Research

Papers & Analysis

Working papers and analyses from the lab, plus related research on decision-making under volatility. Drafts are shared in progress and clearly labeled; completed work is shared in full.

The lab program

Pressure Premium papers

Outputs of the experimental program, preliminary and clearly labeled until data collection completes.

Working paperIn progressUpdated June 1, 2026

Risk Under Pressure: Testing the Psychological Tax on Financial Decision-Making

Sami Muhtadie

Status: In progress
Data: Demo / synthetic
Claim: Preliminary
Next update: See below

Real vs. placeholder

Real: the design, hypotheses, variables, and analysis plan. Placeholder: every coefficient, table, and figure is a synthetic demo estimate, replaced once data is collected.

What is being tested?

Whether randomly assigned pressure conditions move risk-taking, calibration, and herding relative to a control baseline.

What did we find?

Demo estimates: loss framing lowers risk by ~13 points and time pressure raises it by ~9; calibration worsens most under loss framing.

Why does it matter?

This is the empirical core of the thesis: the individual-level evidence that the psychological tax exists and is structured.

Abstract

This paper tests whether experimentally induced pressure changes risk-taking, confidence calibration, and herding behavior. Participants are randomly assigned to control, time-pressure, social-evaluation, or loss-framing conditions. Preliminary analysis examines whether pressure increases decision distortion relative to baseline conditions.

Executive summary

Pressure does not move risk uniformly. Each condition distorts a different part of the decision.
Loss framing is the dominant effect (−13.2 pts vs. control, p<.001 in demo estimates).
Social evaluation drives herding more than it changes risk level.
Confidence and accuracy decouple most under loss framing and time pressure.

Conditions

Control · Time · Social · Loss

Target N

≈260

≈65 per condition

Largest effect

−13.2

Loss framing on risk score

R²

0.21

Demo specification

Methods

Between-subjects random assignment to one pressure condition.
Composite risk score from paired gamble tasks; calibration from confidence vs. realized accuracy.
Herding measured as choice revision after revealed consensus.
OLS condition contrasts against control with a numeracy covariate; pre-registered primary hypotheses.

Key charts

Risk score by condition
Risk shift vs. control
Confidence gap by condition
Herding shift by condition

Regression summary

Demo data

Term	β	SE
Time Pressure	+9.1^*	3.6
Social Evaluation	−4.8	3.5
Loss Framing	−13.2^***	3.4
Numeracy (z)	+2.1	1.5
Constant (control)	52.0^***	2.4

risk_score ~ time_pressure + social_eval + loss_framing + numeracy (OLS, control = reference)
* p<.05 ** p<.01 *** p<.001 · β = change in risk score (0-100) vs. control. Demo estimates.

Planned completion: First results draft after main data collection (target: summer 2026).

Files

Download paper (PDF)

Pending release

Publishes with the completed paper

Download appendix (PDF)

Pending release

Publishes with the completed paper

Citation

Muhtadie, S. (2026). Risk Under Pressure: Testing the Psychological Tax on Financial Decision-Making. The Pressure Premium Lab. Working paper, in progress.

Preliminary and subject to revision. Figures are based on demo data until collection is complete. Results describe condition differences and associations, not universal laws.

Op-edExploratory analysisUpdated June 8, 2026

Is Volatility a Psychological Tax? A Market Application

Sami Muhtadie

Status: Exploratory analysis
Data: Demo / synthetic
Claim: Exploratory · not causal
Next update: See below

Real vs. placeholder

Real: the research question, method, and careful framing. Placeholder: the chart series and the correlation figure are synthetic, with no live VIX or Google-Trends data loaded yet.

What is being tested?

Whether an attention/stress proxy (e.g. Google-Trends search interest) co-moves with a volatility indicator (e.g. VIX, sector vol) around selected event windows.

What did we find?

Demo series show attention rising into volatility spikes within event windows, suggesting co-movement rather than identified causation.

Why does it matter?

It is the bridge from the lab to the market, the most consequential and the most carefully hedged claim in the project.

Abstract

This analysis explores whether attention-based stress proxies, such as search interest in recession- or crisis-related terms, move alongside selected volatility indicators during market-stress periods. The goal is not to prove causality but to examine whether psychological pressure may help explain episodes of overreaction or risk repricing.

Executive summary

Within selected event windows, an attention proxy tends to rise alongside volatility.
Co-movement is strongest around identifiable shocks (macro surprises, an oil shock).
This is association, not causation: confounds and reverse causality are not ruled out.
The honest claim is a hypothesis worth testing with stronger identification, not a finding.

