Authors: Maymin, Philip

Article Type: Editorial

DOI: 10.3233/AF-170061

Citation: Algorithmic Finance, vol. 6, no. 1-2, pp. 1-1, 2017

Authors: Haley, Joseph D.

Article Type: Research Article

Abstract: This paper presents a computational economics model of the property-liability insurance underwriting cycle. This computer experiment is built on downward-sloping demand, a simplistic version of the capacity constraint model of insurance supply, and a simple pricing rule. The pricing rule has each experimental insurer determine its price from the expected losses per-policy (a constant), the previous year’s policyholders’ surplus and the previous year’s number of customers. Through the use of directional bit sequences a common structure is revealed between the simulated aggregate underwriting margin and the actual aggregate underwriting margin, 1930–2000. The common structure between these aggregate variables is evidence …the property-liability underwriting cycle, in a consistent effort to reach equilibrium, follows an algorithmic process. Of more general inference; the pursuit of equilibrium, as an attractor, is the only consistent characteristic of the algorithmically generated process. This algorithmic process precludes the notion of a consistent continuous probability distribution being the basis of a data generating process (DGP). The times series behavior of the simulated underwriting margin, as it fluctuates around the equilibrium attractor, can assume a variety of shapes across many realizations of the algorithmic process. Finally, behavior of the simulated individual companies is not, for the most part, correlated with the aggregate behavior, and virtually all individual transactions are out-of-equilibrium transactions in the sense that they occur along the demand curve. Show more

Keywords: Simulation, capacity constraint model, property-liability underwriting cycle, equilibrium

DOI: 10.3233/AF-170172

Citation: Algorithmic Finance, vol. 6, no. 1-2, pp. 3-21, 2017

Authors: Korotkov, E.V. | Korotkova, M.A.

Article Type: Research Article

Abstract: The purpose of this study was to detect latent periodicity in the presence of deletions or insertions in the analyzed data, when the points of deletions or insertions are unknown. A mathematical method was developed to search for periodicity in the numerical series, using dynamic programming and random matrices. The developed method was applied to search for periodicity in the Euro/Dollar (Eu/$) exchange rate. The presence of periodicity within the period length equal to 24 hours and 25 hours, in the analyzed financial series, was shown. Periodicity can be detected only with insertions and deletions. The results of this study …show that periodicity phase shifts, depend on the observation time. A period of 24 hours is a common phenomenon for foreign exchange rates, indices and stocks of different companies. We show it for the Bank of America and Microsoft stocks, S&P500 and NASDAG indexes and for the gold and silver prices as examples. The reasons for the existence of the periodicity in the financial ranks are discussed. The results can find application in computer systems, for the purpose of forecasting exchange rates. Show more

Keywords: Latent periodicity, dynamic programming, rates, random matrixes, insertions, deletions

DOI: 10.3233/AF-170182

Citation: Algorithmic Finance, vol. 6, no. 1-2, pp. 23-33, 2017

Authors: Capriotti, Luca | Jiang, Yupeng | Macrina, Andrea

Article Type: Research Article

Abstract: We show how Adjoint Algorithmic Differentiation (AAD) can be used to calculate price sensitivities in regression-based Monte Carlo methods reliably and orders of magnitude faster than with standard finite-difference approaches. We present the AAD version of the celebrated least-square algorithms of Tsitsiklis and Van Roy (2001) and Longstaff and Schwartz (2001) . By discussing in detail examples of practical relevance, we demonstrate how accounting for the contributions associated with the regression functions is crucial to obtain accurate estimates of the Greeks, especially in XVA applications.

Keywords: Adjoint algorithmic differentiation (AAD), Monte Carlo methods, Bermudan-style options, valuation adjustments (XVA)

DOI: 10.3233/AF-170201

Citation: Algorithmic Finance, vol. 6, no. 1-2, pp. 35-49, 2017

Authors: Montenegro, Mariana Rosa | Albuquerque, Pedro Henrique Melo

Article Type: Research Article

Abstract: This work aims at the development of an enhanced portfolio selection method, which is based on the classical portfolio theory proposed by Markowitz (1952) and incorporates the local Gaussian correlation model for optimization. This novel method of portfolio selection incorporates two assumptions: the non-linearity of returns and the empirical observation that the relation between assets is dynamic. By selecting ten assets from those available in Yahoo Finance from S&P500, between 1985 and 2015, the performance of the new proposed model was measured and compared to the model of portfolio selection of Markowitz (1952) . The results showed that the …portfolios selected using the local Gaussian correlation model performed better than the traditional Markowitz (1952) method in 63% of the cases using block bootstrap and in 71% of the cases using the standard bootstrap. Comparing the calculated Sharpe ratios, the proposed model yielded a better adjusted risk-return in the majority of the cases studied. Show more

Keywords: Portfolio selection, local Gaussian correlation, nonlinear dependence

DOI: 10.3233/AF-170203

Citation: Algorithmic Finance, vol. 6, no. 1-2, pp. 51-65, 2017