Sitemap
A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Posts
Future Blog Post
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Blog Post number 4
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 2
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 1
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
portfolio
Portfolio item number 1
Short description of portfolio item number 1
Portfolio item number 2
Short description of portfolio item number 2
publications
Exploring the Impact of the U.S. Macroeconomy on the Chinese Stock Market - Based on Market and Individual Stock Dimensions
Profile: Course Project, 2022
This paper Employed the PLS method to analyze the volatility of the Chinese stock market, using 120 macroeconomic variables from the FRED-MD database in the United States. The results indicate a significant relationship with factors such as the global economic system, supply chain dynamics, and the China-US trade war. This paper also calculated the systemic risk posed by Chinese companies to the US macroeconomy, using macroeconomic indicators and individual stock returns, and applied PCA and Sparse-PCA for dimensionality reduction. Found that Sparse-PCA improves the economic interpretability of the 10 principal components more effectively than traditional PCA methods
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Fundamental Factors and Stock Returns - Based on Machine Learning Methods
Profile: Course Project, 2022
This paper utilized 207 fundamental and volume-price factors in the US stock market from January 1985 to October 2022, and employed 10 machine learning algorithms, including linear regression, penalized linear regression, tree methods, and neural networks, to synthesize factor signals and construct investment portfolios. Empirical findings demonstrated that machine learning algorithms effectively discerned the relationship between anomalies (factors) and returns. With a 1-year training window and monthly rebalancing, long-short portfolios yielded average annualized returns between 16.5% and 22.8%, with Sharpe ratios ranging from 0.69 to 1.43. Adjusting the training window to 3 months and 24 months resulted in annualized returns and Sharpe ratios spanning from 11.9% to 19.6%, 0.57 to 1.18; and from 4.96% to 21.2%, 0.59 to 1.54, respectively
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talks
如果把今天，作平常的一天过
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一篇不那么正式的年终总结…
别赶路，感受路
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一篇随记…
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.