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This paper focuses on the pricing of the variance swap in an incomplete market where the stochastic interest rate and the price of the stock are respectively driven by Cox-Ingersoll-Ross model and Heston model with simultaneous L\'{e}vy…

Pricing of Securities · Quantitative Finance 2018-03-15 Ben-zhang Yang , Jia Yue , Nan-jing Huang

Unsupervised structure learning in high-dimensional time series data has attracted a lot of research interests. For example, segmenting and labelling high dimensional time series can be helpful in behavior understanding and medical…

Machine Learning · Computer Science 2017-05-25 Hao Liu , Haoli Bai , Lirong He , Zenglin Xu

Communication is now a standard tool in the central bank's monetary policy toolkit. Theoretically, communication provides the central bank an opportunity to guide public expectations, and it has been shown empirically that central bank…

General Economics · Economics 2018-09-26 Ancil Crayton

We develop a multi-curve term structure setup in which the modelling ingredients are expressed by rational functionals of Markov processes. We calibrate to LIBOR swaptions data and show that a rational two-factor lognormal multi-curve model…

Mathematical Finance · Quantitative Finance 2015-02-27 Stephane Crepey , Andrea Macrina , Tuyet Mai Nguyen , David Skovmand

The study of stochastic variational principles involves the problem of constructing fixed-endpoint and adapted variations of semimartingales. We provide a detailed construction of variations of semimartingales that are not only fixed at…

Mathematical Physics · Physics 2025-09-11 Archishman Saha

Market-based coordination of demand side assets has gained great interests in recent years. In spite of its efficiency, there is a risk that the interaction between the dynamic assets through the price signal could result in an unstable…

Optimization and Control · Mathematics 2017-04-04 Lin Zhao , Wei Zhang

This paper introduces one new multivariate volatility model that can accommodate an appropriately defined network structure based on low-frequency and high-frequency data. The model reduces the number of unknown parameters and the…

Statistical Finance · Quantitative Finance 2022-04-28 Huiling Yuan , Guodong Li , Junhui Wang

This paper presents an axiomatic scheme for interest rate models in discrete time. We take a pricing kernel approach, which builds in the arbitrage-free property and provides a link to equilibrium economics. We require that the pricing…

Pricing of Securities · Quantitative Finance 2009-11-05 Lane P. Hughston , Andrea Macrina

The paper tests the validity of the critique of the fiscal theory of the price level. A stochastic general equilibrium model with continuous time is constructed. An active fiscal policy and a passive monetary policy have been set. Monetary…

Theoretical Economics · Economics 2024-03-05 Andrey Kofnov

One of the most enticing research areas is the stock market, and projecting stock prices may help investors profit by making the best decisions at the correct time. Deep learning strategies have emerged as a critical technique in the field…

Artificial Intelligence · Computer Science 2024-07-26 Karan Pardeshi , Sukhpal Singh Gill , Ahmed M. Abdelmoniem

This chapter covers methodological issues related to estimation, testing and computation for models involving structural changes. Our aim is to review developments as they relate to econometric applications based on linear models.…

Econometrics · Economics 2018-05-11 Alessandro Casini , Pierre Perron

In this work we introduce Heath-Jarrow-Morton (HJM) interest rate models driven by fractional Brownian motions. By using support arguments we prove that the resulting model is arbitrage free under proportional transaction costs in the same…

Pricing of Securities · Quantitative Finance 2009-09-09 Alberto Ohashi

A new test of a wide class of interest rate models is proposed and applied to a recently developed quantum field theoretic model and the industry standard Heath-Jarrow-Morton model. This test is independent of the volatility function unlike…

Statistical Mechanics · Physics 2008-12-02 Belal E. Baaquie , Srikant Marakani

We consider a financial market in discrete time and study pricing and hedging conditional on the information available up to an arbitrary point in time. In this conditional framework, we determine the structure of arbitrage-free prices.…

Mathematical Finance · Quantitative Finance 2023-05-15 Lars Niemann , Thorsten Schmidt

Working on the daily closing prices and logreturns, in this paper we deal with the use of Hidden Markov Models (HMMs) to forecast the price of the EUR/USD Futures. The aim of our work is to understand how the HMMs describe different…

Machine Learning · Statistics 2016-05-09 Sara Rebagliati , Emanuela Sasso , Samuele Soraggi

In this paper, we consider the problem of pricing discretely-sampled variance swaps based on a hybrid model of stochastic volatility and stochastic interest rate with regime-switching. Our modelling framework extends the Heston stochastic…

Mathematical Finance · Quantitative Finance 2016-03-29 Jiling Cao , Teh Raihana Nazirah Roslan , Wenjun Zhang

The classical approach in finance attempts to model the term structure of interest rates using specified stochastic processes and the no arbitrage argument. Up to now, no universally accepted theory has been obtained for the description of…

Condensed Matter · Physics 2009-10-31 Jean Nuyts , Isabelle Platten

Trend and Value are pervasive anomalies, common to all financial markets. We address the problem of their co-existence and interaction within the framework of Heterogeneous Agent Based Models (HABM). More specifically, we extend the…

Statistical Finance · Quantitative Finance 2018-08-01 Adam Majewski , Stefano Ciliberti , Jean-Philippe Bouchaud

The emergence of a variety of graph-based meaning representations (MRs) has sparked an important conversation about how to adequately represent semantic structure. These MRs exhibit structural differences that reflect different theoretical…

Computation and Language · Computer Science 2020-05-01 Lucia Donatelli , Jonas Groschwitz , Alexander Koller , Matthias Lindemann , Pia Weißenhorn

Representations of sequential data are commonly based on the assumption that observed sequences are realizations of an unknown underlying stochastic process, where the learning problem includes determination of the model parameters. In this…

Machine Learning · Statistics 2019-09-17 Ronny Hug , Wolfgang Hübner , Michael Arens