after weeks of intense research and in spite of the current situation, I decided to ask the following question to some experts (you):
I would like to develop/investigate a volatility managed six factor model according to Fama French (2018), where the 6 Fama French factors (Choosing Factors) undergo a volatility management according to Moreira and Murr (2017)? https://www.nber.org/papers/w22208 (Volatility Managed Portfolios). The scope of this procedure is to come up with new, volatility managed FF factors (monthly) in order to calculate the expected return (Risk Premia) for the volatility managed six factor model. Furthermore I would run a test for systematic misspricing and compare the maximum squared sharpe ratios that both of the models generate as well as a principal component analysis and maybe some more stuff.
My questions are:
1.) Does it make sense from a theoretical and practical standpoint?
2.) How to interpret the volatility managed Risk premia? The results are only valid if an investor runs monthly volatility timing, right?
3.) Can this whole volatility managed six factor model be interpreted as an active investment strategy, where all FF 6 factors (strategies) run simultaneously? I think there might be a problem in terms of diversification and repetition as some strategies might run in an opposite way
4.) The volatility managed strategy makes no sense with single stocks, right? It could only make sense when the simultaneous systematic misspricing is lower than the regular FF 6 factor model?
5.) Which constrains should be imposed when selecting the test assets (Firm characteristics/Covariance Matrix)? I guess this approach might only work for (well diversified) portfolios or Test Portfolios by Fama French
I found this approach very appealing, as the 6 factors of FF (2018) act as input "Portfolios/Strategies" for the volatility management procedure according to Moreira and Murr (2017). The 6 Factors of FF (2018) are directly obtained from the well known Fama French research page. Moreira and Murrs` (2017) key findings are : "Managed portfolios that take less risk when volatility is high produce large alphas, substantially increase factor Sharpe ratios, and produce large utility gains for mean-variance investors (...). Volatility timing increases Sharpe ratios because changes in factor volatilities are not offset by proportional changes in expected returns. Our strategy is contrary to conventional wisdom because it takes relatively less risk in recessions and crises yet still earns high average returns".
The FF 6 factor model augments their 5 factor model by the momentum (UMD) factor, that was already included in the Fama French Carhart model (1997). In spite of their 5 factor model, FF (2015) dropped the momentum factor and added RMW (robust minus weak - profitability factor) as well as CMW (conservative minus aggressive - investment factor).
To be more precise: Within Moreira and Murr (2017) - Volatility Managed Portfolios, the 6 fama french factors act as f+1 (buy-and-hold excess return) multiplied by a target level of volatility (scaling factor-c) divided by the portfolios conditional variance. The result of this equation is the volatility managed excess return for the corresponding trading strategy (Fama French factor). The FF factors themselves are factor returns for different trading strategies (e.g. the value factor HML - high minus low describes the premium for running a value strategy, where you take a long position on value stocks (high B/M) and a short position on growth stocks (low B/M)