A dynamic programming framework for promotional deposit arbitrage with eligibility constraints: Numerical illustrations from offer-level calibration
Authors/Creators
Description
Figure Descriptions
Figure 1: Promotional and Normal APYs in the Six-Bank Calibration
A grouped bar chart comparing the promotional APY (blue bars) and normal/post-promotion APY (magenta bars) across six U.S. digital banks: SoFi, Ally, Marcus, Discover, Varo, and CIT Bank. The figure illustrates the yield spread that creates the arbitrage opportunity, with promotional rates ranging from 4.35% to 5.20% and normal rates from 3.00% to 3.60%. Varo offers the highest promotional rate (5.20%) but the lowest normal rate (3.00%), while CIT Bank shows the smallest promotional spread.
Figure 2: Signup Bonuses and Promotional Deposit Caps in the Six-Bank Calibration
A dual-axis chart displaying signup bonuses as blue bars (left axis, in dollars) and deposit caps as a black line with markers (right axis, in thousands of dollars). SoFi offers the highest bonus ($300) with a $50,000 cap, while CIT Bank has the highest cap ($250,000) with a $175 bonus. The figure highlights the inverse relationship between bonus size and deposit capacity across institutions.
Figure 3: Computed Wealth Trajectories over 36 Months
A line plot showing wealth accumulation paths under five benchmark strategies starting from $50,000 initial capital over a 36-month horizon. Strategies include: Static HYSA (blue), Calendar Rotation (magenta), Calendar + Bonus (teal), Bellman Proxy (purple), and Bonus-Aware Bellman Proxy (green). The Bonus-Aware Bellman Proxy achieves the highest terminal wealth (~$56,273), while the static benchmark reaches ~$54,389, demonstrating the value of eligibility-aware optimization.
Figure 4: Reported Monte Carlo Premiums by Strategy
A bar chart displaying the promotional arbitrage premium (percentage gain over static HYSA) across five strategies based on 50,000-path Monte Carlo simulations. The regime-switching optimal strategy yields the highest premium at 14.65%, followed by Promo + Bonus at 12.06%, Optimal Deterministic at 7.59%, and Simple Calendar Rotation at 4.48%. Error bars reflect simulation standard errors.
Figure 5: Sensitivity of the Promotional Arbitrage Premium to Key Parameters
A tornado-style sensitivity diagram showing how the arbitrage premium (%) varies under low, base, and high scenarios for six parameters: tax rate, bonus size, switching cost, promotional volatility, requalification period, and inflation. The premium is most sensitive to bonus size (range: ~11% to ~29%) and requalification length, and least sensitive to inflation. Base-case premium is anchored at approximately 20%.
Figure 6: Eligibility-State Transitions
A state-transition diagram illustrating the three eligibility states for each bank: Ineligible/Waiting (0), Eligible for Promotion (1), and Active Promotion (2). Arrows indicate transitions triggered by account opening/switching, promotional expiration, and requalification period lapse. This figure visualizes the mode-dependent feasibility structure that distinguishes the model from standard switching problems.
Data Description for Zenodo Repository
The replication dataset (data_V3.xlsx) contains seven worksheets supporting the numerical calibration, simulation, and sensitivity analysis reported in the manuscript. All monetary values are in U.S. dollars unless otherwise specified.
|
Worksheet |
Description |
Records |
Key Variables |
|
Fed_Rate_Cycles |
Federal Funds Effective Rate and CPI inflation from January 2020 through May 2026, retrieved from FRED (DFF series). Used to calibrate the opportunity-cost rate and macroeconomic context. |
24 |
Period, Fed_Funds_Rate_Pct, Inflation_CPI_Pct |
|
Bank_Promo_Rates |
Six-bank promotional deposit product calibration extracted from Bankrate and Marcus.com (2025). Defines the core parameters for the dynamic programming model. |
6 |
Bank, Promo_APY_Pct, Normal_APY_Pct, Promo_Window_Months, Requal_Months, Deposit_Cap_Dollars, Bonus_Dollars |
|
Sim_Parameters |
Baseline simulation parameters including initial capital ($50,000), 3-year horizon, 22% tax rate, 2-day ACH delay, $250,000 FDIC limit, and 50,000 Monte Carlo paths. |
14 |
Parameter, Value, Unit, Source |
|
MC_Results |
Monte Carlo simulation outcomes for six strategies: Static HYSA, Simple Rotation, Optimal DP, Promo + Bonus, Regime-Switching, and Behavioral. |
6 |
Strategy, Mean_Terminal_Wealth, Std_Dev, Pi_Pct, Interest_Contribution_Pct, Bonus_Contribution_Pct, Cost_Contribution_Pct |
|
Bootstrap_CIs |
Bias-corrected bootstrap confidence intervals (B = 10,000) for the arbitrage premium of four key strategies. |
4 |
Strategy, Point_Estimate, SE, CI_95_Lower, CI_95_Upper, B |
|
Behavioral_Frictions |
Sensitivity analysis incorporating behavioral frictions: switching fatigue, attention costs, status quo bias, and loss aversion. |
6 |
Friction_Type, Parameter, Pi_Pct, Optimal_Switches, Welfare_Loss_Dollars |
|
Offer_Level_Summary |
Descriptive statistics from an expanded offer-level dataset (N = 847 promotional deposit offers) spanning January 2024 to May 2026. |
12 |
Statistic, Value |
Data Sources
Federal Reserve Economic Data (FRED), Bankrate, Marcus by Goldman Sachs, FDIC Quarterly Banking Profile, IRS Publication 17, NACHA Operating Rules, Doctor of Credit. Retrieval date: 2026-05-26.
Usage
These data support replication of the dynamic programming calibration, Monte Carlo validation, bootstrap inference, and sensitivity analyses reported in the manuscript. The six-bank subset (Bank_Promo_Rates) is the primary calibration input; the offer-level summary provides external validity for parameter ranges.
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fig1_offer_rates.png
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