# Research articles for the 2019-12-10

arXiv

This book, which is in Spanish, provides detailed descriptions, including over 550 mathematical formulas, for over 150 trading strategies across a host of asset classes (and trading styles). This includes stocks, options, fixed income, futures, ETFs, indexes, commodities, foreign exchange, convertibles, structured assets, volatility (as an asset class), real estate, distressed assets, cash, cryptocurrencies, miscellany (such as weather, energy, inflation), global macro, infrastructure, and tax arbitrage. Some strategies are based on machine learning algorithms (such as artificial neural networks, Bayes, k-nearest neighbors). We also give: source code for illustrating out-of-sample backtesting with explanatory notes; around 2,000 bibliographic references; and over 900 glossary, acronym and math definitions. The presentation is intended to be descriptive and pedagogical.

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Este libro proporciona descripciones detalladas, que incluyen m\'as de 550 f\'ormulas matem\'aticas, para m\'as de 150 estrategias de trading para una gran cantidad de clases de activos y estilos de trading. Esto incluye acciones, opciones, bonos (renta fija), futuros, ETFs, \'indices, commodities, divisas, bonos convertibles, activos estructurados, volatilidad (como clase de activos), bienes inmuebles, activos en distress, efectivo, criptomonedas, miscel\'aneos (como clima, energ\'ia, inflaci\'on), macro global, infraestructura y arbitraje impositivo. Algunas estrategias se basan en algoritmos de aprendizaje autom\'atico (como redes neuronales artificiales, Bayes, k vecinos m\'as cercanos). El libro tambi\'en incluye c\'odigo para backtesting fuera de la muestra con notas explicativas; cerca de 2,000 referencias bibliogr\'aficas; m\'as de 900 t\'erminos que comprenden el glosario, acr\'onimos y definiciones matem\'aticas. La presentaci\'on pretende ser descriptiva y pedag\'ogica.

A Contribution to Theory of Factor Income Distribution, Cambridge Capital Controversy and Equity Premium Puzzle
Liu, Xiaofeng
SSRN
Under very general conditions, we construct a micro-macro model for closed economy with a large number of heterogeneous agents. By introducing both financial capital (i.e. valued capitalâ€"equities of firms) and physical capital (i.e. capital goods), our framework gives a logically consistent, complete factor income distribution theory with micro-foundation. The model shows factor incomes obey different distribution rules at the micro and macro levels, while marginal distribution theory and no-arbitrage princi-ple are unified into a common framework. Our efforts solve the main problems of Cambridge capital controversy, and reasonably explain the equity premium puzzle. Strong empirical evidences support our results.

Adaptive Financial Fraud Detection in Imbalanced Data with Time-Varying Poisson Processes
Régis Houssou,Jérôme Bovay,Stephan Robert
arXiv

This paper discusses financial fraud detection in imbalanced dataset using homogeneous and non-homogeneous Poisson processes. The probability of predicting fraud on the financial transaction is derived. Applying our methodology to the financial dataset shows a better predicting power than a baseline approach, especially in the case of higher imbalanced data.

Credit Guarantees and the Cost of Debt: Evidence from Corporate Loans
Beyhaghi, Mehdi
SSRN
Over half of U.S. corporate loans are guaranteed by legal entities separate from borrowing firms. However, little is known about how banks measure the marginal effect of a credit guarantee on loan risk. Using a quasi-experimental setting that accounts for both bank and firm characteristics, I find that banks on average provide a discount of 15% on the cost of borrowing when the guarantor is a U.S. government agency. This discount is about 4.6% when the guarantee is provided by an internal guarantor (parent company). Moreover, the discount provided is generally lower with a private guarantor and a personal guarantor.

Roberto Ernani Porcher Junior
arXiv

This paper questions some current ideas about the practice of specific capital market operations - the so-called day trading operations. The text advanced from theoretical propositions to a detailed analysis of the study entitled "Is it possible to live by day-trading?" (CHAGUE and GIOVANNETTI, 2019), to which it offers a counterpoint. This investigation reveal the existence of important elements that are not yet properly weighed in the treatment of the current theme, leading to loss of dimensions that are - or should be - inseparable from this type of research. The conclusion reached is that the existing scientific evidence does not show that the adoption of the day trade as an occupation is economically unsustainable, nor does it prove the impossibility of evolution of the day traders' operational performance over time.

