Research articles for the 2020-03-17

Analyse des séries temporelles intervalles et prévision en économie de l’énergie (Time Series Analysis Intervals and Energy Economics Forecast)
Tchouamani, Hervé,Sadefo Kamdem, Jules
SSRN
French Abstract: Ce document de travail présente les méthodes d’estimation des paramètres d’un modèle de régression lorsque les variables sont observées sous un format intervalle. Il illustre cette procédure d’estimation sur les données de consommation d’électricité en France, afin d’effectuer une comparaison entre les valeurs prévisionnelles issues des données intervalles et l’intervalle de confiance de la prévision issu des données ponctuelles. Dans un premier temps, nous montrons que l’utilisation des valeurs uniques pour caractériser une variable économique entraîne une perte d’informations. Dans un deuxième temps, ces méthodes d’estimation ont été appliquées aux données intervalles de consommation d’électricité en France dans une optique de prévision. L’examen de l’évolution de nos données via des tests nous a permis de déceler un effet saisonnier, mais pas d’extra-saisonnier. Ainsi, les procédures d’estimation sont mises en sur les données désaisonnalisées par la méthode Census X12, et la prévision prendra en compte les coefficients saisonniers obtenus après désaisonnalisation. Pour mesurer l’intérêt de l’analyse sur les données intervalles, nous avons comparé la prévision sur les données intervalles, à l’intervalle de confiance de la prévision sur les données ponctuelles. Dans la dernière section, l’observation du profil des intervalles de confiance prévisionnels et celui des prévisions sur les données intervalles a révélé l’inclusion de l’intervalle de confiance de la prévision sur les données classiques, dans les bornes prévues par les données intervalles. Cette inclusion persiste avec l’augmentation du niveau de confiance accordé à l’IC de la prévision. Nous avons ainsi conclu sur l’impossibilité des données classiques à couvrir l’intervalle de la vraie valeur de la variable étudiée.English Abstract: This working paper presents the methods for estimating the parameters of a regression model when the variables are observed in an interval format. It illustrates this estimation procedure on electricity consumption data in France, in order to make a comparison between the forecast values ​​from the interval data and the confidence interval of the forecast from the point data. First, we show that the use of single values ​​to characterize an economic variable leads to a loss of information. In a second step, these estimation methods were applied to interval electricity consumption data in France for forecasting purposes. Examining the evolution of our data via tests allowed us to detect a seasonal effect, but not an extra-seasonal one. Thus, the estimation procedures are implemented on seasonally adjusted data by the Census X12 method, and the forecast will take into account the seasonal coefficients obtained after seasonal adjustment. To measure the value of analysis on interval data, we compared the forecast on interval data to the confidence interval of the forecast on point data. In the last section, the observation of the profile of the forecast confidence intervals and that of the forecasts on the interval data revealed the inclusion of the confidence interval of the forecast on the classical data, in the bounds predicted by the interval data. This inclusion persists with the increase in the level of confidence in the forecast confidence interval. We therefore concluded on the impossibility of conventional data to cover the range of the true value of the variable studied.

Artificial intelligence approach to momentum risk-taking
Ivan Cherednik
arXiv

We propose a mathematical model of momentum risk-taking, which is essentially real-time risk management focused on short-term volatility of stock markets. Its implementation, our fully automated momentum equity trading system presented systematically, proved to be successful in extensive historical and real-time experiments. Momentum risk-taking is one of the key components of general decision-making, a challenge for artificial intelligence and machine learning with deep roots in cognitive science; its variants beyond stock markets are discussed. We begin with a new algebraic-type theory of news impact on share-prices, which describes well their power growth, periodicity, and the market phenomena like price targets and profit-taking. This theory generally requires Bessel and hypergeometric functions. Its discretization results in some tables of bids, which are basically expected returns for main investment horizons, the key in our trading system. The ML procedures we use are similar to those in neural networking. A preimage of our approach is the new contract card game provided at the end, a combination of bridge and poker. Relations to random processes and the fractional Brownian motion are outlined.



