# Research articles for the 2021-07-27

A Reconsideration of Safety First
Arzac, Enrique R.
SSRN
This paper studies the choice theoretic properties of safety first and some of its implications for the theory of assets. Its first part presents a brief analysis of the relationship between safety first and the usually adopted axioms of risky choice. Its second part studies the attitudes toward risk of safety-first investors from the point of view of the Arrow-Pratt theory of risk aversion. The results of this analysis are then applied to the portfolio problem, and conditions for the separability of portfolio composition and scale decisions are obtained. Finally, a simple equilibrium valuation model for a market of safety-first investors is derived and shown to include as a special case the valuation formula of the two-parameter capital asset pricing literature.

Bayesian Policy Learning Modeling of COVID-19 Interventions: the Impact on Household Debt Repayment in UK and Internationally
Mamatzakis, E. C.,Ongena, Steven,Tsionas, Mike
SSRN
The rapid spread of COVID-19 across the globe primed a variety of non-pharmaceutical interventions (NPIs). Given these NPIs, whether the SIR parameters followed a Bayesian learning, a random walk pattern or other type of learning with evolving epidemiological data over time has implications for policy learning literature. Using a sample of UK country specific data and also for 168 countries and 51,083 country-date observations (January 1, 2020 to January 9, 2021), we estimate a SIR model with time-varying Î² and Î³ parameters in three context of a dynamic panel vector autoregressive model. Although learning does not seem to be taking place, and despite the absence of evidence of governmentsâ€™ learning from the past, most policy measures are effective in reducing the values of the Î² and Î³ parameters. We also provide estimates of time-varying Î² and Î³ that can be used widely, and we develop novel testing procedures for testing for Bayesian learning.

Bitcoin option pricing: A market attention approach
Alvaro Guinea,Alet Roux
arXiv

A model is proposed that models Bitcoin prices by taking into account market attention. Assuming that market attention follows a mean-reverting Cox-Ingersoll-Ross process and allowing it to influence Bitcoin returns (after some delay) leads to a tractable affine model with semi-closed formulae for European put and call prices. A maximum likelihood estimation procedure is proposed for this model. The accuracy of its call and put prices outperforms a number of standard models when tested on real data.

Constant Function Market Makers: Multi-Asset Trades via Convex Optimization
Guillermo Angeris,Akshay Agrawal,Alex Evans,Tarun Chitra,Stephen Boyd
arXiv

The rise of Ethereum and other blockchains that support smart contracts has led to the creation of decentralized exchanges (DEXs), such as Uniswap, Balancer, Curve, mStable, and SushiSwap, which enable agents to trade cryptocurrencies without trusting a centralized authority. While traditional exchanges use order books to match and execute trades, DEXs are typically organized as constant function market makers (CFMMs). CFMMs accept and reject proposed trades based on the evaluation of a function that depends on the proposed trade and the current reserves of the DEX. For trades that involve only two assets, CFMMs are easy to understand, via two functions that give the quantity of one asset that must be tendered to receive a given quantity of the other, and vice versa. When more than two assets are being exchanged, it is harder to understand the landscape of possible trades. We observe that various problems of choosing a multi-asset trade can be formulated as convex optimization problems, and can therefore be reliably and efficiently solved.

