Research articles for the 2019-07-02

A Model of Presidential Debates
Doron Klunover,John Morgan

Presidential debates are thought to provide an important public good by revealing information on candidates to voters. However, this may not always be the case. We consider an endogenous model of presidential debates in which an incumbent and a contender (who is privately informed about her own quality) publicly announce whether they are willing to participate in a public debate, after taking into account that a voter's choice of candidate depends on her beliefs regarding the candidates' qualities and on the state of nature. Surprisingly, it is found that in equilibrium a debate occurs or does not occur independently of the contender's quality or the sequence of the candidates' announcements to participate and therefore the announcements are uninformative.

A Multivariate Evolutionary Generalised Linear Model Framework with Adaptive Estimation for Claims Reserving
Avanzi, Benjamin,Taylor, Greg,Vu, Phuong Anh,Wong, Bernard
In this paper, we develop a multivariate evolutionary generalised linear model (GLM) framework for claims reserving, which allows for dynamic features of claims activity in conjunction with dependency across business lines to accurately assess claims reserves. We extend the traditional GLM reserving framework on two fronts: GLM fixed factors are allowed to evolve in a recursive manner, and dependence is incorporated in the specification of these factors using a common shock approach.We consider factors that evolve across accident years in conjunction with factors that evolve across calendar years. This two-dimensional evolution of factors is unconventional as a traditional evolutionary model typically considers the evolution in one single time dimension. This creates challenges for the estimation process, which we tackle in this paper. We develop the formulation of a particle filtering algorithm with parameter learning procedure. This is an adaptive estimation approach which updates evolving factors of the framework recursively over time.We implement and illustrate our model with a simulated data set, as well as a set of real data from a Canadian insurer.

A Nova Lei das Estatais afetou as empresas públicas listadas na bolsa? (Has the New State Law Affected Listed Public Companies?)
Kayo, Vitor,Holland, Márcio,Sampaio, Joelson Oliveira
Portuguese Abstract: Esse trabalho estuda os efeitos da introdução de uma nova legislação voltada para empresas estatais no Brasil. Particularmente, analisa se essa nova legislação, ao promover ganhos de governança corporativa, leva à redução da percepção de riscos na administração das companhias e, com isso, na volatilidade dos retornos das ações dessas empresas. Para tanto, são usados estimadores de controle sintético conforme a metodologia ArCo (Artificial Counterfactual), usando dados em painel de séries temporais de alta dimensão, de 2011 a 2018. Nossos resultados mostram que treze de vinte ações analisadas apresentam redução em suas volatilidades, seis das vinte ações apresentam resultados opostos ao esperado e uma ação não apresenta resultado estatisticamente significativo. English Abstract: This paper studies the effects of the new legislation applied to state-owned enterprises in Brazil. In particular, it analyzes whether this new law, by promoting corporate governance gains, leads to a reduction in the perception of risks in its management and, therefore, in the volatility of the stock returns of these companies. For this, synthetic control estimators are used according to the ArCo (Artificial Counterfactual) methodology, using high-dimensional panel time-series data, from 2011 to 2018. Our results show that thirteen out of twenty stocks present a reduction in their volatility, six out of twenty stocks have conflicting results and one stock does not present a statistically significant result.

Application of Projectile Physics and Variable Drag Implications in Determining Market Prices for Futures Derivatives
Mushunje, Leonard
This particular study took an econo-physics route to explain the market behaviour for futures contracts in terms of prices and its market life span. We used projectile motion models defined under two distinct conditions (perfect/horizontal and imperfect/ drag implication) based on Newton’s and Galileo’s laws of motion. Despite that it was more theoretical we managed to derive the futures price functions and the results showed that futures prices depends largely on market forces of demand and supply and underlying assets price behaviour. Also, we managed to find the terminal prices for the securities given the initial prices, which is a worrying matter to the trading parties. From the performance comparison of the two models used, results suggested that futures price function from a drag variable is more powerful in modelling the price behaviour for options than the one sorely controlled by market demand and supply forces. Also, we used the mean absolute deviation (MAD) to validate our Futures derivative pricing model. Fortunately, the obtained MAD results supported the efficiency of our model. However, it should not be carelessly taken that the projectile models used are much good at price motions/movements within the market from time to time with a stunted ability to capture in other facts of interest such as volatility coefficients which paves a research way for other scholars.

