Derivatives
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š Why Long-Term Stock Guarantees Are More Expensive Than They Look I recently came across a fascinating āBusiness Snapshotā in John Hullās classic textbook Options, Futures, and Other Derivatives. It deals with a question many investors assume has an obvious answer: āIf you invest for the long run, arenāt stocks guaranteed to outperform bonds?ā Hull…
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A diversified portfolioās value can be insured using options written on a corresponding index (e.g., the S&P 500). If we assume that the portfolio closely replicates the index, that its dividends match the index dividends, and that its beta equals 1, then by purchasing an appropriate number of put options, it becomes possible to insure…
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Microsoft was one of the first companies to grant stock options to all employees. Later it was estimated that thanks to this decision, more than 10,000 employees became millionaires. Stock-based compensation is still actively used today. It used to be even more popular because it helped attract valuable employees without appearing as an expense on…
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How to Assess a Stockās Risk Based on Historical Data We know that in finance, āriskā usually refers to volatility, i.e., uncertainty regarding changes. Here, I want to highlight a few important points. The volatility (Ļ) measure is very commonly used in practical finance when we: It is therefore important to understand clearly what this…
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Suppose an investment fund (or a development company) promises you an average return of 14% per year. To convince you, they show that over the last 5 years their returns were: 15%, 20%, 30%, ā20%, and 25%. The average of these is indeed 14%. Does the promise sound credible? Letās check mathematically. The promise:A 5-year…
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Why diversification fails during market crises⦠Assume two variables, (x_1) and (x_2), follow generalized Wiener processes: dx1 = a1Ā·dt + b1Ā·dz1 and dx2 = a2Ā·dt + b2Ā·dz2 The corresponding discreteātime versions of these continuous processes are: Īx1=a1*Īt+b1*ε1*Ā āĪt įį Īx=a2*Īt+b2*ε2*Ā āĪt If we assume these processes are independent, then ε1 and ε2 are simply standard normal random…
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1. The starting point ā stock price process We assume that the stock price SSS follows a geometric Brownian motion: dS = μS*dt +ĻS*dz where: find also: Geometric Brownian Motion of Stock Price 2. Applying Itoās Lemma to G=ln (S) We want to find the process followed by G=lnā”S Itoās Lemma tells us that if S…