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Equilibria and Systemic Risk in Saturated Networks
Leonardo Massai,Giacomo Como,Fabio Fagnani
arXiv

We undertake a fundamental study of network equilibria modeled as solutions of fixed point of monotone linear functions with saturation nonlinearities. The considered model extends one originally proposed to study systemic risk in networks of financial institutions interconnected by mutual obligations and is one of the simplest continuous models accounting for shock propagation phenomena and cascading failure effects. We first derive explicit expressions for network equilibria and prove necessary and sufficient conditions for their uniqueness encompassing and generalizing several results in the literature. Then, we study jump discontinuities of the network equilibria when the exogenous flows cross a certain critical region consisting of the union of finitely many linear submanifolds of co-dimension 1. This is of particular interest in the financial systems context, as it shows that even small shocks affecting the values of the assets of few nodes, can trigger catastrophic aggregated loss to the system and cause the default of several agents.

Equity Crowdfunding in Germany and the UK: Follow-Up Funding and Firm Failure
Hornuf, Lars,Schmitt, Matthias,Stenzhorn, Eliza
SSRN
Today, startups often obtain financing via the Internet through many small contributions of nonsophisticated investors. Yet little is known about whether these startups can ultimately build enduring businesses. In this article, we hand-collected data from 14 different equity crowdfunding (ECF) portals and 426 firms that ran at least one successful ECF campaign in Germany or the United Kingdom. We empirically analyze different factors affecting follow-up funding and firm failure. The findings show that German firms that received ECF stood a higher chance of obtaining follow-up funding through business angels or venture capitalists, but also had a higher likelihood of failure. The number of senior managers, subsequent successful ECF campaigns, and the number of venture capital investors all had a positive impact on obtaining post-campaign financing, while firm age had a negative impact. Subsequent successful ECF campaigns were significant predictors decreasing firm failure.

Filtration shrinkage, the structure of deflators, and failure of market completeness
Constantinos Kardaras,Johannes Ruf
arXiv

We analyse the structure of local martingale deflators projected on smaller filtrations. In a general continuous-path setting, we show that the local martingale part in the multiplicative Doob-Meyer decomposition of projected local martingale deflators are themselves local martingale deflators in the smaller information market. Via use of a Bayesian filtering approach, we demonstrate the exact mechanism of how updates on the possible class of models under less information result in the strict supermartingale property of projections of such deflators. Finally, we demonstrate that these projections are unable to span all possible local martingale deflators in the smaller information market, by investigating a situation where market completeness is not retained under filtration shrinkage.

Financial Contagion in a Generalized Stochastic Block Model
Nils Detering,Thilo Meyer-Brandis,Konstantinos Panagiotou,Daniel Ritter
arXiv

One of the most defining features of the global financial network is its inherent complex and intertwined structure. From the perspective of systemic risk it is important to understand the influence of this network structure on default contagion. Using sparse random graphs to model the financial network, asymptotic methods turned out powerful to analytically describe the contagion process and to make statements about resilience. So far, however, they have been limited to so-called {\em rank one} models in which informally the only network parameter is the degree sequence (see (Amini et. al. 2016) and (Detering et. al. 2019) for example) and the contagion process can be described by a one dimensional fix-point equation. These networks fail to account for a pronounced block structure such as core/periphery or a network composed of different connected blocks for different countries. We present a much more general model here, where we distinguish vertices (institutions) of different types and let edge probabilities and exposures depend on the types of both, the receiving and the sending vertex plus additional parameters. Our main result allows to compute explicitly the systemic damage caused by some initial local shock event, and we derive a complete characterisation of resilient respectively non-resilient financial systems. This is the first instance that default contagion is rigorously studied in a model outside the class of rank one models and several technical challenges arise. Moreover, in contrast to previous work, in which networks could be classified as resilient or non resilient, independent of the distribution of the shock, information about the shock becomes important in our model and a more refined resilience condition arises. Among other applications of our theory we derive resilience conditions for the global network based on subnetwork conditions only.

