Transcript Derivatives
Derivatives & Risk Management • Derivatives are mostly used to ‘hedge’ (limit) risk • But like most financial instruments, they can also be used for ‘speculation’ – taking on added risk in the expectation of gain Stodder: Derivatives Basics of Option Pricing • Basic to Option Pricing is the idea of a ‘Riskless Hedge’ • A Riskless Hedge would be a situation in which you can buy some form of insurance that guarantees you the same money -whether the market goes up or down. Stodder: Derivatives Example of Riskless Hedge: Buy ¾ Stock @ $40 and Sell 1 ‘Call’ – Option to Buy @ $35 Ending Stock Price $30 $50 Difference: $20 minus Strike Price - $35 - $35 $0 = Option Value = $0 = $15 $15 Ending Stock Value $30 x 0.75 = $22.50 $50 x 0.75 = $37.50 Difference: $15 minus Strike Price - $35 - $35 $0 = Option Value $0 $15 $15 Ending Stock Value $30 x 0.75 = $22.50 $50 x 0.75 = $37.50 (No one will buy) (No one will buy) minus Option Value = Value of Porftolio $0 $22.50 $15 $22.50 Stodder: Derivatives What is this Call Option Worth? • Since this hedge is riskless, it should be evaluated at the risk-free rate. • Say “risk-free rate” (on US Bonds) is 8%. • In one year, Portfolio of $22.50 has Present Value of PV = $22.50/1.08 = $20.83 Stodder: Derivatives Recall, Stock is now worth $40. So, it costs 0.75($40) = $30.00 to purchase ¾ of a share. Then PV Portfolio = Cost Stock – Value of Option $20.83 = $30 – Value of Option => V.o.O. = $9.17, what you sell it for Stodder: Derivatives We have just derived the price • We take as ‘known’ the present and future prices of the underlying asset. • From this knowledge of future prices, we ‘derive’ the price of the derivative. • We will then derive the probabilities of those future prices. Stodder: Derivatives Run Simulation • From Financial Models Using Simulation and Optimization by Wayne Winston. Stodder: Derivatives Limitations of Log-Normal Assumption • Log-Normality fails to reproduce some of the important features of empirical asset price dynamics such as • Jumps in the asset price • “Fat Tails” of the Probability Distribution Function Empirical pdf St S0 Jump Fat Tails 0 Gaussian T si–1– si Stodder: Derivatives How is this Modeled? • Merton’s (1976) “Jump Diffusion” Process – Size of Jumps is itself Log-Normally Distributed and added to the model. – Timing of Jumps is Poisson Distributed. - Yusaku Yamamoto: Application of the Fast Gauss Transform to Option Pricing www.na.cse.nagoya-u.ac.jp/~yamamoto/work/KRIMS2004.ppt Stodder: Derivatives Derivatives get a ‘Bad Name’ • Most Financial Scandals of the last decade in the US and UK were linked to derivatives, some combination of excessive speculation and fraud: • Barrings Bank • Enron • World-Com • Back-Dating of Options • CDOs on Sub-Prime Mortgages Stodder: Derivatives Reasons for Fraud • Leveraging makes possible fantastic gain, but also horrible losses • Gambler’s ‘Last Desperate Hope’ (Adverse Selection) • Complexity of Derivatives make fraud harder to identify Stodder: Derivatives Greater Long-Term Concern than Fraud: Systemic Risk The Moral Hazard of Insurance • If you had a car that is less damaged by any given car crash – would that make you drive faster? • If you (and everybody else) drove faster, could this actually wind up making you less safe ? Stodder: Derivatives