance and are instructive for ongoing discussions on board gender-diversification.
arXiv
Although wage inequality has evolved in advanced countries over recent decades, it is unknown the extent to which the evolution of wage inequality is attributable to observed factors such as capital and labor quantities or unobserved factors such as labor-augmenting technology. To examine this issue, we estimate an aggregate production function extended to allow for capital-skill complementarity and factor-biased technological change using cross-country panel data and the shift-share instrument. Our results indicate that most of the changes in the skill premium are attributed to observed factors including ICT equipment in the majority of OECD countries.
SSRN
We develop a method for estimating the stock market impact of aggregate events. Based on using data on both stock and options prices, our technique accounts for two important sources of bias present in traditional methods. First, our method takes into account market anticipation, without the need for information on specific firm characteristics. Many event studies only measure a fraction of an event's full value effect, so the measured market reaction at event resolution can be misleading, particularly in the case of a very high degree of market anticipation. Second, our method is robust to the possibility of the event being good news for some firms and bad for others, without prior specification of this heterogeneity. We apply the method to the passage of the Tax Cuts and Jobs Act (TCJA), which exhibits both anticipation and heterogeneity. We estimate the market anticipated the probability of passage to be as high as 95% 30 days before the event. The full value impact of the TCJA is found to be 12.36%, compared to 0.68% when market anticipation is ignored. The firm-level impact of the TCJA is considerably heterogeneous, with large and innovative firms with high growth prospects being the largest winners.
arXiv
Based on some analytic structural properties of the Gini and Kolkata indices for social inequality, as obtained from a generic form of the Lorenz function, we make a conjecture that the limiting (effective saturation) value of the above-mentioned indices is about 0.865. This, together with some more new observations on the citation statistics of individual authors (including Nobel laureates), suggests that about $14\%$ of people or papers or social conflicts tend to earn or attract or cause about $86\%$ of wealth or citations or deaths respectively in very competitive situations in markets, universities or wars. This is a modified form of the (more than a) century old $80-20$ law of Pareto in economy (not visible today because of various welfare and other strategies) and gives an universal value ($0.86$) of social (inequality) constant or number.
SSRN
ETF sponsors promote ETFs as having superior liquidity than their constituents because of ETFs' liquidity in the open market and the underlying stocks' liquidity through the creation/redemption mechanism. We find a liquidity connection between the ETF and its underlying assets suggesting the potential simultaneous liquidity dry-up in both markets. Liquidity spillover increases during the market crisis and positively relates to market volatility and funding constraints. Besides, a stock with high volatility and low trading activity exhibits higher liquidity spillover. Finally, liquidity spillover varies proportionally with ETF arbitrage activity and tends to be lower when short sales constraints exist.
arXiv
We propose to derive deviation measures through the Minkowski gauge of a given set of acceptable positions. We show that given a suitable acceptance set, any positive homogeneous deviation measure can be accommodated in our framework. In doing so, we provide a new interpretation for such measures, namely, that they quantify how much one must shrink a position for it to become acceptable. In particular, the Minkowski gauge of a set which is convex, stable under scalar addition, and radially bounded at non-constants, is a generalized deviation measure. Furthermore, we explore the relations existing between mathematical and financial properties attributable to an acceptance set on the one hand, and the corresponding properties of the induced measure on the other. Dual characterizations in terms of polar sets and support functionals are provided.
SSRN
We test the robustness of the regime switching model for the pegged market USD-HKD introduced in S. Drapeau, Want T. and Wang T. (2021). In particular, two disputable underlying assumptions: 1) A Black and Scholes model with low volatility for the pre-depegging regime. 2) A thin tail distribution -- Poisson type -- for the time of the depegging. For the pre-depegging regime, we consider a bounded model within the pegg -- from Ingersoll and Rady. For the depegging time, we consider fat tail distributions more in line with catastrophic events -- Pareto/Frechet. We derive the option prices formula for each combination of these models and calibrate it to the option data from USD-HKD. In comparison to the benchmark model in \citep{drapeau2019}, it turns out that the relevant resulting characteristics -- probability of a depegging before maturity, appreciation/depreciation at the depegging time as well as post-depegging volatility -- are strongly robust in terms of model choice for this regime switching approach.