Behaving Optimally in Solar Renewable Energy Certificate Markets
Arvind Shrivats,Sebastian Jaimungal
arXiv

SREC markets are a relatively novel market-based system to incentivize the production of energy from solar means. A regulator imposes a floor on the amount of energy each regulated firm must generate from solar power in a given period and provides them with certificates for each generated MWh. Firms offset these certificates against the floor and pay a penalty for any lacking certificates. Certificates are tradable assets, allowing firms to purchase/sell them freely. In this work, we formulate a stochastic control problem for generating and trading in SREC markets from a regulated firm's perspective. We account for generation and trading costs, the impact both have on SREC prices, provide a characterization of the optimal strategy, and develop a numerical algorithm to solve this control problem. Through numerical experiments, we explore how a firm who acts optimally behaves under various conditions. We find that an optimal firm's generation and trading behaviour can be separated into various regimes, based on the marginal benefit of obtaining an additional SREC, and validate our theoretical characterization of the optimal strategy. We also conduct parameter sensitivity experiments and conduct comparisons of the optimal strategy to other candidate strategies.



COVID-19 Effects on the S&P 500 Index
Yilmazkuday, Hakan
SSRN
This paper investigates the effects of the global coronavirus disease 2019 (COVID-19) deaths on the S&P 500 Index using daily data covering the period between December 31st, 2019 and March 12th, 2020. The investigation is achieved by using a structural vector autoregression model, where a measure of the global economic activity and the spread between 10-year treasury constant maturity and the federal funds rate are also included. The empirical results suggest that having one more global COVID-19 death results in 0.02% of a cumulative reduction in the S&P 500 index after one day, 0.06% of a cumulative reduction after one week, and 0.08% of a reduction after one month.

Can this Time be Different? Policy Options in Times of Rising Debt
Ayhan Kose, M.,Nagle, Peter Stephen Oliver,Ohnsorge, Franziska,Sugawara, Naotaka
SSRN
Episodes of debt accumulation have been a recurrent feature of the global economy over the past fifty years. Since 2010, emerging and developing economies have experienced another wave of historically large and rapid debt accumulation. Similar past debt buildups have often ended in widespread financial crises in these economies. This paper examines the factors that are likely to determine the outcome of the most recent debt wave, and considers policy options to help reduce the likelihood that it ends again in widespread crises. It reports two main results. First, the rapid increase in debt has made emerging and developing economies more vulnerable to shifts in market sentiment, notwithstanding historically low global interest rates. Second, policy options are available to lower the likelihood of financial crises, and to help manage the adverse impacts of crises when they do occur. These include sound debt management, strong monetary and fiscal frameworks, and robust bank supervision and regulation. The post crisis debt buildup has coincided with a period of subdued growth as well as the emergence of non-traditional creditors. As a result, policy priorities also need to ensure that debt is spent on productive purposes to improve growth prospects and that all debt related transactions are transparently reported.

Convex Risk Measures based on Divergence
Paul Dommel,Alois Pichler
arXiv

Risk measures connect probability theory or statistics to optimization, particularly to convex optimization. They are nowadays standard in applications of finance and in insurance involving risk aversion. This paper investigates a wide class of risk measures on Orlicz spaces. The characterizing function describes the decision maker's risk assessment towards increasing losses. We link the risk measures to a crucial formula developed by Rockafellar for the Average Value-at-Risk based on convex duality, which is fundamental in corresponding optimization problems. We characterize the dual and provide complementary representations.



Do COVID-19 and crude oil prices drive the US economic policy uncertainty?
Claudiu Albulescu
arXiv

This paper investigates the effect of the novel coronavirus and crude oil prices on the United States (US) economic policy uncertainty (EPU). Using daily data for the period January 21-March 13, 2020, our Autoregressive Distributed Lag (ARDL) model shows that the new infection cases reported at global level, and the death ratio, have no significant effect on the US EPU, whereas the oil price negative dynamics leads to increased uncertainty. However, analyzing the situation outside China, we discover that both new case announcements and the COVID-19 associated death ratio have a positive influence on the US EPU.



