Mathematical foundation
Stochastic calculus, probability theory, linear algebra and differential equations form the core toolkit of every quant.
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QuantClub KSE · Kyiv · 2026
Where mathematics meets finance.
A student-led community bridging rigorous mathematical thinking and modern quantitative finance — from stochastic calculus to algorithmic trading.
01 / MANIFESTO
What is quantitative finance?
Quantitative finance applies mathematical models, statistical methods and computational algorithms to financial markets. It is where pure mathematics becomes a practical superpower.
Market applications
From derivatives pricing and algorithmic trading to portfolio optimisation — math drives modern financial markets.
Data & models
Machine learning, time-series analysis and statistical modelling uncover patterns and manage risk in complex markets.
02 / EVENTS
Events / field notes
Competitions, workshops and meetups by QuantClub KSE.
STATUSDATETITLE / NOTESLINK
Upcomingoffline
Probability and Games Competition
A weekend at KSE Obolon: the offline competition final, student scientific battles with one $1,000 Research Award, invited speakers and a public probability event. An online qualifier precedes the final.
Pastoffline
Quant Interview Workshop
Practice probability, statistics and brainteasers drawn from quantitative finance interviews.
Register
— soon
— soon
UpcomingHybrid
Josef Teichmann · Signature Features in Finance
An English-language lecture by the ETH Zurich professor, joining online. Watch online or at KSE Obolon, 19 Obolonska Naberezhna — with pizza on campus. Part of the Probability and Games lecture series.
Upcomingoffline
Student Research Conference · Scientific Battles
Probability, stochastic processes and quantitative finance. Current undergraduate, Master’s and PhD students are invited to submit research from 1 October. One Student Research Award: $1,000.
Pastoffline
Апроксиматор — Estimathon KSE
A competitive estimation game: 12 problems, 18 attempts and the narrowest credible intervals win.
03 / RESOURCE INDEX
Open resource index
Curated materials for quantitative finance. Access is available via a KSE corporate email.
01
Advances in Financial ML
Machine learning in finance: feature engineering, meta-labeling and cross-validation.
↗02Hedge Fund Strategies
Systematic and discretionary approaches: long/short equity, macro and statistical arbitrage.
↗03Interview Materials
Probability puzzles, brainteasers, mental math and technical questions from leading firms.
↗04Quant Investment Management
Portfolio construction, factor investing, risk parity and quantitative asset management.
↗05Textbooks & Papers
Foundational textbooks and papers on stochastic calculus, derivatives and quantitative methods.
↗04 / SPONSORSHIP
Build the next generation of quants.
Support one activity, a recurring program, or the 2026–27 academic year at KSE Quant Club.
Download sponsorship deck ↓Ways to support
Funding
Prizes, venue, participant travel, catering and materials.
Expertise
Speakers, problem setters, judges, technical reviewers and mentors.
Infrastructure
Datasets, software and compute for practical learning.
Student opportunities
Internships, interviews and research placements.
Planned program / 2026–27
5–6 DecemberProbability and Games Competition & Student Conference
During yearTechnical talks and workshops
During yearRecruiting events
AnnualResearch awards and fellowships
30 NovemberJosef Teichmann · Signature Features in Finance
What sponsors receive
- Name and logo on the agreed activity and its materials.
- A defined role for speakers, workshop leaders, judges or mentors.
- The option to co-design a competition problem, challenge or award.
- Opt-in student introductions for interviews, office hours or recruiting.
- A post-event summary covering participation and agreed outputs.
Choose a single activity, a recurring program or a year-long partnership.
PDF / 06 PAGES ↗05 / INTERVIEW PREP
Mock interview archive
Probability, brain teasers, mental math and finance — select a card, write your solution, then reveal the check.
15 / 15
Find the expected number of rolls needed to see all six faces.
Scratch space only. Not sent or graded; clears when you leave or change the filter.
Model the unseen faces as states; sum the geometric waiting times for each new face.
One envelope contains twice as much as the other. Does switching improve expected value?
Scratch space only. Not sent or graded; clears when you leave or change the filter.
