# Research articles for the 2019-07-04

SSRN

The design of the difficulty adjustment algorithm (DAA) of the Bitcoin system is vulnerable as it dismisses miners' response to the difficulty adjustment. We develop an economic model of the Proof-of-Work based blockchain system. Our model allows miners to pause operation when the expected reward is below the shutdown point. Hence, the supply of aggregate hash power can be elastic in the cryptocurrency price and the difficulty target of the mining puzzle. We prove that, when the hash supply is elastic, the Bitcoin DAA fails to generate a new block at a constant rate. In contrast, the DAA of another blockchain system, Bitcoin Cash, is shown to be stable even when the cryptocurrency price is volatile and the supply of hash power is highly elastic. We also provide empirical evidence and simulation results supporting the model's prediction. Our results indicate that the current Bitcoin system might collapse once a sharp price fall lowers the reward for mining denominated in fiat money. However, such a crisis can be prevented through upgrading.

SSRN

Recent theoretical work suggests that short sellers can manipulate firms in making suboptimal investment decisions. To address this question, I utilize a panel vector autoregression methodology to determine whether short sellers improve or harm the efficiency of firmsâ€™ capital investment. Overall, I show that while short selling lowers capital investment, it nevertheless improves the efficiency of capital investment by Granger-causing an increase to firmsâ€™ marginal product of capital. However, in subsample analyses, I find some support for manipulative short selling taking place in firms with high levels of short-term leverage and mixed evidence in firms with high liquidity.

arXiv

Standard macroeconomic models assume that households are rational in the sense that they are perfect utility maximizers, and explain economic dynamics in terms of shocks that drive the economy away from the stead-state. Here we build on a standard macroeconomic model in which a single rational representative household makes a savings decision of how much to consume or invest. In our model households are myopic boundedly rational heterogeneous agents embedded in a social network. From time to time each household updates its savings rate by copying the savings rate of its neighbor with the highest consumption. If the updating time is short, the economy is stuck in a poverty trap, but for longer updating times economic output approaches its optimal value, and we observe a critical transition to an economy with irregular endogenous oscillations in economic output, resembling a business cycle. In this regime households divide into two groups: Poor households with low savings rates and rich households with high savings rates. Thus inequality and economic dynamics both occur spontaneously as a consequence of imperfect household decision making. Our work here supports an alternative program of research that substitutes utility maximization for behaviorally grounded decision making.

arXiv

We investigate the existence of affine realizations for term structure models driven by L\'evy processes. It turns out that we obtain more severe restrictions on the volatility than in the classical diffusion case without jumps. As special cases, we study constant direction volatilities and the existence of short rate realizations.

SSRN

This unique study examines the moderation effect on the relationship between financial inclusion, and institutional quality on the financial development of 45 Organization of Islamic Cooperation (OIC) countries. For empirical analysis, panel data is used for the period 2000 to 2016. We use the Arellano-Bond Generalized Method of Moments (GMM) and 2sls method in our estimations to draw multidimensional results. The empirical results confirm the significant positive relationship between the FII, IQI, and FDP. Interestingly, we find that institutional quality moderates the financial inclusion and has a significant positive impact on financial development. Our findings are robust to the use of FII, IQI, and FDP. Therefore, policymakers must sensibly understand the pivotal role of financial inclusion and institutional quality in establishing sustainable future development of OIC countries.

arXiv

Using the most comprehensive source of commercially available data on the US National Market System, we analyze all quotes and trades associated with Dow 30 stocks in 2016 from the vantage point of a single and fixed frame of reference. We find that inefficiencies created in part by the fragmentation of the equity marketplace are relatively common and persist for longer than what physical constraints may suggest. Information feeds reported different prices for the same equity more than 120 million times, with almost 64 million dislocation segments featuring meaningfully longer duration and higher magnitude. During this period, roughly 22% of all trades occurred while the SIP and aggregated direct feeds were dislocated. The current market configuration resulted in a realized opportunity cost totaling over $160 million when compared with a single feed, single exchange alternative---a conservative estimate that does not take into account intra-day offsetting events.