Blockchain: Inclusive Technology? (Blockchain: Tecnologia Inclusiva?)
de Mariz, Frederic
Blockchain has the potential to improve the access, quality and cost of financial services, but technical challenges remain: both operational and related to governance.

Buzzwords Build Momentum: Global Financial Twitter Sentiment and the Aggregate Stock Market
Groß-Klußmann, Axel,König, Stephan,Ebner, Markus
We examine the long-term relationship between signals derived from nine years of unstructured social media microblog text data and financial market developments in five major economic regions. Employing statistical language modeling techniques we construct directional sentiment metrics and link these to aggregate stock index returns. To address the noise in finance-related Twitter messages we identify expert users whose tweets predominantly focus on finance topics. We document that expert users are the main drivers behind a significant contemporaneous link between Twitter sentiment and financial markets. Notably, the link remains equally strong in times of major news events impacting the markets. The direct prediction value of expert sentiment metrics for stock index returns, however, is found to be elusive and short-lived. Yet, the relation between expert sentiment metrics and stock indices is sufficient to devise profitable cross-sectional as well as time series momentum investment strategies based on Twitter signals that survive basic transaction cost assumptions. In this context, our results show that expert sentiment signals can yield higher risk-adjusted returns than classical price-signals.

Capital Flows to Emerging Economies: Recent Developments and Drivers
Molina, Luis,Viani, Francesca
Emerging markets have gained prominence as recipients of capital flows since the onset of the financial crisis in 2008. This raises their exposure and goes hand in hand with greater dependence on external financing and heightened sensitivity to global shocks. However, some differences can be observed across regions. For example, while the more stable types of capital flows (direct investment) continue to outweigh other types in Latin America, in Asia and the Middle East the recent increase in capital inflows has taken the form of debt, private in the case of Asia and mostly government debt in the Middle East. Against this background, this article examines the impact on the capital flows to these economies of five potential global shocks: an appreciation of the dollar, a fall in commodity prices, an increase in global aversion to risk, expectations of monetary policy tightening in the United States and lower regional growth compared with advanced economies. The findings of this article suggest that the factor with the greatest impact on portfolio flows to emerging markets is the appreciation of the dollar although, in the case of Latin America, commodity prices also play a very significant role.

Compact embeddings for spaces of forward rate curves
Stefan Tappe

The goal of this note is to prove a compact embedding result for spaces of forward rate curves. As a consequence of this result, we show that any forward rate evolution can be approximated by a sequence of finite dimensional processes in the larger state space.

Comparative analysis of layered structures in empirical investor networks and cellphone communication networks
Peng Wang,Jun-Chao Ma,Zhi-Qiang Jiang,Wei-Xing Zhou,Didier Sornette

Empirical investor networks (EIN) proposed by \cite{Ozsoylev-Walden-Yavuz-Bildik-2014-RFS} are assumed to capture the information spreading path among investors. Here, we perform a comparative analysis between the EIN and the cellphone communication networks (CN) to test whether EIN is an information exchanging network from the perspective of the layer structures of ego networks. We employ two clustering algorithms ($k$-means algorithm and $H/T$ break algorithm) to detect the layer structures for each node in both networks. We find that the nodes in both networks can be clustered into two groups, one that has a layer structure similar to the theoretical Dunbar Circle corresponding to that the alters in ego networks exhibit a four-layer hierarchical structure with the cumulative number of 5, 15, 50 and 150 from the inner layer to the outer layer, and the other one having an additional inner layer with about 2 alters compared with the Dunbar Circle. We also find that the scale ratios, which are estimated based on the unique parameters in the theoretical model of layer structures \citep{Tamarit-Cuesta-Dunbar-Sanchez-2018-PNAS}, conform to a log-normal distribution for both networks. Our results not only deepen our understanding on the topological structures of EIN, but also provide empirical evidence of the channels of information diffusion among investors.