Does a Local Bias Exidt in Equity Crowdfunding?
Hornuf, Lars,Schmitt, Matthias,Stenzhorn, Eliza
SSRN
We use hand-collected data of 20,460 investment decisions and two distinct portals to analyze whether investors in equity crowdfunding direct their investments to local firms. In line with agency theory, the results suggest that investors exhibit a local bias, even when we control for family and friends. In addition to the regular crowd, our sample includes angel-like investors, who invest considerable amounts and exhibit a larger local bias. Well-diversified investors are less likely to suffer from this behavioral anomaly. The data further show that portal design is important for attracting investors more prone to having a local bias. Overall, we find that investors who direct their investments to local firms more often pick start-ups that run into insolvency or are dissolved, which indicates that local investments in equity crowdfunding constitute a behavioral anomaly rather and a rational preference. Here again, however, portal design plays a crucial role.

Equations and Shape of the Optimal Band Strategy
Joachim de Lataillade,Ayman Chaouki
arXiv

We consider the problem of the optimal trading strategy in the presence of a price predictor, linear trading costs and a quadratic risk control. The solution is known to be a band system, a policy that induces a no-trading zone in the positions space. Using a path-integral method introduced in a previous work, we give equations for the upper and lower edges of this band, and solve them explicitly in the case of an Ornstein-Uhlenbeck predictor. We then explore the shape of this solution and derive its asymptotic behavior for large values of the predictor, without requiring trading costs to be small.



Exploring options to measure the climate consistency of real economy investments: The manufacturing industries of Norway
Dobrinevski, Alexander,Jachnik, Raphaël
RePEC
This paper presents results from a first pilot study to measure the consistency of real economy investments with climate change mitigation objectives. The analysis focuses on investments in infrastructure and equipment in the manufacturing industries in Norway between 2010 and 2017, estimated at USD 2.5 billion per year on average. The consistency or inconsistency of these investments is then measured at subsector level based on two readily available reference points: the European Union Taxonomy for Sustainable Activities, and a 2°C scenario for the Nordic region from the International Energy Agency. The analysis further identifies sources of financing in these subsectors and discusses future investment and financing challenges, in light of more ambitious forward-looking decarbonisation targets and needs. Finally, the study draws methodological conclusions and calls for further pilot studies in order to improve and scale up such analysis at international level, including in terms of using different or complementary reference points specifically aligned to the temperature goal of the Paris Agreement.

Gender Roles and the Gender Expectations Gap
D'Acunto, Francesco,Malmendier, Ulrike,Weber, Michael
SSRN
Expectations about macro-finance variables, such as inflation, vary significantly across genders, even within the same household. We conjecture that traditional gender roles expose women and men to different economic signals in their daily lives, which in turn produce systematic variation in expectations. Using unique data on the contributions of men and women to household grocery chores, their resulting exposure to price signals, and their inflation expectations, we show that the gender expectations gap is tightly linked to participation in grocery shopping. We also document a gender gap in other economic expectations and discuss how it might affect economic choices.

Identifying Microgeographies Using Hierarchical Cluster Analysis: Startup Agglomeration and Venture Investment In U.S. Cities
Egan, Edward J.
SSRN
This paper advances a new technique for identifying, delineating, and analyzing microgeographies. It applies this technique to locate and measure agglomerations of high-growth, high-tech (HGHT) startup activity within 205 U.S. cities. Using data from 1995 to 2018 on venture-backed companies, I estimate the effect of startup agglomeration economies on ecosystem growth. I find that a one standard deviation increase in measures of startup agglomeration is associated with around a 12% increase in the next period's venture investment, and that optimal HGHT startup density appears to be around one every 2.5 hectares. I also simulate innovation districts for Houston, Texas. I find that an optimally sized and centrally located innovation district could increase Houston's venture investment by as much 15%, while the currently proposed 'Innovation Corridor' could reduce it by as much as 5%.

On non-uniqueness in mean field games
Erhan Bayraktar,Xin Zhang
arXiv

We analyze an $N+1$-player game and the corresponding mean field game with state space $\{0,1\}$. The transition rate of $j$-th player is the sum of his control $\alpha^j$ plus a minimum jumping rate $\eta$. Instead of working under monotonicity conditions, here we consider an anti-monotone running cost. We show that the mean field game equation may have multiple solutions if $\eta < \frac{1}{2}$. We also prove that that although multiple solutions exist, only the one coming from the entropy solution is charged (when $\eta=0$), and therefore resolve a conjecture of ArXiv: 1903.05788.



