Bad Apples Performance - 2017-12-01
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Performance by Trade Duration
Performance of “Bad Apples” algorithm by trade duration measured in days after alert. All scores (1 to 10).
| Weighted Profit | Average Profit | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Duration | Per Trade | Annual | Compound | $ WR | Per Trade | Annual | Compound | $ WR | Trade WR |
| 1 | 0.6% | 143% | 316% | 66% | 0.5% | 115% | 214% | 64% | 55% |
| 2 | 1.3% | 165% | 414% | 66% | 1.3% | 159% | 384% | 68% | 59% |
| 3 | 1.9% | 161% | 391% | 69% | 1.7% | 143% | 313% | 68% | 59% |
| 4 | 1.9% | 122% | 235% | 67% | 1.9% | 122% | 233% | 65% | 59% |
| 5 | 1.7% | 85% | 132% | 61% | 2.0% | 100% | 168% | 67% | 58% |
| 6 | 1.6% | 67% | 95% | 64% | 2.1% | 88% | 139% | 64% | 58% |
| 7 | 1.6% | 56% | 75% | 61% | 2.2% | 80% | 120% | 64% | 58% |
| 8 | 1.6% | 49% | 63% | 63% | 2.3% | 72% | 104% | 65% | 58% |
| 9 | 1.8% | 51% | 65% | 63% | 2.5% | 70% | 99% | 66% | 58% |
| 10 | 1.7% | 43% | 53% | 61% | 2.6% | 65% | 90% | 67% | 58% |
| 11 | 1.8% | 40% | 49% | 64% | 2.6% | 59% | 80% | 64% | 59% |
| 12 | 1.9% | 40% | 48% | 67% | 2.8% | 58% | 77% | 67% | 59% |
| 13 | 2.0% | 39% | 47% | 69% | 2.8% | 55% | 72% | 67% | 59% |
| 14 | 2.0% | 37% | 44% | 67% | 2.9% | 52% | 67% | 66% | 60% |
| 15 | 2.3% | 39% | 47% | 65% | 3.1% | 52% | 67% | 67% | 60% |
| 16 | 2.3% | 37% | 44% | 66% | 3.1% | 49% | 62% | 66% | 59% |
| 17 | 2.2% | 32% | 37% | 67% | 2.9% | 43% | 52% | 67% | 59% |
| 18 | 2.3% | 33% | 38% | 67% | 3.2% | 45% | 55% | 67% | 59% |
| 19 | 2.6% | 34% | 40% | 67% | 3.3% | 44% | 54% | 67% | 59% |
| 20 | 2.7% | 33% | 39% | 66% | 3.4% | 43% | 52% | 68% | 59% |
| 21 | 3.0% | 35% | 42% | 67% | 3.6% | 43% | 53% | 69% | 60% |
| 22 | 3.0% | 34% | 40% | 67% | 3.7% | 42% | 52% | 67% | 60% |
| 23 | 3.1% | 34% | 40% | 68% | 3.9% | 42% | 52% | 66% | 60% |
| 24 | 3.4% | 36% | 42% | 67% | 4.2% | 44% | 54% | 69% | 60% |
| 25 | 3.8% | 38% | 46% | 68% | 4.5% | 45% | 56% | 71% | 60% |
| 26 | 3.8% | 36% | 43% | 67% | 4.5% | 44% | 53% | 71% | 60% |
| 27 | 3.7% | 34% | 40% | 65% | 4.6% | 43% | 52% | 71% | 59% |
| 28 | 3.7% | 33% | 38% | 65% | 4.7% | 42% | 51% | 70% | 59% |
| 29 | 3.8% | 33% | 38% | 68% | 4.7% | 41% | 50% | 72% | 59% |
| 30 | 3.6% | 31% | 35% | 69% | 4.5% | 38% | 45% | 69% | 59% |
| 31 | 3.6% | 29% | 33% | 69% | 4.4% | 36% | 42% | 69% | 59% |
| 32 | 3.5% | 27% | 31% | 69% | 4.3% | 34% | 40% | 68% | 60% |
| 33 | 3.3% | 26% | 29% | 67% | 4.2% | 32% | 37% | 66% | 59% |
| 34 | 3.4% | 25% | 28% | 68% | 4.3% | 32% | 36% | 67% | 59% |