Competition and Manipulation in Derivative Contract Markets
Zhang, Anthony Lee
This paper develops methods and metrics for quantifying manipulation risk in cash-settled derivative contract markets.I show how to estimate market participants' manipulation incentives, and predict manipulation-induced market distortions, using commonly observed market data. I develop a simple manipulation index, which can be used as a diagnostic metric to detect potentially manipulable contract markets, similar to the Herfindahl-Hirschman index (HHI) in antitrust settings. I apply my results to estimate manipulation risk in a number of contract markets.

Consumer Payment Preferences and the Impact of Technology and Regulation: Insights from the Visa Payment Panel Study
Akana, Tom
The Consumer Finance Institute hosted a workshop in August 2018 featuring Michael Marx, senior director at Visa, Inc., to discuss recent data from the Visa Payment Panel, highlighting the evolution of consumer payment preferences since the Great Recession and the passage of the Credit Card Accountability Responsibility and Disclosure (CARD) Act of 2009. A number of intriguing trends were discussed. Debit card adoption and growth have shown signs of slowing, even as regulatory changes have increased its prevalence recently among younger consumers. Credit card usage continues to grow and has shifted largely to rewards-based products. Payment preferences for younger consumers appear to be influenced by the availability of financial products (driven by social and regulatory influences) as well as the advent of mobile wallets and person-to-person (P2P) technologies. This paper summarizes Marx's presentation along with additional research.

Corporate Social Responsibility and Trade Credit
Xu, Hongkang,Wu, Jia,Dao, Mai
Prior studies show that higher corporate social responsibility (CSR) performance lowers firms’ cost of debt and equity financing. Using a sample of 16,463 U.S. firm-year observations that represent more than 2,455 individual firms over the 1996-2016 period, we investigate the relation between all aspects of CSR and trade credit. We provide strong and robust evidence that higher overall CSR scores are related to a higher level of trade credit. A further examination reveals positive associations between trade credit and the four CSR individual components (i.e., the environment, employee relations, community, and diversity). Taken together, our results highlight the important signaling role that CSR plays in increasing the suppliers’ willingness to extend trade credit. Our study also has an important supply chain implication that emphasizes the role of CSR in designing contracts between buyers and suppliers and the level of trade credit for buyer firms with CSR investments.

Determinants of Bank Selection: An International Student Perspective
Oluwaseyitan, Rotimi,Hashim, Haslinda,Raja Yusof, Raja Nerina
While student bank selection has enjoyed overwhelming research attention over the past few decades, how international student determines and selects their banks has, however, received little attention in the marketing literature. This study explored the determinants of banking selection, among international students in Malaysian public universities. To achieve an in-depth understanding of this phenomenon and their ranking, a qualitative research methodology was employed, along with Analytical Hierarchy Process (AHP). The findings revealed five determinants out of nine identified from the literature, as the principal determinants of banking selection, among international students. These are (i) the third-party influences, (ii) convenience of location, (iii) availability of the ATM, (iv) quality of service, and (v) financial benefits from saving. The third party influence was considered as the most important determinant, and financial benefits from saving as the least important determinant of banking selection, among international students in Malaysia. The second most important was the convenience of location, followed by the availability of the ATM, and the quality of service respectively. The studies on international student bank selection determinant are scanty in literature, this study, therefore, makes a contribution to the existing knowledge in this field.

