Graduation Assignment Equity Average Daily Volume Forecast

Are you looking for a challenging graduation assignment or organization where you can do research? PGGM and MN offer you the opportunity to develop yourself, together with the best professionals in the field.

This assignment is part of the unique Academic Excellence Program (AXP). This program is a cooperation between MN and PGGM, two leading Dutch pension fund service providers. Students will get the opportunity to work alongside investment professionals, collaborate with other students and learn about institutional investing. On regular AXP-days all students in the program will come together in The Hague or Zeist to share ideas, learn from each other, attend presentations from investment teams and discuss job opportunities.

The focus of this assignment is to explore the trading behaviors in a given equity market from the observed daily volume traded. Namely, using the historical market variables or their variations, such as quoted prices, volume traded, realized volatilities etc, to build an analytical model (or a set of models) to forecast tomorrow’s traded volume. The techniques or methodology used to build the model(s) are large of the choice/interest of the candidate. The starting point is expected to be a simple time series model such as moving average, autoregressive, seasonality etc. The extension to machine learning models is highly appreciated, i.e., comparing Random Forest, Clustering, Neural Network etc with the simple time series model. Through the assignment, the candidate is going to be exposed to the following research questions or exercises:

• Investigating different measures and defining the proper measure of ADV to forecast, i.e., if the absolute amount is used, the volume forecasts would not be invariant to certain corporate actions such as stock splits;
• Overviewing the underlying micro structure of the equity market to explore volumes/liquidity from different trading platforms;
• Experiencing real data from the financial market, cleansing them and applying time series analysis;
• Applying advanced machine learning models;
• Evaluating forecasting performance across models.

For this assignment the main location will be PGGM in Zeist where you will be part of the Trading Analytics team. You are expected to be in the office about 50% of your time. This internship should be scheduled within the first half year of 2024.

For these assignments we are looking for ambitious students with:

• Quantitative background (eg. Econometrics, Mathematics, Financial Engineering, etc.).
• Programming skills in Python.

Are you looking for a challenging graduation internship to develop yourself? Do you want to work in one of the best working environments in the Netherlands? Then we invite you to join our motivated enthusiastic team.

As an intern at PGGM you will receive:

• Travel allowance.
• A monthly internship allowance.
• The opportunity to gain work experience and develop your skills.
• A great team made up of the best professionals in the business!