New Cup and Handle Strategy Suggestions

Introduction

Over the vacation I have been examining ways to improve the strategy suggestions for trading stocks on the Cup and Handle watchlist. I was motivated to do this because the published suggestions, which had worked well in 2016, did not function so well in 2017 and so changes were clearly necessary. I approached this by first looking at the factors that influenced whether or not a stock on the watchlist would exceed its breakout price on the next day and then proceeded to find the optimum configuration of these factors that would give the highest probability of predicting a close above breakout price. This process gave me a new metric that predicted a close above BoP with 73% accuracy in 2017 and 66% when back tested to 2014. It also led me to new strategy suggestions for Buy on Alert and Buy at next Open.

Model to Predict Close Above BoP

I have a database of all alerts that were issued since 2014. I extracted from this all the alerts that were issued for stocks on the Cup and Handle Watchlist and then categorized them into two groups: those that closed above their BoP and those that did not. In addition to knowing the alerts that were issued, I maintain a historical database of all stocks on NYSE, NASDAQ and AmEx exchanges and their associated daily metrics. Prices in this database are adjusted for corporate actions (splits, dividends) and the original alert and BoP's were adjusted as necessary for consistency. Using a statistical technique called Discriminant Analysis I was able to identify the factors on the day before the alert was issued that had a statistically significant influence on the final close on the day an alert was issued. These factors, in order of importance were:

• Momentum slope (the rate of change of momentum)
• Momentum
• Positive Quarterly Earnings (last two quarters)
  
• Previous day rise in price and volume
• Volume as a Percentage of 50 day average volume
• Quarterly Earnings Growth Rate Acceleration over previous 4 quarters
• Relative Strength Rank

I further found that this model was most effective for stocks with an average daily volume of at least 500,000 and were in the BoP range $6 - $12. The model is only applied to stocks meeting these criteria.

The following table shows how the model allocated stocks to each group compared to the group to which the stocks belonged. It shows that of 137 alerts in 2017 that satisfied the price and volume preconditions, 100 were allocated correctly (38 to the non-breakout group and 62 to the successful breakout group). That's a success rate of 73%.

When the model was applied to all alerts back to 2014 (including 2017) the success rate fell to 66%. Of 788 stocks that met the price and volume preconditions, 523 were allocated correctly.

Suggested Strategy Using the Breakout Prediction Model

Buy on Alert

Based on this model, we can identify that if an alert is given (meaning the real-time price has reached the BoP) on a stock that the model predicts will close above BoP, then the stock will close above BoP with an approximately 70% probability

If those conditions are met, then by using the backtest tool, I have determined the optimum return trading rules:

Buy if:

• breakout prediction model predicts close above BoP
• volume is equal to or greater than average volume.
• Hold even if the close is not above BoP
• Hold no more than 2 simultaneous positions

Sell if

• intraday low exceeds 3% of most recent high (i.e. a trailing stop of 3%).

Applying these rules to alerts in 2017, and fully reinvesting gains, the backtest tool gave a 71% return.

Notes

1. The backtest parameters shown above were found to be optimum through automated backtest simulations.
2. The optimum parameters suggest using a relatively tight trailing stop (3%) whereas the backtest suggested a 10% trailing stop in 2016. This chart shows market volatility has been trending down since 2016. With lower volatility, a tighter trailing stop is appropriate. This allows cutting losses sooner and moving on to a potentially more profitable trade. If volatility begins to increase in 2018, then the appropriate trailing stop will need to be reassessed.
3. The confirmation volume ratio is not relevant as the backtest suggests that once bought the position should be held until the trailing stop is hit.
4. The breakout prediction modelling process found that Relative Strength (RS) Rank had the weakest influence on breakout probability. I have previously recommended a minimum RS Rank of 92 -94 but I now suggest ignoring RS Rank (our minimum for inclusion on watchlists is 80).
5. Subscribers are welcome to play with the backtest tool. When first activated, these optimum parameters will be automatically entered. Subscribers are welcome to vary the parameters and rerun.

Watchlist Filter Settings

Stocks that are predicted to close above their BoP at the next session can be found by using these settings on the Cup and Handle watchlist.