SSRN
Failing to account for transaction costs materially impacts inferences drawn when evaluating asset pricing models, biasing tests in favor of those employing high cost factors. Ignoring transaction costs, the Hou, Xue, and Zhang (2015) q-factor model and the Barillas and Shanken (2018) six-factor model models have high maximum squared Sharpe ratios and small alphas across 120 anomalies. They do not, however, come close to spanning the achievable mean-variance efficient frontier. Accounting for transaction costs, the Fama and French (2015, 2018) five-factor model has a significantly higher squared Sharpe ratio than either of these alternative models, while variations employing cash profitability perform better still. More generally, these results highlight the importance of incorporating real-world concerns into financial research.
SSRN
This paper is about investigating how different bank liquidity creation activities affect housing markets. Using data of 401 metropolitan statistical areas/divisions (MSAs/MSADs) of the US between 1990 and 2018, we show that not all bank liquidity creation activities boost housing markets. In particular, unlike asset-side and off-balance sheet liquidity creations, funding-side liquidity creation dampens housing markets. The relationships between liquidity creation activities and housing markets are stronger in regions with inelastic house supply, but are flipped when banks face external liquidity shocks. We also find that housing markets dominated by large banks are more sensitive to off-balance sheet liquidity creation activities. Finally, as expected, asset-side and off-balance sheet liquidity creations boost housing markets by driving house prices away from fundamental values. Our results offer a more thorough explanation about how bank liquidity creation fuels the momentum of housing markets.
arXiv
Scaling and multiscaling financial time series have been widely studied in the literature. The research on this topic is vast and still flourishing. One way to analyze the scaling properties of time series is through the estimation of their scaling exponents, that are recognized as being valuable measures to discriminate between random, persistent, and anti-persistent behaviors in these time series. In the literature, several methods have been proposed to study the multiscaling property. In this paper, we use the generalized Hurst exponent (GHE) tool and we propose a novel statistical procedure based on GHE which we name Relative Normalized and Standardized Generalized Hurst Exponent (RNSGHE). This method is used to robustly estimate and test the multiscaling property and, together with a combination of t-tests and F-tests, serves to discriminate between real and spurious scaling. Furthermore, we introduce a new tool to estimate the optimal aggregation time used in our methodology which we name Autocororrelation Segmented Regression. We numerically validate this procedure on simulated time series by using the Multifractal Random Walk (MRW) and we then apply it to real financial data. We present results for times series with and without anomalies and we compute the bias that such anomalies introduce in the measurement of the scaling exponents. We also show how the use of proper scaling and multiscaling can ameliorate the estimation of risk measures such as Value at Risk (VaR). Finally, we propose a methodology based on Monte Carlo simulation, which we name Multiscaling Value at Risk (MSVaR), that takes into account the statistical properties of multiscaling time series. We show that by using this statistical procedure in combination with the robustly estimated multiscaling exponents, the one year forecasted MSVaR mimics the VaR on the annual data for the majority of the stocks analyzed.
SSRN
We explore whether banks learn from past experience and modify their risk culture. Evaluating bank risk culture during the 2014 energy crash fueled by excessive bank lending, we find banks with a quick recovery after the 2007 subprime crisis find it unnecessary to change their risk culture, and banks that struggled to recover modify their risk culture following the subprime crisis. As a result, banks with poorer stock performance and a lower z-score during the subprime crisis that had a quick recovery are more likely to underperform during the energy crash. However, results show that while these banks do not modify their overall risk culture, they have learned from the subprime crisis by better positioning themselves for potential losses. In addition, larger banks and banks that did not receive TARP funding have not significantly changed their risk culture following the subprime crisis.
arXiv
This paper documents the representation of women in Economics academia in India by analyzing the share of women in faculty positions, and their participation in a prestigious conference held annually. Data from the elite institutions shows that the presence of women as the Economics faculty members remains low. Of the authors of the papers which were in the final schedule of the prestigious research conference, the proportion of women authors is again found to be disproportionately low. Our findings from further analysis indicate that women are not under-represented at the post-graduate level. Further, the proportion of women in doctoral programmes has increased over time, and is now almost proportionate. Tendency of women who earn a doctorate abroad, to not return to India, time needed to complete a doctoral program, and responsibilities towards the family may explain lower presence of women in Economics academia in India.