Election Predictions as Martingales: An Arbitrage Approach
Nassim Nicholas Taleb

We consider the estimation of binary election outcomes as martingales and propose an arbitrage pricing when one continuously updates estimates. We argue that the estimator needs to be priced as a binary option as the arbitrage valuation minimizes the conventionally used Brier score for tracking the accuracy of probability assessors.

We create a dual martingale process $Y$, in $[L,H]$ from the standard arithmetic Brownian motion, $X$ in $(-\infty, \infty)$ and price elections accordingly. The dual process $Y$ can represent the numerical votes needed for success.

We show the relationship between the volatility of the estimator in relation to that of the underlying variable. When there is a high uncertainty about the final outcome, 1) the arbitrage value of the binary gets closer to 50\%, 2) the estimate should not undergo large changes even if polls or other bases show significant variations.

There are arbitrage relationships between 1) the binary value, 2) the estimation of $Y$, 3) the volatility of the estimation of $Y$ over the remaining time to expiration. We note that these arbitrage relationships were often violated by the various forecasting groups in the U.S. presidential elections of 2016, as well as the notion that all intermediate assessments of the success of a candidate need to be considered, not just the final one.

Elicitability and Identifiability of Systemic Risk Measures and other Set-Valued Functionals
Tobias Fissler,Jana Hlavinová,Birgit Rudloff

This paper is concerned with a two-fold objective. Firstly, we establish elicitability and identifiability results for systemic risk measures introduced in Feinstein, Rudloff and Weber (2017). Specifying the entire set of capital allocations adequate to render a financial system acceptable, these systemic risk measures are examples of set-valued functionals. A functional is elicitable (identifiable) if it is the unique minimiser (zero) of an expected scoring function (identification function). Elicitability and identifiability are essential for forecast ranking and validation, $M$- and $Z$-estimation, both possibly in a regression framework. To account for the set-valued nature of the systemic risk measures mentioned above, we secondly introduce a theoretical framework of elicitability and identifiability of set-valued functionals. It distinguishes between exhaustive forecasts, being set-valued and aiming at correctly specifying the entire functional, and selective forecasts, content with solely specifying a single point in the correct functional. Uncovering the structural relation between the two corresponding notions of elicitability and identifiability, we establish that a set-valued functional can be either selectively elicitable or exhaustively elicitable. Notably, selections of quantiles such as the lower quantile turn out not to be elicitable in general. Applying these structural results to systemic risk measures, we construct oriented selective identification functions, which induce a family of strictly consistent exhaustive elementary scoring functions. We discuss equivariance properties of these scores. We demonstrate their applicability in a simulation study considering comparative backtests of Diebold-Mariano type with a pointwise traffic-light illustration of Murphy diagrams.

Financial Inclusion In China: Deepening High-Level Financial Inclusion For Foreigners In China
Tampuri Jnr, Mark Yama,Kong, Yusheng,Asare, Isaac
There have been researches in Financial Inclusion in China; however, not much has been researched on Financial Inclusion indicators for foreigners in China. Base on the report of the 2014 Global Findex Database, the paper analyses the determinants of Financial Inclusion in China in general and touches on some reasons for those outcomes. Also, researchers determine financial inclusion indicators and depth for foreigners in China. Questionnaires on Financial Inclusion indicators and individual characteristics are administered to foreigners in China and observe that foreigners largely have access to basic banking services as a transaction account from their banks. Largely, foreigners are satisfied with their bank's services; however, they feel limited in their inability to acquire some sophisticated banking services except for basic service. Observation is made that Wechat and Alipay Payment Services remain the most accessed and used financial services platform which provide the most depth financial access and usage without limitation for foreigners in China, hence foreigners relies mostly on the two services than their traditional bank for their financial transactions.