| 35 | 3.0% | 22% | 24% | 66% | 4.2% | 30% | 34% | 65% | 59% |
| 36 | 3.0% | 21% | 23% | 63% | 4.2% | 29% | 33% | 66% | 60% |
| 37 | 2.7% | 18% | 20% | 63% | 3.9% | 26% | 30% | 64% | 60% |
| 38 | 2.5% | 16% | 18% | 60% | 3.8% | 25% | 28% | 65% | 59% |
| 39 | 2.6% | 17% | 18% | 61% | 4.0% | 26% | 29% | 64% | 60% |
| 40 | 2.7% | 17% | 18% | 58% | 3.9% | 24% | 27% | 64% | 60% |
| 41 | 2.4% | 15% | 16% | 56% | 3.8% | 23% | 26% | 63% | 59% |
| 42 | 2.1% | 13% | 14% | 55% | 3.7% | 22% | 24% | 62% | 59% |
| 43 | 1.8% | 11% | 11% | 55% | 3.5% | 21% | 23% | 60% | 59% |
| 44 | 1.7% | 10% | 10% | 57% | 3.5% | 20% | 22% | 62% | 59% |
| 45 | 1.5% | 8% | 9% | 56% | 3.4% | 19% | 20% | 60% | 59% |
| 46 | 1.7% | 9% | 9% | 56% | 3.8% | 21% | 22% | 61% | 58% |
| 47 | 1.8% | 9% | 10% | 57% | 3.9% | 21% | 23% | 61% | 58% |
| 48 | 1.7% | 9% | 9% | 54% | 4.0% | 21% | 23% | 62% | 59% |
| 49 | 1.7% | 9% | 9% | 56% | 4.0% | 20% | 22% | 62% | 59% |
| 50 | 1.7% | 8% | 9% | 54% | 3.8% | 19% | 21% | 62% | 59% |
| 51 | 1.5% | 8% | 8% | 54% | 3.8% | 19% | 20% | 61% | 59% |
| 52 | 1.5% | 7% | 8% | 54% | 4.0% | 19% | 21% | 61% | 59% |
| 53 | 1.3% | 6% | 6% | 57% | 3.8% | 18% | 19% | 60% | 59% |
| 54 | 1.4% | 6% | 7% | 56% | 4.0% | 19% | 20% | 59% | 59% |
| 55 | 1.5% | 7% | 7% | 56% | 4.1% | 19% | 20% | 60% | 59% |
| 56 | 1.7% | 8% | 8% | 60% | 4.5% | 20% | 22% | 61% | 58% |
| 57 | 1.5% | 7% | 7% | 58% | 4.6% | 20% | 22% | 62% | 59% |
| 58 | 1.7% | 7% | 8% | 60% | 4.7% | 20% | 22% | 62% | 59% |
| 59 | 1.4% | 6% | 6% | 60% | 4.6% | 19% | 21% | 64% | 59% |
| 60 | 1.5% | 6% | 7% | 60% | 4.7% | 20% | 22% | 63% | 59% |
This is alert price to day close price performance for signaled positions. The performance assumes shorting position at the alert price and covering position EOD (end-of-day) on the day of the alert or one of the following days.
“Duration” is the trade duration measured in a number of trading days. It does not count weekends and holidays. Duration represents a short position holding period. If position was shorted and covered on the same day (intraday), the duration is 1. If position was covered on the next day after alert, the duration is 2, etc.
Weighted Profit is calculated as a score-weighted average profit. In a weighted approach dollar allocation to a trade is proportional to the provided score. Average Profit is an arithmetic (equal weight) average profit.
WR is a Win Rate from 0% to 100%. Dollar Win Rate measures ratio between dollars won and lost. Trade Win Rate measures ratio of winning trades by count, ignoring dollar wins.
