mathfin-topic-selection

Problem Selection (mathfin-topic-selection)

When to trigger

• Deciding whether a financial-mathematics idea is a fit for Mathematical Finance
• Holding a result that might be "just a numerical study" and unsure it clears the bar
• Choosing between an incremental extension and a genuinely novel modelling contribution

The Mathematical Finance fit bar

Mathematical Finance evaluates submissions on **methodological novelty and contribution to

financial modelling**, presented with full mathematical rigor. The litmus test is not "is this

about finance" but "does it advance the mathematics of a financial-modelling problem with a

result that needs a proof." Strong topics live in the journal's stochastic-analysis tradition:

1. New tractable models — e.g., a jump/rough/Lévy or stochastic-volatility model with a

provable pricing or hedging characterization.

1. New structural results — existence/uniqueness, FTAP-type equivalences, duality,

verification theorems for control/BSDE problems.

1. New methods — a transform, free-boundary, mean-field, or stochastic-control technique

that solves a previously open financial-modelling problem.

1. New mathematical objects with financial meaning — risk measures, time-consistency

notions, arbitrage concepts with rigorous representation theorems.

Disqualifiers (off-fit)

• Routine computation on financial data with no supporting rigorous analysis — explicitly

not considered by the journal.

• A purely empirical/econometric finance result (better fit for an empirical finance journal).
• An incremental special case of a known theorem with no new technique or insight.
• A model proposed without proofs of its formal properties (the paper must be self-contained,

proofs included).

Active-frontier scan (hedged)

Strands with sustained presence in the journal's recent volumes — verify against the latest

issues before committing, since frontiers move:

• robust finance and model uncertainty (non-dominated superhedging, Knightian preferences);
• rough volatility: approximation theory, short-maturity asymptotics, Markovian lifts;
• mean-field games and large-population equilibria with financially meaningful constraints;
• (martingale) optimal transport methods for model-free pricing bounds;
• equilibrium and price-impact models with frictions; optimal execution theory;
• dynamic risk measures, time consistency, and capital-allocation representations;
• term-structure theory beyond classical HJM, including stochastic discontinuities and

overnight-rate benchmarks.

A topic on a cold strand still fits if the theorem is strong; a hot strand never excuses a

routine corollary.

Tractability stress test

Q1 Can you state the conjectured theorem now, with explicit hypotheses?      no  -> not ready
Q2 Which known machinery carries 80% of the proof?                           none -> high risk
Q3 What is the genuinely new step, in one sentence?                          none -> incremental
Q4 Does a financial quantity (price, hedge, boundary, equilibrium) appear
   in the conclusion, not just the motivation?                               no  -> wrong venue
Q5 Is there a degenerate case you can solve completely first?                yes -> start there

Vignette: choosing between two term-structure problems

Problem A: extend a known HJM consistency theorem from continuous to càdlàg forward curves —

statable theorem, identified obstacle (jump measures break the old compactness step), clear

payoff (benchmark-rate discontinuities at announcement dates). Problem B: simulate a new

three-factor curve model and show it fits swaption smiles. A passes Q1–Q4; B fails Q4's

theorem requirement and lands in the journal's explicit out-of-scope zone. Choose A, and scope

it by Q5: deterministic jump times first, the general case after.

Sharpening questions

• What is the theorem, in one sentence, and why is it new?
• Is the contribution the model, the method, or the result — and is that the novel part?
• Could a referee from the Bachelier-Finance-Society community see the financial-modelling

payoff, not just a math exercise?

• Are the assumptions general enough to matter, but precise enough to prove?

Output format

【Problem】one sentence
【Type of novelty】model / method / structural result / object
【Core theorem】one sentence (what gets proved)
【Financial-modelling payoff】why it matters for pricing/risk/portfolio/microstructure
【Fit verdict】fit / off-fit + reason
【Next step】mathfin-literature-positioning