Behav_Fin_PPT_QualityMinusJunk Factor (1).pptx

Validating Quality minus junk factor in Indian Market

1. Behavioral Finance Submitted By: Group 10 0011/58 Ashish Panwar 0044/58 Lakhshya Khurana 0054/58 Anirudh Agarwal 0128/58 Arun Yadav 0166/58 Simran Diwedi 0167/58 Adarsh Gupta 0179/58 Shubham Kalani 0216/58 Pulkit Pandey Quality Minus Junk

2. INDEX 03 04 05 Hypothesis 01 Variables Portfolio Analysis Portfolio Construction Data 02 06 Performance During Crisis

3. Hypothesis & Theory 01 Quality stocks are defined as stocks that have high profitability, high growth, low risk, and high payouts. 02 03 04 Logically, the prices of such stocks should demand a premium over other stocks and thus should yield lower returns on a long-term basis. But authors find that the price premium being paid by investors for quality stocks is not sufficient, which results in higher risk-adjusted returns on quality stock and negative risk-adjusted returns on junk stocks. Prices and returns are naturally connected, and a uthors have shown that the price of quality negatively predicts the future return on QMJ.

4. Hypothesis & Theory 05 Authors theorize that market prices may be based on superior quality characteristics( some omitted variable/s), explaining limited power of quality of prices. 06 07 08 T he quality characteristics may be correlated with risk factors not captured in the risk adjustments, explaining lack of captured risk in a quality security leading to lower returns. Market prices may fail to fully reflect the characteristics linked to behavioral finance or some other constraints QMJ strategy is different from HML(High-minus-low), in fact both are negatively correlated. QMJ is based on quality characteristics irrespective of prices, while HML is based on stock prices.

5. Data Dataset is collected from CMIE Prowess IQ database. Following parameters for all BSE 500 stocks are compiled: Closing price of the stock Beta & Market Cap Revenue, EBIT, PAT, OCF, Total Assets, Equity Incorporated year Dividend Data is then cleaned for any missing data.

6. Variables Now, it is essential to generate a quality score based on 3 quality measures: Profitability : Using sustainable part of profits in relation to the book values; including measures such as return on equity, return on assets, and cash flows over assets. Growth : Parallelly, we see the growth in the sustainable profits metrics in relation to the book values; which include ROE, ROA, cash flow over assets 3-year growth rates. Safety , which includes stocks with low market beta, volatility, and leverage. For every factor, we normalize the score for all companies and create a normalized factor score, which are all added to create a final quality score. * A 4 th factor, Payout might also be added, including net equity issuance, net debt issuance, and total net payout over profits. Quality = z ( Profitability + Growth + Safety)

7. Portfolio Construction Portfolio is developed by ranking Quality score composite. Quality stock portfolio constitute Top 10 stocks ( Equal-weighted) based on Quality score of a particular year. Junk stock portfolio constitute Bottom 10 stocks ( Equal-weighted) based on Quality score of a particular year. Portfolio is rebalanced at the end of every year. Return of the Portfolio is calculated at the end of every year.

8. Portfolio Analysis CAGR=18.2% CAGR=17.1%

9. Performance during 2008 GFC & 2020 COVID Crisis The Quality portfolio has higher returns during 2008 GFC and 2020 COVID crisis than Junk portfolio. This result is in line to our hypothesis that quality outperform junk during crisis. There could be several reasons that our paper could not able to replicate the hypothesis in year 2009. One of the reason could be: No diversification : Portfolio has only 10 stocks

10. THANK YOU!

11. Appendix 1-2008 2008-Quality 2008-Junk

12. Appendix 2-2020 2020-Quality 2020-Junk