KiBlat Analysis for Stock Selection with Growth Earning Lynch Model

DOI

10.2991/aebmr.k.211225.039How to use a DOI?

Keywords

Greenblatt; Investment; Lynch; Piotroski; Stocks

Abstract

This study was conducted to find an easier screening method, by combining Piotroski and greenblatt then be called KiBlat analysis that has been screened early with modifications to the Growth Earning Lynch Model. The modified screening with KiBlat analysis will be proven in the research period 2015 – 2018. Restrictions in that period are intended to avoid stock market anomaly such as the presidential election in 2014 and 2019 then the anomaly covid 19 in 2020. We used quantitative approach, the initial stage of research conducted data validation by classifying stocks based on Lynch model method and taking data on go-public companies during the research period. The next analysis of this validated stock selection will be reanalyzed by making Piotroski modifications with Greenblatt magic formula. The result will be compared to the historical return of the market for the selection of these stocks. Data analysis was performing by multiple linear regression analysis method. The results of this study showed that the stock selection with validation Earning Lynch Model and analysis it with Piotroski then greeenblatt magic formula has significant impact toward the stock return on companies listed.

Copyright

© 2022 The Authors. Published by Atlantis Press International B.V.

Open Access

This is an open access article under the CC BY-NC license.

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TY  - CONF
AU  - Niken Savitri Primasari
AU  - Mohammad Ghofirin
PY  - 2022
DA  - 2022/01/13
TI  - KiBlat Analysis for Stock Selection with Growth Earning Lynch Model
BT  - Proceedings of the International Conference on Sustainable Innovation Track Accounting and Management Sciences (ICOSIAMS 2021)
PB  - Atlantis Press
SP  - 284
EP  - 289
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.211225.039
DO  - 10.2991/aebmr.k.211225.039
ID  - Primasari2022
ER  -