Research articles for the 2019-12-03

A Machine Learning Approach to Adaptive Robust Utility Maximization and Hedging
Tao Chen,Michael Ludkovski

We investigate the adaptive robust control framework for portfolio optimization and loss-based hedging under drift and volatility uncertainty. Adaptive robust problems offer many advantages but require handling a double optimization problem (infimum over market measures, supremum over the control) at each instance. Moreover, the underlying Bellman equations are intrinsically multi-dimensional. We propose a novel machine learning approach that solves for the local saddle-point at a chosen set of inputs and then uses a nonparametric (Gaussian process) regression to obtain a functional representation of the value function. Our algorithm resembles control randomization and regression Monte Carlo techniques but also brings multiple innovations, including adaptive experimental design, separate surrogates for optimal control and the local worst-case measure, and computational speed-ups for the sup-inf optimization. Thanks to the new scheme we are able to consider settings that have been previously computationally intractable and provide several new financial insights about learning and optimal trading under unknown market parameters. In particular, we demonstrate the financial advantages of adaptive robust framework compared to adaptive and static robust alternatives.

A Simple Proof of the Fundamental Theorem of Asset Pricing
Keith A. Lewis

A simple statement and accessible proof of a version of the Fundamental Theorem of Asset Pricing in discrete time is provided. Careful distinction is made between prices and cash flows in order to provide uniform treatment of all instruments. There is no need for a ``real-world'' measure in order to specify a model for derivative securities, one simply specifies an arbitrage free model, tunes it to market data, and gets down to the business of pricing, hedging, and managing the risk of derivative securities.

A Unified Theory of the Term Structure and the Beta Anomaly
Zhu, Yicheng
Rational expectation models generally suggest that assets with more exposure to systematic risks should carry higher risk premia. However, several empirical findings challenge this result. I propose a novel generalized recursive smooth aversion model that allows agents to show different levels of aversion to short-run consumption risk and long-run shocks. I apply this model to a consumption-based asset pricing model in which the representative agent’s consumption process is subject to rare but large disasters. The calibrated model matches major asset pricing moments, while riskier assets could carry lower risk premia.

A unified Framework for Robust Modelling of Financial Markets in discrete time
Jan Obloj,Johannes Wiesel

We unify and establish equivalence between the pathwise and the quasi-sure approaches to robust modelling of financial markets in discrete time. In particular, we prove a Fundamental Theorem of Asset Pricing and a Superhedging Theorem, which encompass the formulations of [Bouchard, B., & Nutz, M. (2015). Arbitrage and duality in nondominated discrete-time models. The Annals of Applied Probability, 25(2), 823-859] and [Burzoni, M., Frittelli, M., Hou, Z., Maggis, M., & Obloj, J. (2019). Pointwise arbitrage pricing theory in discrete time. Mathematics of Operations Research]. In bringing the two streams of literature together, we also examine and relate their many different notions of arbitrage. We also clarify the relation between robust and classical $\mathbb{P}$-specific results. Furthermore, we prove when a superhedging property w.r.t. the set of martingale measures supported on a set of paths $\Omega$ may be extended to a pathwise superhedging on $\Omega$ without changing the superhedging price.

A weighted finite difference method for subdiffusive Black Scholes Model
Grzegorz Krzyżanowski,Marcin Magdziarz,Łukasz Płociniczak

In this paper we focus on the subdiffusive Black Scholes model. The main part of our work consists of the finite difference method as a numerical approach to the option pricing in the considered model. We derive the governing fractional differential equation and the related weighted numerical scheme being a generalization of the classical Crank-Nicolson scheme. The proposed method has $2-\alpha$ order of accuracy with respect to time where $\alpha\in(0,1)$ is the subdiffusion parameter, and $2$ with respect to space. Further, we provide the stability and convergence analysis. Finally, we present some numerical results.

Achieving the Bank of Japan's Inflation Target
Anand, Rahul,Hong, Gee Hee,Hul, Yaroslav
The Bank of Japan has introduced various unconventional monetary policy tools since the launch of Abenomics in 2013, to achieve the price stability target of 2 percent inflation. In this paper, a forward-looking open-economy general equilibrium model with endogenously determined policy credibility and an effective lower bound is developed for forecasting and policy analysis (FPAS) for Japan. In the model's baseline scenario, the likelihood of the Bank of Japan reaching its 2 percent inflation target over the medium term is below 40 percent, assuming the absence of other policy reactions aside from monetary policy. The likelihood of achieving the inflation target is even lower under alternative risk scenarios. A positive shock to central bank credibility increases this likelihood, and would require less accommodative macroeconomic policies.