SSRN

Using the Emerging Market Debt Crises of the late 1990s, a shock that directly impactedsome U.S. banks but not their domestic borrowers, we study the causal impact of lenderhealth on covenant-violating borrowers. Using difference-in-differences, we find that banksexposed to the crises become relatively more likely to be stringent with covenant violators.Such stringency has real effects, as covenant violators become more likely to suffer a distressed delisting if their lenders are crisis-exposed. We also find effects for lender health onborrower investments, but these effects are not specific to covenant-violating borrowers.

SSRN

Currently financial stress test simulations that take into account multiple interacting contagion mechanisms are conditional on a specific, subjectively imposed stress-scenario. Eigenvalue-based approaches, in contrast, provide a scenario-independent measure of systemic stability, but only handle a single contagion mechanism. We develop an eigenvalue-based approach that gives the best of both worlds, allowing analysis of multiple, interacting contagion channels without the need to impose a subjective stress scenario. This allows us to demonstrate that the instability due to interacting channels can far exceed that of the sum of the individual channels acting alone. We derive an analytic formula in the limit of a large number of institutions that gives the instability threshold as a function of the relative size and intensity of contagion channels, providing valuable insights into financial stability whilst requiring very little data to be calibrated to real financial systems.

arXiv

In online portfolio optimization the investor makes decisions based on new, continuously incoming information on financial assets (typically their prices). In our study we consider a learning algorithm, namely the Kiefer--Wolfowitz version of the Stochastic Gradient method, that converges to the log-optimal solution in the threshold-type, buy-and-sell strategy class.

The systematic study of this method is novel in the field of portfolio optimization; we aim to establish the theory and practice of Stochastic Gradient algorithm used on parametrized trading strategies.

We demonstrate on a wide variety of stock price dynamics (e.g. with stochastic volatility and long-memory) that there is an optimal threshold type strategy which can be learned. Subsequently, we numerically show the convergence of the algorithm. Furthermore, we deal with the typically problematic question of how to choose the hyperparameters (the parameters of the algorithm and not the dynamics of the prices) without knowing anything about the price other than a small sample.

arXiv

Behavioral economics changed the way we think about market participants and revolutionized policy-making by introducing the concept of choice architecture. However, even though effective on the level of a population, interventions from behavioral economics, nudges, are often characterized by weak generalisation as they struggle on the level of individuals. Recent developments in data science, artificial intelligence (AI) and machine learning (ML) have shown ability to alleviate some of the problems of weak generalisation by providing tools and methods that result in models with stronger predictive power. This paper aims to describe how ML and AI can work with behavioral economics to support and augment decision-making and inform policy decisions by designing personalized interventions, assuming that enough personalized traits and psychological variables can be sampled.

SSRN

Two stocks covered by a news article can be considered as connected through a media network. This study examine the impact of media news network on stock return co-movement. Using the number of news articles covering two stocks as a proxy for the strength of media network connection, we nd that the strength of connection predicts cross-sectional variation in return correlation, controlling for other sources of co-movement. We further analyse an exogenous change in common media coverage around the addition of a stock to the S&P 500 index. We show that the media news connection indeed cause an excessive return co-movement. Moreover, high network centrality stocks can achieve higher price efficiency than those low network centrality stocks. Furthermore, high network centrality stocks can predict the returns of connected low network centrality stocks while not vice versa. This indicates some common shocks may affect stocks that are connected in a media news network. Those common shocks signicantly predict connected rm's fundamental and returns, and disseminates slowly from high network centrality stocks to low network centrality stocks in media network.