The apparent paradox comes from using inconsistent conditional distributions for the observed amount.
Two uneven ropes each burn in one hour. Measure exactly 45 minutes.
Scratch space only. Not sent or graded; clears when you leave or change the filter.
Light rope A at both ends and rope B at one end. When A finishes, light B’s other end.
Estimate the expected maximum of repeated independent draws.
Scratch space only. Not sent or graded; clears when you leave or change the filter.
Use the tail-sum formula: integrate one minus the CDF of the maximum.
Stay or switch after the host reveals a goat?
Scratch space only. Not sent or graded; clears when you leave or change the filter.
Switch. Your first pick wins with probability 1/3; switching inherits the remaining 2/3.
How should an option react to volatility and time?
Scratch space only. Not sent or graded; clears when you leave or change the filter.
More volatility expands upside while downside remains bounded; more time usually increases optionality.
Can 100 prisoners achieve a success probability far above random guessing?
Scratch space only. Not sent or graded; clears when you leave or change the filter.
Follow the permutation cycles starting from each prisoner’s own number.
Update the odds after drawing cards without replacement.
Scratch space only. Not sent or graded; clears when you leave or change the filter.
Write the conditional sample space explicitly; the denominator changes after every draw.
Compare waiting times for overlapping head-tail patterns.
Scratch space only. Not sent or graded; clears when you leave or change the filter.
Build states from the longest suffix that is also a prefix of the target pattern.
Relate European calls, puts, stock and a zero-coupon bond.
Scratch space only. Not sent or graded; clears when you leave or change the filter.
Match terminal payoffs: C − P = S₀ − K·e⁻ʳᵀ.
Can an ant reach the end of a uniformly stretching band?
Scratch space only. Not sent or graded; clears when you leave or change the filter.
Yes in the idealised model: the ant’s fractional progress accumulates as a divergent harmonic series.
How many people make a shared birthday more likely than not?
Scratch space only. Not sent or graded; clears when you leave or change the filter.
Compute the complement of all birthdays being distinct; the threshold is 23 people.
Compare strategies with different return and volatility profiles.
Scratch space only. Not sent or graded; clears when you leave or change the filter.
Use excess return divided by volatility, with consistent frequency and annualisation.
What is the chance of hitting a profit target before bankruptcy?
Scratch space only. Not sent or graded; clears when you leave or change the filter.
Solve the boundary-value recurrence; the fair-game case is linear in starting capital.
How long to collect all equally likely coupon types?
Scratch space only. Not sent or graded; clears when you leave or change the filter.
The expectation is n times the nth harmonic number, approximately n(log n + γ).
06 / MARKET MAKING LAB
Make the market
Act as a market maker: quote both sides, manage inventory and try to capture the spread.
Mid price$100.00
Cash$10000.00
Inventory0 shares
P&L+$0.00
BIDS
3899.94
2499.89
5199.84
1999.78
4399.72
SPREAD$0.10
ASKS
100.0621
100.1146
100.1628
100.2257
100.2833
Quick quotes
HOW IT WORKS
Market makers provide liquidity by continuously quoting bid and ask prices. The spread is the gap between the best bid and best ask. The opportunity is capturing that spread; the risk is holding inventory when prices move against you.
07 / ABOUT
About the club
QuantClub KSE is a student-led community exploring quantitative finance, algorithmic trading and mathematical modelling. Our mission is to equip students with the mathematical skills needed for careers in quantitative finance — and make the path more accessible.
What we do
Competitions
Approximathon / Estimathon: tricky quantitative problems solved under time pressure.
Workshops & prep
Probability puzzles, brainteasers, mental math and questions from top quant firms.
Student research
Research talks, scientific battles and discussion of probability, stochastic processes and quantitative finance.
Learning resources
A curated library of textbooks, papers and courses open to all club members.
Our team
08 / ROLE FINDER
Which quant role fits you?
Take a four-step pulse check and get a direction for your next deep dive.
Question 1 / 4
What excites you most?
Join the club.
Mathematics, code, markets — and people to explore them with. Join the QuantClub KSE mailing list for events, workshops, research and opportunities.