Firm-Level Employment, Labour Market Reforms, and Bank Distress
Stieglitz, Moritz,Setzer, Ralph
We explore the interaction between labour market reforms and financial frictions. Our study combines a new cross-country reform database on labour market reforms with matched firm-bank data for nine euro area countries over the period 1999 to 2013. While we find that labour market reforms are overall effective in increasing employment, restricted access to bank credit can undo up to half of long-term employment gains at the firm-level. Entrepreneurs without sufficient access to credit cannot reap the full benefits of more flexible employment regulation.

Hermite Expansion for Transition Densities of Irreducible Diffusions with An Application to Option Pricing
Wan, Xiangwei,Yang, Nian
A diffusion is said to be reducible if there exists a one-to-one transformation of the diffusion into a new one whose diffusion matrix is the identity matrix, otherwise it is irreducible. Most multivariate diffusions such as the stochastic volatility models are irreducible. As pointed out by Ait-Sahalia (2008), the straight Hermite expansion of Ait-Sahalia (2002) will not in general converge for irreducible diffusions. In this paper we manage to develop the Hermite expansion for transition densities of irreducible diffusions, which converges as the time interval shrinks to zero. By introducing a quasi-Lamperti transform unitizing the process’ diffusion matrix at the initial time, we can expand the transition density of the transformed process using Hermite polynomials as the orthogonal basis. Then we derive explicit recursive formulas for the expansion coefficients using the Itˆo-Taylor expansion method, and prove the small-time convergence of the expansion. Moreover, we show that the derived Hermite expansion unifies some existing methods including the expansions of Li (2013) and Yang et al. (2019). In addition, we demonstrate the advantage of Hermite expansion by deriving explicit recursive expansion formulas for European option prices under irreducible diffusions. Numerical experiments illustrate the accuracy and effectiveness of our approach.

Keeping up with the Joneses: Social Status and Wealth Inequality in a Leveraged Asset Market
Deck, Cary A.,Hao, Li,Xu, Weineng,Yeager, Timothy J.
We hypothesize that growing wealth inequality has exacerbated leveraged asset bubbles in the wealthiest nations over the last several decades through a “keeping up with the Joneses” effect. Rising inequality strengthens the desire of households to improve their social status by owning assets such as homes demanded by those with wealth. Given easy access to credit, relatively low-wealth individuals use leverage to bid up asset prices. We test this theory within the popular asset market experiment of Smith, Suchanek, and Williams (1988) where we combine the option to borrow with treatments for wealth inequality and social status. We find that the social status effect indeed leads to asset overpricing, and the impact is the biggest when combining social status with wealth inequality. On the other hand, wealth inequality alone does not lead to greater asset bubbles.

Liquidity and Algorithmic Trading in Brazil
Ramos, Henrique,Perlin, Marcelo
This paper provides evidence of the effect of algorithmic trading (AT) in the liquidity of the Brazilian equity market. A wide debate on the literature asserts that AT may be both beneficial and harmful to market quality. The results of our econometric estimates for a sample of 47 stocks through mid-2017 to mid-2018 show that when a larger horizon is analyzed (20 minutes), the lagged effect of AT reduces market quality. However, the lagged effect of one-minute AT activity reduces both spreads and price impact. Still, the effect of AT on market quality is sensitive to the horizon which is being analyzed.

Local Taxes and the Demand for Skilled Labor: Evidence from 27 Million Job Postings
Campello, Murillo,Gao, Janet,Xu, Qiping
Using big data on the near-universe of US firms' job postings, we document measurable, negative effects of local personal income taxes on the level of education, experience, and professional skills demanded by firms when hiring workers (downskilling). Tax-induced downskilling is identified both at the county level and at individual firms' local branches. It is solely driven by changes in high-income earners' tax rates. Multi-state firms internally reassign their hiring of low- vs. high-quality workers according to local personal income tax changes. This dynamic is more pronounced in industries that rely less on skilled labor and on local resources in their production processes, yet mitigated in firms' headquarter states and states that account for a large fraction of firm sales. Firms also cut IT investment and eventually exit states that increase personal taxes. Our findings point to a "brain-drain"' in states with high personal income taxes, showing how those taxes influence the local demand for human capital and labor market composition.

