What? We want to point out that each single task in quantitative finance can become complex and bear the danger of fundamental mistakes, why those can become horrible in interplay and that there is hope to avoid them and how.
Model Types. There are so many around? Which one should I use? What do they have in common? What are their differences, limitations, uncertainties,..? What does model uncertainty mean? Do more factors really explain more?
Numerical Methods. Famous people use tree methods. When do they make sense? What are advantages of FD and FE methods?
Is MonteCarlo just gambling? What does MC mean? How do I treat, say, Bermudan rights in MC?
Model calibration. Model parameters should be stable and robust. How can I achieve this? Can really? Which data should be used? How many of them?
The fits is good. Why is the price so bad? What does overfitting mean?
Implementation. Faster calculation by parallelisation. What do I have to consider? What can I learn from the Play Station? Is risk management of good nature for parallel constructs?
Who? Andreas Binder and Michael Aichinger.