Optimal Market Making in the Presence of Latency
Xuefeng Gao,Yunhan Wang
arXiv

This paper studies optimal market making for large-tick assets in the presence of latency. We consider a random walk model for the asset price, and formulate the market maker's optimization problem using Markov Decision Processes (MDP). We characterize the value of an order and show that it plays the role of one-period reward in the MDP model. Based on this characterization, we provide explicit criteria for assessing the profitability of market making when there is latency. Under our model, we show that a market maker can earn a positive expected profit if there are sufficient uninformed market orders hitting the market maker's limit orders compared with the rate of price jumps, and the trading horizon is sufficiently long. In addition, our theoretical and numerical results suggest that latency can be an additional source of risk and latency impacts negatively the performance of market makers.



Rentabilidad de los Fondos de Pensiones en España. 2004-2019 (Return of Pension Funds in Spain. 2004-2019)
Fernandez, Pablo,de Apellániz, Eduardo,Fernández Acín, Juan
SSRN
Spanish Abstract: En el periodo diciembre 2004 - diciembre 2019, la rentabilidad del IBEX 35 fue 110% (promedio anual 5,07%) y la de los bonos del Estado a 15 años 77% (promedio anual 3,88%). La rentabilidad media de los fondos de pensiones fue 43,5% (promedio anual 2,44%).Entre los 388 fondos de pensiones con 15 años de historia, sólo 22 superaron la rentabilidad del IBEX 35 y 49 la de los bonos del Estado a 15 años. 3 fondos tuvieron rentabilidad negativa.Los 1.004 fondos de pensiones del sistema individual tenían (diciembre 2019) 7,4 millones de partícipes y un patrimonio de €78.532 millones.English Abstract: During the last 15 year period (2004-2019), the average return of the pension funds in Spain (2.44%) was lower than the return of Government Bonds (3.88%). Only 49 funds (out of 388) had a higher return than the 15-year Government Bonds. Nevertheless, on December 31, 2019, 7.4 million investors had 78.5 billion euros invested in pension funds.

Short-Term Trend: A Jewel Hidden in Daily Returns
Molyboga, Marat,Swedroe, Larry E,Qian, Junkai
SSRN
This paper examines the performance of time-series momentum strategies using daily returns for 78 futures markets across four major asset classes between January 1985 and December 2017. We find that the 252-day, 63-day and 21-day momentum strategies perform similarly to the previously documented 12-month, 3-month and 1-month momentum strategies, respectively. The performance is stronger with volatility-based position sizing, robust to implementation considerations such as a one day gap between signal generation and execution, and persistent across asset classes and sub-periods. We introduce a shorter duration momentum strategy with weekly rebalancing frequency, which cannot be replicated using monthly returns. We find that the short-term strategy is a strong diversifier to the longer-term strategies, but the benefit may be reduced, or even completely offset, if the quality of trade execution is poor. We also find that the positive contribution of short-term momentum is driven by its superior diversifying characteristics rather than due to the rebalancing frequency effect.