Applications of the Deep Galerkin Method to Solving Partial Integro-Differential and Hamilton-Jacobi-Bellman Equations
Ali Al-Aradi,Adolfo Correia,Danilo de Frietas Naiff,Gabriel Jardim,Yuri Saporito

We extend the Deep Galerkin Method (DGM) introduced in Sirignano and Spiliopoulos (2018) to solve a number of partial differential equations (PDEs) that arise in the context of optimal stochastic control and mean field games. First, we consider PDEs where the function is constrained to be positive and integrate to unity, as is the case with Fokker-Planck equations. Our approach involves reparameterizing the solution as the exponential of a neural network appropriately normalized to ensure both requirements are satisfied. This then gives rise to a partial integro-differential equation (PIDE) where the integral appearing in the equation is handled using importance sampling. Secondly, we tackle a number of Hamilton-Jacobi-Bellman (HJB) equations that appear in stochastic optimal control problems. The key contribution is that these equations are approached in their unsimplified primal form which includes an optimization problem as part of the equation. We extend the DGM algorithm to solve for the value function and the optimal control simultaneously by characterizing both as deep neural networks. Training the networks is performed by taking alternating stochastic gradient descent steps for the two functions, a technique similar in spirit to policy improvement algorithms.

Bank Capital and the Cost of Equity
Belkhir, Mohamed,Ben Naceur, Sami,Chami, Ralph ,Samet, Anis
Using a sample of publicly listed banks from 62 countries over the 1991-2017 period, we investigate the impact of capital on banks’ cost of equity. Consistent with the theoretical prediction that more equity in the capital mix leads to a fall in firms’ costs of equity, we find that better capitalized banks enjoy lower equity costs. Our baseline estimations indicate that a 1 percentage point increase in a bank’s equity-to-assets ratio lowers its cost of equity by about 18 basis points. Our results also suggest that the form of capital that investors value the most is sheer equity capital; other forms of capital, such as Tier 2 regulatory capital, are less (or not at all) valued by investors. Additionally, our main finding that capital has a negative effect on banks’ cost of equity holds in both developed and developing countries. The results of this paper provide the missing evidence in the debate on the effects of higher capital requirements on banks’ funding costs.

Bounds on Multi-asset Derivatives via Neural Networks
Luca De Gennaro Aquino,Carole Bernard

Using neural networks, we compute bounds on the prices of multi-asset derivatives given information on prices of related payoffs. As a main example, we focus on European basket options and include information on the prices of other similar options, such as spread options and/or basket options on subindices. We show that, in most cases, adding further constraints gives rise to bounds that are considerably tighter and discuss the maximizing/minimizing copulas achieving such bounds. Our approach follows the literature on constrained optimal transport and, in particular, builds on a recent paper by Eckstein and Kupper (2019, Appl. Math. Optim.).

Can the Global Economy Activity Predict Cryptocurrency Returns
Cheng, Hui-Pei,Yen, Kuang-Chieh
We investigate whether the global economic activity (GEA) index provided by Kilian (2009) can predict the dynamics of the cryptocurrency. First, we find that the lagged two-month GEA index can predict positively the cryptocurrency monthly returns, especially for Bitcoin. It implies that the investor tends to invest more in the Bitcoin when the economic condition was good two months ago. Furthermore, Bitcoin investors would decrease (increase) their investment when the decline (rise) of the S&P 500 index. In addition, we find the Bitcoin return predictability of the GEA index only exists in the one-month-ahead period.

Capital Controls and the Volatility of the Renminbi Covered Interest Deviation
Lin, Zhitao,Qian, Xingwang,Chen, Jinzhao
Abstract: We examine how China’s capital controls affect the volatility of the renminbi (RMB) covered interest deviation (CID). We find that capital controls not only drive up the level of the RMB CID, but also cause the CID to be more volatile, highlighting the tradeoff between the role of capital controls in maintaining financial stability and hindering financial market efficiency. We also find that capital controls result in greater CID volatility in more liberalized RMB exchange regimes. Furthermore, we decompose CID into the interest rate differential (IRD) and forward premium (FP) and find that capital controls normally amplify the volatility of both. However, during the Federal Reserve Bank’s quantitative ease era, capital controls mitigated the volatility of the IRD. Finally, using an error correction model, which enables us to study the association of capital controls with both long-run and short-run volatility simultaneously, we find that, while capital controls increase both the long- and short-run volatility of the IRD and the CID overall, they do not affect FP volatility.

Corporate Pensions and Financial Distress
Duan, Ying,Foroughi, Pouyan,Hotchkiss, Edith S.,Jiao, Yawen
We examine the role of corporate pension plans in determining how firms restructure in financial distress. Both defined benefit (DB) and defined contribution (DC) plans can have significant exposures to the company’s own stock, imposing significant losses on employees if the firm defaults and/or files for bankruptcy. We find that firms with DB plans typically have little exposure to the stock prior to default; the degree of underfunding increases significantly as firms near default, but is not related to restructuring types (bankruptcies versus out of court restructurings). In contrast, large exposures to company stock in DC plans often are not reduced prior to default. High levels of own-company stock ownership are positively related to default and bankruptcy probabilities. Our evidence suggests a link between employee-ownership related managerial entrenchment and default risk.

