The Heston model under stochastic interest rates

Tese de mestrado, Matemática Financeira, Faculdade de Ciências, Universidade de Lisboa,2008In this dissertation the Heston (1993) model is considered, but using, instead of a constant interest rate, stochastic interest rates according to Vasicek (1977) and to Cox, Ingersoll and Ross (1985) models. Under this framework, a closed-form solution is determined for the price of European standard calls, which, by using a manipulation implemented by Attari (2004), only require the evaluation of one characteristic function. For forward-start European calls, starting from the result for standard calls and using analytic characteristic functions, it is determined a closed-form solution that only requires one numerical integration. In the end, the results of these closedform solutions are compared with the results presented by Monte Carlo simulations for the considered models.Nesta dissertação é considerado o modelo de Heston (1993), mas em vez de utilizar uma taxa de juro constante, considera-se taxas de juro estocásticas segundo os modelos de Vasicek (1977) e de Cox, Ingersoll e Ross (1985). Neste contexto, é determinada uma solução fechada para a avaliação de standard calls Europeias, que, por ter sido usada uma manipulação implementada por Attari (2004), apenas necessitará da avaliação de uma função característica. Para calls forward-start Europeias, partindo do resultado apresentado para standard calls e utilizando funções característica analíticas, é determinada uma solução fechada que também recorrerá a apenas uma integração numérica. No final, os resultados destas fórmulas fechadas são comparados com os resultantes de simulações de Monte Carlo para os modelos considerados

Parameter Estimation for the Square-root Diffusions : Ergodic and Nonergodic Cases

22 pagesThis paper deals with the problem of parameter estimation in the Cox-Ingersoll-Ross (CIR) model $(X_t)_{t\geq 0}$. This model is frequently used in finance for example as a model for computing the zero-coupon bound price or as a dynamic of the volatility in the Heston model. When the diffusion parameter is known, the maximum likelihood estimator (MLE) of the drift parameters involves the quantities : $\int_{0}^{t}X_sds$ and $\int_{0}^{t}\frac{ds}{X_s}$. At first, we study the asymptotic behavior of these processes. This allows us to obtain various and original limit theorems on our estimators, with different rates and different types of limit distributions. Our results are obtained for both cases : ergodic and nonergodic diffusion. Numerical simulations were processed using an exact simulation algorithm

Model Dependency of the Digital Option Replication – Replication under an Incomplete Model (in English)

The paper focuses on the replication of digital options under an incomplete model. Digital options are regularly applied in the hedging and static decomposition of many path-dependent options. The author examines the performance of static and dynamic replication. He considers the case of a market agent for whom the right model of the underlying asset-price evolution is not available. The observed price dynamic is supposed to follow four distinct models: (i) the Black and Scholes model, (ii) the Black and Scholes model with stochastic volatility driven by Hull and White model, (iii) the variance gamma model, defined as time changed Brownian motion, and (iv) the variance gamma model set in a stochastic environment modelled as the rate of time change via a Cox-Ingersoll-Ross model. Both static and dynamic replication methods are applied and examined within each of these settings. The author verifies the independence of the static replication on underlying processes.digital options, dynamic and static replication, internal time, Lévy models, replication error, stochastic environment, stochastic volatility, variance gamma process

The Term Structure of Interest-Rate Future Prices

We derive general properties of two-factor models of the term structure of interest rates and, in particular, the process for futures prices and rates. Then, as a special case, we derive a no-arbitrage model of the term structure in which any two futures rates act as factors. The term structure shifts and tilts as the factor rates vary. The cross-sectional properties of the model derive from the solution of a two-dimensional autoregressive process for the short-term rate, which exhibits both mean reversion and a lagged persistence parameter. We show that the correlation of the futures rates is restricted by the no-arbitrage conditions of the model. In addition, we investigate the determinants of the volatility of the futures rates of various maturities. These are shown to be related to the volatilities of the short rate, the volatility of the second factor, the degree of mean reversion and the persistence of the second factor shock. We obtain specific results for futures rates in the case where the logarithm of the short-term rate [e.g., the London Inter-Bank Offer Rate (Libor)] follows a two-dimensional process. Our results lead to empirical hypotheses that are testable using data from the liquid market for Eurocurrency interest rate futures contracts

Distributions Implied by Exchange Traded Options: A Ghost’s Smile?

A new and easily applicable method for estimating risk neutral distributions (RND) implied by American futures options is proposed. It amounts to inverting the Barone-Adesi and Whaley method (1987) (BAW method) to get the BAW-implied volatility smile. Extensive empirical tests show that the BAW smile is equivalent to the volatility smile implied by corresponding European options. Therefore, the procedure leads to a legitimate RND estimation method. Further, the investigation of the currency options traded on the Chicago Mercantile Exchange and OTC markets in parallel provides us with insights on the structure and interaction of the two markets. Unequally distributed liquidity in the OTC market seems to lead to price distortions and an ensuing interesting `ghost- like' shape of the RND density implied by CME options. Finally, using the empirical results, we propose a parsimonious generalisation of the existing methods for estimating volatility smiles from OTC options. A single free parameter significantly improves the fit. Note:The revised version of this paper was published as: Cincibuch, M., 2004. Distributions Implied by American Currency Futures Options: A Ghosts' Smile ? Journal of Futures Markets, 2004, 24(2).

A Fast Mean-Reverting Correction to Heston's Stochastic Volatility Model

We propose a multi-scale stochastic volatility model in which a fast mean-reverting factor of volatility is built on top of the Heston stochastic volatility model. A singular pertubative expansion is then used to obtain an approximation for European option prices. The resulting pricing formulas are semi-analytic, in the sense that they can be expressed as integrals. Difficulties associated with the numerical evaluation of these integrals are discussed, and techniques for avoiding these difficulties are provided. Overall, it is shown that computational complexity for our model is comparable to the case of a pure Heston model, but our correction brings significant flexibility in terms of fitting to the implied volatility surface. This is illustrated numerically and with option data

Discounting the Distant Future: How Much Do Uncertain Rates Increase Valuations?

Costs and benefits in the distant future—such as those associated with global warming, long-lived infrastructure, hazardous and radioactive waste, and biodiversity—often have little value today when measured with conventional discount rates. We demonstrate that when the future path of this conventional rate is uncertain and persistent (i.e., highly correlated over time), the distant future should be discounted at lower rates than suggested by the current rate. We then use two centuries of data on U.S. interest rates to quantify this effect. Using both random walk and mean-reverting models (which are indistinguishable based on historical data), we compute the certainty-equivalent rate—that is, the single discount rate that summarizes the effect of uncertainty and measures the appropriate forward rate of discount in the future. Using the random walk model, which we consider more compelling, we find that the certainty-equivalent rate falls from 3% now to 2% after 100 years, to 1% after 200 years, and down to 0.5% after 300 years. The mean-reverting model leads to a certainty-equivalent rate that remains above 3% for the next 200 years, then falls to 2% after 300 years and to 1% after 400 years. If we use these rates to value consequences at horizons of 400 years, the discounted value increases by a factor of 7,000 based on the random walk model and by a factor of 30 based on the mean-reverting model — both relative to conventional discounting. These results are relevant for a wide range of policy questions involving the distant future. Applying the random walk model to the consequences of climate change, for example, we find that inclusion of discount rate uncertainty doubles the expected present value of mitigation benefits. Other applications and alternative beliefs about the random walk–mean-reverting distinction are easily explored with our table of discount factors over time.