D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 1 Chapter 5: Option Pricing Models: The Black-Scholes Model When I first saw the formula I knew enough about it to know that this is the answer. This solved the ancient problem of risk and return in the stock market. It was recognized by the profession for what it was as a real tour de force. Merton Miller Trillion Dollar Bet, PBS, February, 2000

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 2 Important Concepts in Chapter 5 n The Black-Scholes option pricing model n The relationship of the model’s inputs to the option price n How to adjust the model to accommodate dividends and put options n The concepts of historical and implied volatility n Hedging an option position

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 3 Origins of the Black-Scholes Formula n Brownian motion and the works of Einstein, Bachelier, Wiener, Itô n Black, Scholes, Merton and the 1997 Nobel Prize

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 4 The Black-Scholes Model as the Limit of the Binomial Model n Recall the binomial model and the notion of a dynamic risk-free hedge in which no arbitrage opportunities are available. n Consider the AOL June 125 call option. Figure 5.1, p. 131 shows the model price for an increasing number of time steps. Figure 5.1, p. 131Figure 5.1, p. 131 n The binomial model is in discrete time. As you decrease the length of each time step, it converges to continuous time.

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 5 The Assumptions of the Model n Stock Prices Behave Randomly and Evolve According to a Lognormal Distribution. u See Figure 5.2a, p. 134, 5.2b, p. 135 and 5.3, p. 136 for a look at the notion of randomness. Figure 5.2a, p b, p , p. 136Figure 5.2a, p b, p , p. 136 u A lognormal distribution means that the log (continuously compounded) return is normally distributed. See Figure 5.4, p Figure 5.4, p. 137Figure 5.4, p. 137 n The Risk-Free Rate and Volatility of the Log Return on the Stock are Constant Throughout the Option’s Life n There Are No Taxes or Transaction Costs n The Stock Pays No Dividends n The Options are European

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 6 A Nobel Formula n The Black-Scholes model gives the correct formula for a European call under these assumptions. n The model is derived with complex mathematics but is easily understandable. The formula is

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 7 A Nobel Formula (continued) u where F N(d 1 ), N(d 2 ) = cumulative normal probability    = annualized standard deviation (volatility) of the continuously compounded return on the stock F F r c = continuously compounded risk-free rate

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 8 A Nobel Formula (continued) n A Digression on Using the Normal Distribution u The familiar normal, bell-shaped curve (Figure 5.5, p. 139) Figure 5.5, p. 139Figure 5.5, p. 139 u See Table 5.1, p. 140 for determining the normal probability for d 1 and d 2. This gives you N(d 1 ) and N(d 2 ). Table 5.1, p. 140Table 5.1, p. 140

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 9 A Nobel Formula (continued) n A Numerical Example u Price the AOL June 125 call  S 0 = , X = 125, r c = ln(1.0456) =.0446, T =.0959, =.83.  S 0 = , X = 125, r c = ln(1.0456) =.0446, T =.0959,  =.83. u See Table 5.2, p. 141 for calculations. C = $ Table 5.2, p. 141Table 5.2, p. 141 u Familiarize yourself with the accompanying software F Excel: bsbin3.xls. See Software Demonstration 5.1. Note the use of Excel’s =normsdist() function. F Windows: bsbwin2.2.exe. See Appendix 5.B.

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 10 A Nobel Formula (continued) n Characteristics of the Black-Scholes Formula u Interpretation of the Formula F The concept of risk neutrality, risk neutral probability, and its role in pricing options F The option price is the discounted expected payoff, Max(0,S T - X). We need the expected value of S T - X for those cases where S T > X.

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 11 A Nobel Formula (continued) n Characteristics of the Black-Scholes Formula (continued) u Interpretation of the Formula (continued) F The first term of the formula is the expected value of the stock price given that it exceeds the exercise price times the probability of the stock price exceeding the exercise price, discounted to the present. F The second term is the expected value of the payment of the exercise price at expiration.

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 12 A Nobel Formula (continued) n Characteristics of the Black-Scholes Formula (continued) u The Black-Scholes Formula and the Lower Bound of a European Call F Recall from Chapter 3 that the lower bound would be F The Black-Scholes formula always exceeds this value as seen by letting S 0 be very high and then let it approach zero.

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 13 A Nobel Formula (continued) n Characteristics of the Black-Scholes Formula (continued) u The Formula When T = 0 F At expiration, the formula must converge to the intrinsic value. F It does but requires taking limits since otherwise it would be division by zero. F Must consider the separate cases of S T  X and S T < X.

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 14 A Nobel Formula (continued) n Characteristics of the Black-Scholes Formula (continued) u The Formula When S 0 = 0 F Here the company is bankrupt so the formula must converge to zero. F It requires taking the log of zero, but by taking limits we obtain the correct result.

