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An efficient application of the extended path algorithm in Matlab with examples

Binning, Andrew - 2022

Recent experience with interest rates hitting the effective lower bound and agents facing binding borrowing constraints has emphasised the importance of understanding the behaviour of an economy in which some variables may be restricted at times. The extended path algorithm is a commonly used...

Persistent link: https://www.econbiz.de/10013365558

Portfolio Construction Using Predictive Linear Model – An Adaptive Multi-Objective Approach

Mobasheri, Amir - 2019

integrated framework to examine whether a real-time optimizing investor can benefit from the stock market by allocating assets … on the output of the forecasting model. All aforementioned steps only use data up to the current time and before the … forecasting time. The results are compared to common benchmarks such as the buy-and-hold strategy and additional benchmarks that …

Persistent link: https://www.econbiz.de/10012868096

Portfolio allocation for European markets with predictability and parameter uncertainty

Jondeau, Eric; Rockinger, Michael - 2010

We implement a long-horizon static and dynamic portfolio allocation involving a risk-free and a risky asset. This model is calibrated at a quarterly frequency for ten European countries. We also use maximum-likelihood estimates and Bayesian estimates to account for parameter uncertainty. We find...

Persistent link: https://www.econbiz.de/10008797745

Optimal Selection of Expert Forecasts with Integer Programming

Matsypura, Dmytro - 2017

Combinations of point forecasts from expert forecasters are known to frequently outperform individual forecasts. It is also well documented that combination by simple averaging very often has performance superior to that of more sophisticated combinations. This empirical fact is referred to as...

Persistent link: https://www.econbiz.de/10012966346

Lasso-Type and Heuristic Strategies in Model Selection and Forecasting

Savin, Ivan - 2012

Several approaches for subset recovery and improved forecasting accuracy have been proposed and studied. One way is to apply a regularization strategy and solve the model selection task as a continuous optimization problem. One of the most popular approaches in this research field is given by...

Persistent link: https://www.econbiz.de/10013099334

Assessing multivariate predictors of financial market movements : a latent factor framework for ordinal data

Huber, Philippe; Scaillet, Olivier; Victoria-Feser, … - 2008

Much of the trading activity in Equity markets is directed to brokerage houses. In exchange they provide so-called quot;soft dollarsquot; which basically are amounts spent in quot;researchquot; for identifying profitable trading opportunities. Soft dollars represent about USD 1 out of every USD...

Persistent link: https://www.econbiz.de/10003966616

Lasso-type and heuristic strategies in model selection and forecasting

Savin, Ivan; Winker, Peter - 2012

Persistent link: https://www.econbiz.de/10009630302

Forecasting economic variables with nonlinear models

Teräsvirta, Timo (contributor) - 2005 - Rev. December 29, 2005

This article is concerned with forecasting from nonlinear conditional mean models. First, a number of often applied nonlinear conditional mean models are introduced and their main properties discussed. The next section is devoted to techniques of building nonlinear models. Ways of computing...

Persistent link: https://www.econbiz.de/10002847459

SV mixture : classification using EM algorithm

Hachicha, Ahmed; Hachicha, Fatma; Masmoudi, Afif - 2013

The present paper presents a theoretical extension of our earlier work entitled“A comparative study of two models SV with MCMC algorithm” cited, Rev Quant Finan Acc (2012) 38:479-493 DOI 10.1007/s11156-011-0236-1 where we propose initially a mixture stochastic volatility model providing a...

Persistent link: https://www.econbiz.de/10009755511

Uncertain Covariance Models and Uncertainty-Penalized Portfolio Optimization

Shah, Anish - 2021

Covariance appears throughout investment management, e.g., in risk reporting and control, portfolio construction, risk parity, smart beta, algorithmic trading, and hedging. It is usually represented via multi-factor model. The form’s fewer parameters and structure—comovement through...

Persistent link: https://www.econbiz.de/10013251623