1. Use It As A Mechanical Trading System
I derived T-Rank 2.0's historical performance data from back testing. A trader may want to follow strictly the trading schemes used in the back testing to copy its performance. The schemes are straightforward and should be easy to follow:
- On every weekend compute the ranks of all stocks that satisfies the liquidity requirements documented here.
- Pick the top k stocks. In my back testing I used 20 because I think 20 is the maximum size that is manageable by an individual to reduce volatility. But any constant k would work.
- Allocate fund equally among the k stocks. If you have $200K and want to trade 20 stocks, then each stock gets $10K.
- Place order to buy at market price at market open on Monday.
- Hold the portfolio for n weeks. Any n between 1 and 6 would work and should generate similar returns.
- On the Monday of the (n+1)-th week, liquidate the portfolio at market price at market open.
- Repeat the first step. If a stock is reselected, you can save the steps to sell and buy it back.
In the back test, a 0.5% slippage was deducted from every transaction. As long as that 0.5% covers your commission and bid / ask spread, you should get the same performance.
But there is one concern and that is the liquidity. The liquidity requirements ask for $3 per share and 50K shares daily average volume. So the worst case scenario is that you only have $3 * 50K = $150K traded per day. I think you couldn't put in more than $2K to your market order without significantly moving the price. Multiply that with 20, the size of your portfolio, in the worst case scenario, is only $40K, and the annualized return is $40K * 26.70% = $10.68K. Not bad but you are not going to get rich with this.
I know this is the worst case scenario and you can always allocate more money on stocks with higher liquidity to circumvent this problem. But that may or may not hurt your overall return. I don't have data on this yet. Maybe I should run more back test on this.
Furthermore, the liquidity constraints prevent one from sharing his trading ideas with his friends, which may upset either the trader or his friends.
2. Use It As A Screener
In this way maybe I could publish the top 300 stocks, or stocks with rank above 90 each weekend, and my fellow friends could pick several, say up to 20, from the list and trade. This model works the best if each of my friend has his own way to pick stocks, be it fundamental based or technical based. One may use support and resistance to select the most promising opportunities, while another may check overbought and oversold conditions.
However there are still restrictions:
- Their methods should be different from one another.
- The ranks may not be published together with the stocks, to prevent everyone from simply picking the top ranked stocks.
- Everyone still needs to spend a lot of effort to comb through the 300 stocks, which is time consuming unless they have some automated way to pick stocks.
- It is up to the trader to determine entry and exit. The general suggestion is that one can hold a stock as long as it keeps showing up in the top 300 list.
3. Use It As A Ranking System
So each trader has his own watch list. They are supposed to derive such list based on their own knowledge, market sense, and interest. Then they consult the ranking system to decide which stocks (those with high ranks) they want to put on trade and for the rest they may want to wait a little bit.
This will remove the conflicts among traders that share the ranking system, but it also has higher requirements on each trader.
So each option has its pros and cons. There is really no such thing as free lunch.
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