Stochastic & Finance

2015 ◽  
Author(s):  
Rossano Giandomenico
Keyword(s):  
Stochastic Finance

Stochastic Finance of a Company Associated with Ruin, Restricted Reserve, Dividends and Dividend Strategy

2016 ◽  
Vol 17 (2) ◽  
pp. 125-144
Author(s):  
P. R. Vittal ◽  
V. Thangaraj ◽  
S. Najeema
Keyword(s):  
A Company ◽  
Stochastic Finance

scholarly journals Boundary Conditions of Options: A Demonstration Based on the Stochastic Discount

2017 ◽  
Vol 8 (1) ◽  
pp. 46-57
Author(s):  
Salvador Cruz Rambaud ◽  
Ana María Sánchez Pérez
Keyword(s):  
Boundary Conditions ◽  
Point Of View ◽  
Financial Mathematics ◽  
Discount Function ◽  
Risk Hedging ◽  
Financial Options ◽  
Derivative Instruments ◽  
Principal Contribution ◽  
Natural Way ◽  
Stochastic Finance

Abstract The aim of this paper is to provide a proof of the generally accepted boundary conditions of (call and put) financial options from a novel point of view. To do this, we will use an auxiliary discounting function which will be defined in this work. However, the financial options are derivative instruments whose function is risk hedging in contexts of uncertainty, whereby the employed discount function will be necessarily stochastic. More specifically, we will apply the classic properties of the magnitude “discount” to the so-defined discount function to obtain, in a natural way, the noteworthy boundary conditions of financial options. It is well-known that financial options (belonging to the field of stochastic finance) have been studied without any relation with the magnitude “discount” (more characteristic of the classic Financial Mathematics). Consequently, the principal contribution of this work is the construction of a stochastic discount function as a bridge connecting its associated discount and the financial options, being demonstrated that their properties can be mutually derived.

scholarly journals Escape Velocity backed Avalanche Predictor- Neural Evidence from Nifty

2019 ◽  
Vol 8 (4) ◽  
pp. 486-490
Keyword(s):  
Neural Networks ◽  
Capital Market ◽  
Extreme Event ◽  
Research Work ◽  
Daily Basis ◽  
Regression Splines ◽  
Escape Velocity ◽  
Adaptive Regression ◽  
Adaptive Regression Splines ◽  
Stochastic Finance

The concept of escape velocity has been extended from physics to stochastic finance and used as an avalanche predictor. Escape velocity being an extreme event serves as a perfect proxy of this stochastic finance event. This study identifies the propensity of the capital market to explode on rare occasions, which could be termed as avalanche. The frequency of such movement (both up and down) may not be high; however, the amplitude will be significantly high. The underlying for the study is Nifty, bellwether Indian bourse. Escape velocity has been calculated for Nifty on a daily basis for 17 years and prediction modelling has been constructed applying artificial neural networks (ANN) and multiple adaptive regression splines (MARS) simultaneously. Results indicate queer coupling of US events and Nifty apart from the evident behavioural traces. This research work is aimed at providing an implicit form of avalanche predictor from a distinctly different reference point.

Elements of Stochastic Finance

10.1142/7758 ◽  
2011 ◽  
Author(s):  
Frederi G Viens ◽  
José Enrique Figueroa-López ◽  
Alexandra Chronopoulou
Keyword(s):  
Stochastic Finance

Stochastic Finance

2011 ◽  
Author(s):  
Jan Vecer
Keyword(s):  
Stochastic Finance

First Steps to Stochastic Finance

2001 ◽  
pp. 168-170
Author(s):  
Hans-Joachim Girlichl
Keyword(s):  
Stochastic Finance

Introduction to Stochastic Finance

2018 ◽  
Author(s):  
Jia-An Yan
Keyword(s):  
Stochastic Finance

scholarly journals INITIAL ENLARGEMENT IN A MARKOV CHAIN MARKET MODEL

2011 ◽  
Vol 11 (02n03) ◽  
pp. 389-413
Author(s):  
DARIO GASBARRA ◽  
JOSÉ IGOR MORLANES ◽  
ESKO VALKEILA
Keyword(s):  
Markov Chain ◽  
General Theory ◽  
Stochastic Processes ◽  
Market Model ◽  
Insider Information ◽  
Stochastic Finance

Enlargement of filtrations is a classical topic in the general theory of stochastic processes. This theory has been applied to stochastic finance in order to analyze models with insider information. In this paper we study initial enlargement in a Markov chain market model, introduced by Norberg. In the enlarged filtration, several things can happen: some of the jumps times can be accessible or predictable, but in the original filtration all the jumps times are totally inaccessible. But even if the jumps times change to accessible or predictable, the insider does not necessarily have arbitrage possibilities.

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