347 research outputs found

    Review of stochastic differential equations in statistical arbitrage pairs trading

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    The use of stochastic differential equations offers great advantages for statistical arbitrage pairs trading. In particular, it allows the selection of pairs with desirable properties, e.g., strong mean-reversion, and it renders traditional rules of thumb for trading unnecessary. This study provides an exhaustive survey dedicated to this field by systematically classifying the large body of literature and revealing potential gaps in research. From a total of more than 80 relevant references, five main strands of stochastic spread models are identified, covering the ‘Ornstein–Uhlenbeck model’, ‘extended Ornstein–Uhlenbeck models’, ‘advanced mean-reverting diffusion models’, ‘diffusion models with a non-stationary component’, and ‘other models’. Along these five main categories of stochastic models, we shed light on the underlying mathematics, hereby revealing advantages and limitations for pairs trading. Based on this, the works of each category are further surveyed along the employed statistical arbitrage frameworks, i.e., analytic and dynamic programming approaches. Finally, the main findings are summarized and promising directions for future research are indicated

    Perpetual American double lookback options on drawdowns and drawups with floating strikes

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    We present closed-form solutions to the problems of pricing of the perpetual American double lookback put and call options on the maximum drawdown and the maximum drawup with floating strikes in the Black-Merton-Scholes model. It is shown that the optimal exercise times are the first times at which the underlying risky asset price process reaches some lower or upper stochastic boundaries depending on the current values of its running maximum or minimum as well as the maximum drawdown or maximum drawup. The proof is based on the reduction of the original double optimal stopping problems to the appropriate sequences of single optimal stopping problems for the three-dimensional continuous Markov processes. The latter problems are solved as the equivalent free-boundary problems by means of the smooth-fit and normal-reflection conditions for the value functions at the optimal stopping boundaries and the edges of the three-dimensional state spaces. We show that the optimal exercise boundaries are determined as either the unique solutions of the associated systems of arithmetic equations or the minimal and maximal solutions of the appropriate first-order nonlinear ordinary differential equations

    A Celebration of the Ties That Bind Us: Connections Between Actuarial Science and Mathematical Finance

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    The articles in this volume are contributed by scholars who are not only experts in areas of Actuarial Science (AS) and Mathematical Finance (MF), but also those who present diverse perspectives from both industry and academia. Topics from multiple areas, such as Stochastic Modeling, Credit Risk, Monte Carlo Simulation, and Pension Valuation, among others, that were maybe thought to be the domain of one type of risk manager, are shown time and again to have deep value to other areas of risk management as well. The articles in this collection, in my opinion, contribute techniques, ideas, and overviews of tools that folks in both AS and MF will find useful and interesting to implement in their work. It is also my hope that this collection will inspire future collaboration between those who seek an interdisciplinary approach to risk management

    Ruine et investissement en environnement markovien

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    L'objet de cette thÚse est de modéliser et optimiser les stratégies d'investissement d'un agent soumis à un environnement markovien, et à un risque de liquidité se déclarant quand il ne peut plus faire face à une sortie d'argent faute d'actifs liquides. Durant cette étude, nous supposerons que son objectif est d'éviter la faillite ; il dispose pour cela d'opportunités d'investissement, lui permettant d'accroßtre ses gains futurs en échange d'une dépense immédiate, risquant ainsi une ruine prématurée puisque l'investissement est supposé illiquide : le but du travail est de déterminer les conditions sous lesquelles il est plus judicieux de courir un tel risque de liquidité que de renoncer à un revenu permanent.This thesis aims at modelling and optimize an agent's (called "he") investment strategies when subjected to a Markovian environment, and to a liquidity risk happening when he runs out of liquid assets during an expense. Throughout this work, we deem that he aims at avoiding default; for this purpose, investment opportunities are available to him, allowing to increase his future expected incomes at the price of an immediate expense, therefore risking premature bankruptcy since investment is deemed illiquid: our goal is to find conditions under which incurring such liquidity risks is more advisable than declining a permanent income

