Treasury and ALM Quant
Models how a bank’s income and value respond to interest rates and funding conditions.
The job
A treasury and balance-sheet quant, often called an ALM quant, models how a bank’s income and value respond to interest rates and funding conditions. The two headline numbers are net interest income (NII) and economic value of equity (EVE). Much depends on deposits: how far the bank must raise deposit rates when market rates rise, and how long customers really leave money in accounts with no fixed term. ALM models are assumptions with consequences, so they get reviewed.
- Supports
- A bank’s treasury and asset-liability committee
- Stages
- 5 to learn, then proof of work
- Two routes
- Free resources, or SelfMadeQuant programmes and projects
The roadmap
The same stages either way. The free route uses university courses, lectures, books and papers that are free online. The SelfMadeQuant route maps each stage to our programmes and ends in projects on real market data.
Stage 01 · Foundations
Money markets and bank funding
How a bank funds itself and where liquidity comes from.
- Bank balance sheets
- Money markets
- Funding and liquidity
- Economics of Money and Banking (opens in a new tab)
Perry Mehrling / Columbia University on Coursera
Money markets, bank balance sheets and the hierarchy of funding; free to audit.
- Money creation in the modern economy (opens in a new tab)
Michael McLeay, Amar Radia and Ryland Thomas / Bank of England
How bank lending creates deposits and what limits balance-sheet growth.
- Principles for Sound Liquidity Risk Management and Supervision (opens in a new tab)
Basel Committee on Banking Supervision
The supervisory baseline for managing funding liquidity and running liquidity stress tests.
- Shadow Banking (opens in a new tab)
Zoltan Pozsar, Tobias Adrian, Adam Ashcraft and Hayley Boesky / Federal Reserve Bank of New York
Maps the wholesale funding chains whose stress spills into bank funding.
Stage 02 · Core
Bond maths and the term structure
Duration, convexity and the curve every balance-sheet number is discounted on.
- Bond pricing
- Duration and convexity
- Term structure
- MIT 15.401 Finance Theory I, Fall 2008 (opens in a new tab)
Andrew Lo / MIT OpenCourseWare
Lectures on present value, bond pricing, duration and the term structure.
- The U.S. Treasury Yield Curve: 1961 to the Present (opens in a new tab)
Refet Gürkaynak, Brian Sack and Jonathan Wright / Federal Reserve Board
How the Fed fits a smooth Treasury curve, with the daily dataset it still publishes.
- Fixed Income Securities: Tools for Today's Markets (opens in a new tab)
Bruce Tuckman
The standard reference for DV01, convexity and building discount curves.
Stage 03 · Specialist
ALM, NII and EVE
Deposits and mortgages carry customer options; model them as such.
- NII and EVE
- Deposit betas
- Non-maturity deposits
- Prepayment
- Comptroller's Handbook: Interest Rate Risk (opens in a new tab)
Office of the Comptroller of the Currency
The examiner's view of repricing gaps, earnings simulation and EVE for banks.
- RMS Manual of Examination Policies, Section 7.1: Sensitivity to Market Risk (opens in a new tab)
Federal Deposit Insurance Corporation
How supervisors judge banking-book rate risk, deposit assumptions and model governance.
- Banking on Deposits: Maturity Transformation without Interest Rate Risk (opens in a new tab)
Itamar Drechsler, Alexi Savov and Philipp Schnabl / NBER
Deposit betas and why a deposit franchise hedges long-duration assets.
- SR 10-1: Interagency Advisory on Interest Rate Risk Management (opens in a new tab)
Board of Governors of the Federal Reserve System
Expectations for IRR measurement, including non-maturity deposit and prepayment assumptions.
Stage 04 · Specialist
Panel data econometrics
Deposit betas estimated across thousands of banks.
- Fixed effects
- Panel regression
- Robust standard errors
- Econometrics (opens in a new tab)
Bruce E. Hansen / University of Wisconsin-Madison
Free graduate text with full chapters on panel data, fixed effects and clustering.
- Programming Advice: Finance Panel Data Sets (opens in a new tab)
Mitchell A. Petersen / Kellogg School of Management
Which clustered standard errors to use in finance panels, with code and test data.
- linearmodels (opens in a new tab)
Kevin Sheppard (open source)
Python panel estimators with entity and time effects and clustered errors.
- Econometric Analysis of Cross Section and Panel Data (opens in a new tab)
Jeffrey M. Wooldridge
The standard graduate reference for fixed and random effects estimators.
Stage 05 · Specialist
Regulation and governance
The rules treasury reports against, and defending the assumptions.
- Basel IRRBB
- LCR and NSFR
- Model governance
- Interest rate risk in the banking book (IRRBB standard) (opens in a new tab)
Basel Committee on Banking Supervision
The six prescribed rate shock scenarios and the standardised EVE framework.
- Basel III: The Liquidity Coverage Ratio and liquidity risk monitoring tools (opens in a new tab)
Basel Committee on Banking Supervision
Definitions of high-quality liquid assets and 30-day stressed outflow rates.
- Basel III: the net stable funding ratio (opens in a new tab)
Basel Committee on Banking Supervision
Available and required stable funding factors that shape a bank's funding mix.
Stage 06 · Proof of work
Deposit betas and EVE from Call Reports
Pull quarterly Call Report data for US banks, compute deposit interest expense rates and estimate each bank's deposit beta to SOFR over the 2022 to 2023 hiking cycle with a panel regression. Then apply the Basel IRRBB parallel shocks to see which banks' deposit franchises offset the duration of their securities and loans.
Stage 01 · Foundations
Money markets and bank funding
How a bank funds itself and where liquidity comes from.
- Bank balance sheets
- Money markets
- Funding and liquidity
- Financial Instruments, Markets and Conventions
- Derivatives, funding and liquidity
- Equities, Money Markets, and FX
Stage 02 · Core
Bond maths and the term structure
Duration, convexity and the curve every balance-sheet number is discounted on.
- Bond pricing
- Duration and convexity
- Term structure
- Fixed Income and Interest-Rate Models
- Bond Mathematics and Pricing Fundamentals
- Duration, Convexity, and Rate Sensitivity
- The Term Structure of Interest Rates
Stage 03 · Specialist
ALM, NII and EVE
Deposits and mortgages carry customer options; model them as such.
- NII and EVE
- Deposit betas
- Non-maturity deposits
- Prepayment
- Fixed Income and Interest-Rate Models
- Mortgage-Backed Securities and Securitization
- Short-Rate Models
Stage 04 · Specialist
Panel data econometrics
Deposit betas estimated across thousands of banks.
- Fixed effects
- Panel regression
- Robust standard errors
- Econometrics and Financial Time Series
- Panel Data Econometrics
- Regression Diagnostics and Generalized Least Squares
Stage 05 · Specialist
Regulation and governance
The rules treasury reports against, and defending the assumptions.
- Basel IRRBB
- LCR and NSFR
- Model governance
- Quantitative Risk Management
- Risk in Perspective and the Regulatory Framework
- Professional Quant Practice
- Governance and validation
Stage 06 · Proof of work
Build the projects
Each project is built on real market data and reports what the data said, including when the idea failed.
Practise the interview
Questions this role gets asked, each with a hint and a worked solution.
- Explain duration and convexity, and say which one a bank’s deposit book makes harder to measure.
- You hold mortgage-backed securities and expect a sharp bond rally. Do you want positive or negative convexity?
- Under a Vasicek model, what is the expected short rate in ten years, and why does mean reversion matter for a balance-sheet forecast?
Start the SelfMadeQuant route free: a free account opens one complete topic from each primer and the interview question bank. No card needed.
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