Static arbitrage bounds on basket option prices
By Alexandre d'Aspremont, Laurent El Ghaoui. Mathematical programming, 2003
1,143 citations recorded by the source corpus.
We consider the problem of computing upper and lower bounds on the price of an European basket call option, given prices on other similar options. Although this problem is hard to solve exactly in the general case, we show that in some instances the upper and lower bounds can be computed via simple closed-form expressions, or linear programs. We also introduce an efficient linear programming relaxation of the general problem based on an integral transform interpretation of the call price function. We show that this relaxation is tight in some of the special cases examined before.
Subfields: Economics and Econometrics, Finance
View Paper: https://www.semanticscholar.org/paper/02423b50bb82d1b4c22d08e0107b12a221aa7a6b
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Citations in the corpus
- A Damped Gauss-Newton Method for the Second-Order Cone Complementarity Problem (2009, methodology): “When g is a linear function, (4) reduces to the standard second-order cone program which has extensive applications in engineering design, finance, control, and robust optimization; see [1, 14] and references therein.”
- Autonomous Trajectory Planning for Rendezvous and Proximity Operations by Conic Optimization (2012, background): “A standard SOCP problem is a convex optimization problemwith a linear cost function, equality constraints, and secondorder conic inequality constraints (linear inequality constraints are special cases of second-order cones) [15–17].”
- Distributionally robust joint chance constraints with second-order moment information (2011, background): “In this case, the chance constrained problem becomes a tractable second-order cone program (SOCP), which can be solved in polynomial time, see Alizadeh and Goldfarb [1].”
- Entry Trajectory Optimization by Second-Order Cone Programming (2016, background): “Second-order cone programming (SOCP), a subclass of convex optimization, where the cost function is linear, subject to linear equality and second-order cone constraints [12–14], has proved to be particularly appealing.”
- A Fully Distributed Reactive Power Optimization and Control Method for Active Distribution Networks (2014, background): “SOCP problems are typically solved using convex programming [26], and a global optimal solution can be found using interior point methods in polynomial time [27].”
- Distributionally Robust Convex Optimization (2014, background): “We refer interested readers to [6, 7, 11] for comprehensive guides to reformulating robust counterparts.”
- A constrained robust least squares approach for contaminant release history identification (2006, methodology): “El Ghaoui and Lebret [1997] solved the problem using convex second-order cone programming, which is a subclass of the more general semidefinite programming [Alizadeh and Goldfarb, 2003; Lobo et al., 1998].”
- Living on the edge: phase transitions in convex programs with random data (2013, methodology): “. In particular, the cone Circd(… 4 ) is isometric to the second-order cone L d. Circular cones have numerous applications in optimization; we refer the reader to [BV04, Sec. 4], [BTN01, Sec. 3], and [AG03] for details. We can obtain an accurate expression for the statistical dimension of a circular”
- A new primal-dual path-following method for convex quadratic programming (2006, neutral): “, [2, 4, 5, 6, 7].”
- Interior Point Methods for Nonlinear Optimization (2010, background): “For more details see [3, 11, 88, 91] and the references therein.”
- General closed-form basket option pricing bounds (2016, background): “Then, in a series of papers, Laurence and Wang (2004, 2005), Hobson et al. (2005a, 2005b) and D’Aspremont and El Ghaoui (2006) derived distribution-free bounds in the case of basket options with positive weights.”
- Three-dimensional Mohr-Coulomb limit analysis using semidefinite programming (2007, methodology): “Thus, a large literature exists on the appropriate choice of the analogous set of conditions enabling application of Newton’s method in the same manner as for linear programming [21, 23–30].”
- Robust portfolio selection under downside risk measures (2009, background): “One can refer to Lobo et al. (1998) and Alizadeh and Goldfarb (2003) for the details on secondorder cone programming which has been extensively investigated in the last decade.”