Blog Articles, Case Studies, White-papers.
A Primer on Securities Lending
Whether you are new to capital markets or looking to refresh your technical knowledge, this primer breaks down the essentials of modern securities lending. We will explore
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Data Warehouse Modernization
One of Germany’s largest banks modernized their legacy data warehouse processing pipelines to reduce runtimes by 36%
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The Potential of Databricks
Databricks is a cloud-native unified data and analytics platform designed to run on public cloud infrastructure. We discuss opportunities
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Asset Manager NAV Calculation
Our customer, a leading global investment management firm, had outsourced the pricing of derivative instruments.
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Building the Market Risk System
One of Germany’s largest banks replaced the existing pricing kernel for their market risk system by an in-house development, using the front office pricing library.
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Schätzung von operationellen Risiken
Methodische Herausforderungen und Chancen für die quantitative Schätzung von operationellen Risiken. Die quantitative Schätzung und Steuerung
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EEG Portfolio-bewirtschaftung
Deutschlands Übertragungsnetzbetreiber sind gesetzlich verpflichtet, EEG-Strom sicher und kosteneffizient am Spotmarkt zu vermarkten - mit Fokus auf Systemsicherheit, 24/7-Bewirtschaftung und automatisierte Prozesse.
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Lessons Learned from AQR
This paper outlines the essential steps of the derivative pricing model review process, drawing on experience from the ECB's Asset Quality Review (AQR). It covers model adequacy, parameterisation, calibration, and reserves against model deficiencies.
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Drift Dependence of Optimal Trade Execution Strategies
Every large trade moves the market. The question is by how much, for how long, and how that should shape the way you execute. For a decade, most execution desks and TCA frameworks have answered this question using models that treat price impact as permanent — a one-way street where each trade irreversibly shifts the price level.
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Insider Trading in Discrete Time Kyle Games
Markets are not neutral. Every trade is a signal, and sophisticated participants know it. The question is: how does an informed trader extract value from private information without giving the game away?
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Differential Geometry, (m,λ)-SABR and a Formula by Pierre-Henry Labordère
Options desks price volatility smiles every day using models that, under the hood, require translating a stochastic process into a usable number: the Black-Scholes implied volatility at each strike and expiry.
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A Strong Invariance Principle for the Logarithmic Average of Sample Maxima
Knowing that a statistic converges is not the same as knowing how it converges. For practitioners who build risk models on extreme value theory, the gap matters enormously. A convergence result tells you that, eventually, the logarithmic average of normalized maxima approaches a theoretical limit.
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An Extension of the Almost Sure Max–limit Theorem
Extreme events do not cooperate with theory. A model that works on average, across many hypothetical runs, may still give unreliable guidance for the single realized history a firm is actually managing. That gap, between convergence in distribution and convergence along the observed path
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A Flex Engine In Less Than 101 Lines
We present a framework for building a flexible payoff language and linking it to the pricing kernel.
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Modern Logarithms for the Heston Model
Fourier-based pricing is the workhorse for stochastic volatility models. For the Heston model, the standard approach is to express the option price as an integral of the model's characteristic function over the real line, then evaluate that integral numerically.
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