Option Pricing and Dynamic Discrete Time Hedging for Regime-Switching Geometric Random Walks Models

2010 ◽  
Author(s):  
Bruno Remillard ◽  
Alexandre Hocquard ◽  
Nicolas A. Papageorgiou
Keyword(s):  
Option Pricing ◽  
Random Walks ◽  
Discrete Time ◽  
Regime Switching ◽  
Discrete Time Hedging

scholarly journals Option Pricing and Hedging for Discrete Time Regime-Switching Models

2017 ◽  
Vol 08 (08) ◽  
pp. 1005-1032 ◽  
Author(s):  
Bruno Rémillard ◽  
Alexandre Hocquard ◽  
Hugo Lamarre ◽  
Nicolas Papageorgiou
Keyword(s):  
Option Pricing ◽  
Discrete Time ◽  
Regime Switching ◽  
Regime Switching Models ◽  
Switching Models ◽  
Time Regime

scholarly journals Option Pricing Under Regime-Switching Models: Novel Approaches Removing Path-Dependence

2017 ◽  
Author(s):  
Frrddric Godin ◽  
Van Son Lai ◽  
Denis-Alexandre Trottier
Keyword(s):  
Option Pricing ◽  
Regime Switching ◽  
Path Dependence ◽  
Regime Switching Models ◽  
Switching Models ◽  
Novel Approaches

scholarly journals Discrete Time Multi-State Model with Regime Switching for Modelling COVID-19 Disease Progression and Clinical Outcomes

2021 ◽  
pp. 1-31 ◽  
Author(s):  
Sujatro Chakladar ◽  
Ran Liao ◽  
Will Landau ◽  
Margaret Gamalo ◽  
Yanping Wang
Keyword(s):  
Disease Progression ◽  
Clinical Outcomes ◽  
Discrete Time ◽  
Regime Switching ◽  
State Model

ROBUST STABILITY, STABILISATION AND H-INFINITY CONTROL FOR PREMIUM-RESERVE MODELS IN A MARKOVIAN REGIME SWITCHING DISCRETE-TIME FRAMEWORK

2016 ◽  
Vol 46 (3) ◽  
pp. 747-778 ◽  
Author(s):  
Lin Yang ◽  
Athanasios A. Pantelous ◽  
Hirbod Assa
Keyword(s):  
Discrete Time ◽  
Regime Switching ◽  
Structural Changes ◽  
Linear Matrix ◽  
H Infinity Control ◽  
R Process ◽  
The Stability ◽  
Markovian Regime Switching ◽  
Markovian Regime

AbstractThe premium pricing process and the medium- and long-term stability of the reserve policy under conditions of uncertainty present very challenging issues in relation to the insurance world. Over the last two decades, applications of Markovian regime switching models to finance and macroeconomics have received strong attention from researchers, and particularly market practitioners. However, relatively little research has so far been carried out in relation to insurance. This paper attempts to consider how a linear Markovian regime switching system in discrete-time could be applied to model the medium- and long-term reserves and the premiums (abbreviated here as the P-R process) for an insurer. Some recently developed techniques from linear robust control theory are applied to explore the stability, stabilisation and robust H∞-control of a P-R system, and the potential effects of abrupt structural changes in the economic fundamentals, as well as the insurer's strategy over a finite time period. Sufficient linear matrix inequality conditions are derived for solving the proposed sub-problems. Finally, a numerical example is presented to illustrate the applicability of the theoretical results.

Value-at-Risk and Expected Shortfall approaches for option premiums and the probability of default estimation based on ARMA models

2021 ◽  
Vol 57 (3) ◽  
pp. 126
Author(s):  
Nikolai Berzon
Keyword(s):  
Time Series ◽  
Option Pricing ◽  
Discrete Time ◽  
Value At Risk ◽  
Probability Of Default ◽  
Pricing Models ◽  
Arma Process ◽  
Underlying Asset ◽  
Black Scholes

The need to address the issue of risk management has given rise to a number of models for estimation the probability of default, as well as a special tool that allows to sell credit risk – a credit default swap (CDS). From the moment it appeared in 1994 until the crisis of 2008, that the CDS market was actively growing, and then sharply contracted. Currently, there is practically no CDS market in emerging economies (including Russia). This article is to improve the existing CDS valuation models by using discrete-time models that allow for more accurate assessment and forecasting of the selected asset dynamics, as well as new option pricing models that take into account the degree of risk acceptance by the option seller. This article is devoted to parametric discrete-time option pricing models that provide more accurate results than the traditional Black-Scholes continuous-time model. Improvement in the quality of assessment is achieved due to three factors: a more detailed consideration of the properties of the time series of the underlying asset (in particular, autocorrelation and heavy tails), the choice of the optimal number of parameters and the use of Value-at-Risk approach. As a result of the study, expressions were obtained for the premiums of European put and call options for a given level of risk under the assumption that the return on the underlying asset follows a stationary ARMA process with normal or Student's errors, as well as an expression for the credit spread under similar assumptions. The simplicity of the ARMA process underlying the model is a compromise between the complexity of model calibration and the quality of describing the dynamics of assets in the stock market. This approach allows to take into account both discreteness in asset pricing and take into account the current structure and the presence of interconnections for the time series of the asset under consideration (as opposed to the Black–Scholes model), which potentially allows better portfolio management in the stock market.

A RECOMBINING TREE METHOD FOR OPTION PRICING WITH STATE-DEPENDENT SWITCHING RATES

2016 ◽  
Vol 19 (02) ◽  
pp. 1650012 ◽  
Author(s):  
J. X. JIANG ◽  
R. H. LIU ◽  
D. NGUYEN
Keyword(s):  
Option Pricing ◽  
Regime Switching ◽  
Asset Price ◽  
Numerical Results ◽  
Price Process ◽  
State Dependent ◽  
Switching Models ◽  
Markovian Regime Switching ◽  
Tree Method ◽  
Markovian Regime

This paper develops simple and efficient tree approaches for option pricing in switching jump diffusion models where the rates of switching are assumed to depend on the underlying asset price process. The models generalize many existing models in the literature and in particular, the Markovian regime-switching models with jumps. The proposed trees grow linearly as the number of tree steps increases. Conditions on the choices of key parameters for the tree design are provided that guarantee the positivity of branch probabilities. Numerical results are provided and compared with results reported in the literature for the Markovian regime-switching cases. The reported numerical results for the state-dependent switching models are new and can be used for comparison in the future.

scholarly journals Discrete-Time Option Pricing with Stochastic Liquidity

2016 ◽  
Author(s):  
Markus Leippold ◽  
Steven Schaerer
Keyword(s):  
Option Pricing ◽  
Discrete Time

scholarly journals On a Markov chain approximation method for option pricing with regime switching

2015 ◽  
Vol 12 (2) ◽  
pp. 529-541
Author(s):  
Rongming Wang ◽  
Tak Kuen Siu ◽  
Yang Shen ◽  
Kun Fan
Keyword(s):  
Markov Chain ◽  
Option Pricing ◽  
Approximation Method ◽  
Regime Switching ◽  
Markov Chain Approximation ◽  
Chain Approximation
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