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 15 A Nobel Formula (continued) n Characteristics of the Black-Scholes Formula (continued) u The Formula When  = 0 F Again, this requires dividing by zero, but we can take limits and obtain the right answer F If the option is in-the-money as defined by the stock price exceeding the present value of the exercise price, the formula converges to the stock price minus the present value of the exercise price. Otherwise, it converges to zero.

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 16 A Nobel Formula (continued) n Characteristics of the Black-Scholes Formula (continued) u The Formula When X = 0 F From Chapter 3, the call price should converge to the stock price. F Here both N(d 1 ) and N(d 2 ) approach 1.0 so by taking limits, the formula converges to S 0.

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 17 A Nobel Formula (continued) n Characteristics of the Black-Scholes Formula (continued) u The Formula When r c = 0 F A zero interest rate is not a special case and no special result is obtained.

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 18 The Variables in the Black-Scholes Model n The Stock Price  Let S  then C . See Figure 5.6, p Figure 5.6, p. 148Figure 5.6, p. 148 u This effect is called the delta, which is given by N(d 1 ). u Measures the change in call price over the change in stock price for a very small change in the stock price. u Delta ranges from zero to one. See Figure 5.7, p. 149 for how delta varies with the stock price. Figure 5.7, p. 149Figure 5.7, p. 149 u The delta changes throughout the option’s life. See Figure 5.8, p Figure 5.8, p. 150 Figure 5.8, p. 150

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 19 The Variables in the Black-Scholes Model (continued) n The Stock Price (continued) u Delta hedging/delta neutral: holding shares of stock and selling calls to maintain a risk-free position F The number of shares held per option sold is the delta, N(d 1 ). F As the stock goes up/down by $1, the option goes up/down by N(d 1 ). By holding N(d 1 ) shares per call, the effects offset. F The position must be adjusted as the delta changes.

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 20 The Variables in the Black-Scholes Model (continued) n The Stock Price (continued) u Delta hedging works only for small stock price changes. For larger changes, the delta does not accurately reflect the option price change. This risk is captured by the gamma: u For our AOL June 125 call,

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 21 The Variables in the Black-Scholes Model (continued) n The Stock Price (continued) u If the stock goes from to 130, the delta is predicted to change from.569 to ( )(.0121) = The actual delta at a price of 130 is So gamma captures most of the change in delta. u The larger is the gamma, the more sensitive is the option price to large stock price moves, the more sensitive is the delta, and the faster the delta changes. This makes it more difficult to hedge. u See Figure 5.9, p. 152 for gamma vs. the stock price Figure 5.9, p. 152Figure 5.9, p. 152 u See Figure 5.10, p. 153 for gamma vs. time Figure 5.10, p. 153Figure 5.10, p. 153

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 22 The Variables in the Black-Scholes Model (continued) n The Exercise Price  Let X  Let X , then C  u u The exercise price does not change in most options so this is useful only for comparing options differing only by a small change in the exercise price.

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 23 The Variables in the Black-Scholes Model (continued) n The Risk-Free Rate u Take ln(1 + discrete risk-free rate from Chapter 3).  Let r c  Let r c  then C  See Figure 5.11, p The effect is called rhoFigure 5.11, p. 154 u u In our example, u u If the risk-free rate goes to.12, the rho estimates that the call price will go to ( )(5.57) =.42. The actual change is.43. u u See Figure 5.12, p. 155 for rho vs. stock price.Figure 5.12, p. 155

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 24 The Variables in the Black-Scholes Model (continued) n The Volatility or Standard Deviation u The most critical variable in the Black-Scholes model because the option price is very sensitive to the volatility and it is the only unobservable variable.  Let See Figure 5.13, p  Let  , then C  See Figure 5.13, p. 156.Figure 5.13, p. 156Figure 5.13, p. 156 u This effect is known as vega. u In our problem this is

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 25 The Variables in the Black-Scholes Model (continued) n The Volatility or Standard Deviation (continued) u Thus if volatility changes by.01, the call price is estimated to change by 15.32(.01) =.15 u If we increase volatility to, say,.95, the estimated change would be 15.32(.12) = The actual call price at a volatility of.95 would be 15.39, which is an increase of The accuracy is due to the near linearity of the call price with respect to the volatility. u See Figure 5.14, p. 157 for the vega vs. the stock price. Notice how it is highest when the call is approximately at-the-money. Figure 5.14, p. 157Figure 5.14, p. 157

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 26 The Variables in the Black-Scholes Model (continued) n The Time to Expiration u Calculated as (days to expiration)/365  Let T, then C. See Figure 5.15, p This effect is known as theta:  Let T , then C . See Figure 5.15, p This effect is known as theta:Figure 5.15, p. 158Figure 5.15, p. 158 n In our problem, this would be

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 27 The Variables in the Black-Scholes Model (continued) n The Time to Expiration (continued) u If one week elapsed, the call price would be expected to change to ( )(-68.91) = The actual call price with T =.0767 is 12.16, a decrease of u See Figure 5.16, p. 159 for theta vs. the stock price Figure 5.16, p. 159Figure 5.16, p. 159 u Note that your spreadsheet bsbin3.xls and your Windows program bsbwin2.2 calculate the delta, gamma, vega, theta, and rho for calls and puts.

