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Highlights

At Quantego we are always one step ahead. With QUASAR we have launched the next generation of stochastic optimization software to help companies make smarter decisions in the face of uncertainty. QUASAR is the only general-purpose solver for large-scale stochastic optimization and its performance is accredited by science. By uniting a set of unique and cutting-edge features, QUASAR lifts decision-making to the next level and gets you ahead of your competitors.

Move from forecasts to scenarios

Forecasts ignore uncertainty - scenarios do not. With QUASAR, you make smarter decisions that take all possible outcomes of the future into account.

Be ahead of your competitors

Many companies want to use scenarios, but lack the software that gets it right. QUASAR has it all to keep you ahead of the field: scenario analytics and scenario generation, large-scale stochastic optimization, simulation analysis.

Trust in peer-reviewed expertise

Having active members of the mathematical optimization community aboard helps us and our technology to stay on top. QUASAR is based on a decade of research and the math behind it is published in top-ranked peer-reviewed, scientific journals.

Get your risk under control

Smart decision-makers do not just look at the average profit, but keep an eye on the worst case. QUASAR helps you to not only control but also to optimize your value-at-risk.

Manage the complexity of the real world

Up until now, optimization under uncertainty meant sacrificing detail. Not anymore. QUASAR easily handles decision problems with hundreds of time periods, thousands of decisions, and millions of possible scenarios.

Experience a unique ease-of-use

You want to solve a stochastic optimization problem, but do not know how? You don’t have to! QUASAR’s modeling and solver system is designed towards usability and ease-of-use, so you can focus on modeling and analysis and let QUASAR do the heavy-lifting.

How can I use QUASAR?

QUASAR Python

QUASAR Cloud

QUASAR’s Python package seamlessly integrates with popular packages like Numpy, Pandas, and Matplotlib. QUASAR’s Python integration offers you the shortest path from prototype to fully operational production system. Run QUASAR remotely either on premise or hosted by Quantego using our web-based Jupyter notebooks.

QUASAR Matlab

QUASAR 2 Matlab

QUASAR's MATLAB interface now offers quantitative analysts the power of stochastic optimization with QUASAR from inside their favorite workbench. Simply embed our optimizer into existing code and get productive immediately.

QUASAR Java Backend

QUASAR Java Backend

Easily integrate solutions based on QUASAR into enterprise-wide applications. The Java backend offers developers a user-friendly modeling language, flexible interfaces to model customized stochastic processes, as well as full control over the stochastic optimization solver engine.

QUASAR Apps

QUASAR Apps

No time to develop a custom solution? You don’t have to! With QUASAR apps, we provide interfaces for applications like stochastic hydropower planning, gas storage valuation, etc. QUASAR apps are based on thoroughly tested, flexible models, which can be configured to meet user requirements. Let our consultants help you build a custom application from our templates.

  • The sheer size of our reservoir makes it necessary that our hydropower storage assets must be managed over the medium-term, when there is still significant uncertainty about future hydrologic inflows and power prices. Our asset management therefore clearly benefits from stochastic modeling, but only with QUASAR, we are able to solve the stochastic optimization problem in hourly time steps over a three-year planning horizon.


    Dr. Andreas Eichhorn, Portfolio Management at VERBUND Trading, Vienna, Austria

  • The business environment of energy utilities and energy traders is changing constantly, which makes dealing with uncertainty a daily challenge. To cope with this change, flexible and user-friendly tools are required. QUASAR’s Jupyter integration combines productivity, flexibility, and usability in one tool, which makes it a pleasure to prototype and analyze models for everyday’s work tasks.

    Dr. Elke Moser, Research and Analysis at Energieallianz, Vienna, Austria

Applications in Energy

Learn how energy companies already use QUASAR to make smarter decisions in the face of uncertainty.

Hydro power planning

Stochastic Portfolio Management

Electricity retailers usually hedge against uncertainty by managing a portfolio of financial and physical derivative contracts. Optimizing this portfolio not only requires balancing the expected return with the associated risk but also to anticipate the dynamics of possible investments and prices over time. QUASAR makes it easy to find a risk-optimal investment strategy that takes the future of the portfolio into account.

Gas Storage Valuation

Stochastic Gas Storage Valuation

Energy traders frequently need to price contracts on the storage of gas or develop own trading strategies for storage assets. Existing pricing and trading methods based on the (rolling) intrinsic value are effectively deterministic solutions that underrate the value of storage. Our stochastic solutions provide the true value of storage, along with delta positions, distributions of cash flows and storage contents, as well as optimization of the (conditional) value-at-risk.

Capacity Planning

Stochastic Hydropower Planning

Hydropower operation today not only faces uncertainty about natural inflows but also uncertainty about the evolution of electricity prices, which are themselves subject to uncertainty in generation mix and fuel cost. Using QUASAR, Quantego has developed a comprehensive software that enables optimization of hourly dispatch of interconnected hydropower systems over several years under price and inflow uncertainty.

Try QUASAR now!

You want to experience for yourself how easy it can be to solve complex optimization problems? Register and gain access to a free trial of QUASAR.

More Resources

Natural Gas Storage Contracts

Indifference pricing for natural gas storage contracts. Working Paper

Abstract: Natural gas markets are incomplete due to physical limitations and low liquidity, but most valuation approaches for natural gas storage contracts assume a complete market. We propose an alternative approach based on indifference pricing which does not require this assumption but entails the solution of a high-dimensional stochastic-dynamic optimization problem under a risk measure... [more]

Pumped-Hydro Storage Chains

Optimizing trading decisions for hydro storage systems using approximate dual dynamic programming. Operations Research (2013)

Abstract: We propose a new approach to optimize operations of hydro storage systems with multiple connected reservoirs whose operators participate in wholesale electricity markets. Our formulation integrates short-term intraday with long-term interday decisions. The interday problem is modeled as a Markov decision process of managing storage operation over time... [more]

Quantego - The Quants behind QUASAR

At Quantego we are always one step ahead. Being a research-driven company, we are not only up-to-date with the latest trends in applied math, operations research, and machine learning. Our researchers themselves are renowned scientists in these fields, committed to invent the next generation of decision-making technology. They repeatedly publish their breakthroughs in top-notch peer-reviewed scientific journals. We at Quantego are working aggressively to transform these breakthroughs into professional products and services that help our clients to stay ahead.

Dr. Nils Löhndorf

Dr. Nils Löhndorf

Founder of Quantego and scientist behind the QUASAR stochastic optimizer. PhD in operations research. Assistant professor at WU Vienna.

r. Birgit Löhndorf

Dr. Birgit Löhndorf

Responsible for business management and marketing. PhD in marketing and many years of experience as manager and entrepreneur. Assistant professor at WU Vienna.

Prof. Dr. David Wozabal

Prof. Dr. David Wozabal

Expert for energy modeling and responsible for MATLAB 2 QUASAR. PhD in statistics and operations research. Associate professor at TU München.

Dr. Thomas Maindl

Dr. Thomas Maindl

External partner (Dr. Maindl Consulting) with excellent track record in training, quantitative consulting, and implementation for multinational companies. PhD in astronomy.