Contagion Effect in ASEAN-5 Currency Markets During COVID-19
Shahrier, Nur Ain,Fah, Chung Tin
SSRN
The aim of this study is to examine an existence of contagion in ASEAN-5 currency markets during COVID-19 period, the type of contagion whether it is pure contagion that happens in the short run only or fundamentals-based contagion in the long run and the country source of this contagion effect. The study starts by imposing structure to the regional exchange rates guided by variable lag Granger causality and variable lag Transfer Entropy, followed by co-integration and Error Correction Model (VECM) within the Structural VAR framework to capture the short run, long run and error correction term (ect) in currency market of ASEAN-5. The next empirical framework used is wavelet analysis specifically wavelet power spectrum and wavelet coherency to capture the multi scale time and frequency domain of currency market volatility and covariance respectively. The VECM findings show there exists long run cointegration in the ASEAN-5 currency markets during COVID-19 and any disequilibrium will be adjusted by Indonesian Rupiah, Malaysia Ringgit and Singapore Dollar at daily rate of adjustments of 6.58%, 1.47% and 2.45% respectively. The wavelet power spectrum provides evidence of short run and long run contagion effect in Indonesia, Malaysia and Singapore currency market, while Philippines and Thailand experience minimal contagion effect in the short run and heightened volatility in the long run for Thailand. No long run contagion effect for Philippines. The wavelet coherency shows contagion effect emanating from Indonesia Rupiah to its neighboring countries in the short and only to Thailand and Malaysia in the long run.

Deep Learning for Market by Order Data
Zihao Zhang,Bryan Lim,Stefan Zohren
arXiv

Market by order (MBO) data - a detailed feed of individual trade instructions for a given stock on an exchange - is arguably one of the most granular sources of microstructure information. While limit order books (LOBs) are implicitly derived from it, MBO data is largely neglected by current academic literature which focuses primarily on LOB modelling. In this paper, we demonstrate the utility of MBO data for forecasting high-frequency price movements, providing an orthogonal source of information to LOB snapshots and expanding the universe of alpha discovery. We provide the first predictive analysis on MBO data by carefully introducing the data structure and presenting a specific normalisation scheme to consider level information in order books and to allow model training with multiple instruments. Through forecasting experiments using deep neural networks, we show that while MBO-driven and LOB-driven models individually provide similar performance, ensembles of the two can lead to improvements in forecasting accuracy - indicating that MBO data is additive to LOB-based features.

Development of a Method for Selected Financing of Scientific and Educational Institutions Through Targeted Capital Investment in the Development of Innovative Technologies
Levchenko, Iaroslava,Dmytriieva, Oksana,Shevchenko, Inna,Britchenko, Igor,Kruhlov, Vitalii,Avanesova, Nina,Kudriavtseva, Oksana,Solodovnik, Olesia
SSRN
The problem of supporting scientific and educational institutions is considered. A method of selective financing of scientific and educational institutions that create innovative technologies taking into account their investment in innovative developments is proposed. On the basis of statistical data on the indicators for assessing the activities of scientific and educational institutions and the indicator of the innovative potential of a scientific and educational institution from the production of innovations (PNn), their rating was calculated. The essence of PNn is to compare the indicators of the volumes of income of the special fund Dsfn and the volume of expenditures of the scientific and educational institution Vn.In order to stimulate scientific and educational institutions to create innovative technologies, it was proposed to introduce targeted investments. The problem of quantifying the rate of premium on the basis of an integrated approach in terms of indicators of innovative potential from the production of innovations and the rating of a scientific and educational institution for 2 institutions (namely: K and H) has been solved. Institution K will receive a large increase, and institution N will receive a smaller increase, the value of which will be 56.23 % and 43.76 %, respectively. The results showed the independence of the indicator of the innovative potential of a scientific and educational institution from the production of innovations from the previous rating of a scientific and educational institution, or vice versa. The proposed methodology has been tested by an experimental method, targeted investments have been determined based on an integrated approach in terms of indicators of innovative potential and the rating of a scientific and educational institution.This study is of practical interest to government authorities and grantors when allocating funds according to the vector of selective financing of scientific and educational institutions through targeted investments in the development of innovative technologies, and theoretically â€" to researchers dealing with issues of financial security, protectionism and public administration.

