The 2008 Demo Portfolio lists all the real trades executed in one of my brokerage accounts net of commissions costs and YTD P/L. I generally update the spreadsheet on the same day orders were executed.
The first page of the spreadsheet shows the portfolio YTD P/L and the return for a benchmark I built based on a set of equity indexes. The portfolio includes 4 long and 1 short model rebalanced weekly, with each long model trading 5 stocks, for a total of 20 securities on the long side. The short model triggers a limited number of trades and is composed of around 8 stocks on average. Currently the funds allocation is 120% NAV long and 25% short, but I might change the allocation in the future according to market valuation.
All the models have been backtested on more than 8 years of data and include a post-discovery analysis period of 1/2 years. Each model universe is built based on a set of liquidity, fundamentals and price filters and the final candidates are selected applying a ranking system based on fundamental data. Tools that I use consist of a combination of freely resources available online, such as keelix.com and backtester.org, and commercial tools like portfolio123.com and MathLab. The data used by keelix.com is based on AAII weekly downloads, which consist of a revisited version of Reuters data (previously Mutex). Reuters is also the main data source for portfolio123.com. backtester.org use data published by ValueLine.
HFCF (High Free Cash Flow) and NH (New Highs)
Both HFCF and NH are long momentum screens looking for stocks with good fundamental ratios and close to their 52-weeks highs. They are in facts very similar: HFCF has more stringent value rules selecting stocks with higher free cash flow then their industry peers; NH requires a positive 3 months and 6 months uptrend.
PCF (Price/Cash Flow)
This model can be described as a value mean reversion strategy looking for stocks with high operating cash flow and low debt and disregarding recent price action, thus in general favoring oversold stocks. I introduced the strategy in real trading in October 2007 after I had around 10 years of simulation available. So far it has been a disappointment but the entry time was bad given the recent market performances. I'll have to trust simulation data on this.
LKS (Less Known Stocks)
A large winner in 2007, this model seeks to anticipate large institutional moves in low-liquidity stocks, providing good factors diversification to the portfolio. I got the original idea by looking at the Reuters PowerInvestor screens (it still carries the same name) and then added some other insider trading and price/volume data rules.
SHORT
This is by far the most complex model in terms of number of factors employed in the final ranking system. It was backtested for a period including 2003, a difficult time for short strategies. The model requires stocks with poor fundamentals and avoids short-term oversolds, thus limiting the selection to only a few names every month.
I am currently working on a number of new models to improve portfolio diversification. In particular I would like to add a Commodity and a Healtcare model to the set.
Technorati Tags: investing, trading, quantitative model
The first page of the spreadsheet shows the portfolio YTD P/L and the return for a benchmark I built based on a set of equity indexes. The portfolio includes 4 long and 1 short model rebalanced weekly, with each long model trading 5 stocks, for a total of 20 securities on the long side. The short model triggers a limited number of trades and is composed of around 8 stocks on average. Currently the funds allocation is 120% NAV long and 25% short, but I might change the allocation in the future according to market valuation.
All the models have been backtested on more than 8 years of data and include a post-discovery analysis period of 1/2 years. Each model universe is built based on a set of liquidity, fundamentals and price filters and the final candidates are selected applying a ranking system based on fundamental data. Tools that I use consist of a combination of freely resources available online, such as keelix.com and backtester.org, and commercial tools like portfolio123.com and MathLab. The data used by keelix.com is based on AAII weekly downloads, which consist of a revisited version of Reuters data (previously Mutex). Reuters is also the main data source for portfolio123.com. backtester.org use data published by ValueLine.
HFCF (High Free Cash Flow) and NH (New Highs)
Both HFCF and NH are long momentum screens looking for stocks with good fundamental ratios and close to their 52-weeks highs. They are in facts very similar: HFCF has more stringent value rules selecting stocks with higher free cash flow then their industry peers; NH requires a positive 3 months and 6 months uptrend.
PCF (Price/Cash Flow)
This model can be described as a value mean reversion strategy looking for stocks with high operating cash flow and low debt and disregarding recent price action, thus in general favoring oversold stocks. I introduced the strategy in real trading in October 2007 after I had around 10 years of simulation available. So far it has been a disappointment but the entry time was bad given the recent market performances. I'll have to trust simulation data on this.
LKS (Less Known Stocks)
A large winner in 2007, this model seeks to anticipate large institutional moves in low-liquidity stocks, providing good factors diversification to the portfolio. I got the original idea by looking at the Reuters PowerInvestor screens (it still carries the same name) and then added some other insider trading and price/volume data rules.
SHORT
This is by far the most complex model in terms of number of factors employed in the final ranking system. It was backtested for a period including 2003, a difficult time for short strategies. The model requires stocks with poor fundamentals and avoids short-term oversolds, thus limiting the selection to only a few names every month.
I am currently working on a number of new models to improve portfolio diversification. In particular I would like to add a Commodity and a Healtcare model to the set.
Powered by ScribeFire.
Technorati Tags: investing, trading, quantitative model
No comments:
Post a Comment