Designing Dual Class Sunsets: The Case for a Transfer-Centered Approach
Moore, Marc T.
Dual class stock (DCS) structures, and their implications for managerial accountability and corporate governance more broadly, have become prevalent concerns for corporate lawyers and policymakers. Recent academic and practitioner debates on DCS have tended to focus less on the general merits and drawbacks of DCS versus one share/one vote structures, and more on the specific common-ground concern as to whether and how such structures are subjected to contingent reversal or “sunset”. This Article compares the relative advantages and disadvantages of time-, ownership- and transfer-centered models of DCS sunset provision. It argues in favor of the transfer-centered model on the grounds that: (a) its specific event-based trigger renders it less arbitrary in application than the time-centered model, and protects against the possibility of founders being prevented prematurely from realizing their long-term strategic vision (as is a risk with the time-centered sunset model); (b) it avoids the moral hazard and other perverse controller incentives that are prone to ensue from time-centered sunsets; and (c) unlike both the time- and ownership-centered models (which are motivated primarily by agency cost concerns), the transfer-centered model is sensitive to the powerful non-financial incentives that controllers typically have to safeguard and promote firm value, even where their corporate control rights significantly outweigh their corresponding cash flow rights. Accordingly, it suggests that the SEC and principal US exchanges should resist recent calls from influential investor-related bodies to mandate time-based sunsets. Instead, domestic policymakers should look overseas to Hong Kong and Singapore, whose respective listing authorities have recently introduced transfer-based sunset requirements for DCS issuers, in considering the most appropriate blueprint for any future regulatory initiatives in this regard.

Digital Financial Advice Solutions â€" Evidence on Factors Affecting the Future Usage Intention and the Moderating Effect of Experience
Gerlach, Johannes M.,Lutz, Julia K. T.
Recently, Digital Financial Advice Solutions (i.e., “Robo Advice” or “Robo Advisory”) are emerging rapidly within the financial services sectors, which can be outlined by the respective Assets und Managements’ CAGR of 255.9% from 2016 to 2018 in Germany (Kaya, 2019). However, these developments imply both opportunities and threats for traditional financial institutions: On the one hand, potential customer out-migrations, the loss of cross-selling potentials and potential yields as well as challenged competitiveness pose significant risks. On the other hand, if traditional banks manage to implement appropriate measures timely, the recent developments also offer great market potentials. Thus, it is inevitable to identify, understand and discuss factors that drive the customers’ future usage intention of Digital Financial Advice Solutions. As a result, we derive, from the traditional financial institutions point of view, strategic and managerial implications on how to deal with the currently emerging trends of Digital Financial Advice Solutions. For this purpose, we conducted a questionnaire-based online survey, which ultimately led to 600 evaluable observations. Finally, according to the two strands of literature this study bases on, i.e., the Net Valence Framework and Unified Theory of Acceptance and Use of Technology 2, we built a structural model that incorporates a comprehensive set of variables. In doing so, we contribute to not only the general understanding of Digital Financial Advice Solutions and two different strands of literature but also to the solution of issues that are of great relevance for practitioners, too. Subsequently, this study concludes by the derivation of future research requirements regarding these, both theoretically and practically, important matters.

Economics of Accounting Earnings
Frankel, Richard M.,Kothari, S.P.,Zuo, Luo
This book is not a review of the empirical accounting literature. This book tells a story and relates it to salient empirical phenomena. Why does accounting exist? Our answer is that financial accounting helps firms operate efficiently. That efficiency is manifested in many ways, and it is contextual (e.g., investment decisions and capital allocation, corporate governance, managers’ performance assessment, and contracts among various stakeholders). We often use shareholder value as the measure of efficiency, though we discuss regulation, social and contract efficiency.

Efficiency With(out) Intermediation in Repeated Bilateral Trade
Lamba, Rohit
This paper analyzes repeated version of the bilateral trade model where the independent payoff relevant private information of the buyer and the seller is correlated across time. Using this setup it makes the following five contributions. First, it derives necessary and sufficient conditions on the primitives of the model as to when efficiency can be attained under ex post budget balance and participation constraints. Second, in doing so, it introduces an intermediate notion of budget balance called interim budget balance that allows for the extension of liquidity but with participation constraints for the issuing authority, interpreted here as an intermediary). Third, it pins down the class of all possible mechanisms that can implement the efficient allocation with and without an intermediary. Fourth, it provides a foundation for the role of an intermediary in a dynamic mechanism design model under informational constraints. And, fifth, it argues for a careful interpretation of the "folk proposition" that less information is better for efficiency in dynamic mechanisms under ex post budget balance and observability of transfers.

Electricity Net Generation and the Cryptocurrency Market
Cheng, Hui-Pei,Yen, Kuang-Chieh
In this paper, we investigate whether the Bitcoin return can predict the electricity net generation in the United States. By utilizing the data from February 2014 to July 2019, we find that higher Bitcoin return leads to a higher electricity net generation via the possible channel that increases the Bitcoin trading volume. Furthermore, we find that the US-China trade war could weaken the connection between the U.S. electricity net generation and Bitcoin volume while the China crypto-trade policy has no effect on the relationship.

