Recently I wrote about lessons learned while I was conducting a manual backtest that made effective use of VectorVest’s outstanding Master Retirement WatchList. This week I sought to automate the process to make it easy for everyone to do their own testing and create their own trading system for possible implementation.
To recap, here are the salient lessons from last week’s essay:
- The earlier you step in and buy high quality stocks when the market is rising from a significant bottom, the faster the gains start to add up. A low Buy-Sell-Ratio, BSR around 0.20 or lower combined with a low MTI around 0.60 or lower indicates the market is near a bottom.
- The Master Retirement WatchList in the Special WatchLists folder provides a reliable source high quality stocks, mostly high RV and RS, that consistently outperforms the market over time. The WatchList is updated every Monday night by adding top stocks from eight of VectorVest’s best conservative, prudent and retirement searches.
- For consistent returns and a high win ratio, only buy stocks that are rising in price, have rising earnings, and ideally a VectorVest “B” or Buy rating. A rising slope of VectorVest’s exclusive 40-week Moving Average of RT additionally puts probabilities on your side.
- Having Sell-rules is essential for locking in gains and avoiding substantial losses.
To automate my plan, I first needed to create and save a search that would return stocks with rising prices and rising EPS from the Master Retirement WatchList. Here are the criteria I settled on, but go ahead and modify if you wish. Click on UniSearch to begin.
|Sort = RS*CI|
|Time of Search||Stock WatchList||=||Master Retirement Watchlists|
|Time of Search||Stock 40 Day MA(RT)||>||1|
|Time of Search||Stock EPS – (Earnings Per Share)||>||26 weeks ago Stock EPS|
|Time of Search||Stock REC – (Recommendation)||=||Buy|
Next, I went to the Backtester. With a little trial and error, I settled on the settings set out below. My test period was 01/04/2019 to 10/18/2019, the same as last week. Here are the settings: (defaults are used unless specifically noted):
Account Settings – $100,000 account size; $9.95 per trade Commission; Execute test in weekly pricing mode. (I wanted a strategy that doesn’t take a lot of time!)
Timing – GLB/RT Kicker
Rules (UP) – Buy from the above search. Stop Criteria: 25% Trailing Stop with 10% Max Loss. Automatically replace closed positions. Try to maintain 16 positions and open a maximum of 6 positions in a single day. When entering this situation: Don’t close any open position. Invest average portfolio value.
Rules (Down): No action
Rules (Neutral): No Action
How were my results? How about a gain of 24.62% or 31.33% ARR and a max drawdown of just 5.12%? Just 18 trades, 15 winners and 3 losers for a win-rate of 83%. Best trade was 32 shares of Shopify, SHOP for a gain of $6,923.77. Worst trade was 127 shares of Great Canadian Gaming, GC, a loss of $912.71. I’m ready to convert the Backtest to Portfolio Manager where I can set up my alerts and live trades.
So, while last week’s manual Backtest with buy and sell decisions determined by the graphs delivered marginally better results, it was a lot more work and decisions were somewhat subjective. An automated system like this, where buy and sell alerts are based on your pre-set rules, is more accurate, easier to implement and simple to carryout, and I’m pleased with my results. You may do even better by testing and AUTOMATING YOUR TRADING PLAN WITH A GREAT WATCHLIST.