Moving into the Mainstream: Who Graduates from Secured Credit Card Programs?
Santucci, Larry
Secured credit cards--credit cards whose limit is fully or partially collateralized by a bank deposit--are considered a gateway product to mainstream credit access. As consumers demonstrate good usage and repayment behavior, they may be offered the opportunity to graduate to an unsecured credit card. This paper uses anonymized account-level data to examine the prevalence of account graduation in the secured credit card market since 2012. Using a fixed effects regression model, we identify a set of usage and repayment behaviors that are correlated with account graduation.

Negative Peer Disclosure
Cao, Sean,Fang, Vivian W.,Lei, Lijun (Gillian)
This paper provides evidence of negative peer disclosure, an emerging corporate strategy to publicize adverse news about industry peers on social media. Its propensity increases with product market rivalry, technology proximity, and information uncertainty. Consistent with firms issuing negative peer disclosures to signal quality, they experience an excess return of 1.6-1.7% over the market and industry during a two-day event window and exhibit superior operating performance in the following year. Such signaling suggests that firms are capable of internalizing information spillovers from peer firms’ adverse news. Overall, these results rationalize peer disclosure and broaden the scope of literature beyond self-disclosure.

Optimal Bookmaking
Matthew Lorig,Zhou Zhou,Bin Zou

We introduce a general framework for continuous-time betting markets, in which a bookmaker can dynamically control the prices of bets on outcomes of random events. In turn, the prices set by the bookmaker affect the rate or intensity of bets placed by gamblers. The bookmaker seeks a price process that maximizes his expected (utility of) terminal wealth. We obtain explicit solutions or characterizations to the bookmaker's optimal bookmaking problem in various interesting models.

Optimistic Bull or Pessimistic Bear: Adaptive Deep Reinforcement Learning for Stock Portfolio Allocation
Xinyi Li,Yinchuan Li,Yuancheng Zhan,Xiao-Yang Liu

Portfolio allocation is crucial for investment companies. However, getting the best strategy in a complex and dynamic stock market is challenging. In this paper, we propose a novel Adaptive Deep Deterministic Reinforcement Learning scheme (Adaptive DDPG) for the portfolio allocation task, which incorporates optimistic or pessimistic deep reinforcement learning that is reflected in the influence from prediction errors. Dow Jones 30 component stocks are selected as our trading stocks and their daily prices are used as the training and testing data. We train the Adaptive DDPG agent and obtain a trading strategy. The Adaptive DDPG's performance is compared with the vanilla DDPG, Dow Jones Industrial Average index and the traditional min-variance and mean-variance portfolio allocation strategies. Adaptive DDPG outperforms the baselines in terms of the investment return and the Sharpe ratio.

Price Dynamics with Circuit Breakers
Lera, Sandro Claudio,Sornette, Didier ,Ulmann, Florian
We develop a self-consistent model of the dynamics of an asset price in the presence of a circuit breaker (imposed trading halt). The investors' anticipation of the probability of the halt, and of the dynamics of the underlying value during the halt, feedbacks on the price process. This leads to coupled integral and stochastic differential equations. With first-order analytical solutions compared with a full numerical treatment, the theory predicts generally an increased price volatility prior to the trigger point, as has been reported in the empirical literature. The theory also shows the existence of a competition between a repelling "momentum" term associated with the propensity for investors to anchor on trends and an attractive "rational drift" term corresponding to the anticipation of theimpact of the stopping period. Thus, the sole existence of a circuit breaker leads either to a beneficial effect of impeding the price drop for a while or, on the contrary, to the negative effect of attracting the price to the circuit breaker level (known as the "magnet effect"). The latter occurs when the fundamental price has larger negative drifts and is relatively close to the circuit breaker level. We successfully calibrate our model on three different circuit breakers: Cboe bitcoin futures, the Shanghai CSI300 index and the S&P500. Finally, we propose first steps toward a more robust design of circuit breakers.

