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Shuzhen Yang

Publications and source records attributed to Shuzhen Yang.

At least 37 records · Page 2Linked to original sources
arXiv2021

Distributional uncertainty of the financial time series measured by G-expectation

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

q-fin.MF↗
arXiv2020

Discrete time multi-period mean-variance model: Bellman type strategy and Empirical analysis

In this paper, we attempt to introduce the Bellman principle for a discrete time multi-period mean-variance model. Based on this new take on the Bellman principle, we obtain a dynamic time-consistent optimal strategy and related efficient frontier. Furthermore, we develop a varying investment period discrete time multi-period mean-variance model and obtain a related dynamic optimal strategy and an optimal investment period. This paper compares the highlighted dynamic optimal strategies of this study with the 1/n equality strategy, and shows that we can secure a higher return with a smaller risk based on the dynamic optimal strategies.

q-fin.MF↗
arXiv2020

Bellman type strategy for the continuous time mean-variance model

To investigate a time-consistent optimal strategy for the continuous time mean-variance model, we develop a new method to establish the Bellman principle. Based on this new method, we obtain a time-consistent dynamic optimal strategy that differs from the pre-committed and game-theoretic strategies. A comparison with the existing results on the continuous time mean-variance model shows that our method has several advantages. The explicit solutions of the dynamic optimal strategy and optimal wealth are given. When the dynamic optimal strategy is given at the initial time, we do not change it in the following investment time interval.

q-fin.PM↗
arXiv2020

A varying terminal time structure for stochastic optimal control under constrained condition

In this study, we propose a varying terminal time structure for the optimal control problem under state constraints, in which the terminal time follows the varying of the control via the constrained condition. Focusing on this new optimal control problem, we investigate a novel stochastic maximum principle, which differs from the traditional optimal control problem under state constraints. The optimal pair of the optimal control model can be verified via this new stochastic maximum principle.

math.OC↗
arXiv2020

Improving Value-at-Risk prediction under model uncertainty

Several well-established benchmark predictors exist for Value-at-Risk (VaR), a major instrument for financial risk management. Hybrid methods combining AR-GARCH filtering with skewed-$t$ residuals and the extreme value theory-based approach are particularly recommended. This study introduces yet another VaR predictor, G-VaR, which follows a novel methodology. Inspired by the recent mathematical theory of sublinear expectation, G-VaR is built upon the concept of model uncertainty, which in the present case signifies that the inherent volatility of financial returns cannot be characterized by a single distribution but rather by infinitely many statistical distributions. By considering the worst scenario among these potential distributions, the G-VaR predictor is precisely identified. Extensive experiments on both the NASDAQ Composite Index and S\&P500 Index demonstrate the excellent performance of the G-VaR predictor, which is superior to most existing benchmark VaR predictors.

q-fin.RM↗
arXiv2020

A varying terminal time mean-variance model

To improve the efficient frontier of the classical mean-variance model in continuous time, we propose a varying terminal time mean-variance model with a constraint on the mean value of the portfolio asset, which moves with the varying terminal time. Using the embedding technique from stochastic optimal control in continuous time and varying the terminal time, we determine an optimal strategy and related deterministic terminal time for the model. Our results suggest that doing so for an investment plan requires minimizing the variance with a varying terminal time.

math.OC↗
arXiv2019

Multi-time state mean-variance model in continuous time

In the continuous time mean-variance model, we want to minimize the variance (risk) of the investment portfolio with a given mean at terminal time. However, the investor can stop the investment plan at any time before the terminal time. To solve this kind of problem, we consider to minimize the variances of the investment portfolio at multi-time state. The advantage of this multi-time state mean-variance model is that we can minimize the risk of the investment portfolio along the investment period. To obtain the optimal strategy of the multi-time state mean-variance model, we introduce a sequence of Riccati equations which are connected by a jump boundary condition. Based on this sequence Riccati equations, we establish the relationship between the means and variances of this multi-time state mean-variance model. Furthermore, we use an example to verify that minimizing the variances of the multi-time state can affect the average of Maximum-Drawdown of the investment portfolio.

q-fin.MF↗
arXiv2018

The connection between discrete and continuous state constraints optimal control systems: the deterministic case

An optimal control problem driven by an ordinary differential equation under continuous state constraints is considered in this study. From an operational point of view, we introduce a discrete state constraints optimal control problem and prove that this discrete state constraints optimal control problem is a near-optimal control problem of the original problem. Furthermore, we show that the optimal solution of the near-optimal control problem converges to the optimal solution of the original one. Finally, we use a linear quadratic optimal problem to verify the main results of this study.

math.OC↗
arXiv2018

A protonated brownmillerite electrolyte for superior low-temperature proton conductivity

Design novel solid oxide electrolyte with enhanced ionic conductivity forms one of the Holy Grails in the field of materials science due to its great potential for wide range of energy applications. Conventional solid oxide electrolyte typically requires elevated temperature to activate the ionic transportation, while it has been increasing research interests to reduce the operating temperature due to the associated scientific and technological importance. Here, we report a conceptually new solid oxide electrolyte, HSrCoO2.5, which shows an exceptional enhanced proton conductivity at low temperature region (from room temperature to 140 oC). Combining both the experimental results and corresponding first-principles calculations, we attribute these intriguing properties to the extremely-high proton concentration as well as the well-ordered oxygen vacancy channels inherited from the novel crystalline structure of HSrCoO2.5. This result provides a new strategy to design novel solid oxide electrolyte with excellent proton conductivity for wide ranges of energy-related applications.

