Hi, I'm Melisa!

I am a curious researcher, finance enthusiast, and tech-savvy problem solver.

My academic path has been shaped by the Technical University of Berlin and Humboldt-Universität zu Berlin, where I am completing my M.Sc. in Business Administration with a focus on Finance, Accounting, and Tech.

Professionally, I bring 5+ years across finance, accounting, and treasury in VC-backed startups, with hands-on exposure to high-growth environments.

My recently completed Master’s Thesis tested how source attribution (Wall Street Journal vs. Reddit) and benchmark wording shape retail-investor judgments — a 2×2 LLM experiment with GPT-5-mini and FinBERT, 520 simulated responses.

I combine skills in Python and R with ERP and financial analysis experience, turning complex data into clear insights. Academically, I have worked on corporate restructuring cases (M&A, PE, LBOs, and financial distress).

My academic projects are primarily empirical and inspired by reproducibility and transparency principles of TRR 266. 💻 Besides the projects showcased below, my work ranges from AI-enhanced satellite imagery in institutional lending to an analysis of the British census – examining statistical data collection, inflation-driven costs, and system adaptation under technological and economic change.

On the creative side, I enjoy photography and design in Pixelmator. Check out a liquid-style uni logo animation below!

Let’s connect and collaborate!

Master’s Thesis · Credibility of Earnings Headline Sources (cehs-llm)

Same earnings numbers, different source — does it change what retail investors believe and do?

Designed and ran a 2×2 between-subjects LLM pretest (GPT-5-mini, temperature = 1.0) generating 520 simulated retail-investor responses. Stimuli varied by source (Wall Street Journal vs. Reddit r/stocks) and benchmark wording (verifiable GICS industry average vs. subjective “selected peers”). Headlines were pre-screened for sentiment neutrality via FinBERT; sample size set by Monte Carlo power analysis targeting 80% power.

What I found. WSJ headlines came with a ~51-point credibility boost over Reddit — and almost all of the “who said it” effect on buying decisions flows through that trust alone. The twist: vague “peers” wording actually made investors want to buy more, even while they flagged it as more biased. They see the cherry-picking — and still bite. Altogether, these design cues explain about 42.5% of what drives buy intent. That’s a lot for one packaging tweak.

A WSJ label buys trust that no benchmark wording can replicate — but the “right” benchmark wording still nudges investment decisions. For investor relations, financial communications, and platform design: channel strategy and benchmark presentation are not neutral packaging. First LLM-supported experiment in this niche, with full reproducibility (frozen prompts, hardwired data, make-driven pipeline).

See the full GitHub project here — code, data, and thesis PDF.

LLM experiment GPT-5-mini FinBERT Monte Carlo power Behavioral finance Investor relations Reproducible research
Mean buy intent by source × benchmark condition Exploratory mediation coefficients for Reddit and Peers effects FinBERT sentiment neutrality check

Quarto Thesis Template for HU Berlin

Can thesis writing be simplified and made reproducible for an entire faculty?

Authored an open-source Quarto/LaTeX thesis template for the Institute of Accounting and Auditing at the School of Business & Economics, HU Berlin — compliant with both institute and faculty formatting guidelines.

Why it matters. Empirical theses usually mean juggling three separate stacks — LaTeX for writing, Python or R for analysis, and a third tool for plots and tables. This template collapses all of it into one reproducible Quarto + Python + LaTeX pipeline: data, code, figures, and the final PDF all render from a single command.

Works offline (no Overleaf downtime), integrates Zotero for free, and lives in Git — so a broken laptop the night before submission isn’t a disaster. Ships with a complete working example on Gapminder data, so students start from a running project rather than a blank page. Saves each student ~20+ hours of setup and turns the thesis into a reproducible research artifact the next cohort can build on.

Quarto LaTeX Reproducible workflows HU Berlin
Celebration GIF

Women in Economics Initiative @ HU Berlin

Student Initiative Member in the women's network at the School of Business and Economics.

WiE is a volunteer-run, non-profit association committed to advancing gender equality in the field of economics. Its mission is to support equal opportunity and balanced representation across academia, business, and the public sector, while providing a forum where women can exchange ideas and offer mutual support.