Based on published signals and EOD data upto 60 days after alert:
• Weighted Allocation Profit per Trade peaks at 3.8% on the 25th day
• Weighted Allocation Annual (Simple Sum) Profit peaks at 165% on the 2nd day
• Weighted Allocation Annual Compounded Profit peaks at 414% on the 2nd day
• Weighted Allocation Dollar Win Rate peaks at 69% on the 3rd day
• Average Profit per Trade peaks at 4.7% on the 28th day
• Average Annual (Simple Sum) Profit peaks at 159% on the 2nd day
• Average Annual Compounded Profit peaks at 384% on the 2nd day
• Average Dollar Win Rate peaks at 72% on the 29th day
• Trade Win Rate peaks at 60% on the 14th day
Generally trade return is higher for longer trade duration. However, executing more trades per year may result in a better annual return.
Annual and Compounded returns are estimated based on 252 trading days in a calendar year.
Please note that these numbers may change substantially as more signals are issued by the algorithm.
This is simplified alert-to-close performance calculations. An experienced day trader, who is able to capture highs and lows, would have outperformed simplified performance substantially.
Profits in the weighted approach will appear more “jumpy” (volatile) compared to the equal weight approach because a handful of positions with a higher score will determine the total outcome.
Also because we started publishing these signals recently, the profits for trades with longer duration will appear more “jumpy” due to a smaller number of positions associated with those trades.
These trades are theoretical. They do not include trading costs. Deducting 0.2-0.5% per trade for trading costs is a reasonable assumption for most traders. Trading frequently can incur substantial commissions. Holding a short position with a high borrowing interest rate for excessive period of time may result in substantial borrowing fees. Although high borrowing interest rates usually decline when stock’s volatility goes down.
Performance by Trade Duration for Score 2 and Above
Performance of “Bad Apples” algorithm by trade duration for scores 2 to 10.
| Weighted Profit | Average Profit | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Duration | Per Trade | Annual | Compound | $ WR | Per Trade | Annual | Compound | $ WR | Trade WR |
| 1 | 0.6% | 156% | 371% | 65% | 0.6% | 153% | 359% | 63% | 56% |
| 2 | 1.3% | 164% | 411% | 69% | 1.4% | 175% | 468% | 70% | 59% |
| 3 | 1.9% | 163% | 405% | 67% | 2.0% | 167% | 422% | 67% | 60% |
| 4 | 1.9% | 119% | 227% | 64% | 2.1% | 132% | 268% | 67% | 60% |
| 5 | 1.4% | 69% | 99% | 60% | 1.7% | 88% | 139% | 60% | 59% |
| 6 | 1.2% | 51% | 66% | 61% | 1.8% | 76% | 111% | 63% | 58% |
| 7 | 1.1% | 40% | 49% | 62% | 1.9% | 70% | 100% | 64% | 58% |
| 8 | 1.1% | 35% | 42% | 63% | 2.0% | 62% | 85% | 65% | 57% |
| 9 | 1.3% | 37% | 44% | 64% | 2.3% | 63% | 87% | 64% | 57% |
| 10 | 1.1% | 28% | 32% | 60% | 2.3% | 59% | 79% | 63% | 58% |
| 11 | 1.1% | 26% | 29% | 64% | 2.4% | 55% | 72% | 63% | 59% |
| 12 | 1.2% | 26% | 30% | 66% | 2.5% | 52% | 67% | 65% | 60% |
| 13 | 1.3% | 26% | 30% | 67% | 2.5% | 49% | 63% | 66% | 60% |
| 14 | 1.5% | 26% | 30% | 64% | 2.8% | 50% | 64% | 65% | 60% |
| 15 | 1.8% | 30% | 35% | 64% | 3.2% | 54% | 71% | 64% | 61% |
| 16 | 1.8% | 29% | 33% | 64% | 3.2% | 51% | 65% | 66% | 59% |
| 17 | 1.6% | 24% | 27% | 65% | 2.9% | 43% | 53% | 64% | 59% |
| 18 | 1.7% | 24% | 27% | 64% | 3.0% | 42% | 52% | 67% | 59% |
| 19 | 2.0% | 27% | 31% | 63% | 3.2% | 42% | 52% | 66% | 60% |
| 20 | 2.2% | 27% | 31% | 65% | 3.4% | 42% | 52% | 66% | 60% |
Taking fewer positions may improve returns, but also may result in strategy/portfolio being more volatile (risky).