Estimating Permanent Price Impact via Machine Learning
Philip, Richard
In this paper, we show that vector auto-regression (VAR) models, which are commonly used to estimate permanent price impact, are misspecified and can produce conflicting and incorrect inferences when the price impact function is nonlinear. We propose an alternative method to estimate permanent price impact by modifying a reinforcement learning (RL) framework. Our approach assumes the data is stationary and Markov, but is otherwise unrestrictive. We obtain empirical estimates for our model using an iterative learning rule and demonstrate that our model captures nonlinearities and makes correct inferences.

Financial Openness and Capital Inflows to Emerging Markets: In Search of Robust Evidence
Cerdeiro, Diego,Komaromi, Andras
We reassess the connection between capital account openness and capital flows in an empirical framework that is grounded in theory and makes use of previously unexplored variation in the data. We demonstrate how our theory-consistent regressions may overcome some ubiquitous measurement problems in the literature by relying on interaction terms between financial openness and traditional push-pull factors. Within our proposed framework, we ask: what can be said robustly about the effect of capital account restrictions on capital flows? Our results warrant against over-interpreting the existing cross-country evidence as we find very few robust relationships between capital account restrictiveness and various types of capital inflows. Countries with a higher degree of financial openness are more susceptible to some, but by no means all, push and pull factors. Overall, the results are still consistent with a complex set of tradeoffs faced by policymakers, where the ability to shield the domestic economy from volatile capital flow cycles must be weighed against the sources of exogenous risks and potential long run growth effects.

Geographic Variation in M&A Activity, Spillovers, and Valuation Shocks
Rajamani, Anjana,Schlingemann, Frederik P.
We document large and persistent differences in the acquisitiveness of firms in the U.S. based on the location of their headquarters. We hypothesize and find evidence that local peer effects in M&A activity contribute to such persistence. Specifically, the acquisitiveness of non-dominant industry firms in an economic area (EA) relates positively to valuations and idiosyncratic return shocks of local dominant industry firms. Local spillover effects are stronger for firms headquartered in EAs with higher M&A activity and dominant industries in these EAs are subject to larger positive valuation shocks. Overall, our results suggest that firms perceive the valuations of their local peers as informative for their acquisition decisions. The market seems skeptical with respect to firms responding to local peer valuation shocks as we find an inverse relation between announcement returns and idiosyncratic returns shocks of their local dominant industry peers.

German Bond Yields and Debt Supply: Is There a 'Bund Premium'?
Paret, Anne-Charlotte,Weber, Anke
Are Bunds special? This paper estimates the 'Bund premium' as the difference in convenience yields between other sovereign safe assets and German government bonds adjusted for sovereign credit risk, liquidity and swap market frictions. A higher premium suggests less substitutability of sovereign bonds. We document a rise in the 'Bund premium' in the post-crisis period. We show that there is a negative relationship of the premium with the relative supply of German sovereign bonds, which is more pronounced for higher maturities and when risk aversion proxied by bond market volatility is high. Going forward, we expect German government debt supply to remain scarce, with important implications for the ECB's monetary policy strategy.

Granger Predictability of Oil Prices after the Great Recession
Benk, Szilard,Gillman, Max
Real oil prices surged from 2009 through 2014, comparable to the 1970's oil shock period. Standard explanations based on monopoly markup fall short since inflation remained low after 2009. This paper contributes strong evidence of Granger (1969) predictability of nominal factors to oil prices, using one adjustment to monetary aggregates. This adjustment is the subtraction from the monetary aggregates of the 2008-2009 Federal Reserve borrowing of reserves from other Central Banks (Swaps), made after US reserves turned negative. This adjustment is key in that Granger predictability from standard monetary aggregates is found only with the Swaps subtracted.

Higher Education and Financial Behavior: The Effect of Studying Mathematics and Economics on Financial Outcomes
Hvidberg, Kristoffer Balle
This paper presents new evidence on the effect of education on financial behavior. In particular, I investigate whether obtaining a degree from a study program with a mathematical or economic curriculum affects individuals’ future loan default probability. I identify the causal effects of different types of education on financial behavior by exploiting the GPA admission thresholds to higher education programs in a fuzzy regression discontinuity design. I compare people who have applied for the same fields of study but who are quasi-randomly allocated to different different fields of study due to small differences in their GPA from upper secondary school.I estimate the effects using a unique combination of administrative data on admissions to post-secondary education and third party reported data on the universe of personal loans. I find that completing a mathematical or economic field of study decreases the probability of default post graduation for the applicants who did not have one of these fields as their most preferred field of study.

In Search of Lost Time: Examining the Duration of Sudden Stops in Capital Flows
David, Antonio C.,Goncalves, Carlos
This paper investigates what factors affect the duration of sudden stops in capital flows using quarterly data for a large panel of countries. We find that countries with floating exchange rate regimes tend to experience shorter sudden stop episodes and that fixed exchange rate regimes are associated with longer periods of low output growth following sudden stops. These effects are quantitatively large: having a flexible exchange rate regime increases the probability of exiting the sudden stop state by between 50 to 80 percent. Flexible exchange rate regimes significantly shorten the duration of output decelerations following sudden stops by over 30 percent. Positive variations in terms of trade also abbreviate the duration of sudden stops. In terms of policies, identification is trickier, but the evidence suggests that monetary policy tightening shortens the duration of sudden stops. Changes in capital account restrictions do not seem to matter.

