This study reviews various time series forecasting models in order to find the best fit for the VDAX and VSTOXX for one month and one year. Additionally, the influence of the trading volume of the DAX is examined. Both durations are found to be stationary by the Phillips-Perron test, that is why non-integrated models are used. For a duration of one month, a GARCHX(1,1) model is the best fit in-sample as well as out-of-sample, while the best fit for a duration of one year is found to be a ARX(1) model. Based on the forecasts, two trading strategies are tested for each duration, which is a long only strategy and a combination of long and short trades. The performance of both strategies is compared with a simple buy and hold strategy on each VDAX and VSTOXX. It is found that an excess return over the buy and hold strategy can be generated for both durations even with transaction costs.

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This research should help scholars and practitioners to manage the transition of monolithic legacy application systems to microservices and to better understand the migration process, its steps, characteristics and provide guidance on how best to approach it. We performed a systematic literature review and analyzed migration approaches presented by other researches. We propose to leverage Robotic Process Automation technology to extract business logic, create and deploy bots, which are then used to mimic microservices. In essence, this represents a novel use case, integrating RPA technology into the migration approach in order to reduce uncertainty and risk of failure.

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