Is Dollar-Cost Averaging as effective as we think it is? and  Uncertainty and Strategy in Fair Allocation of Indivisible Items

Speaker: Agassi Lu and Fahimeh Ziaei |PhD Candidates (Mathematics)

Date: November 21, 2024
Time: 4 pm
Room: P110 (Peters Building) & Hybrid

Abstract: Dollar Cost Averaging (DCA) is a widely used investment strategy where fixed amounts are invested at regular intervals, regardless of market conditions, in order to mitigate the impact of market volatility and reduce risks by spreading purchases over time. Our study indicates that while
DCA can lower the volatility of returns by reducing exposure to short-term market fluctuations which makes it preferable for risk-averse investors, it generally underperforms other strategies due to the lack of consistent market growth observed over long periods. This research provides a nuanced perspective on DCA’s utility in retirement savings. It highlights that while DCA may suit conservative investors, other strategies remain statistically advantageous in a predominantly upward-trending market. 

Bio:  Agassi’s research focuses on quantitative finance and risk management. He is currently a student representative of the CANSSI SPARK group. He is also a student researcher at Canada's Financial Wellness Lab.

Abstract:  In collective decision-making, fair and efficient allocation of indivisible items is a notable challenge. Our study assesses various algorithms—such as sequential selection, balanced alternation, and fallback bargaining—analyzing their success in meeting fairness criteria like envy-freeness, Pareto
optimality, maximin, and Borda sum. With two players and a strict preference ordering, fallback bargaining emerges as the holistic algorithm, achieving most criteria but struggling as the item
count increases. The impact of player preferences indicated by Kendall Tau rank correlation, reveals that greater preference similarity improves Pareto-optimal and maximin outcomes but reduces envy-free results, making fallback bargaining less effective. The analysis of risk-averse versus risk-acceptant
strategies further enrich the understanding of fair allocation. To overcome practical limitations, a novel method is proposed to expedite fallback bargaining, making it more feasible for real-world applications with larger sets of items.

Bio:  Fahimeh’s research focuses on the development and analysis of algorithms for fair and efficient allocation of indivisible items. She was awarded the Best Student Paper Award at the International Conference on Group Decisions and Negotiations.