● SYS:LIVE │ USR:yeungtailo@gmail.com │ BUILD 2026.08.r19 │ CPU --% │ MEM -.-GB │ ON_MARKET ▮ LUGANO --:--:-- CET
Tai Lo Yeung Tai Lo Yeung

Iam a PhD candidate in the Department of Economics at USI. I received my bachelor’s degree in financial engineering from 武漢大學 (WHU) in 2014 and a research master’s in finance from 中國社會科學院研究生院 (GSCASS) in 2019, where I studied at the Institute of Finance and Banking. That training sparked my lasting interest in China’s financial development and economic policy. I then earned a master’s degree in economics from 香港科大商學院 (HKUST Business School) in 2020 and another master’s degree in economics and finance from Barcelona School of Economics (UPF) in 2021 with a full tuition waiver. I was a visiting scholar in the Finance Department at the Wharton School (UPenn), from January to June 2025, hosted by Prof. Sylvain Catherine.

I am a financial economist working in household finance. I study how households turn earnings into wealth and how they use that wealth when circumstances change, with a focus on earnings risk, experience and memory, and the institutions governing saving and housing.

Curriculum Vitæ [updated October 2026]

Research

My research in household and behavioral finance asks how households turn earnings into wealth and use that wealth when circumstances change. I study how earnings opportunities, financial experience, and the institutions governing saving and housing shape participation, accumulation, and asset sales. Combining longitudinal surveys in the United States and Japan with investor and housing records in China, I connect evidence on individual decisions to models of portfolio choice and exchange.

01

Earnings risk and financial accumulation

For working households, labor income finances current spending and provides the resources to build wealth. Uncertainty about future earnings can shape how much they save, how much investment risk they take, and when they enter financial markets. I study how adverse earnings shocks and opportunities for gains influence these decisions over the life cycle.

02

Experience and financial choice

Past financial gains and losses can influence household decisions long after they occur. What people remember and how they interpret these outcomes can shape their beliefs about risk and their willingness to invest. I study how financial experience and responsibility for past choices affect subsequent decisions and wealth accumulation.

03

Housing in household balance sheets

Housing is the largest asset on many households’ balance sheets. Its value and the ability to sell it can therefore influence saving, consumption, investment, and decisions about where to live. This central role motivates my interest in how households make decisions in housing markets and how those decisions shape their broader financial circumstances.

// next steps — connecting memory and beliefs to life-cycle models of financial participation and wealth accumulation

Fields of Interest

Primary

  • Household Finance
  • Behavioral Finance
  • Asset Pricing

Secondary

  • Chinese Economy
  • Urban Economics
  • Labor Economics

References

  1. Lorenz Kueng Institute of Economics (IdEP), USI · Swiss Finance Institute lorenz.kueng@usi.ch
  2. Jessica Wachter Department of Finance, The Wharton School · University of Pennsylvania jwachter@wharton.upenn.edu
  3. Alberto Plazzi Institute of Finance (IFin), USI · Swiss Finance Institute alberto.plazzi@usi.ch

