To help you get the best results using the Quant Investing stock screener I asked a few long time subscribers to show you how they use the screener.
In this article Domenico from Italy shows you how he implements a multi factor quantitative investment strategy.
[Comments in square brackets are mine]
Multi-factor quint investment strategy
My investment strategy includes two steps:
- Build a portfolio of around 30 to 35 global stocks, selected using a multi-factor model
- Implement an overlay through derivatives (futures and or CFDs) to change the net exposure of the portfolio (from 0% to +150%) based on a simple trend following / momentum model.
Data quality is very important
I use the Quant Investing stock screener for the first step of the strategy.
I tested other data vendors but I chose Quant Investing for:
- Its superior data quality (that's paramount: you can build the best model, but if data is garbage it's useless) and
- The option to export large amount of data in Microsoft Excel. This gives me the flexibility to select the indicators I need and combine them in a flexible way.
[To export the results of your screen click the Export Data to MS Excel button]
I use these ratios and indicators to get ideas
In detail, the two main factors I use are:
- Value - I build my own composite value ranking in Excel with the following ratios:
- Price to Book,
- Price to Sales,
- Enterprise Value to EBIT,
- Enterprise Value to EBITDA,
- Enterprise Value to Free Cash Flow
- Momentum - I also build my own momentum indicator in Excel using different periods from 3 to 12 months.
I assign smaller weights to these three factors:
- Yield (shareholder yield, change in total assets, external finance)
- Quality (mainly profitability, but also leverage and accruals)
- Low volatility
I avoid stocks with large or increasing short selling amounts.
[You can do this with the two ratios Short Int % and Short Int % Change – currently only available for the US market]
Some factors (value, quality and yield) have historically produced better risk-adjusted returns if calculated on an intra-sector basis. Working with excel gives me the flexibility to do that.
[To do this make sure you add the Sector and Sub Sector fields to the data you export to Excel.]
All fees and taxes are considered
After combining the different factor scores of each stock (value and momentum) into one total score, I convert it into an expected return, net of trading fees on different exchanges, Tobin taxes (currency transaction taxes), double and withholding taxes on dividends etc.
I then select the stocks with the highest expected net return, given some geographic and sector concentration limits I put in place.
A final check before buying
As I said, I find the quality of the data provided by the Quant-Investing screener satisfactory, but before buying a stock I perform several manual checks, of which the most important are:
- Is data correct?
- Are the ratios and indicators affected by one-off transactions and events (sale of non-core assets, special dividends)?
- Is the company currently part of a takeover/merger?
[For more information on additional research we suggest you do read this article: This is how we select ideas for the Quant Value newsletter]
I hope you have found the article helpful and special thanks to Domenico for sharing his strategy.
PS To implement multi factor quant strategies in your portfolio sign up here