SSRN
Information-theoretic methods have recently been proposed for the simultaneous recovery of investors’ beliefs about future macroeconomic and financial outcomes and their risk preferences from observed asset prices. These methods estimate beliefs and preferences to minimize the statistical discrepancy between the recovered beliefs and the true data generating process (DGP), subject to asset pricing Euler equation constraints. This paper develops the asymptotic properties of these subjective beliefs estimators. We compare empirically the beliefs recovered with alternative estimators in this class, that differ on the basis of the statistical divergence functions used to characterize the discrepancy between the beliefs and the DGP.
arXiv
This is an informal and sketchy review of six topical, somewhat unrelated subjects in quantitative finance: rough volatility models; random covariance matrix theory; copulas; crowded trades; high-frequency trading & market stability; and "radical complexity" & scenario based (macro)economics. Some open questions and research directions are briefly discussed.
SSRN
Do investors reach for yield when interest rates are low, and how does this behavior influence house prices? This paper uses the unique setting of 17th-18th century Amsterdam to answer this question, using newly-collected archival data on investment portfolios and the universe of property transactions in this period. Exploiting exogenous shocks in the supply of safe government bonds, I show that wealthy investors shifted their wealth towards higher-yielding assets such as real estate when bond yields were decreasing. This behavior exacerbated booms and busts in house prices and resulted in a persistent increase in housing wealth inequality. Reach for yield behavior was not limited to real estate assets and contributed to the development of international financial markets.
SSRN
Using a novel measure, we study how the personal religiosity (or sense of higher purpose) of independent directors affects the effectiveness of their intense board oversight. We find that, relative to their non-religious counterparts, religious monitoring-intensive directors exhibit significantly lower sensitivity of CEO turnover to firm performance over a holding period of 1 year. However, for the more extended holding period of 2 years, this difference in sensitivity significantly switches direction, consistent with the “higher purpose, incentives, and economic performance†theory, which suggests that believers in higher purpose will tend to hold a longer-term perspective. We also find that religious monitoring-intensive directors further reduce both earnings management and excess total CEO compensation, especially when the lead independent director and/or a majority of the principal monitoring committee chairs are also religious. Overall, our findings show that religious monitoring-intensive directors differentially influence intense board oversight results and, thereby, help infuse or propagate a corporate culture consistent with an authentic organizational higher purpose.
SSRN
The public CbCR requirement for EU financial institutions leaves leeway to the reporting firms as regards the calculating and presentation of the data. Based on a sample of CbCRs published by EU-headquartered multinational bank groups, we analyze the reporting behavior and the degree of transparency across the reports. We observe a large heterogeneity with respect to the place of publication of the CbCR, its content, the readability of the data tables as well as the list of entities that should be published together with the by-country data. We also identify differences between headquarter countries, with CbCRs prepared by bank groups from the United Kingdom and Germany being the most transparent. Inconsistencies in reporting inhibit the interpretability and the comparability of the data. We conclude that the specification of the underlying data source and of the applicable consolidation scope as well the establishment of uniform definitions of the reportable items are essential for an appropriate consideration of the reports by all addressees. Our analyses are particularly important in light of the proposal for a public CbCR for large multinational firms in the EU.
arXiv
The rapid uptake of renewable energy technologies in recent decades has increased the demand of energy researchers, policymakers and energy planners for reliable data on the spatial distribution of their costs and potentials. For onshore wind energy this has resulted in an active research field devoted to analysing these resources for regions, countries or globally. A particular thread of this research attempts to go beyond purely technical or spatial restrictions and determine the realistic, feasible or actual potential for wind energy. Motivated by these developments, this paper reviews methods and assumptions for analysing geographical, technical, economic and, finally, feasible onshore wind potentials. We address each of these potentials in turn, including aspects related to land eligibility criteria, energy meteorology, and technical developments relating to wind turbine characteristics such as power density, specific rotor power and spacing aspects. Economic aspects of potential assessments are central to future deployment and are discussed on a turbine and system level covering levelized costs depending on locations, and the system integration costs which are often overlooked in such analyses. Non-technical approaches include scenicness assessments of the landscape, expert and stakeholder workshops, willingness to pay / accept elicitations and socioeconomic cost-benefit studies. For each of these different potential estimations, the state of the art is critically discussed, with an attempt to derive best practice recommendations and highlight avenues for future research.
arXiv
We consider a general framework of optimal mechanism design under adverse selection and ambiguity about the type distribution of agents. We prove the existence of optimal mechanisms under minimal assumptions on the contract space and prove that centralized contracting implemented via mechanisms is equivalent to delegated contracting implemented via a contract menu under these assumptions. Our abstract existence results are applied to a series of applications that include models of optimal risk sharing and of optimal portfolio delegation.
