35 verified PDFs
by AR van Rosendael · 2018 · Cited by 214 — The Machine learning score shows the highest predictive performance compared with the other coronary com- puted tomography angiography scores.
by D Dobrev · 2010 · Cited by 77 — In order to find the contribution of high frequency information, similarly to our one- factor model, we consider two versions of the two factor model: (i) the ...
by RAY DALIO · 2011 · Cited by 39 — The All Weather approach to asset allocation leverages up low risk assets and deleverages high risk assets so that the expected returns and risks of all the ...
The review examined radiomics, machine-learning, and deep-learning techniques applied to CTA images for detecting stenosis, calcification, and ...
In this document, I'll mainly be focusing on quant trading rather than research. This is a place where buyers and sellers can meet to trade things.
'quantitative/ systematic' investing has been a growing force in the market (but remains a minority) — supported by technological improvements and data ...
We demonstrate how investors can use its results to better understand the nature of risks and exposures of various strategies, and the extent to ...
The ideas behind the research papers helped inspire and create this fast growing area called quant investing in the late 1990s and early 2000s.
Asset Allocation, i.e., allocating the investment capital to Equities, Fixed Income, Commodities and their subclasses.
by S Aleti · 2023 · Cited by 16 — I construct a novel dataset of 224 high-frequency factor portfolios in order to study the cross-section of expected returns in a continuous- ...
What is Quantitative Finance? • Application of the mathematics of uncertainty to problems concerning financial markets. • Most important : we don't (know ...
Traditional quant factors are the foundation of quant investing, alpha models included. Count does not include use of novel techniques in risk ...
The objective of this paper is to describe how an investor can define a target return, split between that of Strategic Asset Allocation (SAA) and excess return
Machine learning algorithms are capable to achieve automatic atherosclerotic plaques segmentation. Some of the methods have a fast processing ...
This is a reprint of articles from the Special Issue published online in the open access journal. Mathematics (ISSN 2227-7390) (available at: https://www.mdpi.
