{"ok":true,"nota":{"id":"f0cf8951dd17ebdd","slug":"un-metodo-matematico-para-calcular-precios-de-opciones-financieras-evi-f0cf89","titulo":"Un método matemático para calcular precios de opciones financieras evita errores por datos ruidosos","resumen":"El autor propone un método de regularización para estimar la volatilidad implícita a partir de precios de mercado. Compara criterios automáticos con criterios basados en la diferencia entre compra y venta, y evalúa qué parámetro funciona mejor.","fuente":"zenodo","fuenteNombre":"Zenodo · Investigación abierta","color":"#1682d4","autor":"Avtonomov, Petr","url":"https://doi.org/10.5281/zenodo.23473607","imagen":"/hoy/portada/f0cf8951dd17ebdd","tema":"economia","subtemas":["mercados financieros","opciones","volatilidad","modelos matematicos","riesgo"],"entidades":["Zenodo","Black-Scholes","Dupire"],"formato":"dato","entretenimiento":false,"pubTs":"2026-10-28T14:47:28.000Z","indexTs":"2026-10-30T00:40:35.175Z","hash":"96e25c1cd938660f12f9c83e22651deb98aeb0537a88192ac8078d9c74e99625","tsa":{"time":"Oct 30 00:41:20 2026 GMT","provider":"freetsa.org","sobre":"sello"},"stats":{"views":0,"likes":0,"clicks":0,"dwell":0},"tipo":"normal","registro":"hallazgo","porQueImporta":"Los precios de las opciones que se negocian en los mercados traen ruido, y calcular de forma directa sobre ellos produce resultados absurdos y oscilantes. El trabajo muestra que suavizar esos cálculos con una penalización matemática da números más razonables para valuar riesgos. Para quien ahorra o invierte, esto explica por qué los modelos financieros que usan los bancos no son tan exactos como parecen. Del otro lado, el método sigue siendo una propuesta de una sola persona y no fue validado con datos de mercados argentinos.","quienFirma":"Preprint en Zenodo (autor individual, sin institución principal declarada)","confianza":"preprint","consulta":null},"sello":{"hash":"96e25c1cd938660f12f9c83e22651deb98aeb0537a88192ac8078d9c74e99625","sello":"cc9eaca9bf6eaa01e1c94a8811f4a854e6f7fbfcecde735ec1c6931e1157adca","beacon":{"drand":{"cadena":"8990e7a9aaed2ffed73dbd7092123d6f289930540d7651336225dc172e51b2ce","ronda":6596328,"aleatorio":"9d983852a683e9f8b9f18f2510f7481834a83814cf6f7683d7808c4e512554dc","tiempo":"2026-10-30T00:41:00.000Z"},"nist":{"cadena":2,"pulso":2005097,"salida":"FE7ED64332A6455A1756D4CC13E2C4432712FA769BD2BD3F70B2CCB4E06AADB39EFF9B48C1E43A122F614C7F58F10DDACEFBCA37D488FBBC6025BBF5DAD1AEA5","tiempo":"2026-10-30T00:39:00.000Z"},"noAntes":"2026-10-30T00:41:00.000Z"},"verificacion":{"drand":true,"nist":true},"tsa":{"time":"Oct 30 00:41:20 2026 GMT","provider":"freetsa.org","sobre":"sello"},"original":{"titulo":"Implied Volatility as an Ill-Posed Inverse Problem: A Constrained Regularization Approach","descripcion":"<p class=\"ds-markdown-paragraph\"><span class=\"\">Classical financial models, such as Black-Scholes, assume constant volatility. In reality, inverting market prices to extract implied volatility reveals a non-linear U-shaped distortion known as the \"volatility smile\" or \"skew.\" In this paper, I demonstrate that recovering the local volatility surface (Dupire model) is a severely ill-posed inverse problem. Naive point-by-point inversion of market prices amplifies bid-ask noise into chaotic, physically meaningless oscillations.</span></p> <p class=\"ds-markdown-paragraph\"><span class=\"\">To resolve this, I propose a constrained regularization approach using a Tikhonov penalty on the second derivative (curvature) of the volatility curve. By comparing automatic criteria (L-curve) with market-based criteria (bid-ask spread), I show that the optimal regularization parameter acts as the \"price of i","pubDate":"2026-10-28T14:47:28Z","url":"https://doi.org/10.5281/zenodo.23473607"},"indexado":"2026-10-30T00:40:35.175Z"}}