Dhaka Water-logging: Causes, Effects and Remedial Policy Options
Hossain Ahmed Taufiq
arXiv

Water-logging is a major challenge for Dhaka city, the capital of Bangladesh. The rapid, unregulated, and unplanned urbanization, as well as detrimental social, economic, infrastructural, and environmental consequences, not to mention diseases like dengue, challenge the several crash programs combating water-logging in the city. This study provides a brief contextual analysis of the Dhakas topography and natural, as well as storm water drainage systems, before concentrating on the man-made causes and effects of water-logging, ultimately exploring a few remedial measures.

Distributional uncertainty of the financial time series measured by G-expectation
Shige Peng,Shuzhen Yang
arXiv

Based on law of large numbers and central limit theorem under nonlinear expectation, we introduce a new method of using G-normal distribution to measure financial risks. Applying max-mean estimators and small windows method, we establish autoregressive models to determine the parameters of G-normal distribution, i.e., the return, maximal and minimal volatilities of the time series. Utilizing the value at risk (VaR) predictor model under G-normal distribution, we show that the G-VaR model gives an excellent performance in predicting the VaR for a benchmark dataset comparing to many well-known VaR predictors.

Epidemic and Pandemic Risk Transfer Solutions and Options for Public Sector Support
Kraut, Gunther,de Kuiper, Raymond
SSRN
The current COVID-19 pandemic caused a significant shock to the world economy which led to large-scale government support measures and thus proved the non-resilience of the current financial ecosystem, with devastating effects on the human global population. As research indicates, pandemic disease outbreaks will increase in frequency and impact in the future. This paper addresses the question how to possibly create a prudent and resilient financial ecosystem resistant to future disease outbreaks and minimalizing the individual financial and economic impact. While insurance risk transfer solutions have been available for epidemic risk, fundamental hurdles of insurability prevent the supply of sufficient capacity to address the magnitude of potential economic losses. A risk transformation market platform is described which enables a wider participation of capacity providers. While initially focusing on a specialty market segment, it is analysed how governments can contribute, alongside private sector investors, to an accelerated industrialization of this market segment. It is shown how the challenge of affordability for insureds can be addressed without requiring premium subsidies, thus maintaining risk-adequate incentives which are relevant for preparedness.

Impact of the COVID-19 Pandemic on the Spanish Commercial Real Estate Market
FernÃ¡ndez Cerezo, Alejandro,Lamas, Matias,Roibas, Irene,Vegas SÃ¡nchez, Raquel
SSRN
The COVID-19 pandemic has had a major impact on the recent performance of the Spanish commercial real estate market. In particular, the crisis has led to a sharp decrease in nonresidential investment and has triggered a correction in sale prices, transaction numbers and new financing operations. It has also affected Spanish real estate investment trusts specialising in this market, both in terms of the number of vehicles created and of their stock prices and the value of their real estate assets. By contrast, to date there has been no significant deterioration in credit quality linked to the commercial real estate market.

Income Inequality and Intergenerational Mobility in India
arXiv

Using three rounds of NSS datasets, the present paper attempts to understand the relationship between income inequality and intergenerational income mobility (IGIM) by segregating generations into social and income classes. The originality of the paper lies in assessing the IGIM using different approaches, which we expect to contribute to the existing literature. We conclude that the country has low-income mobility and high inequality which is no longer associated with a particular social class in India. Also, both may have a negative or positive relationship, hence needs to be studied at a regional level.

Inference and forecasting for continuous-time integer-valued trawl processes and their use in financial economics
Bennedsen, Mikkel,Lunde, Asger,Shephard, Neil,Veraart, Almut E.D.
RePEC
This paper develops likelihood-based methods for estimation, inference, model selection, and forecasting of continuous-time integer-valued trawl processes. The full likelihood of integer-valued trawl processes is, in general, highly intractable, motivating the use of composite likelihood methods, where we consider the pairwise likelihood in lieu of the full likelihood. Maximizing the pairwise likelihood of the data yields an estimator of the parameter vector of the model, and we prove consistency and asymptotic normality of this estimator. The same methods allow us to develop probabilistic forecasting methods, which can be used to construct the predictive distribution of integer-valued time series. In a simulation study, we document good finite sample performance of the likelihood-based estimator and the associated model selection procedure. Lastly, the methods are illustrated in an application to modelling and forecasting financial bid-ask spread data, where we find that it is beneficial to carefully model both the marginal distribution and the autocorrelation structure of the data. We argue that integer-valued trawl processes are especially well-suited in such situations.