As part of the initiative, I helped organise a Science Cinema collaboration with unifilm.de. The event highlighted the achievements of Nobel Prize–winning women economists and gave students a space to reflect on representation, career choices, and confidence in pursuing research paths.

Women in economics Student initiative Diversity & inclusion
Women in Economics Science Cinema Event

Earnings Management and Investor Protection

Do stronger investor rights curb earnings management across countries?

Replicated Leuz–Nanda–Wysocki (2003) on Worldscope (1990–1999). 31 countries · 18,040 firms · 123,469 firm-years. Rebuilt EM1–EM4 plus aggregate score; country ranks closely match the original. Patterns hold: weaker protection → more smoothing, larger accruals, loss avoidance.

Benchmark for cross-country disclosure risk and governance screens. Provides a benchmark for governance risk screens - useful in corporate treasury or strategy teams evaluating disclosure risks across international subsidiaries.

Treasury Cash management Worldscope Investor protection Cross-country Reproducible research

Sentiment Dynamics of Fed Speeches

Can central bank tone signal crisis severity and policy intent?

Analyzed 70+ Federal Reserve speeches from 2008 with VADER sentiment analysis. Mapped tone shifts across quarters and policymakers, capturing deliberate use of tone to support credibility and calm markets, with a sharp rebound during the December QE1 announcement. Quantifies how communication tone can stabilize expectations - the same type of analysis FP&A teams can use when modeling macro shocks on company forecasts. Methodology is generalizable and may be extended to international central banks (e.g., ECB), and broader macro-financial event detection pipelines.

Conducted at DIW Berlin (German Institute for Economic Research).

FP&A NLP Sentiment analysis VADER Reproducible research
Sentiment of individual speeches Quarterly mean & median sentiment Aggregate tone plot

AI Job-Matching Simulation

Can AI recommendations improve job matches – and for whom?
Inspired by Le Barbanchon et al. (2023) and refined through discussion with the author.

Built a Python simulation to pre-test a proposed U.S. RCT study design. RCT-style simulation shows higher match quality, retention ≈93% vs 78%, and wages ≈$47.9k vs $44.0k for treated job seekers. Biggest relative gains for low-skill workers; effects robust across repeated runs.

Highly relevant for fresh graduates entering job markets. Simulated RCT outcomes inform labor market policy, but in corporate settings the same simulation logic can test hiring strategies, retention investments, or workforce planning scenarios.

Simulation RCT-experiment Synthetic data Cosine similarity Subgroup analysis
Simulation pipeline Retention vs wage outcomes

How Much New Information is There in Earnings?

Do quarterly earnings announcements provide new information or mainly confirm what markets already know?

Replicated and extended Ball & Shivakumar (2008) across datasets: mapped CRSP/Compustat to Worldscope/Datastream and aligned IDs, dates, and event windows. Event-study regressions show earnings explain ≈1–2% of annual stock return variation. Extended analysis to 2007–2023 and to Canada to test robustness across time and markets.

Inspired my Master’s Thesis and contributes to debates on market efficiency and the role of accounting disclosures in investment decisions.

Reproducible research Cross-database mapping CRSP / Compustat Worldscope / Datastream Event-window analysis
Replication – Figure 1

Audit Market Concentration in the EU

How concentrated is EU auditing - who really signs PIE opinions across countries?

Replicated the EC (2024) figure using WRDS Audit Analytics Transparency Reports (2021). Computed Big 4, CR4, and 10KAP shares per country + EU aggregate. Big 4 exceed ≈80% in 11 Member States; EU-level ≈70% (10KAP ≈90%). Harmonized network names and duplicates to ensure cross-country comparability.

Useful for competition policy and regulatory debates - where diversification is real vs. where Big 4 dominance persists.

WRDS / Audit Analytics Big4 · CR4 · 10KAP HHI / market shares Reproducible research
EU audit market shares (Figure 3)

P/B Ratios and Future Residual Income

Does P/B embed expectations about future residual income under clean-surplus logic?

Computed deflated residual income with a constant 8% cost of equity and grouped firms into 20 P/B buckets (trimmed P/B ≤ 7). Replicates Penman-style patterns: high P/B → higher near-term residuals that mean-revert; low P/B → persistently negative residuals.

Practical for screening and valuation cross-checks.

Worldscope Residual income P/B grouping Reproducible research