{"title":"Using directional bit sequences to reveal the property-liability underwriting cycle as an algorithmic process","authors":"Joseph D. Haley","doi":"10.3233/AF-170172","DOIUrl":null,"url":null,"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.","PeriodicalId":42207,"journal":{"name":"Algorithmic Finance","volume":"6 1","pages":"3-21"},"PeriodicalIF":0.3000,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/AF-170172","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Algorithmic Finance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/AF-170172","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍:
Algorithmic Finance is both a nascent field of study and a new high-quality academic research journal that seeks to bridge computer science and finance. It covers such applications as: High frequency and algorithmic trading Statistical arbitrage strategies Momentum and other algorithmic portfolio management Machine learning and computational financial intelligence Agent-based finance Complexity and market efficiency Algorithmic analysis of derivatives valuation Behavioral finance and investor heuristics and algorithms Applications of quantum computation to finance News analytics and automated textual analysis.