Performance by Trade Duration for Score 8 and Above
Performance of “Bad Apples” algorithm by trade duration for scores 8 to 10.
| Weighted Profit | Average Profit | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Duration | Per Trade | Annual | Compound | $ WR | Per Trade | Annual | Compound | $ WR | Trade WR |
| 1 | 0.7% | 182% | 513% | 56% | 0.7% | 187% | 541% | 57% | 57% |
| 2 | 1.7% | 209% | 695% | 61% | 1.7% | 216% | 747% | 62% | 59% |
| 3 | 2.8% | 234% | 908% | 63% | 2.8% | 239% | 958% | 63% | 61% |
| 4 | 2.3% | 146% | 323% | 64% | 2.4% | 151% | 346% | 64% | 63% |
| 5 | 1.8% | 91% | 147% | 63% | 1.9% | 97% | 161% | 62% | 63% |
| 6 | 1.8% | 74% | 107% | 60% | 1.8% | 75% | 111% | 60% | 61% |
| 7 | 1.0% | 36% | 43% | 60% | 1.0% | 38% | 45% | 60% | 59% |
| 8 | 0.5% | 17% | 19% | 58% | 0.6% | 19% | 21% | 58% | 59% |
| 9 | 0.3% | 9% | 10% | 59% | 0.4% | 11% | 12% | 59% | 59% |
| 10 | -0.7% | -17% | -16% | 60% | -0.6% | -16% | -15% | 60% | 58% |
| 11 | -0.9% | -20% | -18% | 61% | -0.8% | -19% | -18% | 60% | 59% |
| 12 | -0.8% | -17% | -15% | 58% | -0.8% | -16% | -15% | 58% | 59% |
| 13 | -0.7% | -13% | -12% | 62% | -0.6% | -12% | -11% | 62% | 59% |
| 14 | -0.8% | -14% | -13% | 61% | -0.7% | -13% | -12% | 61% | 59% |
| 15 | -0.5% | -9% | -9% | 62% | -0.5% | -8% | -8% | 62% | 60% |
| 16 | -0.6% | -10% | -9% | 61% | -0.6% | -9% | -9% | 61% | 59% |
| 17 | -0.5% | -8% | -7% | 62% | -0.5% | -7% | -7% | 62% | 59% |
| 18 | -0.2% | -3% | -3% | 62% | -0.2% | -3% | -3% | 61% | 59% |
| 19 | 0.3% | 3% | 3% | 63% | 0.3% | 4% | 4% | 63% | 60% |
| 20 | 0.2% | 2% | 3% | 61% | 0.2% | 3% | 3% | 63% | 59% |
Performance by Trade Duration for High Alert Price and Score 2 and Above
Performance of “Bad Apples” algorithm by trade duration for high alert price and scores 2 to 10.