International Bank Lending Channel of Monetary Policy
Albrizio, Silvia ,Choi, Sangyup,Furceri, Davide,Yoon, Chansik
How does domestic monetary policy in systemic countries spillover to the rest of the world? This paper examines the transmission channel of domestic monetary policy in the cross-border context. We use exogenous shocks to monetary policy in systemically important economies, including the U.S., and local projections to estimate the dynamic effect of monetary policy shocks on bilateral cross-border bank lending. We find robust evidence that an increase in funding costs following an exogenous monetary tightening leads to a statistically and economically significant decline in cross-border bank lending. The effect is weakened during periods of high uncertainty. In contrast, the effect is found to not vary according to the degree of borrower country riskiness, further weakening support for the international portfolio rebalancing channel.

Liquidity and Profitability Relationship and Financial Fallacy
Panigrahi, CMA(Dr.) Ashok
Theoretically, a company needs to maintain a liquidity level that is not detrimental to its profitability. Empirical evidence shows a negative correlation between liquidity and profitability but a company cannot operate with zero liquidity in order to maximize its profits. Normally firms try to maximize their profitability by maintaining the desired liquidity, but increasing profitability will definitely lead to reduce firms’ liquidity and increased stress on liquidity would tend to affect the profitability adversely. In general, low or no working capital and large payables of a firm are considered as a sign of serious financial trouble and negative working capital is often viewed by rating agencies as an alarm of default risk, which may lead to the firm incurring higher interest cost on its loans. In this paper, the researcher has conducted a comparative study of the liquidity and profitability position of two Indian pharmaceutical companies i.e. Ajanta Pharma and Primal Pharma. The analysis shows that in the case of Ajanta Pharma, there is a significant positive relationship between liquidity and profitability measures. In other words, CR and QR are positively correlated with ROA, ROE, and NP, and the relationship is significant, whereas, in case of Piramal Pharma, the relationship between liquidity and profitability measures is very weak and insignificant. Although the risk and return theories of finance indicate that the relationship between liquidity and profitability should be negative; there have been studies that produced different results. These findings seem to be really interesting because they indicate that there are different kinds of relationships between liquidity and profitability in different industries, and these relationships in different industries might be different in different countries as well. This difference in the relationship between liquidity and profitability could lead to a difference in management of the liquidity. Hence the author feels that there is a fallacy in the established rule of finance that liquidity and profitability have always an inverse relationship, i.e, both are negatively related to each other. As proved in the case of Ajanta Pharma, an organization can increase its profitability even after keeping its liquidity intact.

Lying to Speak the Truth: Selective Manipulation and Improved Information Transmission
Povel, Paul,Strobl, Günter
We show that firms may benefit from allowing some earnings management, because it can make noisy signals more informative. We model a firm that cannot observe a manager's cost of effort, her effort choice, and whether she manipulated a publicly observable signal. An optimal contract links compensation to both the eventually realized firm value and the (possibly manipulated) signal, since both are noisy measures of effort provision. It may be optimal to allow for manipulation of the signal by a manager who exerted a high effort level: Doing so can convert a falsely unfavorable signal into a favorable signal, thereby strengthening the link between effort and compensation.

Machine Learning and Causality: The Impact of Financial Crises on Growth
Tiffin, Andrew
Machine learning tools are well known for their success in prediction. But prediction is not causation, and causal discovery is at the core of most questions concerning economic policy. Recently, however, the literature has focused more on issues of causality. This paper gently introduces some leading work in this area, using a concrete example-assessing the impact of a hypothetical banking crisis on a country's growth. By enabling consideration of a rich set of potential nonlinearities, and by allowing individually-tailored policy assessments, machine learning can provide an invaluable complement to the skill set of economists within the Fund and beyond.

Macrofinancial Linkages and Growth at Risk in the Dominican Republic
Bespalova, Olga,Rousset, Marina
This paper uses the Growth-at-Risk (GaR) methodology to examine how macrofinancial conditions affect the growth outlook and its probability distribution. Using this approach, we evaluate risks to GDP growth in the Dominican Republic using quarterly data for 1996-2018. We group macrofinancial conditions in five principal determinants, based on 32 indicators. The Dominican Republic's growth distribution appears most vulnerable to negative shocks to domestic financial conditions, domestic leverage, domestic demand, and external demand, with additional repercussions from the external cost of borrowing in the longer run. Our findings show that domestic monetary policy plays a particularly important role in reducing growth vulnerabilities when the economy is weak.

Managerial Foreign Experience and Corporate Risk-Taking: Evidence from China
Sun, Zixiong,Anderson, Hamish D.,Chi, Jing
This study investigates the relation between managerial foreign experience and corporate risk-taking in China. We find that foreign experienced managers are positively associated with corporate risk-taking and this relationship mainly exists in private firms rather than in state owned enterprises (SOEs). The positive association is more pronounced for executives who gain their foreign experience from countries with advanced management practices and for foreign practical experience rather than educational experience. Short-term visiting experience has no impacts on corporate risk-taking. The positive relationship between managerial foreign experience and corporate risk-taking in private firms is more persistent among firms with more resources, better corporate governance or weak external environments and monitoring. Finally, evidence shows that risk-taking executives with foreign experience are more likely to enhance firm value and performance.

