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@hopeful_readings: #fypシ゚viral #waffle #halloween #crystaltiktok #mediumship
🌌🕊💜Hopeful Readings💜🕊🌌
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Thursday 15 October 2026 19:11:29 GMT
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LOW BUDGET EDIT 🔥these are not their voicelines, I forgot to post on a certain date sowii anyways maybe someday i could make this real hehe #fyp #fypage #fyppppppppppppppppppppppp #abcxyz #AprilFools
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➡️ Part 30 of Quantitative Finance From Scratch: the Black-Scholes formula. A call option is the right to buy a stock at a fixed price (the strike) on a fixed date. Fischer Black and Myron Scholes published the formula in 1973 (Journal of Political Economy), Robert Merton derived it another way, and in 1997 Scholes and Merton received the Nobel Memorial Prize in Economic Sciences. Black had died in 1995. C = S N(d1) - K e^(-rt) N(d2), with d1 = [ln(S/K) + (r + σ²/2) t] / (σ √t) and d2 = d1 - σ √t. S is today's stock price, K the strike, r the risk free rate, t the time to expiry in years, σ the volatility, and N the cumulative standard normal distribution. The stock's expected return does not appear, because stock and cash can copy the option. Our test run (blackscholes.py, 16 lines of numpy, seed 30): stock 100, strike 100, 1 year, rate 4 %, volatility 20 %. Then d1 = 0.3, d2 = 0.1, N(d1) = 0.618, N(d2) = 0.540, and the price is 61.79 - 51.87 = 9.93. One million risk neutral Monte Carlo prices give an average discounted payoff of 9.92 (standard error 0.014). With the stock at 100 the same option costs 4.49 with 3 months left and 15.08 with 2 years left. Honest notes: the model assumes a constant volatility and price paths without jumps. If you solve the formula backwards from real option prices, the volatility changes with the strike (the smile), so in practice each option gets its own implied volatility for the stock. #quantfinance #blackscholes #options #finance #python
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