| Weighted Profit | Average Profit | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Duration | Per Trade | Annual | Compound | $ WR | Per Trade | Annual | Compound | $ WR | Trade WR |
| 1 | 0.7% | 186% | 536% | 61% | 0.7% | 183% | 520% | 60% | 55% |
| 2 | 2.0% | 257% | 1,178% | 67% | 2.1% | 262% | 1,235% | 66% | 62% |
| 3 | 2.8% | 238% | 945% | 67% | 2.7% | 230% | 867% | 66% | 61% |
| 4 | 2.4% | 154% | 358% | 62% | 2.7% | 170% | 437% | 65% | 61% |
| 5 | 1.7% | 84% | 129% | 61% | 2.0% | 103% | 178% | 63% | 60% |
| 6 | 1.4% | 58% | 78% | 62% | 1.8% | 76% | 113% | 63% | 60% |
| 7 | 1.0% | 37% | 44% | 64% | 1.7% | 60% | 82% | 64% | 60% |
| 8 | 0.6% | 20% | 22% | 63% | 1.4% | 44% | 54% | 65% | 60% |
| 9 | 1.2% | 35% | 41% | 63% | 1.9% | 53% | 69% | 64% | 60% |
| 10 | 1.4% | 35% | 42% | 61% | 2.1% | 53% | 69% | 62% | 61% |
| 11 | 2.0% | 46% | 57% | 65% | 2.5% | 57% | 75% | 65% | 62% |
| 12 | 1.7% | 35% | 42% | 64% | 2.0% | 43% | 53% | 65% | 61% |
| 13 | 1.9% | 37% | 45% | 67% | 2.2% | 43% | 53% | 63% | 63% |
| 14 | 2.1% | 38% | 46% | 64% | 2.6% | 47% | 60% | 65% | 64% |
| 15 | 2.9% | 49% | 62% | 63% | 3.5% | 59% | 78% | 68% | 65% |
| 16 | 3.3% | 51% | 66% | 64% | 3.7% | 58% | 77% | 68% | 64% |
| 17 | 2.8% | 41% | 50% | 65% | 3.0% | 45% | 56% | 66% | 63% |
| 18 | 2.5% | 35% | 41% | 66% | 2.7% | 38% | 45% | 67% | 63% |
| 19 | 2.6% | 34% | 40% | 63% | 2.8% | 37% | 45% | 64% | 63% |
| 20 | 2.6% | 32% | 37% | 65% | 2.9% | 36% | 43% | 66% | 63% |
This section demonstrates that “sell high” approach may result in improved strategy returns.
For demonstration purposes we arbitrary defined “high alert price” as an alert price higher than either previous day Open, previous day Close, or same day Open.
Top Performers Alert-to-Close
Performance of selected positions identified by “Bad Apples” algorithm since we started publishing alerts mid-February 2017.
| Alert Date | Signal | Symbol | Alert | Close | Decline |
|---|---|---|---|---|---|
| 2-Mar-2017 | Sell | TOPS | $ 569.97 | $ 0.43 | –99.9% |
| 22-Feb-2017 | Sell | ORIG | $ 9771.75 | $ 24.19 | –99.8% |
| 10-Mar-2017 | Sell | DRYS | $ 1667.78 | $ 4.25 | –99.7% |
| 23-Mar-2017 | Sell | DCIX | $ 1490.58 | $ 7.03 | –99.5% |
| 11-Jul-2017 | Sell | ATW | $ 7.63 | $ 0.13 | –98.3% |
| 7-Mar-2017 | Sell | RNVA | $ 2.47 | $ 0.09 | –96.4% |
| 23-Feb-2017 | Sell | FNCX | $ 1.45 | $ 0.06 | –95.9% |
| 23-Mar-2017 | Sell | VSR | $ 2.01 | $ 0.09 | –95.5% |
| 14-Feb-2017 | Sell | UNXL | $ 1.06 | $ 0.05 | –95.2% |
| 28-Aug-2017 | Sell | RTNB | $ 2.55 | $ 0.16 | –93.7% |
| 14-Mar-2017 | Sell | DRWI | $ 1.90 | $ 0.12 | –93.7% |
| 6-Mar-2017 | Sell | DXTR | $ 1.72 | $ 0.13 | –92.4% |
| 15-Mar-2017 | Sell | CERU | $ 31.20 | $ 2.46 | –92.1% |
| 19-Jun-2017 | Sell | MYO | $ 22.60 | $ 2.21 | –90.2% |
| 28-Mar-2017 | Sell | IMUC | $ 3.27 | $ 0.33 | –89.9% |
| 22-Feb-2017 | Sell | ARGS | $ 1.40 | $ 0.16 | –88.3% |
| 24-Apr-2017 | Sell | STV | $ 1.65 | $ 0.2 | –87.8% |
| 27-Feb-2017 | Sell | JAGX | $ 1.24 | $ 0.16 | –87.5% |
| 22-Feb-2017 | Sell | MBOT | $ 8.41 | $ 1.14 | –86.4% |
| 28-Feb-2017 | Sell | SDRL | $ 1.77 | $ 0.3 | –83.1% |
| 11-Apr-2017 | Sell | WINT | $ 1.55 | $ 0.27 | –82.6% |
| 17-Mar-2017 | Sell | BIOA | $ 2.57 | $ 0.45 | –82.5% |
