Abstract

24:I[63208,["8920","static/chunks/8920-efbff8517d590b7e.js","9097","static/chunks/9097-7e60ff382fede0de.js","5914","static/chunks/5914-356082358a498a0b.js","9903","static/chunks/9903-11222066602aad8e.js","5438","static/chunks/5438-cfc6cd3ec63ed58c.js","3851","static/chunks/3851-d9d99b9df58ccefb.js","4621","static/chunks/4621-60797c2425663d2a.js","6871","static/chunks/6871-85cb03c97585f46a.js","6736","static/chunks/6736-932312a004c99faf.js","4550","static/chunks/4550-0bf059e3050c08b3.js","688","static/chunks/688-a6a2ac7bff269cd3.js","3984","static/chunks/3984-063c0b62f32133c7.js","7038","static/chunks/7038-4f87670d4e55ef18.js","9039","static/chunks/9039-75366c62dc7d0d0e.js","4563","static/chunks/4563-ad980d1babbf7b0b.js","6761","static/chunks/6761-0c10d1446de7ae1c.js","744","static/chunks/744-1e76229abb9e297b.js","7342","static/chunks/7342-1586df78600bf911.js","3617","static/chunks/3617-1f62a097637f4747.js","5895","static/chunks/5895-caa6c774914eb108.js","7481","static/chunks/7481-3b84c503a2ebfb3f.js","3668","static/chunks/3668-7dab69e4121c33af.js","39","static/chunks/39-e93a27d0920e6d92.js","2881","static/chunks/2881-445cc2384af2c6f9.js","2364","static/chunks/2364-e83d52fb21729d99.js","3208","static/chunks/3208-e65462d166bd3688.js","7582","static/chunks/app/toc/%5Btla%5D/%5Bvolume%5D/%5Bissue%5D/page-694a0e465c2c1334.js"],"default"] 25:T40e,

This paper contributes to the existing stock market anomaly literature by being the first to analyze the benefits of combining two distinct anomalies; specifically, the low-volatility and mean-reversion anomalies. Our results show that on a long-only basis, these two time-varying anomalies could be combined into a double-sort investment strategy that includes some desirable characteristics from each of them, thereby making the portfolio return accumulation more stable over time. As the added-value of low-volatility investing stems mostly from the risk-reduction side, while contrarian stocks are generally highly volatile with remarkable upside potential, the use of the double-sort portfolio-formation in which the contrarian stocks are picked from the sub-set of below-median volatility stocks can shorten the below-market performance periods that have occasionally materialized for plain low-volatility or plain contrarian investors.

Abstract

JEL classification: G11

26:T4ed,

In this paper, a shorter and more publication focused version of our recent article “A Bottom-Up Approach to the financial Markets” ( Mahdavi-Damghani, & Roberts, S. 2019.) is presented. More specifically we propose a new approach to studying the financial markets using the Bottom-Up approach instead of the traditional Top-Down. We achieve this shift in perspective, by re-introducing the High Frequency Trading Ecosystem (HFTE) model Mahdavi-Damghani, B. 2017. More specifically we specify an approach in which agents in Neural Network format designed to address the complexity demands of most common financial strategies interact through an Order-Book. We introduce in that context concepts such as the Path of Interaction in order to study our Ecosystem of strategies through time. We show how a Particle Filter methodology can then be used in order to track the market ecosystem through time. Finally, we take this opportunity to explore how to build a realistic market simulator which objective would be to test real market impact without incurring any research costs.

27:T5db,