Market making and incentives design in the presence of a dark pool: a deep reinforcement learning approach
Bastien Baldacci,Iuliia Manziuk,Thibaut Mastrolia,Mathieu Rosenbaum

We consider the issue of a market maker acting at the same time in the lit and dark pools of an exchange. The exchange wishes to establish a suitable make-take fees policy to attract transactions on its venues. We first solve the stochastic control problem of the market maker without the intervention of the exchange. Then we derive the equations defining the optimal contract to be set between the market maker and the exchange. This contract depends on the trading flows generated by the market maker's activity on the two venues. In both cases, we show existence and uniqueness, in the viscosity sense, of the solutions of the Hamilton-Jacobi-Bellman equations associated to the market maker and exchange's problems. We finally design deep reinforcement learning algorithms enabling us to approximate efficiently the optimal controls of the market maker and the optimal incentives to be provided by the exchange.

On the Preferences of CoCo Bond Buyers and Sellers: A Logistic Regression Analysis
Caporale, Guglielmo Maria,Kang, Woo-Young
This paper estimates the preference scores of CoCo bond buyers and sellers by running logistic regressions taking into account both bond and issuing bank’s characteristics, and also considers the role of countryâˆ'specific CoCo bond market competitiveness. Buyers are defined as having a preference for CoCo bonds if their return-to-risk is higher than the corresponding 25th, 50th and 75th annual percentile values; the preferences of buyers and sellers are assumed to be mutually exclusive. Differences in the degree of risk aversion of buyers and sellers and in the determinants of their preferences are found across percentiles. Further, coupon payment, conversion mechanism, credit rating and P/B ratio appear to be the strongest global determinants of CoCo bond trading between buyers and sellers, these being very responsive to CoCo bond and issuing bank’s characteristics in most European countries, Brazil, Mexico and China (especially in the UK and China).

Optimal Taxation with Homeownership and Wealth Inequality
Borri, Nicola,Reichlin, Pietro
We consider optimal taxation in a model with wealth-poor and wealth-rich households, where wealth derives from business capital and homeownership, and investigate the consequences on these tax rates of a rising wealth inequality at steady state. The optimal tax structure includes some taxation of labor, zero taxation of financial and business capital, a housing wealth tax on the wealth-rich households and a housing subsidy on the wealth-poor households. When wealth inequality increases, the optimal balance between labor and housing wealth taxes depends on the source of the increasing wealth.

Pricing FX Options under Intermediate Currency
S. Maurer,T.E. Sharp,M.V. Tretyakov

We introduce a new pricing mechanism for FX options, which is based on the idea of an intermediate pseudo-currency market. This approach allows us to price options on all FX markets simultaneously under the same risk-neutral measure which ensures consistency of FX option prices across all markets. In particular, it is sufficient to calibrate a model to the volatility smile on the domestic market as, due to the consistency of pricing formulas, the model automatically reproduces the correct smile for the inverse pair (the foreign market). We first consider the case of two currencies and then we extend the pricing mechanism to the multi-currency setting. We illustrate the new pricing mechanism by applying it to the Heston and SABR stochastic volatility models, to the model in which exchange rates are described by an extended skewed normal distribution, and also to the model-free approach of option pricing.

Pricing Sovereign Debt in Resource-Rich Economies
McGregor, Thomas
How do oil price movements affect sovereign spreads in an oil-dependent economy? I develop a stochastic general equilibrium model of an economy exposed to co-moving oil price and output processes, with endogenous sovereign default risk. The model explains a large proportion of business cycle fluctuations in interest-rate spreads in oil-exporting emerging market economies, particularly the countercyclicallity of interest rate spreads and oil prices. Higher risk-aversion, more impatient governments, larger oil shares and a stronger correlation between domestic output and oil price shocks all lead to stronger co-movements between risk premiums and the oil price.

Quantization goes Polynomial
Giorgia Callegaro,Lucio Fiorin,Andrea Pallavicini

Quantization algorithms have been successfully adopted to option pricing in finance thanks to the high convergence rate of the numerical approximation. In particular, very recently, recursive marginal quantization has been proven to be a flexible and versatile tool when applied to stochastic volatility processes. In this paper we apply for the first time quantization techniques to the family of polynomial processes, by exploiting their peculiar nature. We focus our analysis on the stochastic volatility Jacobi process, by presenting two alternative quantization procedures: the first is a new discretization technique, whose foundation lies on the polynomial structure of the underlying process and which is suitable for vanilla option pricing, the second is based on recursive marginal quantization and it allows for pricing of (vanilla and) exotic derivatives. We prove theoretical results to assess the induced approximation errors, and we describe in numerical examples practical tools for fast vanilla and exotic option pricing.

