Arbitrage Pricing Theory as a Restricted Nonlinear Multivariate Regression Model: Iterated Nonlinear Seemingly Unrelated Regression Estimates

1988 ◽  
Vol 6 (1) ◽  
pp. 29 ◽  
Author(s):  
Marjorie B. McElroy ◽  
Edwin Burmeister
Keyword(s):  
Regression Model ◽  
Multivariate Regression ◽  
Seemingly Unrelated Regression ◽  
Arbitrage Pricing Theory ◽  
Arbitrage Pricing ◽  
Multivariate Regression Model ◽  
Unrelated Regression ◽  
Pricing Theory

ARBITRAGE PRICING THEORY IN ERGODIC MARKETS

2018 ◽  
Vol 21 (05) ◽  
pp. 1850036 ◽  
Author(s):  
GABRIEL FRAHM
Keyword(s):  
Factor Model ◽  
Relative Number ◽  
Seemingly Unrelated Regression ◽  
Arbitrage Pricing Theory ◽  
Arbitrage Pricing ◽  
Expected Return ◽  
Unrelated Regression ◽  
Pricing Theory ◽  
Equilibrium Market ◽  
Traditional Approaches

Traditional approaches to Arbitrage Pricing Theory (APT) propose a factor model, but empirical applications of APT are, nowadays, based on seemingly unrelated regression. I drop the factor model and assume only that the market is ergodic. This enables me to apply the theory of Hilbert spaces in a natural way. The expected return on any asset can always be approximated by an affine-linear function of its betas and we are able to estimate the relative number of assets that violate the APT equation by taking the expected returns and betas in the market into account. I present a simple sufficient condition for the APT equation in its inexact form. Further, I show that the APT equation holds true in its exact form if and only if an equilibrium market is exhaustive, which means that it must be possible to replicate the betas and idiosyncratic risk of each asset by some strategy that diversifies away all approximation errors in the market.

scholarly journals Valuation of Government Bonds: the Exchange Rate Is an Important Aspect

2017 ◽  
Vol 65 (6) ◽  
pp. 1911-1916
Author(s):  
Blanka Francová
Keyword(s):  
Regression Model ◽  
Interest Rates ◽  
Arbitrage Pricing Theory ◽  
Arbitrage Pricing ◽  
Data Set ◽  
Government Bonds ◽  
Exchange Risk ◽  
Pricing Theory ◽  
Multi Linear Regression ◽  
The Relationship

Interest rates are currently very low in the countries. In these countries bonds are issued with low or negative yields. In this paper, I empirically investigate the factors that affect the price of bonds. I follow international arbitrage pricing theory to determine the relationship between factors and the price of bonds. The international arbitrage pricing theory applies a multi‑linear regression model. The regression model is used for emerging markets and developing markets separately. I have a unique data set of 46 countries. The main data are the monthly returns on government bonds in the period 2010–2015. Exchange risk influences the bond prices. Currency movements can bring further yield for investors.

scholarly journals L2,1-norm regularized multivariate regression model with applications to genomic prediction

2021 ◽  
Author(s):  
Alain J Mbebi ◽  
Hao Tong ◽  
Zoran Nikoloski
Keyword(s):  
Variable Selection ◽  
Regression Model ◽  
Multivariate Regression ◽  
Statistical Testing ◽  
Supplementary Information ◽  
Nucleotide Polymorphisms ◽  
Multiple Traits ◽  
Multivariate Regression Model ◽  
Proposed Model ◽  
Iterative Optimization Algorithm

AbstractMotivationGenomic selection (GS) is currently deemed the most effective approach to speed up breeding of agricultural varieties. It has been recognized that consideration of multiple traits in GS can improve accuracy of prediction for traits of low heritability. However, since GS forgoes statistical testing with the idea of improving predictions, it does not facilitate mechanistic understanding of the contribution of particular single nucleotide polymorphisms (SNP).ResultsHere, we propose a L2,1-norm regularized multivariate regression model and devise a fast and efficient iterative optimization algorithm, called L2,1-joint, applicable in multi-trait GS. The usage of the L2,1-norm facilitates variable selection in a penalized multivariate regression that considers the relation between individuals, when the number of SNPs is much larger than the number of individuals. The capacity for variable selection allows us to define master regulators that can be used in a multi-trait GS setting to dissect the genetic architecture of the analyzed traits. Our comparative analyses demonstrate that the proposed model is a favorable candidate compared to existing state-of-the-art approaches. Prediction and variable selection with datasets from Brassica napus, wheat and Arabidopsis thaliana diversity panels are conducted to further showcase the performance of the proposed model.Availability and implementation: The model is implemented using R programming language and the code is freely available from https://github.com/alainmbebi/L21-norm-GS.Supplementary informationSupplementary data are available at Bioinformatics online.

scholarly journals Rectal Staphylococcus aureus Carriage and Recurrence After Endoscopic Sinus Surgery for Chronic Rhinosinusitis With Nasal Polyps: A Prospective Cohort Study

2021 ◽  
pp. 014556132110197
Author(s):  
Yue Peng ◽  
Zhao Liu ◽  
Zhijian Yu ◽  
Aiwu Lu ◽  
Tao Zhang
Keyword(s):  
Staphylococcus Aureus ◽  
Cohort Study ◽  
Regression Model ◽  
Chronic Rhinosinusitis ◽  
Endoscopic Sinus Surgery ◽  
Prospective Cohort ◽  
Multivariate Regression ◽  
Nasal Polyps ◽  
Sinus Surgery ◽  
Multivariate Regression Model

Objective: Chronic rhinosinusitis with nasal polyps (CRSwNPs) remains a major challenge due to its high recurrence rate after endoscopic sinus surgery (ESS). We aimed to investigate the risk factors of recurrence among patients who underwent ESS for Chronic rhinosinusitis (CRS). Methods: Prospective cohort study including 391 cases in a single institution receiving ESS were included for analysis from 2014 and 2017. Baseline characteristics including rectal Staphylococcus aureus ( S aureus) carriage in patients receiving ESS for CRSwNPs. The primary outcome was the recurrence of CRSwNPs. Multivariate regression model was established to identify independently predictive factors for recurrence. Results: Overall, 142 (36.3%) cases with recurrence within 2 years after ESS were observed in this study. After variable selection, multivariate regression model consisted of 4 variables including asthma (odds ratio [OR] = 3.41; P < .001), nonsteroidal anti-inflammatory drug allergy (OR = 2.27; P = .005), previous ESS (OR = 3.64; P < .001), and preoperative carriage of S aureus in rectum (OR = 2.34; P = .001). Conclusions: Based on our results, surgeons could predict certain groups of patients who are at high risk for recurrence after ESS. Rectal carriage of S aureus is more statistically related to the recurrence of CRSwNP after ESS compared with skin and nasal carriage.

Sign in / Sign up

Export Citation Format

Share Document