Empirical Analysis of an Online Algorithm for Multiple Trading Problems

Abstract

If we trade in financial markets we are interested in buying at low and selling at high prices. We suggest an active trading algorithm which tries to solve this type of problem.The algorithm is based on reservation prices. The effectiveness of the algorithm is analyzed from a worst case and an average case point of view. We want to give an answer to the questions if the suggested active trading algorithm shows a superior behaviour to buy-andhold policies. We also calculate the average competitive performance of our algorithm using simulation on historical data.

Experimental Analysis of an Online Trading Algorithm

“…The ratio c t (k) can be interpreted as the geometric return we can achieve by buying and selling sequentially as stated in [5].…”

Online Financial Algorithms: Competitive Analysis

“…Online player is always interested in buying low and selling high. An active online algorithm [16] can solve such problems. Now the big question is whether this active algorithm outperform buy and hold policies.…”