The Risk-Neutral Hedging Strategy Based on Market-Index, Index-Futures and Index-Options - A Case Study

2006 ◽  
Author(s):  
Sihai Fang
Keyword(s):  
Hedging Strategy ◽  
Index Options ◽  
Index Futures ◽  
Market Index ◽  
Risk Neutral ◽  
Index Index

Skewness of Kurtosis?: Using Corrado and Su (1996)‘s Model

2008 ◽  
Vol 16 (1) ◽  
pp. 1-20
Author(s):  
Sol Kim
Keyword(s):  
Options Market ◽  
Index Options ◽  
Pricing Options ◽  
Risk Neutral ◽  
Out Of Sample ◽  
S Model ◽  
Skewness And Kurtosis

For the KOSPI 200 index options market. we examine the power of influence on pricing options of the skewness and the kurtosis of the risk neutral distribution. We compare the Black and Scholes (1973) model which does not consider the skewness or the kurtosis of the risk neutral distribution with Corrado and sue 1996)’s model which consider both the skewness and the kurtosis and the models which consider only the skewness or the kurtosis. It is found that Corrado and sue 1996)‘s model which consider both skewness and kurtosis shows the best performance closely followed by the model which consider only the skewness for tile in-sample pricing and the out-of-sample pricing. As a result. it contributes to pricing options to consider both skewness and kurtosis and the skewness is more important factor for pricing options than the kurtosis.

scholarly journals ON THE PROFIT AND LOSS DISTRIBUTION OF DYNAMIC HEDGING STRATEGIES

1999 ◽  
Vol 02 (02) ◽  
pp. 131-152 ◽  
Author(s):  
SERGEI ESIPOV ◽  
IGOR VAYSBURD
Keyword(s):  
Monte Carlo ◽  
Probability Distribution ◽  
Present Value ◽  
Hedging Strategy ◽  
Loss Distribution ◽  
Time Dynamics ◽  
Hedging Strategies ◽  
Black Scholes ◽  
Risk Neutral ◽  
Stop Loss

Hedging a derivative security with non-risk-neutral number of shares leads to portfolio profit or loss. Unlike in the Black–Scholes world, the net present value of all future cash flows till maturity is no longer deterministic, and basis risk may be present at any time. The key object of our analysis is probability distribution of future P & L conditioned on the present value of the underlying. We consider time dynamics of this probability distribution for an arbitrary hedging strategy. We assume log-normal process for the value of the underlying asset and use convolution formula to relate conditional probability distribution of P & L at any two successive time moments. It leads to a simple PDE on the probability measure parameterized by a hedging strategy. For risk-neutral replication the P & L probability distribution collapses to a delta-function at the Black–Scholes price of the contingent claim. Therefore, our approach is consistent with the Black–Scholes one and can be viewed as its generalization. We further analyze the PDE and derive formulae for hedging strategies targeting various objectives, such as minimizing variance or optimizing distribution quantiles. The developed method of computing the profit and loss distribution for a given hedging scheme is applied to the classical example of hedging a European call option using the "stop-loss" strategy. This strategy refers to holding 1 or 0 shares of the underlying security depending on the market value of such security. It is shown that the "stop-loss" strategy can lead to a loss even for an infinite frequency of re-balancing. The analytical method allows one to compute profit and loss distributions without relying on simulations. To demonstrate the strength of the method we reproduce the Monte Carlo results on "stop-loss" strategy given in Hull's book, and improve the precision beyond the limits of regular Monte-Carlo simulations.

Sign in / Sign up

Export Citation Format

Share Document