# Research articles for the 2020-03-17

SSRN

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
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 EspaÃ±a. 2004-2019 (Return of Pension Funds in Spain. 2004-2019)
Fernandez, Pablo,de ApellÃ¡niz, Eduardo,FernÃ¡ndez AcÃ­n, 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 aÃ±os 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 aÃ±os de historia, sÃ³lo 22 superaron la rentabilidad del IBEX 35 y 49 la de los bonos del Estado a 15 aÃ±os. 3 fondos tuvieron rentabilidad negativa.Los 1.004 fondos de pensiones del sistema individual tenÃ­an (diciembre 2019) 7,4 millones de partÃ­cipes y un patrimonio de â‚¬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

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 firmâ€™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.