Founder & Head of Research, Fortress Hill Advisors

Alex Ng

Alex Ng is the founder and head of research of the economic and investment research house Fortress Hill Advisors. Prior to founding Fortress Hill Advisors, he worked as an economic research analyst across government, academic, and financial institutes including the Hong Kong Financial Secretary’s Office (Office of the Government Economist), Economic Research Center of the Institute of Asia-Pacific Studies at CUHK, and State Street Global Markets. Alex holds a Master of Arts in Economics degree from Columbia University in the City of New York and a Bachelor of Arts in Economics and Mathematics from Wesleyan University (CT, USA).

Our firm's expertise lies in macroeconomics, global macro,  global thematic research, company and equity research, multi-asset strategy, event driven, and ESG.

We also do proprietary trading on the firm's capital, to try to vindicate our investment thesis. Our flagship publication, Heard from Fortress Hill (HFFH) provides our weekly market observations and is freely available on our website: https://fortresshill-advisors.com/hffh/

Founder & Head of Research

U.S. September Nonfarm Payroll - A Strong Month and Less Downside Risk

US Banks - Strong Weekly Balance Sheet Figures for Loans, Loan Loss Reserves and Time Deposits

US August Nonfarm Payroll Suggests Only 25 Bps Rate Cut

US Nonfarm Payroll Change 272k (consensus 185k) in May-24

US Nonfarm Payroll Change 206k (consensus 190k) in Jun-24

US July Job Reports: Shifting Away to Services Sector

Fortress Hill Advisors

Founded in Hong Kong in 2019, Fortress Hill Advisor seeks to provide premium economic and financial researches.

Premium Economic & Investment Research

Macroeconomics

<ul>
<li>Klein (2022)* found that prediction quality varies across economists and rejected the hypothesis of equal predictive ability. It is worth building our proprietary model on monthly changes of nonfarm payroll.</li>
<li>We follow Bhatia (2020)# and add improvement on our own to arrive at our proprietary nonfarm payroll prediction model. The growth in payrolls is surprisingly stationary.</li>
<li>Public impressions fall prey to the recency bias that assumes the most recent experience is a signal of the future that is distinct from the past.</li>
</ul>


Klein (2022)* found that prediction quality varies across economists and rejected the hypothesis of equal predictive ability. It is worth building our proprietary model on monthly changes of nonfarm payroll.
We follow Bhatia (2020)# and add improvement on our own to arrive at our proprietary nonfarm payroll prediction model. The growth in payrolls is surprisingly stationary.
Public impressions fall prey to the recency bias that assumes the most recent experience is a signal of the future that is distinct from the past.


Proprietary Nonfarm Payroll Prediction Model: Methodology and Sep 2024 Prediction