Financial Liberalization, Government Stability, and Currency Crises â€" Some Evidence from South Korea and Emerging Market Economies
Chiu, Eric M. P.
SSRN
Purpose â€" Recent empirical studies have reached mixed results on the effects of financial liberalization and currency crises. We argue that this relationship is likely to depend both on whether controls are primarily on the degrees of financial liberalization and on the stability of the government. Using the disaggregated data on financial liberalization recently developed by Abiad et al (2010) for a sample of 30 emerging countries over the period 1995-2015, we attempt to investigate the political economy determinants of currency crises. Design/methodology â€" Our empirical model considers the relationship between financial liberalization and currency crises for emerging market economies. This study employs the existing theoretical framework to identify the disaggregate level for financial liberalization across countries. Using a multivariate logit model, this study attempts to estimate the interrelationship among financial liberalization, government stability and currency crises complemented by a case study of South Korea. Findings â€" Our main findings can be summarized as follows: we find strong support for the proposition that more liberalized financial institutions are positively associated with the probability of currency crises especially under less stable governments, but reduce the risks of currency crises especially for more stable governments. We also examine the role of financial systems with the case of South Korea after Asian financial crises and the results are further supported and consistent with the empirical findings. Originality/value â€" Existing studies focus on the economic factors across countries. This paper instead attempts to evaluate the effects of financial liberalization and currency crises by incorporating political considerations with newly developed dataset on financial liberalization, which are essential to the understanding of the causes of currency crises.

Italia 3 Trim 2019: Pil, Debito & Co (Italy 3Q 2019: GDP, Debt & Co.)
Mazziero, Maurizio,Lawford, Andrew,Serafini, Gabriele
SSRN
Italian Abstract: Ricerca sulla situazione economica italiana basata sui dati economici ufficiali; vengono analizzati e confrontati con il passato il debito pubblico, le riserve ufficiali, il PIL, l'inflazione e la disoccupazione. English Abstract: Research into the state of the Italian economy based on official economic data; the current Sovereign Debt, Official Reserves, GDP, Inflation and Unemployment situation is presented and and compared with the past.

Long-run implied market fundamentals: An exploration
Zimmermann, Heinz
SSRN
The paper studies the volatility and correlation pattern of the fundamental valuation parameters (growth rate and its determinants, discount rate) calculated from widely used valuation ratios using the Gordon formula and relate them to some well-known results from the asset pricing literature. Our results reveal a substantially different picture of the volatility and cyclicality of the implied valuation parameters compared to estimates from econometric models using historical returns. We argue, in the spirit of Campbell (2008), that implied Gordon parameters can be interpreted as empirical proxies for conditional steady-state market fundamentals, which is supported by our findings.

Making Good on LSTMs' Unfulfilled Promise
Daniel Philps,Artur d'Avila Garcez,Tillman Weyde
arXiv

LSTMs promise much to financial time-series analysis, temporal and cross-sectional inference, but we find that they do not deliver in a real-world financial management task. We examine an alternative called Continual Learning (CL), a memory-augmented approach, which can provide transparent explanations, i.e. which memory did what and when. This work has implications for many financial applications including credit, time-varying fairness in decision making and more. We make three important new observations. Firstly, as well as being more explainable, time-series CL approaches outperform LSTMs as well as a simple sliding window learner using feed-forward neural networks (FFNN). Secondly, we show that CL based on a sliding window learner (FFNN) is more effective than CL based on a sequential learner (LSTM). Thirdly, we examine how real-world, time-series noise impacts several similarity approaches used in CL memory addressing. We provide these insights using an approach called Continual Learning Augmentation (CLA) tested on a complex real-world problem, emerging market equities investment decision making. CLA provides a test-bed as it can be based on different types of time-series learners, allowing testing of LSTM and FFNN learners side by side. CLA is also used to test several distance approaches used in a memory recall-gate: Euclidean distance (ED), dynamic time warping (DTW), auto-encoders (AE) and a novel hybrid approach, warp-AE. We find that ED under-performs DTW and AE but warp-AE shows the best overall performance in a real-world financial task.

Market Price of Trading Liquidity Risk and Market Depth
Masaaki Kijima,Christopher Ting
arXiv

Price impact of a trade is an important element in pre-trade and post-trade analyses. We introduce a framework to analyze the market price of liquidity risk, which allows us to derive an inhomogeneous Bernoulli ordinary differential equation. We obtain two closed form solutions, one of which reproduces the linear function of the order flow in Kyle (1985) for informed traders. However, when traders are not as asymmetrically informed, an S-shape function of the order flow is obtained. We perform an empirical intra-day analysis on Nikkei futures to quantify the price impact of order flow and compare our results with industry's heuristic price impact functions. Our model of order flow yields a rich framework for not only to estimate the liquidity risk parameters, but also to provide a plausible cause of why volatility and correlation are stochastic in nature. Finally, we find that the market depth encapsulates the market price of liquidity risk.

