Predicting exchange rate volatility: genetic programming vs. GARCH and RiskMetrics

This article investigates the use of genetic programming to forecast out-of-sample daily volatility in the foreign exchange market. Forecasting performance is evaluated relative to GARCH(1,1) and RiskMetrics models for two currencies, DEM and JPY. Although the GARCH/RiskMetrics models appear to have a inconsistent marginal edge over the genetic program using the mean-squared-error (MSE) and R2 criteria, the genetic program consistently produces lower mean absolute forecast errors (MAE) at all horizons and for both currencies.Foreign exchange rates ; Forecasting ; Programming (Mathematics)

Bayesian inference for dynamic choice models without the need for dynamic programming

Programming (Mathematics)

A New Reduction from Search SVP to Optimization SVP

It is well known that search SVP is equivalent to optimization SVP. However, the former reduction from search SVP to optimization SVP by Kannan needs polynomial times calls to the oracle that solves the optimization SVP. In this paper, a new rank-preserving reduction is presented with only one call to the optimization SVP oracle. It is obvious that the new reduction needs the least calls, and improves Kannan's classical result. What's more, the idea also leads a similar direct reduction from search CVP to optimization CVP with only one call to the oracle

The Lax conjecture is true

In 1958 Lax conjectured that hyperbolic polynomials in three variables are determinants of linear combinations of three symmetric matrices. This conjecture is equivalent to a recent observation of Helton and Vinnikov.Comment: 7 pages, Proceedings to the AMS, to appear. Added background materia