Event windows

Macro · stress · oil shock

Corr (demo)

0.74

Attention vs. volatility, in-window

Identification

None yet

Stated limitation

Claim

Hypothesis

Not causal proof

Volatility vs. attention proxy

Demo data

Synthetic series across selected event windows, illustrative of the method, not a result.

Methods

Event-window comparison of a volatility indicator and an attention proxy.
Descriptive co-movement and simple correlation during selected stress windows.
VIX / sector volatility and Google-Trends-style attention series (synthetic placeholders for now).
Explicit discussion of confounds and the absence of an identification strategy.

Key charts

Volatility vs. attention proxy over time
Event-window markers

Planned completion: After the event-window dataset (VIX / sector vol + attention) is assembled.

Files

Download memo (PDF)

Pending release

Publishes with the completed paper

Citation

Muhtadie, S. (2026). Is Volatility a Psychological Tax? A Market Application. The Pressure Premium Lab. Exploratory analysis.

Exploratory. Demonstrates association, not causation. Market-data work does not claim causal proof without stronger identification. Series shown are synthetic placeholders.

Related research

Adjacent work on volatility & fiscal decision-making

Completed research that sits beside the lab's program. It doesn't use the Pressure Premium method, but it pursues the same question at a different scale: how instability turns into damage, and what buffers it.

Honors researchCompleteCompleted May 1, 2026

Wealth Without Stability: Oil Revenue Volatility and the Limits of Saudi Fiscal Diversification, 1980-2000

Sami Fayez Muhtadie · Honors Seminar · Humanities & Social Science Research · May 2026

Status: Complete
Type: Honors research
Method: Econometric + archival
Access: Open PDF

How this connects to the lab

This paper sits outside the lab's experimental program. It is macroeconomic history, not behavioral finance. But it shares the lab's central question: how does volatility turn into damage, and what absorbs it? Where the Pressure Premium studies volatility's cost on an individual's judgment and asks whether cognitive discipline buffers it, this study examines volatility's cost on a state's economy and finds that fiscal diversification is the buffer. It is the same mechanism, instability translating into worse outcomes mediated by a structural cushion, examined one level up, from the trading desk to the treasury. It also gives the lab's oil-volatility thread (Podcast Episode 5 and the market-application analysis) a historical backbone.

What is being tested?

Whether Saudi oil-revenue volatility (not oil wealth) damaged the non-oil economy in 1980-2000, and whether fiscal diversification mediated the severity.

What did we find?

Volatility damaged all non-oil sectors broadly, contradicting Dutch Disease's tradable-sector prediction, with limited fiscal diversification as the primary transmission mechanism.

Why does it matter?

It isolates volatility as the destabilizing force and a structural buffer as what determines the damage, the same logic the lab applies to individuals, examined at the level of a state.

Abstract

This honors research paper argues that the driver of Saudi Arabia's late-twentieth-century economic instability was not oil wealth but oil revenue volatility, the instability of the state's petroleum earnings. Using a mixed-methods design (time-series OLS, a sector-year panel, and a fiscal-composition interaction, alongside archival evidence from SAMA reports, Five-Year Development Plan reviews, and IMF Article IV consultations), it examines three crisis episodes between 1980 and 2000. It finds that revenue volatility damaged the non-oil economy broadly, rather than concentrating in tradable sectors as the Dutch Disease model would predict, and that the state's limited fiscal diversification was the primary mechanism translating instability into decline.

Key findings

The relevant variable is oil-revenue volatility, not oil wealth.
Damage was broad across all non-oil sectors, contradicting the Dutch Disease prediction of tradable-sector concentration.
Limited fiscal diversification was the primary mechanism transmitting volatility into economic decline.
Severity tracked how concentrated the economy was in petroleum exports at the time.
Econometric results are treated as corroborating evidence within a historical argument, not as standalone proof.

Methods

Time-series OLS linking revenue instability to non-oil performance.
Sector-year panel regression across the 1980-2000 window.
Fiscal-composition interaction analysis.
Archival corroboration: SAMA annual reports, Five-Year Development Plan reviews, IMF Article IV consultations.

Figures

Oil-revenue volatility series, 1980-2000
Sector-level contraction by crisis episode
Regression output & visualizations (appendix)

Read it

Read the full paper (PDF)

Full PDF, opens in a new tab

Citation

Muhtadie, S. F. (2026). Wealth Without Stability: Oil Revenue Volatility and the Limits of Saudi Fiscal Diversification, 1980-2000. Honors Seminar research paper.

Completed honors research paper, shared in full. Independent of the Pressure Premium experimental program and included as related work on fiscal decision-making under volatility.