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We devise a neural network based compression/completion methodology for financial nowcasting. The latter is meant in a broad sense encompassing completion of gridded values, interpolation, or outlier detection, in the context of financial time series of curves or surfaces (also applicable in higher dimensions, at least in theory). In particular, we introduce an original architecture amenable to the treatment of data defined at variable grid nodes (by far the most common situation in financial nowcasting applications, so that PCA or classical autoencoder methods are not applicable). This is illustrated by three case studies on real data sets. First, we introduce our approach on repo curves data (with moving time-to-maturity as calendar time passes). Second, we show that our approach outperforms elementary interpolation benchmarks on an equity derivative surfaces data set (with moving time-to-maturity again). We also obtain a satisfying performance for outlier detection and surface completion. Third, we benchmark our approach against PCA on at-the-money swaption surfaces redefined at constant expiry/tenor grid nodes. Our approach is then shown to perform as well as (even if not obviously better than) the PCA which, however, is not be applicable to the native, raw data defined on a moving time-to-expiry grid)., Comment: his article has been accepted for publication in Journal of Computational Finance, publishedby Incisive Media Ltd

High-$T_{\rm C}$ superconductors show anomalous transport properties in their normal states, such as the bad-metal and pseudogap behaviors. To discuss their origins, it is important to speculate whether these behaviors are material-dependent or universal phenomena in the proximity of the Mott transition, by investigating similar but different material systems. An organic Mott transistor is suitable for this purpose owing to the adjacency between the two-dimensional Mott insulating and superconducting states, simple electronic properties, and high doping/bandwidth tunability in the same sample. Here we report the temperature dependence of the transport properties under electron and hole doping in an organic Mott electric-double-layer transistor. At high temperatures, the bad-metal behavior widely appears except at half filling regardless of the doping polarity. At lower temperatures, the pseudogap behavior is observed only under hole doping, while the Fermi-liquid-like behavior is observed under electron doping. The bad-metal behavior seems a universal high-energy scale phenomenon, while the pseudogap behavior is based on lower energy scale physics that can be influenced by details of the band structure., Comment: 12 pages, 8 figures

When firms want to buy back their own shares, they have a choice between several alternatives. If they often carry out open market repurchase, they also increasingly rely on banks through complex buyback contracts involving option components, e.g. accelerated share repurchase contracts, VWAP-minus profit-sharing contracts, etc. The entanglement between the execution problem and the option hedging problem makes the management of these contracts a difficult task that should not boil down to simple Greek-based risk hedging, contrary to what happens with classical books of options. In this paper, we propose a machine learning method to optimally manage several types of buyback contract. In particular, we recover strategies similar to those obtained in the literature with partial differential equation and recombinant tree methods and show that our new method, which does not suffer from the curse of dimensionality, enables to address types of contract that could not be addressed with grid or tree methods.

A Mott insulator sometimes induces unconventional superconductivity in its neighbors when doped and/or pressurized. Because the phase diagram should be strongly related to the microscopic mechanism of the superconductivity, it is important to obtain the global phase diagram surrounding the Mott insulating state. However, the parameter available for controlling the ground state of most Mott insulating materials is one-dimensional owing to technical limitations. Here we present a two-dimensional ground-state mapping for a Mott insulator using an organic field-effect device by simultaneously tuning the bandwidth and bandfilling. The observed phase diagram showed many unexpected features such as an abrupt first-order superconducting transition under electron doping, a recurrent insulating phase in the heavily electron-doped region, and a nearly constant superconducting transition temperature in a wide parameter range. These results are expected to contribute toward elucidating one of the standard solutions for the Mott-Hubbard model. Theoretical calculations reproducing the main features of our experimental results have also been conducted., Comment: 34 pages, 11 figures

In most illiquid markets, there is no obvious proxy for the market price of an asset. The European corporate bond market is an archetypal example of such an illiquid market where mid-prices can only be estimated with a statistical model. In this OTC market, dealers / market makers only have access, indeed, to partial information about the market. In real time, they know the price associated with their trades on the dealer-to-dealer (D2D) and dealer-to-client (D2C) markets, they know the result of the requests for quotes (RFQ) they answered, and they have access to composite prices (e.g., Bloomberg CBBT). This paper presents a Bayesian method for estimating the mid-price of corporate bonds by using the real-time information available to a dealer. This method relies on recent ideas coming from the particle filtering / sequential Monte-Carlo literature.

This paper presents several models addressing optimal portfolio choice, optimal portfolio liquidation, and optimal portfolio transition issues, in which the expected returns of risky assets are unknown. Our approach is based on a coupling between Bayesian learning and dynamic programming techniques that leads to partial differential equations. It enables to recover the well-known results of Karatzas and Zhao in a framework \`a la Merton, but also to deal with cases where martingale methods are no longer available. In particular, we address optimal portfolio choice, portfolio liquidation, and portfolio transition problems in a framework \`a la Almgren-Chriss, and we build therefore a model in which the agent takes into account in his decision process both the liquidity of assets and the uncertainty with respect to their expected return.

