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The Black–Litterman method is widely used in the investment management industry to incorporate views in investment portfolios. The method applies when views are expressed as expected returns over the horizon for which allocation decisions are made, i.e., the investment horizon.

In practice, the investor’s views are typically formulated for the near future while the investor’s investment horizon is much longer. To incorporate such views, we developed the time-dependent Black–Litterman method and show that, in a time-dependent setting, a distinction should be made between unconditional and conditional views.

Furthermore, we have demonstrate its use for buy and hold investors. Also, we show that the investor’s views have a plausible impact on resulting allocation decisions.

Want to know more?
Please download our paper!

Enabling asset managers of housing associations to create their own machine learning models to assist them with their decision making

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Artificial Intelligence (AI) is increasingly used in many domains nowadays. We see data used as input for such models becoming a precious commodity for our clients. With the right tools data can be transformed in valuable insights supporting decision making processes. At Tech Labs we put significant effort into enhancing traditional econometric models on its accuracy while retaining the economic interpretability and exploring innovative ways the make use of proprietary and public data available. In this article we show by example how Dutch housing associations can monetize their data with valuable insights on strategic level. We build a prototype called ASTOR which assist asset managers on creating policies for their real estate portfolio (e.g. …

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This year’s Ethereum Community Conference took place in Paris, in the beautiful building of Conservatoire National des Arts et Métiers. There were 120+ speakers, 800+ attendees, 4 days, 5 conference halls streaming live in parallel and it was only the 2nd edition! The focus of the conference was on 8 tracks: Data, Privacy, Security, EVM, Identity, Compliance, Dapps and a General path. A ninth track brought lighting presentations on innovative projects under development and various workshops, such as deploying an application with Iexec, introduction to scuttlebutt, next generation EVM, Remixbrowser IDE, consensus testing, game theory introduction, …

Nudging autonomous investment decision making for smart contract powered asset management

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Dr. Nudge — Created at the Blockchaingers Hackathon 2018

Just like last year, an Ortec Finance Tech Labs team participated at the Blockchaingers Hackathon 2018. Again a very well-organized mind blowing event where 700 pioneers across 63 teams competed with each other within 7 tracks of global challenges. In our track, the future of pensions, nine teams were present. A nice mix between cooperate, student and start-up teams.

As of April 1 Joris Cramwinckel will start his PhD research at the Finance Group at the University of Amsterdam. The PhD project will focus on blockchain applications for pensions. The research will be interdisciplinary, mainly Finance and Computer Science, contributing to the feasibility of disintermediated pension plans. Prof. dr. Marc Francke (UvA) will be promotor, Dr. Andreas Peter (UTwente) copromotor and Dr. Maarten Everts (UTwente) co-supervisor. In addition, Prof. dr. Jaco van de Pol (UTwente) will fulfill an advisory role.

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Blockchain for Pensions

Technical innovations are currently fueling financial disintermediation. Where artificial intelligence has already gained ground in several finance domains like robo-advisory, fraud detection and AI-driven trading strategies, blockchain technologies is yet scraping the surface of applications in Finance. This technology is, among many other applications, accelerating the application of peer-to-peer finance and risk sharing. …

Michelle is writing her thesis at Tech Labs about chatbots that are embedded inside a web application. She will even create her own chatbot to support financial planners.

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Background information — chatbots

Over the last few years there has been a significant rise in the use of conversational chatbots [1]. Today, we find chatbots everywhere: in the messenger app of Facebook, in Slack, HipChat, WhatsApp, at company websites etc. The main purpose of most of these chatbots is to take over some of the work activities of a support professional. In general the chatbot will answer standard questions that are normally answered by a support professional. …

With conversational interfaces we have finally found a way to improve upon the old point & click paradigm, but how can such an interface be developed?

At Tech Labs we are looking into and working on several possibilities, one of them is Alexa, by Amazon. What started as a Hackathon project is becoming a much more important focus for our research. After creating several skills we started looking at ways to share the knowledge about creating skills for Alexa, the most easily accessible way is through a workshop we created and open-sourced on Github that you can sign up for here.

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Looking for new innovative methods to improve UX is, among Blockchain, AI and Software Technologies one of the main pillars of Tech Labs. Mainly because we provide very complex software solutions and making them simple and easy to use is difficult, but new innovations in UX might make our software more accessible to our users. To this end we tried working with the Amazon Alexa on our hackathon, with success. The skills we created for the real estate department were easy to use and just worked. …

Ortec Finance expands its activities as of 1st January 2018 with the launch of a new entity, named Data Analytics. The entity will focus on big data analysis and will be located at the Ortec Finance head office in Rotterdam.

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35 years of experience

Ortec Finance Data Analytics came into being as a result of the wishes and needs of our customers. Ortec Finance has a unique track record in the field of advanced analytics, and has been analyzing data for more than 35 years. We therefore have the expertise, network and infrastructure in place that enable us to respond to every development in the field of big data analysis. In order to continue to provide the best response to developments in data analytics, Ortec Finance conducts academic research that further strengthens its expertise in relevant technologies, helping it to refine existing models.

Insight and optimization

Ortec Finance Data Analytics helps customers better understand their data and therefore improve their business operations. Data Analytics will provide scalable solutions wherever possible by making use of existing platforms and the infrastructure of companies such as IBM, Microsoft and Google. Data Analytics will initially focus on existing Ortec Finance customer groups, for example pension funds, housing corporations, insurers and banks. …

A master thesis on combining machine learning and econometric modeling. Can we optimize accuracy while maintaining interpretability?

The role of property valuations

Property valuations play an important role in many applications. The Valuation of Immovable Property Act (Wet Waardering Onroerende Zaken, WOZ), requires annual valuation of properties, in order to use this value as input for local property taxes and national income and wealth taxes. Property valuation is also important for mortgage applications and for measuring the performance of a real estate portfolio.

Before a property is sold, we cannot know its price. And since the real estate market is not liquid, we cannot simply use past transaction prices. Hence automated valuation models using statistical methods to estimate the market value are often used for this task. These models use various property characteristics to estimate its market price. …


The need for speed in risk management applications is unabated. If an applications’ performance is improved, users and consultants tend to fill this space rapidly with additional requirements or more complicated calculation settings. Since processor speeds are hardly improving (Figure 1), applications should adopt other paradigms to comply with their current computational requirements. At Ortec Finance we tailor the High Performance Computing (HPC) techniques used in our applications to the domain and to the application usage. Previously, we published articles and posts about heterogeneous computing for nested simulation applications and heavy quantitative model calibrations. In addition, we research web and cloud technologies like Docker, and serverless computing for server-client applications which require elasticity and high availability. These techniques do not assimilate into the more traditional desktop applications in our portfolio. These applications can have very specific requirements (e.g. for security, OS, workload types, etc.) for which no off-the-shelf solutions are available. In this post we focus on our preference for using the Microsoft HPC (MS HPC) framework to distribute our calculation-intensive platform GLASS. We will briefly discuss the road to our decision to use MS HPC, and subsequently explain the match with the MS HPC features to our requirements. …


R&D Labs

We work and experiment with both new modelling approaches and IT techniques and concepts in order to research their applicability to investment decision making

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