scholarly journals Simulation of COVID-19 epidemic spread using Stochastic Differential Equations with Jump diffusion for SIR Model

2021 ◽  
Author(s):  
Zaineb El kharrazi ◽  
Sahar Saoud
Keyword(s):  
Differential Equations ◽  
Stochastic Differential Equations ◽  
Jump Diffusion ◽  
Sir Model ◽  
Epidemic Spread

AN ERGODIC BSDE RISK REPRESENTATION IN A JUMP-DIFFUSION FRAMEWORK

2021 ◽  
pp. 2150015
Author(s):  
CALISTO GUAMBE ◽  
LESEDI MABITSELA ◽  
RODWELL KUFAKUNESU
Keyword(s):  
Differential Equations ◽  
Stochastic Differential Equations ◽  
Risk Measures ◽  
Risk Measure ◽  
Jump Diffusion ◽  
Backward Stochastic Differential Equations ◽  
Financial Position ◽  
Entropic Risk Measure ◽  
Risk Representation

We consider the representation of forward entropic risk measures using the theory of ergodic backward stochastic differential equations in a jump-diffusion framework. Our paper can be viewed as an extension of the work considered by Chong et al. (2019) in the diffusion case. We also study the behavior of a forward entropic risk measure under jumps when a financial position is held for a longer maturity.

Forecasting dirty tanker freight rate index by using stochastic differential equations

2018 ◽  
Vol 05 (04) ◽  
pp. 1850034 ◽  
Author(s):  
Hossein Jafari ◽  
Ghazaleh Rahimi
Keyword(s):  
Time Series ◽  
Differential Equations ◽  
Stochastic Model ◽  
Stochastic Differential Equations ◽  
Simulated Data ◽  
Jump Diffusion ◽  
Freight Rate ◽  
Time Series Models ◽  
Modeling And Forecasting

The accurate forecasting of freight rate index is one of the most important issues in shipping market. The continuous and jump-diffusion stochastic differential equations are used for modeling and forecasting of Baltic exchange Dirty Tanker Index (BDTI). Actual observations and simulated data are applied to estimate the best stochastic model. The comparison of forecasting between SDE methods and the ARIMA time series models show that SDE models have better accuracy than the time series techniques.

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