Research

Work in Progress

“The American `Reparations' That Weren't” (Draft Available by July 2025)

In one of the most prominent revisionist arguments of financial history, Stephen Schuker inverted the Weimar reparations narrative. He contends that far from being crushed by its treaty obligations, Weimar Germany was a net beneficiary, (1)receiving ``reparations'' equivalent to 2.1% of national income from 1919--1931, {(2)}~paid by largely gullible and irrationally optimistic American investors at a negative and unjustifiable risk premium. This essay refutes both of these claims. Systematic reconstruction of balance of payments data reveals that net foreign resource transfers during 1924-1931 averaged only 0.6% of national income. Achieving Schuker's figure would require the hyperinflation years (1919-1923) to have sustained annual inflows exceeding 4.5% of GNI every single year, which is highly implausible given documented capital flight and chaos. The corrected figure of 0.6% indicates that Germany functioned not as a net beneficiary but as an intermediary, with reparations absorbing 70% of foreign capital inflows. This dependence created a precarious financial structure that collapsed when credit flows reversed in 1929 and bottomed in 1931. Schuker correctly identified how foreign capital incentivized German policymakers to avoid fiscal adjustment, but his inflated aggregate figure misrepresents the outcome of this strategy. The corrected data recasts Weimar Germany not as a privileged net beneficiary, but as a fragile financial intermediary whose solvency was predicated on using foreign loans to service its political debts.

Questionable Research Ideas:

Here is a list of bad economics research ideas I have from brain-fuzz and drawing from daily inspirations from random encounters of papers: they are often challenging, undesirable, and difficult to research but nonetheless interesting. If you are an economics or economic history researcher: you would be more than welcome to take look! 

If you spot potential in any of these ideas - perhaps you know of relevant datasets, can suggest improved empirical strategies, or see ways to make them more feasible - I'd love to hear from you. I'm also open to potential collaboration. Feel free to reach out at sihao.feng@stcatz.ox.ac.uk

Curating Alpha: The Predictive Power of Institutional Narratives in the Art Market

Asset pricing paradigms struggle where value is socially constructed, as in the art market, relying on expert narratives rather than discernible cash flows. This paper pioneers an approach to empirically capture these narratives, testing whether the quantifiable dynamics of institutional validation predict long-run art market returns. We move beyond standard financial data to construct unique, century-long time-series indices reflecting shifts in expert consensus. These indices codify the evolving endorsement from key arbiters of taste—museum acquisitions, major exhibitions, and scholarly attention—across granular art categories. The central hypothesis posits that lagged changes in these publicly visible, yet costly-to-process, signals of institutional legitimacy act as a latent factor, predicting future price appreciation distinct from standard risk exposures or price-based momentum effects. We investigate if the slow diffusion and interpretation of this qualitative, expert-driven information create systematic return predictability in this notoriously heterogeneous, illiquid market with limited arbitrage. Operationalizing institutional narratives into predictive signals allows a rigorous test of how subjective expert validation influences asset prices. We examine if the slow incorporation of these quantifiable public signals generates return predictability distinct from known factors, providing insights into price formation and market efficiency for assets reliant on qualitative assessment.

St. Catherine’s College, University of Oxford