Monetary Policy and the Corporate Bond Market: Reaching for Yield or Information Effects?
Smolyansky, Michael,Suarez, Gustavo
SSRN
Does expansionary monetary policy induce investors to reach for yield and drive up the price of risky assets? Or, do investors interpret monetary policy easing as a signal that economic fundamentals are weaker than they previously believed, prompting riskier asset prices to fall? We test these two competing hypotheses â€" i.e., the â€œreaching for yieldâ€ hypothesis and the â€œFed information effectâ€ hypothesis â€" in the context of the U.S. corporate bond market and find evidence strongly in favor of the latter. Following an unanticipated easing (tightening) of monetary policy on Federal Open Markets Committee announcement days, returns on corporate bonds with higher credit risk underperform (outperform) relative to safer corporate bonds. We conclude that monetary policy surprises are predominantly interpreted by market participants as signaling information about the state of the economy.

Paralyzed by Shock: The Portfolio Formation Behavior of Peer-to-Business Lending Investors
Dorfleitner, Gregor,Hornuf, Lars,Weber, Martina
SSRN
We study the investor behavior on a leading peer-to-business lending platform and identify a new investment mistake â€" a default shock bias. First, we find that investors stop investing in new loans and cease from diversifying their portfolio after experiencing a loan default. The default shock significantly worsens the risk-return profile of investorsâ€™ loan portfolios. The defaults investors experience are often not beyond what could have been expected based on the information that was provided by the platform ex-ante. Second, investment experience on the platform is related to better investment decisions in general, but does not reduce the default shock bias. These findings have important implications not only for the behavioral finance literature, but also more generally for new forms of Internet-based finance.

Particulate Air Pollution, Birth Outcomes, and Infant Mortality: Evidence from Japan's Automobile Emission Control Law of 1992
Tatsuki Inoue,Nana Nunokawa,Daisuke Kurisu,Kota Ogasawara
arXiv

This study investigates the impacts of the Automobile NOx Law of 1992 on ambient air pollutants and fetal and infant health outcomes in Japan. Using panel data taken from more than 1,500 monitoring stations between 1987 and 1997, we find that NOx and SO2 levels reduced by 87% and 52%, respectively in regulated areas following the 1992 regulation. In addition, using a municipal-level Vital Statistics panel dataset and adopting the regression differences-in-differences method, we find that the enactment of the regulation explained most of the improvements in the fetal death rate between 1991 and 1993. This study is the first to provide evidence on the positive impacts of this large-scale automobile regulation policy on fetal health.

Pricing Climate Risk
Gostlow, Glen
SSRN
I exploit a new dataset from Four Twenty Seven and identify physical climate risk factors that can explain the variation in global individual stock returns. North American stocks are currently exposed to an extreme rainfall factor and an overall climate risk factor. European and Japanese stocks are currently exposed to an extreme rainfall factor, a heat stress factor, and an overall climate risk factor. I assess the pricing of policy related to these risks by drawing on new data from the Transition Pathway Initiative that summarises publicly-available information on a firm's emissions and targets. Physical climate risk and transition risk factors cannot explain the returns of portfolios sorted on standard accounting variables (such as investment, momentum and profitability), and vice-versa. However, a quality factor can explain both climate-related and non-climate-related portfolios. Climate risks may be mispriced and quality captures a confounding association between the environment and the zoo of factors used to explain asset returns.

Regulating Fintech: Objectives, Principles, and Practices
SSRN
We provide an overview and key elements on the ongoing debate of whether and how to regulate fintech. The paper reviews three objectives of financial regulation (investor protection, market integrity, safeguarding financial stability) in the context of recent fintech developments, covers three guiding principles many regulators follow (legal certainty, technology neutrality, and proportionality), and ends with a suggested synopsis of current fintech regulatory practices: â€œwait-and-seeâ€, â€œsame risk, same rulesâ€ (â€œduck typingâ€), or â€œnew functionality, new rulesâ€ (â€œcodingâ€).