Information Foraging in the Attention Economy
Charlie Pilgrim,Weisi Guo,Thomas T. Hills
arXiv

Over the past 200 years, rising rates of information proliferation have created new environments for information competition and, consequently, new selective forces on information evolution. These forces influence the information diet available to consumers, who in turn choose what to consume, creating a feedback process similar to that seen in many ecosystems. As a first step towards understanding this relationship, we apply animal foraging models of diet choice to describe the evolution of long and short form media in response to human preferences for maximising utility rate. The model describes an increase in information rate (i.e., entropy) in response to information proliferation, as well as differences in entropy between short-form and long-form media (such as social media and books, respectively). We find evidence for a steady increase in word entropy in diverse media categories since 1900, as well as an accelerated entropy increase in short-form media. Overall the evidence suggests an increasingly competitive battle for our attention that is having a lasting influence on the evolution of language and communication systems.

LOB modeling using Hawkes processes with a state-dependent factor
Emmanouil Sfendourakis,Ioane Muni Toke
arXiv

A point process model for order flows in limit order books is proposed, in which the conditional intensity is the product of a Hawkes component and a state-dependent factor. In the LOB context, state observations may include the observed imbalance or the observed spread. Full technical details for the computationally-efficient estimation of such a process are provided, using either direct likelihood maximization or EM-type estimation. Applications include models for bid and ask market orders, or for upwards and downwards price movements. Empirical results on multiple stocks traded in Euronext Paris underline the benefits of state-dependent formulations for LOB modeling, e.g. in terms of goodness-of-fit to financial data.

Mortality in Germany during the Covid-19 pandemic
Alois Pichler,Dana Uhlig
arXiv

The Covid-19 pandemic still causes severe impacts on society and the economy. This paper studies excess mortality during the pandemic years 2020 and 2021 in Germany empirically with a special focus on the life insurer's perspective. Our conclusions are based on official counts of German governmental offices on the living and deaths of the entire population. Conclusions, relevant for actuaries and specific insurance business lines, including portfolios of pension, life, and health insurance contracts, are provided.

New sources of economies and diseconomies of scale in on-demand ridepooling systems and comparison with public transport
Andres Fielbaum,Alejandro Tirachini,Javier Alonso-Mora
arXiv

On-demand ridepooling (ODRP) can become a powerful alternative to reduce congestion and emissions, if it attracts private car users. Therefore, it is crucial to identify the strategic phenomena that determine when ODRP systems can run efficiently. In this paper, we analyze the performance of an ODRP system, in which the fleet of low-capacity vehicles is endogenously adapted to the demand, and operated in a zone covered by a single transit line. The routing of the on-demand fleet follows some of the rules of public transport systems; namely, it is not-for-profit, some users can be required to walk, and all requests must be served. Considering both users' and operators' costs we identify two sources of scale economies: when demand grows, the average cost is reduced due to a) an equivalent of the Mohring Effect (also present in public transport), and b) due to matching users with more similar routes when they are assigned to the vehicles, which we call Better-matching Effect. A counter-balance force, called Flex-route Effect, is observed when the vehicle loads increase and users face longer detours. We find a specific demand range in which the latter effect dominates the others, imposing diseconomies of scale when only users' costs are considered. Such a phenomenon emerges because the routes are not fixed; hence, it is not observed in traditional public transport systems. However, when considering both users' and operators' costs, scale economies prevail. Our simulations show that relaxing door-to-door vehicle requirements to allow short walks is crucial for the performance of ODRP. In fact, we observe that an ODRP system with human-driven vehicles and walks allowed has a total cost at a similar level to that of a door-to-door ODRP system with driverless vehicles.

