Asset Management

• The team meets once a week, then divides the work between research and the platform.
• On the research side, members study portfolio risk metrics and models, decide which ones are useful and write each fund's report from the calculated KPIs.
• On the development and operations side, members implement those models, add tests and keep the CI/CD pipeline ready for production.
• Both sides meet in the report. Research sets the requirement, development implements it and the fund manager receives the result.

• The platform itself: 210 Python modules behind seven task workspaces, with CI/CD and a nightly pipeline that replays every transaction and recomputes the analytics after the close.
• A risk report per fund, with KPIs, mandate breach alerts and recommendations, sent to the fund leads.
• Research articles on risk and portfolio management. Asset Management publishes one article a month in the TIC Journal, alternating between Risk and Macro.

You start by reviewing the project files and onboarding material with the team. You then help a current member improve the platform or write a section of a risk report, using previous reports as a reference.

This team suits people who like building systems and tend to notice what could work better. Students designed the platform, chose its methodology and still run it, so a member can follow one feature from the initial research to its use by a fund manager. Every risk analyst is also allocated to a fund and therefore understands how the portfolio behind their report is managed.

Risk has a lot in common with Quantitative Trading: Python, models and portfolio data are part of both. Risk uses them to assess exposures, limits and model reliability for funds managed by people. Quant teams use them to construct strategies or build the systems that execute those strategies.

vs Portfolio Optimisation →

Both teams research portfolio models in Python. Portfolio Optimisation builds and validates an allocation or strategy. Risk independently measures the exposure and mandate compliance of portfolios managed by the fund teams.

vs Strategy Application →

Both teams operate production data systems. Strategy Application uses model output to place unattended orders. Risk uses portfolio data to produce controls, reports and recommendations, while the fund manager makes the final decision.

vs Macro →

Both teams reach the same fund decisions from opposite ends. Macro starts from what is changing in the economy, in monetary policy and in geopolitics, and uses indicators to confirm that reading. Risk starts from the KPIs measured on each portfolio, and the exposures, limits and model validation behind them.

Risk checks whether each portfolio stays within its mandate and reports concerns such as concentration or changes in exposure to the fund lead. The fund manager makes the final investment decision. The team validates data, tests models and reviews code changes before they reach production.

The dashboard includes a tutor linked to its KPIs and charts, with 33 reviewed concepts, 16 lessons, 18 methodology guides and a seven-level learning path. Members can use it to understand the metrics they are working with. Its formulas and worked examples are not generated by a language model.

• The work is organised in projects rather than fixed themes. Small sub-teams take one project and move it forward on their own time during the week.
• Once a week the whole team meets informally: each sub-team says what it has done, what it is thinking of including and where it is stuck, and hears from the people working on something else. Everyone follows every project, including the ones they are not on.
• Projects run in cycles of three to four weeks. The sub-teams start and finish at roughly the same time, and at the end of each cycle the teams are reshuffled and a new cycle begins.
• Finished work is presented to the team and, whenever possible, to the rest of TIC.

• The Monthly Macro Report: executive summary, market snapshot, growth, inflation and monetary policy, the US, Europe and emerging markets, FX, debt, credit and commodities, geopolitics, a theme of the month, and the concrete implications for each fund.
• Sector analyses: a study of one industry in slides, with the macro context acting on it, the trends and the risks, and a reading applied to the funds. They are built from the start to be presented outside TIC, to companies.
• Articles for the TIC Journal. Asset Management publishes one a month, alternating between Macro and Risk.
• Short videos for the club's Instagram, which take the team's own work and explain a current subject in an accessible way.

You join a sub-team of three and produce a test Monthly Macro Report on a month that has already passed. It is not published: it exists so you learn the structure of the report, the sources the team uses and how to read indicators such as CPI, PMI and yields, starting from the work the team has already done. Longer-standing members follow the new sub-teams closely through this first project. At the end of the cycle you join the normal rotation, on the report and on the sector analyses.

This team suits people who follow the news and want to understand how events affect markets and investments. No prior knowledge is expected: you learn the indicators and research tools with the team. Members work in small groups, meet deadlines and share their analysis through presentations, articles and videos.

Macro brings the reading of the economic, monetary and geopolitical context into the funds' decisions, but does not build the quantitative models behind them. That is what separates it from Quantitative Trading, which develops models and strategies with a far heavier focus on quantitative execution. Macro starts from what is changing in the economy, in markets and in industries, and the indicators come afterwards to confirm the reading.

vs Investment Banking →

Investment Banking researches one company and the deal or position that follows from it. We work at the level of an economy, a region, a market or an industry, and the reading we produce is the context those decisions sit in.

vs Risk →

Both teams reach the same fund decisions from opposite ends. Risk starts from the KPIs measured on each portfolio, and the exposures, limits and model validation behind them. We start from the economy, monetary policy and geopolitics, and use indicators to confirm that reading.

There are no fixed thematic desks any more. A cycle lasts three to four weeks, and when it ends the sub-teams are reshuffled: a new sector analysis, the report for the month that has just closed, new videos. Over a semester that means working on different subjects with different people rather than owning one corner of the research all year, and the weekly meeting is what keeps everyone across the projects they are not on.