Remarks on stochastic automatic adjoint differentiation and financial models calibration
Dmitri Goloubentsev,Evgeny Lakshtanov
arXiv

In this work, we discuss the Automatic Adjoint Differentiation (AAD) for functions of the form $G=\frac{1}{2}\sum_1^m (Ey_i-C_i)^2$, which often appear in the calibration of stochastic models. { We demonstrate that it allows a perfect SIMD\footnote{Single Input Multiple Data} parallelization and provide its relative computational cost. In addition we demonstrate that this theoretical result is in concordance with numeric experiments.}

Shadow Banking Modes: The Chinese versus US System
Dang, Tri Vi,Liu, Loretta,Wang, Honglin,Yao, Aidan
SSRN
Using newly collected data this paper shows that Chinese shadow banking is different from the US counterpart in two important dimensions. The Chinese system creates information insensitive investment products by implicit guarantee rather than financial engineering and operates on a banking platform instead of capital markets. The theoretical model analyses why Chinese shadow banking is bank-centric and discusses the role of the Chinese government and welfare implications. This paper also formalizes the conceptual differences between implicit guarantee and securitization as well as asymmetric perception of implicit guarantee and neglected risks.

Speculative Trading, Prospect Theory and Transaction Costs
Tse, Alex S. L.,Zheng, Harry
SSRN
A speculative agent with Prospect Theory preference chooses the optimal time to purchase and then to sell an indivisible risky asset as to maximize the expected utility of the round-trip profit net of transaction costs. The optimization problem is formulated as a sequential optimal stopping problem and we provide a complete characterization of the solution. Depending on the preference and market parameters as well as the initial price of the asset, the optimal strategy can be "buy and hold", "buy low sell high", "buy high sell higher" or "no trading". Transaction costs do not necessarily curb speculative trading. For example, while a large proportional transaction cost on sale can unambiguously suppress trading participation, introducing a fixed market entry fee will indeed encourage trading when the asset price level is high.

Tax Avoidance And Earning Management In Pakistan
SSRN
Tax avoidance and evasion are major problems in Pakistan. The study attempts to provide information to investors and regulatory authorities of Pakistan about tax avoidance and its consequences. Book Effective Tax Rate (BETR) and Cash Effective Tax Rate (CETR) are used to measure tax avoidance. The unbalanced panel data of 189 non-financial firms are used for empirical analysis. The results of panel regression models show that managers manipulate the profitability signal via tax avoidance. Managers use tax avoidance to beat earnings targets, however, no evidence found to practice tax avoidance to just meet the profitability margin. In line with the behavioral finance view, the quick response of the stock market is positive to tax avoidance because investors focus on profitability without detail screening of cash flows. However, tax avoider firms are likely to have lower future profitability and future stock returns than other benchmark firms.

The JOBS Act and Mergers and Acquisitions
Chu, Yongqiang,Liu, Ming,Zhang, Shu
SSRN
We examine how the Jumpstart Our Business Startup Act (JOBS Act) affect mergers and acquisitions. We find that U.S. private targets are valued higher after the JOBS Act relative to public targets acquired by US acquirers. The announcement returns of acquirers who acquired US private targets after the JOBS Act are lower. Consistent with the argument that the JOBS Act affects firms with higher disclosure costs more, we find that the effect is more pronounced for firms with higher disclosure costs.

Two Dimensional Communication Technologies In Social Networks: Welfare Analysis
Use of healthcare services is inadequate in Ethiopia in spite of the high burden of diseases. User-fee charges are the most important factor for this deficiency in healthcare utilization. Hence, the country is introducing community based and social health insurances since 2010 to tackle such problems. This study was conducted cross-sectionally, in March 2013, to assess willingness of rural households to pay for community-based health insurance in Debub Bench district of Southwest Ethiopia. Two-stage sampling technique was used to select 845 households. Selected households were contacted using simple random sampling technique. Double bounded dichotomous choice method was used to illicit the willingness to pay. Data were analyzed with STATA 11. Krinsky and Rob method was used to calculate the mean/median with 95% CI willingness to pay after the predictors have been estimated using Seemingly Unrelated Bivariate Probit Regression. Eight hundred and eight (95.6%) of the sampled households were interviewed. Among them 629(77.8%) households were willing to join the proposed CBHI scheme. About 54% of the households in the district were willing to pay either the initial or second bids presented. On average, these households were willingness to pay was 162.61 Birr per household (8.9 US$) annually. If the community based health insurance is rolled out in the district, about half of households will contribute 163 Birr (8.9 US$) annually. If the premium exceeds the amount specified, majority of the households would not join the scheme. Key words: community based health insurance, willingness to pay, contingent valuation method, double bounded dichotomous choice, Krinsky and Robb, rural households, Ethiopia.