R&D Expenditure as a Response to Peer Influence
Bui, Dien Giau,Chen, Yehning,Lin, Chih-Yung,Lin, Tse-Chun
This paper examines the response of a focal firm to peer R&D spending. We find that a one-standard-deviation increase in peer R&D investment is associated with approximately a 13.7 percent increase in a firm’s R&D. Using trade secret legal protection among peers as the instrumental variable yields similar results. This peer effect on R&D spending is more prominent for firms with tighter financial constraints, overconfident or highly incentivized CEOs, higher growth opportunity, and in more competitive or innovative industries. We also find that managerial learning and relative-wealth concerns seem to be the dominating economic mechanisms for the peer effect. Finally, firms with more peer R&D spending have higher subsequent innovation output and firm value. However, this bright side of the peer effect comes with both higher stock-return volatility and stock-price crash risk.

Regulatory and Market Challenges of Initial Coin Offerings
Andrés, Pablo de,Arroyo, David,Correia, Ricardo,Rezola, Alvaro
This article analyzes the main problems and the solutions adopted in the market for Initial Coin Offerings (ICO), an alternative financing solution that has experienced spectacular growth and notoriety in recent years. This market relies on the use of Blockchain protocols and is, therefore, characterized as disintermediated, decentralized and unregulated. The problems we identify in this article, their severity, and the solutions currently being adopted to address them, lead us to conclude that it is unlikely that either of these characteristics will survive in the near future. Our results also indicate that the concerns expressed by regulators and other market agents regarding ICO markets are well founded. We find it particularly disturbing that such a new, revolutionary market already displays many of the problems of traditional financial markets, and that these problems were exactly the ones that occurred at the genesis of the last financial crisis.

Robust XVA
Maxim Bichuch,Agostino Capponi,Stephan Sturm

We introduce an arbitrage-free framework for robust valuation adjustments. An investor trades a credit default swap portfolio with a risky counterparty, and hedges credit risk by taking a position in defaultable bonds. The investor does not know the return rate of her counterparty bond, but is confident that it lies within a uncertainty interval. We derive both upper and lower bounds for the XVA process of the portfolio, and show that these bounds may be recovered as solutions of nonlinear ordinary differential equations. The presence of collateralization and closeout payoffs leads to important differences with respect to classical credit risk valuation. The value of the super-replicating portfolio cannot be directly obtained by plugging one of the extremes of the uncertainty interval in the valuation equation, but rather depends on the relation between the XVA replicating portfolio and the close-out value throughout the life of the transaction. Our comparative statics analysis indicates that credit contagion has a nonlinear effect on the replication strategies and on the XVA.

Size matters for OTC market makers: viscosity approach and dimensionality reduction technique
Philippe Bergault,Olivier Guéant

In most OTC markets, a small number of market makers provide liquidity to clients from the buy side. More precisely, they set prices at which they agree to buy and sell the assets they cover. Market makers face therefore an interesting optimization problem: they need to choose bid and ask prices for making money out of their bid-ask spread while mitigating the risk associated with holding inventory in a volatile market. Many market making models have been proposed in the academic literature, most of them dealing with single-asset market making whereas market makers are usually in charge of a long list of assets. The rare models tackling multi-asset market making suffer however from the curse of dimensionality when it comes to the numerical approximation of the optimal quotes. The goal of this paper is to propose a dimensionality reduction technique to address multi-asset market making with grid methods. Moreover, we generalize existing market making models by the addition of an important feature for OTC markets: the variability of transaction sizes and the possibility for the market maker to answer different prices to requests with different sizes.

