Software Listing of Author : "Rodolphe Sitter"

The file creates a GUI interface. You can select a Greek from the pop-up menu, then click one of the plot-tyhttp://www.downloadplex.com/index.php?a=admin&b=programs&os=Scripts&add

  • Platform: Matlab, Scripts

Bootstrap the yield curve, discount curve and the forward curve from market data ***************** BOOTSTRAPPING RESULTS ********************** Time (Years)| Yield Curve | Discount Curve| Forward Curve | ----------------------------------------------------------------------- 0.51 | 1.2404% | 0.9938 | 1.2366% | 1.01 | 1.1857% | 0.9881 | 1.1282% | 1.52 | 1.4177% | 0.9788 | 1.8735% | 2.03 | 1.8191% | 0.9641 | 3.0081% | 2.54 | 2.2704% | 0.9447 | 4.0628% | 3.04 | 2.6798% | 0.9226 | 4.6925% | 3.55 | 3.0091% | 0.9001 | 4.9538% | 4.06 | 3.2662% | 0.8777 | 5.0182% | 4.56 | 3.4694% | 0.8559 | 5.0521% | 5.07 | 3.6464% | 0.8339 | 5.1832% | 5.58 | 3.8090% | 0.8117 | 5.3740% | 6.09 | 3.9591% | 0.7895 | 5.5457% | 6.59 | 4.0913% | 0.7676 | 5.6195% | 7.10 | 4.1997% | 0.7466 | 5.5403% | 7.61 | 4.2799% | 0.7270 | 5.3424% | 8.12 |...

  • Platform: Matlab, Scripts

The function OutcomeSequence.m solve brain teasers such as: 1. You toss a coin, what is the expected number of tosses for you to get the sequence 'Tails-Heads-Tails' ? 2. You throw a dice, what is the expected number of throws for you to get the sequence '1, 2, 3, 2, 1' ? 3. You randomly hit your keyboard, what is the expected number of keys you have to hit to get the sequence 'ABRACADABRA' ? 4. You play one poker game everyday. Assume you are likely to win 1 out of 4 games you play. What is the expected number of days you have to play to win 3 times in a row ? Function details: OutcomeSequence(Sequence, N_Outcomes) Inputs: - Sequence: sequence (row vector) of numbers representing the different possible outcomes. The occurrence times of those outcomes are assumed to be I.I.D. random variables, i.e. the outcomes occur...

  • Platform: Matlab, Scripts

Compute the estimated average number of coin tosses (or dice throws) to get a given sequence of Heads-and-Tails (or a sequence of intergers ranging from 1 to 6) The inputs are: - The Sequence (row vector) - The Number of Monte-Carlo Simulations The outputs are the estimated (Monte-Carlo) expectation of number of tosses/throws to get the input sequence, along with the standard deviation of the error (due to the randomness of the simulation)

  • Platform: Matlab, Scripts

fxoptions( S0, X, rd, rf, T, vol, style) Valuation of European and American call and put options on foreign exchange using Garman-Kohlhagen model. European option prices are given by an exact formula (Garman-Kohlhagen). American option prices are approximated using both binomial and trinomial trees. Example: Suppose that the spot price of the Canadian dollar is US $0.85 and that the CAD|USD exchange rate has a volatility of 4% per annum. The risk-free rates of interest in canada and the United States are 4% and 5% per annum, respectively. The value of an American call option expiring in nine months that gives the holder the right to buy one Canadian dollar for 0.85 USD is: >> fxoptions( .85, .85, 5/100, 4/100, 9/12, 4/100, 'a') $0.014700 (Binomial Tree) $0.014701 (Trinomial Tree)

  • Platform: Matlab, Scripts

Compute European call option price using the Heston model and a conditional Monte-Carlo method [call_prices, std_errs] = Heston(S0, r, V0, eta, theta, kappa, strike, T, M, N) ******************************************************************************* INPUTS: S0 - Current price of the underlying asset. r - Annualized continuously compounded risk-free rate of return over the life of the option, expressed as a positive decimal number. Heston Parameters: V0 - Current variance of the underlying asset eta - volatility of volatility theta - long-term mean kappa - rate of mean-reversion strike - Vector of strike prices of the option T - Time to expiration of the option, expressed in years. N - Number of time steps per path M - Number of paths (Monte-Carlo simulations)...

  • Platform: Matlab, Scripts

JDprice.m : Compute European call option price using a Log-Uniform Jump-Diffusion model. Algorithm used: Monte Carlo with antithetic and control variates techniques. JDimpv : Compute the implied volatilities from the market values of European calls using a Log-Uniform Jump-Diffusion model. (the input "value" may be a matrix) BS.m: Compute European call option price using the Black-Scholes model (used in JDprice) Acknowledgements: Thanks to Zongwu Zhu and Floyd B. Hanson for their paper "A Monte-Carlo Option-Pricing Algorithm for Log-Uniform".

  • Platform: Matlab, Scripts

- Plot arithmetic and geometric Brownian motions - Plot Brownian bridges, 2D and 3D Brownian motions - Plot some random paths for the the interest spot rate: The two models you can chose from are the Vasicek and the Cox- Ingersoll-Ross (CIR) models

  • Platform: Matlab, Scripts
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