RePEC

This article describes how the opportunities and challenges of FinTech Sharia in the face of the industrial revolution 4.0. By using a negation approach, this study concludes that FinTech Sharia which is the development of technological innovations that are in accordance with sharia provisions and becomes a solution to avoid interest transactions. The synergy between the Islamic financial sector and information technology innovation should also be a challenge as well as an opportunity for all actors in the Islamic finance industry to catch up with the conventional financial industry.

arXiv

This paper is concerned with an optimal reinsurance and investment problem for an insurance firm under the criterion of mean-variance. The driving Brownian motion and the rate in return of the risky asset price dynamic equation cannot be directly observed. And the short-selling of stocks is prohibited. The problem is formulated as a stochastic linear-quadratic (LQ) optimal control problem where the control variables are constrained. Based on the separation principle and stochastic filtering theory, the partial information problem is solved. Efficient strategies and efficient frontier are presented in closed forms via solutions to two extended stochastic Riccati equations. As a comparison, the efficient strategies and efficient frontier are given by the viscosity solution for the Hamilton-Jacobi-Bellman (HJB) equation in the full information case. Some numerical illustrations are also provided.

arXiv

This article presents a set of tools for the modeling of a spatial allocation problem in a large geographic market and gives examples of applications. In our settings, the market is described by a network that maps the cost of travel between each pair of adjacent locations. Two types of agents are located at the nodes of this network. The buyers choose the most competitive sellers depending on their prices and the cost to reach them. Their utility is assumed additive in both these quantities. Each seller, taking as given other sellers prices, sets her own price to have a demand equal to the one we observed. We give a linear programming formulation for the equilibrium conditions. After formally introducing our model we apply it on two examples: prices offered by petrol stations and quality of services provided by maternity wards. These examples illustrate the applicability of our model to aggregate demand, rank prices and estimate cost structure over the network. We insist on the possibility of applications to large scale data sets using modern linear programming solvers such as Gurobi. In addition to this paper we released a R toolbox to implement our results and an online tutorial (this http URL)

RePEC

This article describes how the opportunities and challenges of FinTech Sharia in the face of the industrial revolution 4.0. By using a negation approach, this study concludes that FinTech Sharia which is the development of technological innovations that are in accordance with sharia provisions and becomes a solution to avoid interest transactions. The synergy between the Islamic financial sector and information technology innovation should also be a challenge as well as an opportunity for all actors in the Islamic finance industry to catch up with the conventional financial industry.

arXiv

This paper introduces measures for how each moment contributes to the precision of the parameter estimates in GMM settings. For example, one of the measures asks what would happen to the variance of the parameter estimates if a particular moment was dropped from the estimation. The measures are all easy to compute. We illustrate the usefulness of the measures through two simple examples as well as an application to a model of joint retirement planning of couples. We estimate the model using the UK-BHPS, and we find evidence of complementarities in leisure. Our sensitivity measures illustrate that the precision of the estimate of the complementarity is primarily driven by the distribution of the differences in planned retirement dates. The estimated econometric model can be interpreted as a bivariate ordered choice model that allows for simultaneity. This makes the model potentially useful in other applications.

RePEC

The post financial crisis period has been associated with increased countercyclical use of various financial policies, including residency-based measures. This paper analyses in a single analytical framework the relative effectiveness of three types of financial policies – macroprudential (foundations), currency-based (fences), and residency-based measures (fire doors). The findings in this paper are based on a granular quarterly database of adjustments in these policies that covers both advanced and emerging economies from 2000 to 2015. The results show that residency-based measures on bonds and credit reduce capital inflows but provide limited support for a credit-mitigation role. While no evidence emerges that macroprudential measures alter capital inflows, most appear effective in reducing credit growth. Currency-based measures may reduce both inflows and credit growth (particularly FX reserve requirements and FX lending regulations). These results indicate that the impact of policies needs to be analysed at a granular level and that policy makers should adopt an integrated view of the financial policy toolkit.

SSRN

This paper explores the modelling of time-varying dynamics of the elasticity of substitution between money and liquid assets considered near-money. The liquidity premium between near-money assets over other safe but illiquid assets can vary with time, depending on economic conditions. The model presented in this paper introduces dynamics into the elasticity of substitution between deposits and near-money assets in order to explicitly capture such variation in the modelling of liquidity premium. Adding an autoregressive structure to the elasticity of substitution accounts for the pattern of expansion and contraction described in the credit markets literature, and yields a more realistic model for the expansion and contraction of liquidity in funding markets. The model is applied to U.S. and Canadian data and is shown to exhibit key economic features with important policy implications for market participants and regulators.