Zobrazeno 1 - 10
of 33
pro vyhledávání: '"Chulwoo Han"'
Publikováno v:
European Journal of Operational Research. 307:929-947
This paper develops a pairs trading strategy via unsupervised learning. Unlike conventional pairs trading strategies that identify pairs based on return time series, we identify pairs by incorporating firm characteristics as well as price information
Autor:
Chulwoo Han
Publikováno v:
Management science, 0202, Vol.68(10), pp.7701-7741 [Peer Reviewed Journal]
This paper documents the bimodality of momentum stocks: both high- and low-momentum stocks have nontrivial probabilities for both high and low returns. The bimodality makes the momentum strategy fundamentally risky and can cause a large loss. To alle
Publikováno v:
SSRN Electronic Journal.
Publikováno v:
Annual International Conference on Accounting & Finance. 2018, p348-374. 27p.
Publikováno v:
Journal of financial markets, 2022, Vol.59(Part B), pp.100677 [Peer Reviewed Journal]
Using a robust measure that captures the market’s reaction to analysts’ target price releases, we show that the initial stock price reaction corresponds to target prices, but the price drifts in the opposite direction for a long period, resulting
Autor:
Chulwoo Han
Publikováno v:
Journal of banking and finance, 2020, Vol.120, pp.105953 [Peer Reviewed Journal]
This paper develops a shrinkage model for portfolio choice. It places a layer on a conventional portfolio problem where the optimal portfolio is shrunk towards a reference portfolio. The model can accommodate a wide range of portfolio problems with v
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2f6952dc5109e08f0eb9eb3292774679
http://dro.dur.ac.uk/31671/
http://dro.dur.ac.uk/31671/
Autor:
Frank C. Park, Chulwoo Han
Publikováno v:
Journal of Banking and Finance, 2022, Vol.134, pp.106319 [Peer Reviewed Journal]
Employing methods of differential geometry, we propose a new framework for covariance dynamics modeling. Our approach respects the intrinsic geometric properties of the space of covariance matrices and allows their natural evolution. We develop covar
Publikováno v:
International review of financial analysis, 2018, Vol.55, pp.156-169 [Peer Reviewed Journal]
This paper investigates the dynamics and drivers of credit risk discovery between stock and CDS markets in the US. Our research is distinguished from the existing literature in three aspects: 1) we employ an improved method to measure the information
Publikováno v:
Expert systems with applications, 2017, Vol.83, pp.187-205 [Peer Reviewed Journal]
Deep learning networks are applied to stock market analysis and prediction.A comprehensive analysis with different data representation methods is offered.Five-minute intraday data from the Korean KOSPI stock market is used.The network applied to resi