    Essays in Quantitative Finance

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    This thesis contributes to the quantitative finance literature and consists of four research papers.Paper 1. This paper constructs a hybrid commodity interest rate market model with a stochastic local volatility function that allows the model to simultaneously fit the implied volatility of commodity and interest rate options. Because liquid market prices are only available for options on commodity futures (not forwards), a convexity correction formula is derived to account for the difference between forward and futures prices. A procedure for efficiently calibrating the model to interest rate and commodity volatility smiles is constructed. Finally, the model is fitted to an exogenously given cross-correlation structure between forward interest rates and commodity prices. When calibrating to options on forwards (rather than futures), the fitting of cross-correlation preserves the (separate) calibration in the two markets (interest rate and commodity options), whereas in the case of futures, a (rapidly converging) iterative fitting procedure is presented. The cross-correlation fitting is reduced to finding an optimal rotation of volatility vectors, which is shown to be an appropriately modified version of the “orthonormal Procrustes” problem. The calibration approach is demonstrated on market data for oil futures.Paper 2. This paper describes an efficient American Monte Carlo approach for pricing Bermudan swaptions in the LIBOR market model using the Stochastic Grid Bundling Method (SGBM) which is a regression-based Monte Carlo method in which the continuation value is projected onto a space in which the distribution is known. We demonstrate an algorithm to obtain accurate and tight lower–upper bound values without the need for the nested Monte Carlo simulations that are generally required for regression-based methods.Paper 3. The credit valuation adjustment (CVA) for over-the-counter derivatives are computed using the portfolio’s exposure over its lifetime. Usually, future exposure is approximated by Monte Carlo simulations. For derivatives that lack an analytical approximation for their mark-to-market (MtM) value, such as Bermudan swaptions, the standard practice is to use the regression functions from the least squares Monte Carlo method to approximate their simulated MtMs. However, such approximations have significant bias and noise, resulting in an inaccurate CVA charge. This paper extend the SGBM to efficiently compute expected exposure, potential future exposure, and CVA for Bermudan swaptions. A novel contribution of the paper is that it demonstrates how different measures, such as spot and terminal measures, can simultaneously be employed in the SGBM framework to significantly reduce the variance and bias.Paper 4. This paper presents an algorithm for simulation of options on LĂ©vy driven assets. The simulation is performed on the inverse transition matrix of a discretised partial differential equation. We demonstrate how one can obtain accurate option prices and deltas on the variance gamma (VG) and CGMY model through finite element-based Monte Carlo simulations

    Visually-guided timing and its neural representation

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    Stimulus-driven timing is a fundamental aspect of human and animal behavior. This type of timing can be subdivided into three principal axes: interval generation, storage, and evaluation. In this thesis, we present results related to each of these axes and describe their implications for how we understand timed behavior. In Chapter 2, we address interval generation, which is the process of creating an internal representation of an ongoing temporal interval. While several studies have found evidence for neural oscillators which may subserve this function, it has remained an open question whether such a mechanism can be useful for timing at even the lowest level of cortex. To address this question, we analyze electrophysiological data collected from rats performing a timing task and find evidence that, indeed, timed reward-seeking behavior tracks oscillatory states in primary visual cortex. This kind of finding raises an important question: how is this temporal information stored after the interval has been generated? This process is called interval storage, and we address the sources of noise that might corrupt it in Chapter 3. Specifically, we devise a novel timing task for humans (BiCaP) to address whether memory biases can account for performance on a classification task, in which a subject must decide whether a test interval is more similar to one or another reference interval. We find that they do, and argue that these sources of noise must be accounted for in theories of timing. In Chapter 4, we deal with interval evaluation which is the process of using this stored temporal information to make valuation decisions. We study this process through the lens of foraging behavior. Specifically, we develop and test a framework that rationalizes observed spatial search patterns of wild animals and humans by accounting for the temporal information they gather about their environment, and how they discount delayed rewards (temporal discounting). Lastly, in Chapter 5, we discuss how these processes are integrated and the implications of these findings for theories of timing
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