Quantum-Inspired Weighting Approach to Correlation Diversified Passive Portfolio Strategy
Sakurai, Yutaka,Yuki, Yusuke,Katsuki, Ryota,Yazane, Takashi,Ishizaki, Fumio
In this paper, we present a quantum-inspired new approach for passive portfolio strategy improving index investing. The proposed method adjusts weight vector of original index based on the permutation of assets composing the original index. We seek the permutation of assets such that assets with strong correlation to many other assets should be placed in the central part of permutation. Since the number of permutations can be prohibitively large, it is difficult to find the optimal permutation. To overcome the computational difficulty, we introduce a quantum-inspired new technology. By reducing the weights of assets placed in the central area of permutation, we can construct portfolios which are more diversified and have better risk-return characteristics than original index. To examine the usefulness of the proposed method, we apply it to 30 DJIA assets and 33 TOPIX sector indices, and we provide numerical experiments. The numerical experiments show that portfolios constructed by the proposed method can achieve higher return with lower volatility than the original indices, while their behaviors are still similar to those of the original indices.

SWAP ANLAYIŞININ NƏZƏRI STRUKTURU (Theoretical Concept of Swap Structure)
Soltanəlili, Kərim,Akbulaev, Nurkhodzha
Azerbaijani Abstract: Ölkələrin inkişafı maliyyə bazarlarının inkişafına və maliyyə bazarlarının inkişafı da maliyyəalətlərinin inkişafına bağlıdır. Bu mənada Faiz Swap’ı, dünyadakı tətbiq və işləyişi ilə bu inkişafların qabaqcıllarından biri olmaqdadır. Bu mənada Azərbaycanda da bu vasitənin tətbiqinin yayılması həm maliyyə bazarların inkişafına, həm də müəssisələrin borc xərclərinin aşağı salınmasına köməkçi olacaq. Bu məqalədə SWAP müqavilələri araşdırılmış və maliyyə bazarlarındaki tətbiqinə diqqət yetirilmişdir.English Abstract: To developing stock exchange and other financial markets must be vary financial instruments that deal with to improvement financial markets. Finally, interest Rate SWAPS is the one of first for developing forward market. In this sense, expanding the use of this tool in Azerbaijan in the development of both financial markets, but also will help to reduce operating costs of the debt. In this research, SWAP contracts were studied as a financial tool in Forward Markets.

Speed-up credit exposure calculations for pricing and risk management
Kathrin Glau,Ricardo Pachon,Christian Pötz

We introduce a new method to calculate the credit exposure of European and path-dependent options. The proposed method is able to calculate accurate expected exposure and potential future exposure profiles under the risk-neutral and the real-world measure. Key advantage of is that it delivers an accuracy comparable to a full re-evaluation and at the same time it is faster than a regression-based method. Core of the approach is solving a dynamic programming problem by function approximation. This yields a closed form approximation along the paths together with the option's delta and gamma. The simple structure allows for highly efficient evaluation of the exposures, even for a large number of simulated paths. The approach is flexible in the model choice, payoff profiles and asset classes. We validate the accuracy of the method numerically for three different equity products and a Bermudan interest rate swaption. Benchmarking against the popular least-squares Monte Carlo approach shows that our method is able to deliver a higher accuracy in a faster runtime.

Statistical mechanics and time-series analysis by L\'evy-parameters with the possibility of real-time application
Alexander Jurisch

We develop a method that relates the truncated cumulant-function of the fourth order with the L\'evian cumulant-function. This gives us explicit formulas for the L\'evy-parameters, which allow a real-time analysis of the state of a random-motion. Cumbersome procedures like maximum-likelihood or least-square methods are unnecessary. Furthermore, we treat the L\'evy-system in terms of statistical mechanics and work out it's thermodynamic properties. This also includes a discussion of the fractal nature of relativistic corrections. As examples for a time-series analysis, we apply our results on the time-series of the German DAX and the American S\&P-500\,.

Swing Pricing and Fragility in Open-End Mutual Funds
Jin, Dunhong,Kacperczyk, Marcin T.,Kahraman, Bige,Suntheim, Felix
How to prevent runs on open-end mutual funds? In recent years, markets have observed an innovation that changed the way open-end funds are priced. Alternative pricing rules (known as swing pricing) adjust funds' net asset values to pass on funds' trading costs to transacting shareholders. Using unique data on investor transactions in U.K. corporate bond funds, we show that swing pricing eliminates the first-mover advantage arising from the traditional pricing rule and significantly reduces redemptions during stress periods. The positive impact of alternative pricing rules on fund flows reverses in calm periods when costs associated with higher tracking error dominate the pricing effect.