No free lunch for markets with multiple num\'eraires
Laurence Carassus
arXiv

We consider a global market constituted by several submarkets, each with its own assets and num\'eraire. We provide theoretical foundations for the existence of equivalent martingale measures and results on superreplication prices which allows to take into account difference of features between submarkets.

Proof of non-convergence of the short-maturity expansion for the SABR model
Alan L. Lewis,Dan Pirjol
arXiv

We study the convergence properties of the short maturity expansion of option prices in the uncorrelated log-normal ($\beta=1$) SABR model. In this model the option time-value can be represented as an integral of the form $V(T) = \int_{0}^\infty e^{-\frac{u^2}{2T}} g(u) du$ with $g(u)$ a payoff function'' which is given by an integral over the McKean kernel $G(s,t)$. We study the analyticity properties of the function $g(u)$ in the complex $u$-plane and show that it is holomorphic in the strip $|\Im(u) |< \pi$. Using this result we show that the $T$-series expansion of $V(T)$ and implied volatility are asymptotic (non-convergent for any $T>0$). In a certain limit which can be defined either as the large volatility limit $\sigma_0\to \infty$ at fixed $\omega=1$, or the small vol-of-vol limit $\omega\to 0$ limit at fixed $\omega\sigma_0$, the short maturity $T$-expansion for the implied volatility has a finite convergence radius $T_c = \frac{1.32}{\omega\sigma_0}$.

Quasi-sure essential supremum and applications to finance
Laurence Carassus
arXiv

A notion of essential supremum is developed when the uncertainty is measured by a family of non-dominated and non-compact probability measures. It provides new perspectives on super-replication and allows the Absence of Instantaneous Profit (AIP) to be characterized.

Rethinking RibÄ and the â€˜Islamicâ€™ Banking Experimentation
SSRN
The efficiency of a financial intermediation system is assessed by its ability to achieve allocative efficiency, asset transformation and the subsequent economic development. In case of an Islamic Banking and Finance as an alternate financial intermediation system adherence to the injunction of Islam is also critical. A critical appraisal of the state of contemporary Islamic Banking and finance (IBF) reveals that IBF has neither been able to achieve the aspirations of Islamic rhetoric, nor has been efficient in terms of asset transformation and economic development. This paper is an intuitive pursuit to explore the economic sense of established principles of IBF, and the reasons of the persistent divergence of IBF, being accused to be based on ruses and sophistry. Disentangling the varying viewpoints, the underdevelopment of IBF has been attributed to misinterpretation of RibÄ, which has been explicated through a narrow fiqhi and legally deterministic approach. Deeming â€˜a collaborative and dynamic IjtihÄdâ€™ as the elixir, this paper insists on the exigency of revisiting the definition of RibÄ through a dynamic and collaborative IjtihÄdi effort â€" i.e., a definition that incorporates the modern modes of economic cooperation and the contemporary financial intermediation ecosystem. The paper articulates RibÄ in an agency theoretic framework to eschew expropriation of wealth, and assure protection of property rights, to sustain financial stability and economic development.

Risk-Sensitive Credit Portfolio Optimization under Partial Information and Contagion Risk
Lijun Bo,Huafu Liao,Xiang Yu
arXiv

This paper investigates the finite horizon risk-sensitive portfolio optimization in a regime-switching credit market with physical and information-induced default contagion. It is assumed that the underlying regime-switching process has countable states and is unobservable. The stochastic control problem is formulated under partial observations of asset prices and sequential default events. By establishing a martingale representation theorem based on incomplete and phasing out filtration, we connect the control problem to a quadratic BSDE with jumps, in which the driver term is non-standard and carries the conditional filter as an infinite-dimensional parameter. By proposing some truncation techniques and proving a uniform a priori estimates, we obtain the existence of a solution to the BSDE using the convergence of solutions associated to some truncated BSDEs. The verification theorem can be concluded with the aid of our BSDE results, which in turn yields the uniqueness of the solution to the BSDE.