arXiv
Scientific research in the United States could receive a large increase in federal funding--up to 100 billion dollars over five years -- if proposed legislation entitled the Endless Frontiers Act becomes law. This bipartisan and bicameral bill, introduced in May 2020 by Senators Chuck Schumer (D-NY) and Todd Young (R-IN) and Congressmen Ro Khanna (D-CA) and Mike Gallagher (R-WI), is intended to expand the funding of the physical sciences, engineering, and technology at the National Science Foundation (NSF) and create a new Technology Directorate focused on use-inspired research. In addition to provisions to protect the NSF's current missions, a minimum of 15\% of the newly appropriated funds would be used to enhance NSF's basic science portfolio. The Endless Frontier Act offers a rare opportunity to enhance the breadth and financial support of the American research enterprise. In this essay, we consider the benefits and the liabilities of the proposed legislation and recommend changes that would further strengthen it.
SSRN
We develop a new variational Bayes approximation method to deal with sparse estimation of large-dimensional vector autoregressive models. Unlike traditional Markov Chain Monte Carlo (MCMC) algorithms, our approach allows to directly model sparsity in the cross-industry lead-lag relationships which otherwise could only be indirectly imposed via a structural form representation of the model. Empirically, we investigate the out-of-sample predictability of the returns for a large cross section of industry portfolios, spanning almost a hundred years of monthly data. We provide robust evidence that by explicitly shrinking weak cross sectional interdependencies one can substantially increase both the statistical and economic performance of VAR models when forecasting financial returns. This result holds across alternative shrinkage priors, such as the Bayesian LASSO, the Normal-Gamma and the Horseshoe prior.
arXiv
In this paper we study arbitrage theory of financial markets in the absence of a num\'eraire both in discrete and continuous time. In our main results, we provide a generalization of the classical equivalence between no unbounded profits with bounded risk (NUPBR) and the existence of a supermartingale deflator. To obtain the desired results, we introduce a new approach based on disintegration of the underlying probability space into spaces where the market crashes at deterministic times.
SSRN
We look at an enhanced loss-harvesting strategy, tax-rate arbitrage, which exploits the differential between short- and long-term tax rates. Our study relies on ATBAT, an After-Tax Back-Testing Analysis Tool that lets us examine tax-managed strategies over numerous historical periods. For the ideal tax-rate arbitrage investor, one who is subject to federal only tax rates, who has a long horizon and a planned liquidation date, and who launches the strategy from all cash, tax-rate arbitrage generated an average of 0.78% in excess after-tax active return at a 10-year horizon relative to a standard loss-harvesting strategy. Other investors with different profiles may benefit from tax-rate arbitrage but typically to a lesser extent.
SSRN
This paper tests asset pricing models using individual stocks as test assets, rather than sorted portfolios. Sorted portfolios have the severe limitation that the researcher must know, in advance, reliable predictors of expected returns. We show how to generate appropriately sized tests and verify that our tests have considerable test power. In simulations when the CAPM describes the population, our tests (correctly) reject the Fama and French (2015) six factor model 97.5% of the time, while our tests (incorrectly) reject the CAPM less than 5%. We apply our tests to several leading factor models and reject nine of the eleven models tested. The instrumented factor model of Kelly, Pruitt and Su stands out as the most successful.
SSRN
COVID-19 placed a special role to ï¬scal policy in rescuing companies short of liquidity from insolvency. In the ï¬rst months of the crisis, SMEs as the backbone of Europe’s real economy beneï¬ted from large and mainly indiscriminate aid measures. Avoiding business failures in a whatever it takes fashion contrasts, however, with the cleansing mechanism of economic crises: a mechanism which forces unviable ï¬rms out of the market, thereby reallocating resources efficiently. By focusing on ï¬rms’ pre-crisis ï¬nancial standing, we estimate the extent to which the policy response induced an insolvency gap and analyze whether the gap is characterized by ï¬rms which had already struggled before the pandemic. With the policy measures being focused on smaller ï¬rms, we also examine whether this insolvency gap differs with respect to ï¬rm size. Based on credit rating and insolvency data for the near universe of actively rated German ï¬rms, our results suggest that the policy response to COVID-19 has triggered a backlog of insolvencies in Germany that is particularly pronounced among ï¬nancially weak, small ï¬rms, having potential long term implications on economic recovery.