News & Forthcoming

§ Video et Taceo §

Household finance · experience · memory · Chinese economy

Research

Filter
|
|
[01]
JEL  C18 · D14 · G11 · J31
JMP

Beyond Variance: Asymmetric Labor Income Risk and Portfolio Entry

Upside earnings opportunities predict stock-market entry at a given mean earnings growth and variance; a life-cycle model shows how earnings dynamics and saving responses shape households’ resources and participation.
Presented at: Fourth Georgia Tech – Atlanta Fed Household Finance Conference (Georgia Tech, 2026), AFA 2026 (Philadelphia, 2026), 19th International Behavioural Finance Conference (Booth School of Business, 2025), 14th International Moscow Finance Conference (HSE Moscow, 2025), SFI PhD Student Workshop (University of Zurich, 2025), 10th Luxembourg Workshop on Household Finance and Consumption (Central Bank of Luxembourg, 2025), German Finance Association (DGF) Annual Meeting 2025 Doctoral Workshop (University of Hagen, 2025), Gerzensee Alumni Conference (Study Center Gerzensee, 2024, 2025), Macro Finance Research Program (MFR) 2024 Summer Session for Young Scholars (University of Chicago, 2024), Frankfurt Summer School 2024 (The Deutsche Bundesbank, 2024), 2nd Workshop on Applied Macroeconomics and Monetary Policy (University of St. Gallen, 2024), RES PhD Conference 2024 (University of Portsmouth, 2024), USI IdEP Brown Bag (USI, 2023, 2024, 2025)
Show Figures
Portfolio entry and subsequent risky shares by initial ownership. A source-standard-deviation increase in upside composition predicts 1.60 percentage points more entry among initial nonholders, controlling for mean earnings growth and variance.
Upside earnings opportunities predict greater market entry at fixed mean and variance. Bars show 95% clustered confidence intervals.
Data and model entry gradients for the upper and lower earnings tails, alongside their earnings-law and decision-rule contributions. Cell-specific laws turn the upper-tail gradient positive and strengthen the negative lower-tail gradient relative to pooled laws.
Group-specific earnings dynamics recover opposing entry relationships missed by pooling, but model magnitudes remain smaller than in the data.
Controlled upside and downside earnings-composition changes lasting one year, five years, or the working life, holding conditional mean and variance fixed. The five-year upside change eventually lowers cumulative first entry; the working-life change is near zero after ten years. These are model illustrations, not fitted empirical magnitudes.
Duration matters for entry: the five-year upside effect reverses, while the working-life effect is near zero after ten years. Model illustration.
Financial wealth paths after controlled earnings-composition changes of different durations. Working-life upside lowers buffer saving for longer and produces a larger wealth shortfall than a five-year change; downside produces the opposite pattern. Effects are illustrative, not an empirical fit.
Persistent upside lowers buffer saving for longer and produces a larger wealth shortfall. Controlled model illustrations, not fitted empirical magnitudes.
[02]
JEL  D14 · D91 · G11 · G14 · G41
WORKING PAPERw/4

Navigating Through Fear and Greed: The Experience-Driven Disposition Effect

Past realized losses are associated with a stronger disposition effect and gains with a weaker one; a memory-based model offers an explanation through cue-dependent recall.
with Rong Liu (TJU), Jessica Wachter (Wharton), Michael Kahana (UPenn) and Yongjie Zhang (TJU)
Presented at: Finance Brownbag (University of Bristol, 2026), Workshop on Cognitive Economics (University of Zurich, 2026), SFS Cavalcade North America (University of Virginia, 2026), Memory, Beliefs, and Choice (MBC) (University of Pennsylvania, 2025), USI IdEP Brown Bag (USI, 2024)
Show Figures
Gain-by-loss and gain-by-win interaction coefficients across 5% to 30% return thresholds, opposite in sign throughout
Accumulated losses and gains are associated with opposite changes in the disposition effect.
[03]
JEL  G12 · G14 · R21 · R31
WORKING PAPER

When Price Stops Clearing: Valuation Disagreement and Housing Illiquidity

Larger asking-price deviations are associated with slower sales, more online saves, and fewer viewings; a search model links valuation difficulty to housing illiquidity.
Presented at: Rising Scholar Conference in Finance (University of Zurich, 2026), UEA Summer School (LSE, 2026), USI IdEP Brown Bag (USI, 2024)
Show Figures
Relative asking-price slopes for an indicator of a sufficiently precise recorded transaction date within thirteen weeks of posting, among completed transactions. Slopes are flatter in higher-dispersion markets. Panels use log-price and local standard-deviation units; whiskers show plus or minus one standard error. These are associations, not causal price-cut effects or sale probabilities.
Asking-price slopes are flatter in higher-dispersion markets. The outcome is a recorded-date indicator, not sale probability; whiskers show one standard error.
JEL  G11 · G40 · G41 · G51 · D14 · D91
WORK IN PROGRESSw/1

Not My Mistake

with Chaojie (Jay) Liu (Bristol)
Preliminary evidence compares the same investor across self-directed and robo-advised accounts, asking whether who chose the holdings changes how a gain or loss is acted upon.
JEL  D14 · D13 · E21 · J16 · J21
WORK IN PROGRESS

Scarred Balance Sheets: Labor-Market Entry and Women's Own Financial Buffers in Japan

Data: Panel Data Research Center (PDRC) at Keio University, Project ID: 10446
Weaker early labor markets are associated with smaller personal financial buffers among Japanese women, mainly deposits; common-age comparisons do not establish faster accumulation at equal income.
Data: Japanese Panel Survey of Consumers (JPSC), Panel Data Research Center at Keio University
Show Figures
Entry conditions and the distribution of women’s own financial assets. Each point estimates the association with holding at least the asset threshold shown; bars are pointwise 95% normal-reference intervals with childhood-prefecture-clustered standard errors. These are asset thresholds, not event time.
Entry conditions and the distribution of women’s own financial assets. Each point estimates the association with holding at least the asset threshold shown; bars are pointwise 95% normal-reference intervals with childhood-prefecture-clustered standard errors. These are asset thresholds, not event time.
JEL  H55 · J22 · J32 · J38
WORK IN PROGRESSw/1

