Risk Aware k-Min Search Algorithm
Javeria Iqbal, Iftikhar Ahmad, Asadullah Shah, A B M Asadullah · 2019 IEEE 6th International Conference on Engineering Technologies and Applied Sciences (ICETAS) · 2019
Online search and trading algorithms are designed with the prime objective of maximizing the overall profit of investors in a financial market. Investors in any financial market tend to manage their risk levels for better overall returns by the end of investment horizon. Thus the real world applicability of such algorithms lacks the aspect of risk management policy. We consider the problem of online k-min search, where an online player (investor) wants to to acquire (buy)$k$units of an asset by using the minimum possible wealth. In this work, we investigate the k-min search problem and introduce the risk aware k-min search algorithm under the risk reward framework. Further, we show that the presented algorithm meets the bounds presented by AI-Binali (Algorithmica, 1999).