| 10-Apr-2017 | Sell | CYTX | $ 1.88 | $ 0.33 | –82.4% |
| 24-Mar-2017 | Sell | HTGM | $ 11.93 | $ 2.13 | –82.1% |
| 29-Mar-2017 | Sell | RTTR | $ 1.73 | $ 0.32 | –81.4% |
| 27-Mar-2017 | Sell | UVXY | $ 71.96 | $ 13.45 | –81.3% |
| 27-Mar-2017 | Sell | TVIX | $ 39.04 | $ 7.34 | –81.2% |
| 17-Feb-2017 | Sell | ZSAN | $ 3.09 | $ 0.61 | –80.3% |
| 13-Jul-2017 | Sell | CIE | $ 2.52 | $ 0.5 | –80.2% |
| 20-Jul-2017 | Sell | XCO | $ 2.61 | $ 0.52 | –80.1% |
Close price is the latest day close price from a previous trading day. Alert price is adjusted for splits and dividends if any.
These trades are theoretical. They do not include trading costs. Our actual profits will differ.
Recent Top Performers High-to-Low
Performance of selected recent positions identified by “Bad Apples” algorithm using the “sell spikes, buy dips” (high-to-low) approach as reviewed in the afternoon on Friday, December 1, 2017.
| Alert Date | Signal | Symbol | High | Low | Decline | Days |
|---|---|---|---|---|---|---|
| 17-Nov-2017 | Sell | DCIX | $ 13.10 | $ 6.21 | –52.6% | 6 |
| 28-Nov-2017 | Sell | PZRX | $ 1.62 | $ 0.77 | –52.5% | 1 |
| 27-Nov-2017 | Sell | TEUM | $ 1.56 | $ 0.86 | –44.9% | 4 |
| 17-Nov-2017 | Sell | ICON | $ 2.56 | $ 1.52 | –40.6% | 5 |
| 17-Nov-2017 | Sell | KOOL | $ 4.14 | $ 2.80 | –32.4% | 7 |
| 22-Nov-2017 | Sell | QD | $ 17.66 | $ 12.03 | –31.9% | 2 |
| 27-Nov-2017 | Sell | LMFA | $ 3.15 | $ 2.20 | –30.2% | 4 |
| 28-Nov-2017 | Sell | APEN | $ 6.37 | $ 4.45 | –30.1% | 4 |
| 22-Nov-2017 | Sell | MOSY | $ 1.51 | $ 1.14 | –24.5% | 6 |
| 28-Nov-2017 | Sell | AQMS | $ 3.82 | $ 2.90 | –24.1% | 3 |
| 22-Nov-2017 | Sell | WPCS | $ 1.58 | $ 1.20 | –24.1% | 5 |
| 22-Nov-2017 | Sell | ACST | $ 2.10 | $ 1.61 | –23.3% | 3 |
| 22-Nov-2017 | Sell | NURO | $ 2.14 | $ 1.65 | –22.9% | 2 |
| 22-Nov-2017 | Sell | ITUS | $ 3.04 | $ 2.36 | –22.4% | 6 |
| 27-Nov-2017 | Sell | CLSN | $ 3.30 | $ 2.56 | –22.4% | 5 |
| 17-Nov-2017 | Sell | VIPS | $ 9.99 | $ 7.90 | –20.9% | 2 |
| 27-Nov-2017 | Sell | NXTD | $ 1.56 | $ 1.24 | –20.5% | 2 |
| 22-Nov-2017 | Sell | JT | $ 5.89 | $ 4.75 | –19.4% | 3 |
| 22-Nov-2017 | Sell | SPI | $ 1.19 | $ 0.96 | –19.3% | 7 |
| 17-Nov-2017 | Sell | FOSL | $ 8.17 | $ 6.64 | –18.7% | 9 |
| 27-Nov-2017 | Sell | JMEI | $ 3.63 | $ 2.97 | –18.2% | 5 |
| 22-Nov-2017 | Sell | DMPI | $ 1.04 | $ 0.86 | –17.3% | 3 |
| 27-Nov-2017 | Sell | PPDF | $ 10.27 | $ 8.60 | –16.3% | 4 |
| 30-Nov-2017 | Sell | CHEK | $ 1.05 | $ 0.88 | –16.2% | 2 |
| 29-Nov-2017 | Sell | HMNY | $ 14.45 | $ 12.21 | –15.5% | 3 |
| 28-Nov-2017 | Sell | CCCL | $ 2.12 | $ 1.81 | –14.6% | 4 |
| 22-Nov-2017 | Sell | MBOT | $ 1.23 | $ 1.06 | –13.8% | 4 |
| 30-Nov-2017 | Sell | SHLD | $ 4.46 | $ 3.85 | –13.7% | 2 |
| 28-Nov-2017 | Sell | MOMO | $ 26.33 | $ 22.76 | –13.6% | 3 |
| 29-Nov-2017 | Sell | CREG | $ 3.28 | $ 2.86 | –12.8% | 3 |
Field “Days” shows the number of trading days between high and low. It does not count weekends and holidays.
These trades are theoretical. They do not include trading costs and assume “sell spikes, buy dips” style of trading (capturing highs and lows) during a two-week period (10 trading days) after the alert. Our actual profits will differ.