Robustness and sensitivity analyses for rough Volterra stochastic volatility models
Jan Matas,Jan Pospíšil
arXiv

In this paper we perform robustness and sensitivity analysis of several continuous-time rough Volterra stochastic volatility models with respect to the process of market calibration. Robustness is understood in the sense of sensitivity to changes in the option data structure. The latter analyses then should validate the hypothesis on importance of the roughness in the volatility process dynamics. Empirical study is performed on a data set of Apple Inc. equity options traded in four different days in April and May 2015. In particular, the results for RFSV, rBergomi and aRFSV models are provided.

Sejarah Pemikiran Politik Indonesia: Tanggapan Intelektual Muslim di Masa Orde Baru dan Pudarnya Peran ICMI pada Pasca-Reformasi (History of Indonesian Political Thought: Responses Muslim Intellectuals in the New Order and the Fading Role of ICMI in Post-Reform)
SSRN

The climate in climate economics
Doris Folini,Felix Kübler,Aleksandra Malova,Simon Scheidegger
arXiv

We develop a generic calibration strategy for climate models used in economics. The key idea is to choose the free model parameters to match the output of large-scale Earth System Models, which are run on pre-defined future emissions scenarios and collected in the Coupled Model Intercomparison Project (CMIP5). We propose to use four test cases that are considered pivotal in the climate science literature. Two of these tests are highly idealized to allow for the separate examination of the carbon cycle and the temperature response. Another two tests incorporate gradual changes in CO2 emissions, exogenous forcing, and the temperature response. We re-calibrate the free parameters of the climate part of the seminal DICE-2016 model for three different CMIP5 model responses: the multi-model mean as well as two other CMIP5 models that exhibit extreme equilibrium climate sensitivities. As an additional novelty, our calibrations of DICE-2016 allow for an arbitrary time step in the model explicitly. We show that i) both the temperature equations and the carbon cycle in DICE-2016 are miscalibrated and that ii) by re-calibrating its coefficients, we can match all three CMIP5 targets. We apply the economic model from DICE-2016 in combination with the newly calibrated climate model to compute the social cost of carbon and the optimal warming. We find that in our updated model, the social cost of carbon is very similar to DICE-2016, however, the optimal long-run temperature lies almost one degree below that obtained by DICE-2016. This difference in climate behavior is reflected in the over-sensitivity of the social cost of carbon to the discount rate. Under the optimal mitigation scenario, the temperature predictions of DICE-2016 (in contrast to our proposed calibration) fall outside of the CMIP5 scenarios, suggesting that one might want to be skeptical about policy predictions derived from DICE-2016.

They Chose to Not Tell You
Bruce Knuteson
arXiv

The world's stock markets display a strikingly suspicious, decades long pattern of overnight and intraday returns that nobody (other than us) has plausibly explained and that nobody (other than us) has clearly and persistently alerted you to. We use correspondence on this topic over the past five years to show that the silence of others on this issue does not arise from their having a good reason to believe this pattern is fine. Separately, and regardless of whether this pattern turns out to be fine, we have documented that people in a position to alert you to the presence of strikingly suspicious return patterns in the world's stock markets that nobody can innocuously explain are aware of this issue, have no good reason to believe it is not a problem, and chose to not tell you.

Transferencias No Condicionadas a La Vejez: La Respuesta a Los Problemas De FocalizaciÃ³n Y Cobertura En El Sistema Pensional Colombiano (Unconditional Transfers to Elderes: The Answer to the Targeting and Coverage Problems of the Colombian Pension System)
HernÃ¡ndez RodrÃ­guez, JosÃ© Antonio,Salamanca, Mauricio Santa MarÃ­a
SSRN