The Effect of Classification Shifting on Firm Success
Anagnostopoulou, Seraina C.,Gounopoulos, Dimitrios,Malikov, Kamran,Pham, Hang
The study examines the effect of earnings management by classification shifting on firm success, by focusing on the survival of newly listed firms. We argue that shifting income-decreasing expenses from core to special items should negatively associate with future operating performance because of a) improper signaling of actual repeatable core profitability; and, more importantly b) in accordance with recent evidence by Cain, Kolev, and McVay (2019), suggesting a negative effect of opportunistic special items on future profits and cash flows. We find that classification shifting strongly and negatively affects future Initial Public Offering (IPO) success and survival. Our evidence indicates that this negative impact actually stems from adverse effects of non-transitory opportunistic special items, which constitute the tool for applying classification shifting, on future profits and operating cash flows, while our results are mitigated for IPO firms operating within stronger business contexts. Our findings provide evidence on the longer-term effects of a method of earnings management that has long been considered “soft,” and without any longer-term reversing consequences. Our evidence does not support this proposition in the case of newly listed IPO firms engaging in classification shifting around the time of issue.

Time-inconsistent consumption-investment problems in incomplete markets under general discount functions
Yushi Hamaguchi

In this paper we study a time-inconsistent consumption-investment problem with random endowments in a possibly incomplete market under general discount functions. We provide a necessary condition and a verification theorem for an open-loop equilibrium consumption-investment pair in terms of a coupled forward-backward stochastic differential equation. Moreover, we prove the uniqueness of the open-loop equilibrium pair by showing that the original time-inconsistent problem is equivalent to an associated time-consistent one.

Transnational Fiduciary Law: Spaces and Elements
Kuntz, Thilo
In recent years, fiduciary law has increasingly moved to the center of scholarly attention in the common-law world. Even a cursory review shows ample evidence of the importance of fiduciary-related norms; not only both in common-law and civil-law jurisdictions, but also beyond the nation state. Although civil-law countries have no tradition of the trust as a legal institution, courts and scholars alike coin relationships based on some kind of personal or professional trust “fiduciary”. Additionally, the trust as a legal institution is gaining ground in civil-law countries, either following a national recognition of the Hague Trust Convention (e.g., Italy, the Netherlands) or because they have introduced trust legislation (Japan and other countries in East Asia). A number of more sector-specific rules and regulations issued by institutions and initiatives such as the OECD Principles of Corporate Governance and the UN report on “Fiduciary Duty for the 21st Century” are shaping legal norms and legislation. In other areas of the law with regulations and rules spreading beyond the nation state, scholars have been trying to spell out a concept of “transnational law”, determined to embrace the notion of “something being there” which doesn’t quite fit the bill of the traditional dichotomy of national law or international law. Given the phenomena described above, the question driving this paper is subsequently: Is there such a thing as transnational fiduciary law? Answering this question and mapping a research agenda proves to be a thorny issue, however. Not only is fiduciary law itself “elusive”. The same is true for transnational law and transnational legal theory. Methodologically, this makes thinking about transnational fiduciary law a daunting task.Grappling with all these issues, this paper aims to make a twofold contribution: First and foremost, it establishes transnational fiduciary law as a field, existing at the intersection of transnational law and fiduciary law. Second, it expands both transnational law and fiduciary law by establishing new perspectives on both fields. It explores how transnational law may evolve out of national norms. Additionally, the paper shows the possibility of crossing the common law-civil law divide in fiduciary law and demonstrates that, compared to the traditional common-law view, the fiduciary duty of loyalty may develop different kinds of distinctiveness in transnational settings. It builds on two main examples: Horizontal transnational ordering of the trust in East Asia and vertical ordering of fiduciary law with respect to standards and principles concerning environmental, social and governance (ESG) issues.

Variance Reduction Applied to Machine Learning for Pricing Bermudan/American Options in High Dimension
Ludovic Goudenège,Andrea Molent,Antonino Zanette

In this paper we propose an efficient method to compute the price of multi-asset American options, based on Machine Learning, Monte Carlo simulations and variance reduction technique. Specifically, the options we consider are written on a basket of assets, each of them following a Black-Scholes dynamics. In the wake of Ludkovski's approach (2018), we implement here a backward dynamic programming algorithm which considers a finite number of uniformly distributed exercise dates. On these dates, the option value is computed as the maximum between the exercise value and the continuation value, which is obtained by means of Gaussian process regression technique and Monte Carlo simulations. Such a method performs well for low dimension baskets but it is not accurate for very high dimension baskets. In order to improve the dimension range, we employ the European option price as a control variate, which allows us to treat very large baskets and moreover to reduce the variance of price estimators. Numerical tests show that the proposed algorithm is fast and reliable, and it can handle also American options on very large baskets of assets, overcoming the problem of the curse of dimensionality.

Very Noisy Option Prices and Inferences Regarding Option Returns
Duarte, Jefferson,Jones, Christopher S.,Wang, Junbo L.
We show that microstructure biases in the estimation of expected option returns and risk premia are large, in some cases over 50 basis points per day. We propose a new method that corrects for these biases. We then apply our method to real data and produce three main findings. First, the expected returns of straddles and delta-hedged options written on the S&P 500 Index are smaller than previously estimated in the literature. Second, delta-hedged options and straddles written on individual stocks have negative expected returns. Third, the price of individual equity volatility risk is about 45% of the price of market volatility. These findings show that the stylized finding that volatility is not priced in individual stock options is due to microstructure biases.