Transition metal dichalcogenide (TMDC) monolayers have attracted much attention due to their strong light absorption and excellent electronic properties. These advantages make this type of two-dimensional crystal a promising one for optoelectronic device applications. In the case of photoelectric conversion devices such as photodetectors and photovoltaic cells, p-n junctions are one of the most important devices. Here, we demonstrate photodetection with WSe2 monolayer films. We prepare the electrolyte-gated ambipolar transistors and electrostatic p-n junctions are formed by the electrolyte-gating technique at 270 K. These p-n junctions are cooled down to fix the ion motion (and p-n junctions) and we observed the reasonable photocurrent spectra without the external bias, indicating the formation of p-n junctions. Very interestingly, two-terminal devices exhibit higher photoresponsivity than that of three-terminal ones, suggesting the formation of highly balanced anion and cation layers. The maximum photoresponsivity reaches 5 mA/W in resonance with the first excitonic peak. Our technique provides important evidence for optoelectronics in atomically thin crystals., Comment: Accepted in Applied Physics Letters (2016)

It is widely recognised that the effect of doping into a Mott insulator is complicated and unpredictable, as can be seen by examining the Hall coefficient in high $T_{\rm c}$ cuprates. The doping effect, including the electron-hole doping asymmetry, may be more straightforward in doped organic Mott insulators owing to their simple electronic structures. Here we investigate the doping asymmetry of an organic Mott insulator by carrying out electric-double-layer transistor measurements and using cluster perturbation theory. The calculations predict that strongly anisotropic suppression of the spectral weight results in the Fermi arc state under hole doping, while a relatively uniform spectral weight results in the emergence of a non-interacting-like Fermi surface in the electron-doped state. In accordance with the calculations, the experimentally observed Hall coefficients and resistivity anisotropy correspond to the pocket formed by the Fermi arcs under hole doping and to the non-interacting Fermi surface under electron doping., Comment: 40 pages with 17 figures, accepted for publication in Nature Communications

For the last two decades, most financial markets have undergone an evolution toward electronification. The market for corporate bonds is one of the last major financial markets to follow this unavoidable path. Traditionally quote-driven i.e., dealer-driven) rather than order-driven, the market for corporate bonds is still mainly dominated by voice trading, but a lot of electronic platforms have emerged. These electronic platforms make it possible for buy-side agents to simultaneously request several dealers for quotes, or even directly trade with other buy-siders. The research presented in this article is based on a large proprietary database of requests for quotes (RFQ) sent, through the multi-dealer-to-client (MD2C) platform operated by Bloomberg Fixed Income Trading, to one of the major liquidity providers in European corporate bonds. Our goal is (i) to model the RFQ process on these platforms and the resulting competition between dealers, and (ii) to use our model in order to implicit from the RFQ database the behavior of both dealers and clients on MD2C platforms.

In spite of the growing consideration for optimal execution in the financial mathematics literature, numerical approximations of optimal trading curves are almost never discussed. In this article, we present a numerical method to approximate the optimal strategy of a trader willing to unwind a large portfolio. The method we propose is very general as it can be applied to multi-asset portfolios with any form of execution costs, including a bid-ask spread component, even when participation constraints are imposed. Our method, based on convex duality, only requires Hamiltonian functions to have $C^{1,1}$ regularity while classical methods require additional regularity and cannot be applied to all cases found in practice.

Charge transport in MoS2 in the low carrier density regime is dominated by trap states and band edge disorder. The intrinsic transport properties of MoS2 emerge in the high density regime where conduction occurs via extended states. Here, we investigate the transport properties of mechanically exfoliated mono-, bi-, and trilayer MoS2 sheets over a wide range of carrier densities realized by a combination of ion gel top gate and SiO2 back gate which allows us to achieve high charge carrier (>10^13) density. We discuss the gating properties of the devices as a function of layer thickness and demonstrate resistivities of as low as 1 k{\Omega} for monolayer and 420{\Omega} for bilayer devices at 10 K. We show that from the capacitive coupling of the two gates, quantum capacitance can be roughly estimated to be on the order of 1 {\mu}F/cm^2 for all devices studied. Temperature dependence of the carrier mobility in the high density regime indicates that short-range scatterers limit charge transport at low temperatures., Comment: 25 pages

In this article, we consider the optimal execution problem associated to accelerated share repurchase contracts. When firms want to repurchase their own shares, they often enter such a contract with a bank. The bank buys the shares for the firm and is paid the average market price over the execution period, the length of the period being decided upon by the bank during the buying process. Mathematically, the problem is new and related to both option pricing (Asian and Bermudan options) and optimal execution. We provide a model, along with associated numerical methods, to determine the optimal stopping time and the optimal buying strategy of the bank.

This article considers the pricing and hedging of a call option when liquidity matters, that is, either for a large nominal or for an illiquid underlying asset. In practice, as opposed to the classical assumptions of a price-taking agent in a frictionless market, traders cannot be perfectly hedged because of execution costs and market impact. They indeed face a trade-off between hedging errors and costs that can be solved by using stochastic optimal control. Our modelling framework, which is inspired by the recent literature on optimal execution, makes it possible to account for both execution costs and the lasting market impact of trades. Prices are obtained through the indifference pricing approach. Numerical examples are provided, along with comparisons to standard methods.

The monolayer transition metal dichalcogenides have recently attracted much attention owing to their potential in valleytronics, flexible and low-power electronics and optoelectronic devices. Recent reports have demonstrated the growth of large-size 2-dimensional MoS2 layers by the sulfurization of molybdenum oxides. However, the growth of transition metal selenide monolayer has still been a challenge. Here we report that the introduction of hydrogen in the reaction chamber helps to activate the selenization of WO3, where large-size WSe2 monolayer flakes or thin films can be successfully grown., Comment: 1 page, 3 figures