Overview
“Bad Apples” is one of our best algorithms for detecting securities with expected strong downward movement.
Based on backtests we expect a decline of 5-8% on average for three days to two weeks after the alert.
“Bad Apples” continue to decline for about five months. Between months 1 and 5, the decline is about 1-3% per month on average.
Although individual stocks can perform very differently.
From our perspective “Bad Apples” are not good buy candidates for a longer term holding.
This algorithm relies on principles of Capital Preservation and Getting Out of a Failing Position Quickly.
What this algorithm is looking for:
• impactful negative news
• strong overreaction to a mild positive news
• PR-driven stocks
• advancing stocks without a catalyst
• pump-and-dumps
• targets of short selling
• unprofitable companies
• companies bleeding money
• weak fundamental data
• the riskiest stocks on the market (day traders love them, but investors try to avoid)
• stocks breaking down through strong support levels
• discrepancy between retail traders activity (“dumb” money) and institutional investing (“smart” money)
To distinguish between trading activity originated from retail traders, institutional traders, and market makers we may analyze social media, Internet posts, size and patterns of executed orders, darkpool orders, block orders, size and patterns of bid and ask offers at Level I and Level II. Securities, which went up due to a retail traders activity and not due to an institutional investing, are likely to go down after the hype is gone.
We approach trading statistically. We will have losers. What is important for us is that winners outperform losers overall. We diversify to reduce risks and make strategy more liquid.
“Bad Apples” algo does not use price targets and stop losses.
In cash or retirement accounts, we sell “Bad Apple” positions and avoid them for about five months.
Alternatively, if a stock with a strong inverse correlation to “Bad Apple” exists, we may take a long position of such inverted stock. Although we rarely take a leveraged fund as a long position due to decay (fees and contango).
In margin accounts, we may short “Bad Apples” and buy to cover when the stock bottoms out. The best time to cover short “Bad Apple” position is when stock’s volatility and volume substantially subside.
Also shorting the spikes and covering on dips may give very good results.
Long means positive number of shares and short means negative number of shares in portfolio. Do not confuse these financial terms with holding stocks for a long or short period of time.
Trading costs understood as commissions, fees, interest, and slippage.
Share prices in calculations are adjusted for splits and dividends.
No leverage is used in calculations.
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Disclaimer
We are not your investment advisor. We do not recommend buying or selling any securities. Signals are generated by a computer program. Past performance is no guarantee of future results. Signals are provided for research and educational purposes only. Trade at your own risk. You assume full responsibility for your investment decisions.