SSRN
We develop a model of freeze-out merger and tender offers and test it in an economy where merger and tender regulation are extremely different. Using a relatively large sample of 329 freeze-out offers in Israel during 2000-2019, we document evidence consistent with the model. We also find that tender offers: 1) are the preferred technique; 2) offer lower premiums; and 3) suffer from a relatively large (40%) offer rejection rate. These findings deviate from U.S. evidence, and are partly due to differences in the tender offer procedures. Thus, our study illustrates that the tender offer procedure is a delicate one, and explains why Delaware has often amended it.
SSRN
The aim of this paper is to knowledge the problems faced by toward Islamic banks in Jordan adherence the s to AAOIFI accounting standards. And to study the problems faced with adherence to AAOIFI accounting standards, a meticulous market survey was conducted from banking (employees of the financial department) in Islamic banks in Jordan â€" their number 4 â€" banks. A structured questionnaire was designed and distributed in person among respondents â€" their number 80 â€" employees in the financial departments. We are found towards adherence to AAOIFI accounting standards. Internal and external problems are found to adherence Islamic banks to AAOIFI accounting standards. The sample is limited to Islamic banks in Jordan. This is necessitated by the lack of adaptation elsewhere. Also, there is little research in Jordan on adherence to AAOIFI accounting standards developed by this body. This paper, along with the previous study, helps to address this gap.
SSRN
We study the impact of regulations expanding bank branching in India. We find that public sector banks (PSBs) reduce their lending to poorly performing firms when branching expands in a district. Non-performing loans at PSBs also increase when branching expands. Also, inefficient firms that depend on PSBs deleverage and are more likely to exit after branching expands in a district. At the plant level, exposure to branching is associated with an expansion in size and employment. These results suggest that greater credit market competition can lead to more efficient lending and increased economic activity in economies with protected credit markets.
SSRN
Do government initiatives that promote credit access incentivize banks to produce information about borrower characteristics and allocate credit efficiently? To address this question we develop a theoretical model of information production, regulation and bank competition and test empirically its predictions by examining the impact of the Community Reinvestment Act's (CRA) lending program on small businesses. Our analysis reveals that, on average, the CRA eligibility-induced surge of loans leads to an improvement in the credit score of small businesses. However, we observe no improvement in the credit score of small businesses in markets with high bank competition intensity. We suggest that high competition erodes bank's incentives for information production. Therefore, blanket interventions that stimulate credit access to targeted borrowers may not uniformly improve credit allocation across all local markets. We recommend that government interventions aiming to increase credit access should also enact policies that lower information acquisition costs, especially in high bank competition markets.
SSRN
The chapter continues and advances our earlier research on ‘Board Models in Europe’.** We explore ‘The Structure of the Board of Directors’ with a view to the basic governance structure as provided by a board model vis-à -vis techniques of structuring the decision-making body, which can be used independent of the chosen board model. We focus on boards of large business corporations with a stock exchange listing to secure cross-country comparability. Our three sample jurisdictions are the US, the UK and Germany. France and Italy are also considered to round out the discussion of selected issues. Our key findings are as follows:1. Board models like the one-tier board, as used in the US and the UK, or the two-tier board, as used in Germany, provide a basic governance structure that enables the use of specific governance strategies. It is the use of specific governance strategies, not the choice of a board model, which determines the role of the board in alleviating agency problems between owners and managers, controlling and non-controlling shareholders, and shareholder and stakeholder constituencies. Based on this finding, the choice of the suitable board model should be left to private parties.2. The market for corporate control is known as a removal strategy that alleviates the agency problem between owners and managers of potential target companies. To achieve this effect, it must be ensured that takeover defenses are adopted in the interest of shareholders rather than as a means to shield the incumbent board from removal by the acquirer. The governance options include focusing the board structure through the allocation of decision-making power to independent directors (US) or to the supervisory board (Germany), and, as an alternative, reinstalling shareholder decision-making and thus removing the board from its coordination task (UK). Counter-intuitively, one might group US and German law together, despite differences in their basic board structures and despite the European Union’s adoption of UK-style control shift regulation.3. The three sample jurisdictions follow a similar pattern for securing fairness of related party transactions (RPTs). The UK relies on a structuring of the shareholder body, requiring ex-ante approval of the disinterested shareholders (MOM approval), a strategy that is also used in France but in a weaker form due to the possibility of ex-post authorization. In the US, the predominant choice seems to be structuring the board so as to leave the decision to independent directors, a strategy that Italy has, on one hand, sought to enhance with the obligatory involvement of a minority appointed director but, on the other hand, has weakened by allowing the board to override a recommendation of the independent directors. Germany also relies on board structuring in that it requires supervisory board approval of RPTs, but compared to the use of independent directors, the cooperation between the two boards provides a basis for manager-friendly results one would expect only from a jurisdiction that openly promotes board empowerment.4. The most far-reaching advance of the corporate purpose debate relates to a further structuring of the board so as to provide employee representatives with a voice, as known from German co-determination. Proposals to reallocate a proportion of the appointment rights from shareholders to employees have not found their way into legal reform in the US or the UK. Out of the governance strategies discussed in this chapter, it is only employee co-determination that calls for a basic governance structure which solely a two-tier board model can provide.