Supreme Court Journalism: From Law to Spectacle?
Sullivan, Barry,Tilley, Cristina
SSRN
Few people outside certain specialized sectors of the press and the legal profession have any particular reason to read the increasingly voluminous opinions through which the Justices of the Supreme Court explain their interpretations of the Constitution and laws. Most of what the public knows about the Supreme Court necessarily comes from the press. That fact raises questions of considerable importance to the functioning of our constitutional democracy: How, for example, does the press describe the work of the Supreme Court? And has the way in which the press describes the work of the Court changed over the past several decades?This Article seeks to address those questions by comparing the language used in print media coverage of two highly salient cases involving similar legal issues decided fifty years apart: Brown v. Board of Education and Parents Involved in Community Schools v. Seattle School District No. 1. Our study suggests that, at least in highly salient cases, the nature of print media coverage may well have changed dramatically during that fifty-year interval. More specifically, our study suggests that while the mid-twentieth century press described the Court’s decisions largely in terms of the legal questions presented, the contemporary press seems more likely to describe the Court’s decisions in non-legal termsâ€"as something resembling a spectacle, in which unelected judges are presumed to decide cases, not on properly contested legal grounds, but based on their respective political commitments.That conclusion is striking. First, it suggests that in the ongoing scholarly debate over the nature of the Justices’ approach to their work, the press has chosen sides. Rather than closely interrogating the Court’s work to determine whether particular analyses and results can be defended on legal grounds, contemporary reporting seems to proceed on the assumption that that question lacks salienceâ€"because we already know that the Justices’ political views and allegiances are the true drivers of Supreme Court decisions. Thus, contemporary press coverage tends to emphasize such factors as the political affiliation of the president who appointed a particular Justice. Second, it raises questions about the way in which the contemporary press is discharging its responsibility to educate the public about the Court and its work. It also raises the possibility that the public will become predisposed to doubt the Court’s legitimacy, and, indeed, the very legitimacy of the American system of judicial review. If the Court’s decisions really reflect nothing more than the Justices’ political predilections and commitments, or those of the elites to which they belong, it is important for the public to know that. Nothing could be more important than discovering and documenting the fact that the Justices wear no clothes. On the other hand, whether Supreme Court decisions deserve to be viewed in that way is a question that needs to be tested through a careful examination of the Court’s work product. It is something to be proved rather than presumed. The contemporary print media’s seemingly casual assumption that the main point about reporting on the Supreme Court is not to test the validity of the Court’s reasoning, and explore its flaws, but to try to trace connections between the Justices’ voting behavior and their political or other commitments, may well corrode public confidence in the Court. If that occurs unnecessarily, and without adequate justification, the consequences for the institution of judicial review may well be dire. Moreover, if the public’s expectations are lowered, so too may be the standards the Justices set for themselves and each other. In other words, if the press leads us to believe that the Court’s work product is nothing more than politics, that may well become a self fulfilling prophecyâ€"if it has not already happened.

The X-Value Factor
de Oliveira Souza, Thiago
SSRN
Value normalizes size by book equity, which is a (relatively bad) proxy for expected cash flows. X-value normalizes size by the recursive out-of-sample expectation of each firm’s net income, based on its financials, with coefficients estimated by industry. Unlike value (but similarly constructed), the resulting X-value factor is unspanned by the Fama/French factors â€" market, size, value, investment, and profitability â€" individually or in different combinations (each factor and the market; all factors together; all except value). X-value spans the value and investment premiums with a Sharpe ratio of 0.57 (compared to 0.39 for value).

Transport plans with domain constraints
Erhan Bayraktar,Xin Zhang,Zhou Zhou
arXiv

This paper focuses on martingale optimal transport problems when the martingales are assumed to have bounded quadratic variation. First, we give a result that characterizes the existence of a probability measure satisfying some convex transport constraints in addition to having given initial and terminal marginals. Several applications are provided: martingale measures with volatility uncertainty, optimal transport with capacity constraints, and Skorokhod embedding with bounded times. Next, we extend this result to multi-marginal constraints. Finally, we consider an optimal transport problem with constraints and obtain its Kantorovich duality. A corollary of this result is a monotonicity principle which gives a geometric way of identifying the optimizer.



When Are Financial Covenants Relevant?
Davydenko, Sergei A.,Elkamhi, Redouane,Salerno, Marco
SSRN
This paper shows that financial covenants have no value for creditors of highly levered firms, because an attempt to enforce their rights in technical default would result in a lower payoff than continued operations under shareholders' control. This explains the widespread use of cov-lite loans by junk firms. By contrast, for investment-grade firms tightly set covenants allow creditors to demand full repayment while the firm is still solvent. This ensures that creditors sustain no loss regardless of the underlying default probability, mitigating their concerns about the firm's financial health and alleviating adverse selection in lending. We show that the optimal strictness of financial covenants is hump-shaped in the firm's leverage.