An iterated Azéma-Yor type embedding for finitely many marginals by Obloj, J, Spoida, P

“…We are motivated, as was the case for several earlier works in the field, by questions arising in mathematical finance which we highlight below.…”

Signatures in machine learning and finance by Perez Arribas, I

“…<p>Developed to give meaning to differential equations driven by rough signals, rough path theory has opened in recent years a new approach to tackle certain problems in other fields such as mathematical finance and machine learning. This is due to certain algebraic and analytical properties of an object called the <em>rough path signature</em>. …”

On robust pricing--hedging duality in continuous time by Hou, Z, Obloj, J

“…We pursue robust approach to pricing and hedging in mathematical finance. We consider a continuous time setting in which some underlying assets and options, with continuous paths, are available for dynamic trading and a further set of European options, possibly with varying maturities, is available for static trading. …”

Probability, random processes, and statistical analysis / by 335324 Kobayashi, Hisashi, Mark, Brian L. (Brian Lai-bue), 1969-, Turin, William

Adaptive Data Selection-Based Machine Learning Algorithm for Prediction of Component Obsolescence by Kyoung-Sook Moon, Hee Won Lee, Hongjoong Kim

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An Efficient Localized RBF-FD Method to Simulate the Heston–Hull–White PDE in Finance by Tao Liu, Malik Zaka Ullah, Stanford Shateyi, Chao Liu, Yanxiong Yang

“…The Heston–Hull–White three-dimensional time-dependent partial differential equation (PDE) is one of the important models in mathematical finance, at which not only the volatility is modeled based on a stochastic process but also the rate of interest is assumed to follow a stochastic dynamic. …”
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Effect of Stop-Loss Reinsurance on Primary Insurer Solvency by Corina Constantinescu, Alexandra Dias, Bo Li, David Šiška, Simon Wang

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Robust pricing–hedging dualities in continuous time by Hou, Z, Obłój, J

“…We pursue a robust approach to pricing and hedging in mathematical finance. We consider a continuous-time setting in which some underlying assets and options, with continuous price paths, are available for dynamic trading and a further set of European options, possibly with varying maturities, is available for static trading. …”

Stochastic Volatility: Selected Readings

“…Collects sixteen of the main papers that have influenced the econometrics of stochastic volatility, which is associated with financial economics and mathematical finance. Papers discuss a subordinated stochastic process model with finite variance for speculative prices; a study of daily sugar prices, 1961-79; the behavior of random variables with nonstationary variance and the distribution of security prices; the pricing of options on assets with stochastic volatilities; the dynamics of exchange rate volatility; multivariate stochastic variance models; stochastic autoregressive volatility; long memory in continuous-time stochastic volatility models; Bayesian analysis of stochastic volatility models; stochastic volatility, likelihood inference, and a comparison with ARCH models; estimation of stochastic volatility models with diagnostics; pricing foreign currency options with stochastic volatility; a closed-form solution for options with stochastic volatility, with applications to bond and currency options; a unified approach to the joint estimation of objective and risk neutral measures for the purpose of options valuation; the distribution of realized exchange rate volatility; and econometric analysis of realized volatility and its use in estimating stochastic volatility models. …”

Robust trading of implied skew by Nadtochiy, S, Obloj, J

“…Rogers (2001) Robust hedging of barrier options, Mathematical Finance 11 (3), 285–314.], which exploits the given beliefs on the implied skew. …”

Geometry and Spectral Theory Applied to Credit Bubbles in Arbitrage Markets: The Geometric Arbitrage Approach to Credit Risk by Simone Farinelli, Hideyuki Takada

“…We apply Geometric Arbitrage Theory (GAT) to obtain results in mathematical finance for credit markets, which do not need stochastic differential geometry in their formulation. …”
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Classifying a Lending Portfolio of Loans with Dynamic Updates via a Machine Learning Technique by Fazlollah Soleymani, Houman Masnavi, Stanford Shateyi

“…In this work, an application of machine learning approach in mathematical finance and banking is discussed. It is shown how we can classify some lending portfolios of banks under several features such as rating categories and various maturities. …”
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Nonlinear differential equations based on the B-S-M model in the pricing of derivatives in financial markets by Tao Limin, Xu Liping, Sulaimani Hani Jamal

“…The pricing and hedging of financial derivatives have become one of the hot research issues in mathematical finance today. In the case of non-risk neutrality, this article uses the martingale method and probability measurement method to study the pricing method and hedging strategy of financial derivatives. …”
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Empirically Effective Bond Pricing Model and Analysis on Term Structures of Implied Interest Rates in Financial Crisis by Kariya, T, Wang, J, Wang, Z, Doi, E, Yamamura, Y

“…In this paper we first clarify the theoretical relation between our stochastic discount function approach and the spot rate or forward rate approach in mathematical finance. Then we make a comprehensive empirical study on the capacity of the model in view of its pricing capability for individual GBs with different attributes and in view of its capacity of describing the movements of term structures of interest rates that JGBs imply as yield curves. …”

Fully Polynomial Time Approximation Schemes for Stochastic Dynamic Programs by Halman, Nir, Klabjan, Diego, Li, Chung-Lun, Orlin, James B, Simchi-Levi, David

“…Using our framework, we provide the first FPTASs for several NP-hard problems in various fields of research such as knapsack models, logistics, operations management, economics, and mathematical finance. Extensions of our framework via the use of the newly established computational rules are also discussed.…”
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Deep splitting method for parabolic PDEs by Beck, Christian, Becker, Sebastian, Cheridito, Patrick, Jentzen, Arnulf, Neufeld, Ariel

“…We test the method on different examples from physics, stochastic control and mathematical finance. In all cases, it yields very good results in up to 10,000 dimensions with short run times.…”
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High dimensional American options by Firth, N

“…Pricing single asset American options is a hard problem in mathematical finance. There are no closed form solutions available (apart from in the case of the perpetual option), so many approximations and numerical techniques have been developed. …”

A Spectral Method Approach to Quadratic Normal Volatility Diffusions by Peter Kink

“…This paper is concerned with the quadratic volatility family of driftless stochastic differential equations (SDEs), also known in the literature as Quadratic Normal Volatility models (QNV), which have found applications primarily in mathematical finance, but can also model dynamics of stochastic processes in other fields such as mathematical biology and physics. …”
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Digital Finance in the Context of Common Wealth Helps Regional Economic Development of High Quality by Zhang Chenjing, Mao Di, Ma Fenfen

“…Secondly, spatial panel information originate 30 all regions in China are used to study the coordinated action condition among mathematical finance and the progress with quality as the main goal regional financial condition using the spatial face-plate pattern. …”
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Modelling of multiple constraints portfolio optimization using modified particle swarm optimization by Zaheer, Kashif

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