Social Insurance Mandates and Earnings Adjustment: Evidence from Japan

with Yi Yao (USI)
Data: Panel Data Research Center (PDRC) at Keio University, Project ID: 9763
Adjustment to Japan’s employer insurance mandate differs with prior household coverage: dependent spouses show a larger announcement-to-enforcement decline in earnings-band membership than direct contributors.
Show Figures
Main-job earnings: annual adjustment and sensitivity of the enforcement-minus-announcement contrast. The earnings-band decline for dependent spouses reverses an announcement-period increase; net changes from the earlier baseline are less precisely estimated.
Main-job earnings: annual adjustment and sensitivity of the enforcement-minus-announcement contrast. The earnings-band decline for dependent spouses reverses an announcement-period increase; net changes from the earlier baseline are less precisely estimated.
JEL  R31 · I28 · D23 · H42
WORK IN PROGRESS

Grandfathering at Sale: Nonportable School Rights and Housing Exchange

Preserving owners’ school rights while resetting buyers’ rights is associated with 30–45% lower seasonal sales growth; timing evidence does not establish permanently lost sales.
Show Figures
A transfer resets school rights while eligible owners retain previous admission rules.
A transfer resets school rights while eligible owners retain previous admission rules.
Price-independent completed-sale counts for 111 formerly key-school and 102 ordinary-school communities, comparing winter-to-spring changes in 2017, 2018, and 2019. Three- and four-month windows show weaker relative sales growth in formerly key-school communities around January 2019; the chart does not establish permanently lost sales.
Price-independent sales counts show weaker seasonal growth in formerly key-school communities. Levels are recorded completions, not permanently lost sales.
JEL  J12 · J23 · N35 · O25 · P23
WORK IN PROGRESSw/1

Industrial Composition and Marriage Timing in China’s Third Front

with Yi Yao (USI)
Heavy-industry exposure is associated with greater young singlehood inside Third Front provinces, but cohort comparisons do not establish a causal effect of the construction campaign.
Presented at: GLO-Guangzhou-2026 (IESR, 2026), USI IdEP Brown Bag (USI, 2026)
Show Figure
The 1982 resident-stock marriage-age gradient is compared with pseudo-1982 gradients reconstructed from retrospective first-marriage histories in the 2000 census
The 1982 census stock and retrospective first-marriage histories deliver similar point estimates, but they describe differently selected populations.
i.

Python

Here is a highly recommended course to learn Python coding for economics:

ii.

MATLAB

  • Structural Estimation [in preparation]

A very good introductory lecture on structural estimation is available on YouTube, offered by Prof. Michael Keane.

iii.

R

  • Structural Estimation [in preparation]
Serkan Karadas and Minh Tam Tammy Schlosky, Determinants of Retirement Savings Decisions: Evidence from a 401(k) Plan
Chicago, IL —
Federico Baldi-Lanfranchi, Cost Savings in Mutual Funds
SFI PhD Student Workshop, Zurich —

Undergraduate

Essentials of Corporate Finance

Postgraduate

Empirical Methods in (Household) Finance

  • C0: TBC

Topics in Behavioral Finance

  • TBC

Structural Estimation

  • C0: This section introduces the simplest structural estimation framework from Blundell, Pistaferri, and Preston (2008), demonstrating how to apply the Generalized Method of Moments (GMM) to estimate parameters in a log-linear consumption model.
  • C1: TBC

Using Claude AI for Research

  • Slides: A hands-on workshop on using Claude AI for research and writing.

This page documents my investment journey beginning in 2025. I will track and report the realized returns for each investment.

Portfolio as of July 20, 2026

On June 18, 2026, I purchased four mutual funds focused on China’s AI supply chain, in response to the U.S. government’s block on Claude’s Fable 5 model on June 12, 2026. I realized the position on July 20, 2026, at a loss of approximately 15%.

Portfolio as of April 16, 2025

On February 5, 2025, I purchased the following stocks in response to the AI boom in China:

  • Alibaba – 28.1% allocation at HKD 97.00 per share; realized on February 13, 2025 at HKD 115.40.
  • HSBC – 46.4% allocation at HKD 80.15 per share; realized on March 11, 2025 at HKD 85.00.
  • Xiaomi (W) – 25.5% allocation at HKD 39.15 per share; realized on February 13, 2025 at HKD 41.80.
Tokyo, January 2017
TokyoJan 2017
Praha, December 2022
PrahaDec 2022
Lugano, December 2022
LuganoDec 2022
Zermatt, December 2023
ZermattDec 2023
NY, May 2025
New YorkMay 2025
UT, May 2025
UtahMay 2025