SSRN
We study the effects of central bank communication about financial stability on individuals’ expectations and risk-taking. Using a randomized information experiment, we show that communication causally affects individuals’ beliefs and investment behavior, consistent with an expectations channel of financial stability communication. Individuals receiving a warning from the central bank expect a higher probability of a financial crisis and reduce their demand for risky assets. This reduction is driven by downward revisions in individuals’ expected Sharpe ratios due to lower expected returns and higher perceived downside risks. In addition, these individuals deposit a smaller fraction of their savings at riskier banks.
SSRN
Housing wealth is a largely untapped resource that can help older adults supplement their incomes and buffer financial shocks in retirement. The federally insured reverse mortgage offers adults age 62 and older access to home equity with no required monthly payment, and protection for homeowners and their heirs against negative equity. Despite estimates of a large potential market, take-up of reverse mortgages in the U.S. is very low, with less than 2 percent of the population age 62 and older holding a reverse mortgage. In this paper, we review barriers to borrowing from home equity, including an estimate of the size of the population who may be unable to borrow due to an inability to afford monthly mortgage payments. We describe the market for federally insured reverse mortgages, including trends and challenges over time, as well as recent policy reforms. We then present a set of reforms to improve the market for reverse mortgages, including streamlined product offerings that target specific consumer segments, and the use of risk-based underwriting and preventing servicing. These reforms are intended to reduce the probability of default, foreclosure, and negative equity (crossover risk), while reducing frictions in the market for consumers and lenders.
SSRN
We model the welfare consequences of mandates to invest in sustainable firms. There is underspending on the mitigation of damage to capital from climate disasters. In lieu of capital taxes to address this externality, mandates incentivize firms to mitigate by creating a wedge in the cost of capital for those who qualify by spending a sufficient amount on mitigation. Despite being a dynamic stochastic general equilibrium model, there are several testable implications, including that this wedge equals a firm's mitigation spending divided by its Tobin's q. Fixing the wealth allocated to mandates, we calculate the welfare-maximizing qualification criterion. Based on this criterion and global warming projections, mandates are not stringent enough to achieve first best.
SSRN
In this paper, we study a recent, high-profile 2021 event, often known as the GameStop episode, where Robinhood and several other retail-oriented brokerage firms restrict equity purchases and/or options positions in GameStop equity and around 30 other stocks. While these restrictions are short-lived, lasting from a day to just over a week, and have at most modest effects on trading volume and equity bid-ask spreads, they have large effects on stock returns and options markets. We find that when equity restrictions are imposed, affected stocks fall in price, with cumulative abnormal returns of -18.53% in the first two hours and -95.34% in the first five trading days of equity restrictions. When restrictions are later lifted, share prices do not reverse their earlier declines. Traders also move from equities to the options markets, with large increases in options trading volumes and open interest. Options prices rise sharply in implied volatility terms, and implied volatilities rise by much more than realized volatilities. Options purchasers are thus wildly overpaying to buy puts and calls, which create large transfers from options purchasers to options market-makers and other options sellers.
SSRN
We employ several technical analyses models and account for investor’s sentiment to establish a benchmark on the optimal time to entry or to exit from the Bitcoin market. Unlike companies that they have quarterly earnings, Bitcoin is not a company with earning. Yet, we argue the Bitcoin “halving†is the closest to company’s earnings. Indeed, we show that one of the key determinant of Bitcoin price fluctuation is the Bitcoin “halving,†in terms of quantity and timing. We also examine how market distraction and liquidity influence Bitcoin price. Thus, we suggest entry when stock market distraction and/or liquidity is high and we approaching the halving; exit otherwise. Collectively, we introduce two key determinants, investors’ distraction and Bitcoin halving, to understand Bitcoin price movement.