Smart network based portfolios
Gian Paolo Clemente,Rosanna Grassi,Asmerilda Hitaj

In this article we deal with the problem of portfolio allocation by enhancing network theory tools. We use the dependence structure of the correlations network in constructing some well-known risk-based models in which the estimation of correlation matrix is a building block in the portfolio optimization. We formulate and solve all these portfolio allocation problems using both the standard approach and the network-based approach. Moreover, in constructing the network-based portfolios we propose the use of two different estimators for the covariance matrix: the sample estimator and the shrinkage toward constant correlation one. All the strategies under analysis are implemented on two high-dimensional portfolios having different characteristics, covering the period from January $2001$ to December $2017$. We find that the network-based portfolio consistently better performs and has lower risk compared to the corresponding standard portfolio in an out-of-sample perspective.

Solving the Reswitching Paradox in the Sraffian Theory of Capital
Carlo Milana

The possibility of re-switching of techniques in Piero Sraffa's intersectoral model, namely the returning capital-intensive techniques with monotonic changes in the profit rate, is traditionally considered as a paradox putting at stake the viability of the neoclassical theory of production. It is argued here that this phenomenon can be rationalized within the neoclassical paradigm. Sectoral interdependencies can give rise to non-monotonic effects of progressive variations in income distribution on relative prices. The re-switching of techniques is, therefore, the result of cost-minimizing technical choices facing returning ranks of relative input prices in full consistency with the neoclassical perspective.

Sparse Index Clones via the Sorted L1-Norm
Kremer, Philipp,Brzyski, Damian,Bogdan, Malgorzata,Paterlini, Sandra
Index tracking and hedge fund replication aim at cloning the return time series properties of a given benchmark, by either using only a subset of its original constituents or by a set of risk factors. In this paper, we propose a model that relies on the Sorted L1 Penalized Estimator, called SLOPE, for index tracking and hedge fund replication. SLOPE is capable of not only providing sparsity but also to form groups among assets depending on their partial correlation with the index or the hedge fund return times series. The grouping structure can then be exploited to create individual investment strategies that allow building portfolios with a smaller number of active positions, but still comparable tracking properties. Considering equity index data over the period from December 2004 to January 2016 and hedge fund returns from June 1994 to July 2017, we show that the SLOPE based approaches can often outperform state-of-the-art non-convex approaches.

Time Delay and Investment Decisions: Evidence from An Experiment in Tanzania
Nikolov, Plamen
Attitudes toward risk underlie virtually every important economic decision an individual makes. In this experimental study, I examine how introducing a time delay into the execution of an investment plan influences individuals’ risk preferences. The field experiment proceeded in three stages: a decision stage, an execution stage and a payout stage. At the outset, in the Decision Stage (Stage 1), each subject was asked to make an investment plan by splitting a monetary investment amount between a risky asset and a safe asset. Subjects were informed that the investment plans they made in the Decision Stage are binding and will be executed during the Execution Stage (Stage 2). The Payout Stage (Stage 3) was the payout date. The timing of the Decision Stage and Payout Stage was the same for each subject, but the timing of the Execution Stage varied experimentally. I find that individuals who were assigned to execute their investment plans later (i.e., for whom there was a greater delay prior to the Execution Stage) invested a greater amount in the risky asset during the Decision Stage.

Tracking VIX with VIX Futures: Portfolio Construction and Performance
Leung, Tim,Ward, Brian
We study a series of static and dynamic portfolios of VIX futures and their effectiveness to track the VIX index. We derive each portfolio using optimization methods, and evaluate its tracking performance from both empirical and theoretical perspectives. Among our results, we show that static portfolios of different VIX futures fail to track VIX closely. VIX futures simply do not react quickly enough to movements in the spot VIX. In a discrete-time model, we design and implement a dynamic trading strategy that adjusts daily to optimally track VIX. The model is calibrated to historical data and a simulation study is performed to understand the properties exhibited by the strategy. In addition, comparing to the volatility ETN, VXX, we find that our dynamic strategy has a superior tracking performance.