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 28 The Black-Scholes Model When the Stock Pays Dividends n Known Discrete Dividends u Assume a single dividend of D t where the ex-dividend date is time t during the option’s life. u Subtract present value of dividends from stock price.  Adjusted stock price, S, is inserted into the B-S model: u See Table 5.3, p. 160 for example. Table 5.3, p. 160Table 5.3, p. 160 u The Excel spreadsheet bsbin3.xls allows up to 50 discrete dividends. The Windows program bsbwin2.2 allows up to three discrete dividends.

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 29 n Continuous Dividend Yield u Assume the stock pays dividends continuously at the rate of .  Subtract present value of dividends from stock price. Adjusted stock price, S, is inserted into the B-S model. u See Table 5.4, p. 161 for example. Table 5.4, p. 161Table 5.4, p. 161 u This approach could also be used if the underlying is a foreign currency, where the yield is replaced by the continuously compounded foreign risk-free rate. u The Excel spreadsheet bsbin3.xls and Windows program bsbwin2.2 permit you to enter a continuous dividend yield. The Black-Scholes Model in the Presence of Dividends (continued)

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 30 The Black-Scholes Model and Some Insights into American Call Options n Table 5.5, p. 163 illustrates how the early exercise decision is made when the dividend is the only one during the option’s life Table 5.5, p. 163 Table 5.5, p. 163 n The value obtained upon exercise is compared to the ex- dividend value of the option. n High dividends and low time value lead to early exercise. n Your Excel spreadsheet bsbin3.xls and Windows program bsbwin2.2 will calculate the American call price using the binomial model.

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 31 Estimating the Volatility n Historical Volatility u This is the volatility over a recent time period. u Collect daily, weekly, or monthly returns on the stock. u Convert each return to its continuously compounded equivalent by taking ln(1 + return). Calculate variance. u Annualize by multiplying by 250 (daily returns), 52 (weekly returns) or 12 (monthly returns). Take square root. See Table 5.6, p for example with AOL. Table 5.6, p Table 5.6, p u Your Excel spreadsheet hisv2.xls will do these calculations. See Software Demonstration 5.2.

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 32 Estimating the Volatility (continued) n Implied Volatility u This is the volatility implied when the market price of the option is set to the model price. u Figure 5.17, p. 168 illustrates the procedure. Figure 5.17, p. 168 Figure 5.17, p. 168 u Substitute estimates of the volatility into the B-S formula until the market price converges to the model price. See Table 5.7, p. 169 for the implied volatilities of the AOL calls. Table 5.7, p. 169Table 5.7, p. 169 u A short-cut for at-the-money options is

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 33 Estimating the Volatility (continued) n Implied Volatility (continued) u For our AOL June 125 call, this gives u This is quite close; the actual implied volatility is.83. u Appendix 5.A shows a method to produce faster convergence.

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 34 Estimating the Volatility (continued) n Implied Volatility (continued) u Interpreting the Implied Volatility F The relationship between the implied volatility and the time to expiration is called the term structure of implied volatility. See Figure 5.18, p Figure 5.18, p. 170 Figure 5.18, p. 170 F The relationship between the implied volatility and the exercise price is called the volatility smile or volatility skew. Figure 5.19, p These volatilities are actually supposed to be the same. This effect is puzzling and has not been adequately explained. Figure 5.19, p. 171 Figure 5.19, p. 171 F The CBOE has constructed indices of implied volatility of one- month at-the-money options based on the S&P 100 (VIX) and Nasdaq (VXN). See Figure 5.20, p Figure 5.20, p. 172Figure 5.20, p. 172

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 35 Put Option Pricing Models n Restate put-call parity with continuous discounting n Substituting the B-S formula for C above gives the B-S put option pricing model n N(d 1 ) and N(d 2 ) are the same as in the call model.

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 36 Put Option Pricing Models (continued) n Note calculation of put price: n The Black-Scholes price does not reflect early exercise and, thus, is extremely biased here since the American option price in the market is A binomial model would be necessary to get an accurate price. With n = 100, we obtained n See Table 5.8, p. 175 for the effect of the input variables on the Black- Scholes put formula. Table 5.8, p. 175Table 5.8, p. 175 n Your software also calculates put prices and Greeks.