cond-mat.mtrl-sci↗
arXiv2018

The Pontryagin's maximum principle for stochastic differential systems under state constraints

In this study, we consider an optimal control problem driven by a stochastic differential equation with state constraints. Here, the state constraints mean the constraints about the path of state. In order to show the maximum principe for the optimal control problem under state constraints, we investigate a new near optimal control problem. In the following, we establish the stochastic maximum principle for the new optimal control problem under multi-time state constraints. In the end, we give a production planning example to verify the main results of this study.

math.OC↗
arXiv2017

On an Optimal Extraction Problem with Regime Switching

This paper studies a finite-fuel two-dimensional degenerate singular stochastic control problem under regime switching that is motivated by the optimal irreversible extraction problem of an exhaustible commodity. A company extracts a natural resource from a reserve with finite capacity, and sells it in the market at a spot price that evolves according to a Brownian motion with volatility modulated by a two-state Markov chain. In this setting, the company aims at finding the extraction rule that maximizes its expected discounted cash flow, net of the costs of extraction and maintenance of the reserve. We provide expressions both for the value function and for the optimal control. On the one hand, if the running cost for the maintenance of the reserve is a convex function of the reserve level, the optimal extraction rule prescribes a Skorokhod reflection of the (optimally) controlled state process at a certain state and price dependent threshold. On the other hand, in presence of a concave running cost function it is optimal to instantaneously deplete the reserve at the time at which the commodity's price exceeds an endogenously determined critical level. In both cases, the threshold triggering the optimal control is given in terms of the optimal stopping boundary of an auxiliary family of perpetual optimal selling problems with regime switching.

math.OC↗
arXiv2017

High quality atomically thin PtSe2 films grown by molecular beam epitaxy

Atomically thin PtSe2 films have attracted extensive research interests for potential applications in high-speed electronics, spintronics and photodetectors. Obtaining high quality, single crystalline thin films with large size is critical. Here we report the first successful layer-by-layer growth of high quality PtSe2 films by molecular beam epitaxy. Atomically thin films from 1 ML to 22 ML have been grown and characterized by low-energy electron diffraction, Raman spectroscopy and X-ray photoemission spectroscopy. Moreover, a systematic thickness dependent study of the electronic structure is revealed by angle-resolved photoemission spectroscopy (ARPES), and helical spin texture is revealed by spin-ARPES. Our work provides new opportunities for growing large size single crystalline films for investigating the physical properties and potential applications of PtSe2.

cond-mat.mtrl-sci↗
arXiv2016

The necessary and sufficient conditions for stochastic differential systems with multi-time states cost functional

From economics point of view, we investigate a new optimal control problem driven by a stochastic differential equation with a multi-time states cost functional. By constructing a series of first-order adjoint equations, we establish the stochastic maximum principle and sufficient optimality conditions for this new optimal control problem. A constraints problem also be studied. In the end, we develop a near optimal control problem for a general cost functional.

math.OC↗
arXiv2016

Multidimensional viscosity solutions theory of semi-linear partial differential equations

In this study, we concern the multidimensional viscosity solutions theory of a kind of semi-linear partial differential equations (PDEs). A new definition of viscosity solution for this multidimensional semi-linear PDEs which is related to a type of multidimensional backward stochastic differential equations (BSDEs) is given. Further more, we establish the existence and uniqueness results for the viscosity solution of this semi-linear PDEs via the comparison theorem of the related BSDEs and a smooth approximation technique.

math.DS↗
arXiv2015

Monolayer charge-neutral graphene on platinum with extremely weak electron-phonon coupling

Epitaxial growth of graphene on transition metal substrates is an important route for obtaining large scale graphene. However, the interaction between graphene and the substrate often leads to multiple orientations, distorted graphene band structure, large doping and strong electron-phonon coupling. Here we report the growth of monolayer graphene with high crystalline quality on Pt(111) substrate by using a very low concentration of an internal carbon source with high annealing temperature. The controlled growth leads to electronically decoupled graphene: it is nearly charge neutral and has extremely weak electron-phonon coupling (coupling strength $λ$ $\approx$ 0.056) as revealed by angle-resolved photoemission spectroscopic measurements. The thermodynamics and kinetics of the carbon diffusion process is investigated by DFT calculation. Such graphene with negligible graphene-substrate interaction provides an important platform for fundamental research as well as device applications when combined with a nondestructive sample transfer technique.

cond-mat.mtrl-sci↗
arXiv2013

The Numerical Properties of G-heat equation and Related Application

In this paper, we consider the numerical convergence of G-heat equation which was first introduced by Peng. The G-heat equation extends the classical heat equation with uncertain volatility. For G-heat equation is nonlinear partial differential equation(PDE), we prove that the Newton iteration is convergence and the fully implicit discretization is monotone and stable. Then, we have the fully implicit discretization convergence to the viscosity solution of a G-heat equation.

math.NA↗
arXiv2013

Solutions for Functional Fully Coupled Forward-Backward Stochastic Differential Equations

In this paper, we study a functional fully coupled forward-backward stochastic differential equations (FBSDEs). Under a new type of integral Lipschitz and monotonicity conditions, the existence and uniqueness of solutions for functional fully coupled FBSDEs is proved. We also investigate the relationship between the solution of functional fully coupled FBSDE and the classical solution of the path-dependent partial differential equation (P-PDE). When the solution of the P-PDE has some smooth and regular properties, we solve the related functional fully coupled FBSDE and prove the P-PDE has a unique solution.

math.PR↗