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 37 Managing the Risk of Options n Here we talk about how option dealers hedge the risk of option positions they take. n Assume a dealer sells 1,000 AOL June 125 calls at the Black-Scholes price of with a delta of Dealer will buy 569 shares and adjust the hedge daily. u To buy 569 shares at $ and sell 1,000 calls at $ will require $58,107. u We simulate the daily stock prices for 35 days, at which time the call expires.

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 38 Managing the Risk of Options (continued) n The second day, the stock price is There are now 34 days left. Using bsbin3.xls, we get a call price of and delta of We have u Stock worth 569($ ) = $68,590 u Options worth -1,000($ ) = -$10,478 u Total of $58,112 u Had we invested $58,107 in bonds, we would have had $58,107e.0446(1/365) = $58,114. n Table 5.9, pp shows the remaining outcomes. We must adjust to the new delta of We need 500 shares so sell 69 and invest the money ($8,318) in bonds. Table 5.9, pp Table 5.9, pp

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 39 Managing the Risk of Options (continued) n At the end of the second day, the stock goes to and the call to The bonds accrue to a value of $8,319. We have u Stock worth 500($ ) = $53,486 u Options worth -1,000($4.7757) = -$4,776 u Bonds worth $8,319 (includes one days’ interest) u Total of $57,029 u Had we invested the original amount in bonds, we would have had $58,107e.0446(2/365) = $58,121. We are now short by over $1,000. n At the end we have $56,540, a shortage of $1,816.

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 40 Managing the Risk of Options (continued) n What we have seen is the second order or gamma effect. Large price changes, combined with an inability to trade continuously result in imperfections in the delta hedge. n To deal with this problem, we must gamma hedge, i.e., reduce the gamma to zero. We can do this only by adding another option. Let us use the June 130 call, selling at with a delta of.5086 and gamma of Our original June 125 call has a gamma of The stock gamma is zero. n We shall use the symbols  1,  2,  1 and  2. We use h S shares of stock and h C of the June 130 calls.

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 41 Managing the Risk of Options (continued) n The delta hedge condition is u h S (1) - 1,000  1 + h C  2 = 0 n The gamma hedge condition is u -1,000  1 + h C  2 = 0 n We can solve the second equation and get h C and then substitute back into the first to get h S. Solving for h C and h S, we obtain u h C = 1,000(.0121/.0123) = 984 u h S = 1,000( (.0121/.0123).5086) = 68 n So buy 68 shares, sell 1,000 June 125s, buy 985 June 130s.

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 42 Managing the Risk of Options (continued) n The initial outlay will be u 68($ ) - 1,000($ ) + 985($ ) = $6,219 n At the end of day one, the stock is at , the 125 call is at , the 130 call is at The portfolio is worth u 68($ ) - 1,000($ ) + 985($8.6344) = $6,224 n It should be worth $6,219e.0446(1/365) = $6,220. n The new deltas are.4999 and.4384 and the new gammas are.0131 and.0129.

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 43 Managing the Risk of Options (continued) n The new values are 1,012 of the 130 calls so we buy 27. The new number of shares is 56 so we sell 12. Overall, this generates $1,214, which we invest in bonds. n The next day, the stock is at $ , the 125 call is at $ and the 130 call is at $ The bonds are worth $1,214. The portfolio is worth u 56($ ) - 1,000($4.7757) + 1,012($3.7364) + $1,214 = $6,210. n The portfolio should be worth $6,219e.0446(2/365) = $6,221. n Continuing this, we end up at $6,589 and should have $6,246, a difference of $343. We are much closer than when only delta hedging.

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 44 Summary n See Figure 5.21, p. 182 for the relationship between call, put, underlying asset, risk-free bond, put-call parity, and Black-Scholes call and put option pricing models. Figure 5.21, p. 182Figure 5.21, p. 182

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 45 Appendix 5.A: A Shortcut to the Calculation of Implied Volatility n This technique developed by Manaster and Koehler gives a starting point and guarantees convergence. Let a given volatility be  * and the corresponding Black-Scholes price be C(  * ). The initial guess should be n You then compute C(  1 * ). If it is not close enough, you make the next guess.

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 46 Appendix 5.A: A Shortcut to the Calculation of Implied Volatility (continued) n Given the i th guess, the next guess should be n where d 1 is computed using  1 *. Let us illustrate using the AOL June 125 call. C(  ) = The initial guess is

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 47 Appendix 5.A: A Shortcut to the Calculation of Implied Volatility (continued) n At a volatility of.4950, the Black-Scholes value is The next guess should be n where.1533 is d 1 computed from the Black-Scholes model using.4950 as the volatility and is the square root of 2 . Now using.8260, we obtain a Black-Scholes value of 13.49, which is close enough to So.83 is the implied volatility.

D. M. ChanceAn Introduction to Derivatives and Risk Management, 6th ed.Ch. 5: 48 Appendix 5.B: The BSBWIN2.2 Windows Software

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