Suppose there’s a guy named Kai. He works morning shifts at a chain coffee shop and likes to check the lowest prices during his breaks. He set himself a rule: $CAKE if the lows of two consecutive closed daily candles are no more than 0.3% apart, measured against the average of those two lows, and the second day closes bullish (its close is higher than its open), he buys at the second day’s close, holds for 4 days, and sells at the close of day 4. While holding the position and on the day he sells, even if the same pattern appears again, he doesn’t open a new position.
I applied this rule to Binance spot CAKE/USDT closed daily candles from August 17 to November 14 (UTC, 90 candles in total). The November 15 candle hasn’t closed yet, so it wasn’t included.
There were exactly 6 qualifying patterns during those 90 days. They didn’t overlap, and he took all 6.
The first trade looked promising. The low was 1.692 on August 25 and 1.69 on August 26, a difference of 0.12%. The second day closed bullish, so he bought at 1.736. Four days later, on August 30, he sold at 1.81, making 4.26%. Kai told his coworkers at the shop, “Both days touched the same level. That’s pretty accurate.”
The turning point came after he sold. He sold on August 30 and stayed out of the market for 27 days. On September 26, the price hit 2.847 intraday, 57.29% above his sale price. What made it more frustrating was that the next pattern appeared on September 26 and 27: lows of 2.721 and 2.724, just 0.11% apart. September 27 closed bullish, so he bought back in at the closing price of 2.831. That close was the highest close of the 90 days, and the price also touched the 90-day high of 2.863 intraday. Four days later, on October 1, he sold at 2.565, losing 9.40%.
The next 4 trades all lost money. He bought at 2.527 on October 3 and sold at 2.252 on October 7, losing 10.88%—his worst trade. On October 20 he bought at 2.227 and sold at 2.08 on October 24, losing 6.60%. He bought at 2.018 on November 4 and sold at 1.846 on November 8, losing 8.52%. Right after he sold on November 8, that day’s low of 1.825 was again close to the next day’s low of 1.823, just 0.11% apart. November 9 closed bullish, so following his rule, he bought back in at 1.865. Four days later, on November 13, he sold at 1.707, losing another 8.47%.
Across all 6 trades, he had 1 winner and 5 losers, for a compounded return of -34.17%. The only winner was the first trade, at 4.26%; without it, the remaining 5 trades compounded to -36.86%. If he had bought at the August 17 close of 1.466 and held until the November 14 close of 1.577, he would have made 7.57%. Over the same period, $BTC went from 64532.1 to 64150, a return of -0.59%, essentially flat.
The 90-day low occurred on August 17, at 1.447. The November 14 close was 44.92% below the September 27 high; it would have to rise 81.55% to return to that high.
Kai made 4.26% on his first trade. During the 27 days he stayed out of the market, he missed the sharpest part of the rally. Then he bought back in at the highest close of the 90 days, and all 4 subsequent trades lost money. The same rule produced completely different results at the end of August and at the September high.
The above is based on historical data from closed candles. It doesn’t indicate what will happen next and isn’t investment advice. If you also wait for the lows of two days to come close together before buying, would you care about missing the gains during those 27 days after selling?
I applied this rule to Binance spot CAKE/USDT closed daily candles from August 17 to November 14 (UTC, 90 candles in total). The November 15 candle hasn’t closed yet, so it wasn’t included.
There were exactly 6 qualifying patterns during those 90 days. They didn’t overlap, and he took all 6.
The first trade looked promising. The low was 1.692 on August 25 and 1.69 on August 26, a difference of 0.12%. The second day closed bullish, so he bought at 1.736. Four days later, on August 30, he sold at 1.81, making 4.26%. Kai told his coworkers at the shop, “Both days touched the same level. That’s pretty accurate.”
The turning point came after he sold. He sold on August 30 and stayed out of the market for 27 days. On September 26, the price hit 2.847 intraday, 57.29% above his sale price. What made it more frustrating was that the next pattern appeared on September 26 and 27: lows of 2.721 and 2.724, just 0.11% apart. September 27 closed bullish, so he bought back in at the closing price of 2.831. That close was the highest close of the 90 days, and the price also touched the 90-day high of 2.863 intraday. Four days later, on October 1, he sold at 2.565, losing 9.40%.
The next 4 trades all lost money. He bought at 2.527 on October 3 and sold at 2.252 on October 7, losing 10.88%—his worst trade. On October 20 he bought at 2.227 and sold at 2.08 on October 24, losing 6.60%. He bought at 2.018 on November 4 and sold at 1.846 on November 8, losing 8.52%. Right after he sold on November 8, that day’s low of 1.825 was again close to the next day’s low of 1.823, just 0.11% apart. November 9 closed bullish, so following his rule, he bought back in at 1.865. Four days later, on November 13, he sold at 1.707, losing another 8.47%.
Across all 6 trades, he had 1 winner and 5 losers, for a compounded return of -34.17%. The only winner was the first trade, at 4.26%; without it, the remaining 5 trades compounded to -36.86%. If he had bought at the August 17 close of 1.466 and held until the November 14 close of 1.577, he would have made 7.57%. Over the same period, $BTC went from 64532.1 to 64150, a return of -0.59%, essentially flat.
The 90-day low occurred on August 17, at 1.447. The November 14 close was 44.92% below the September 27 high; it would have to rise 81.55% to return to that high.
Kai made 4.26% on his first trade. During the 27 days he stayed out of the market, he missed the sharpest part of the rally. Then he bought back in at the highest close of the 90 days, and all 4 subsequent trades lost money. The same rule produced completely different results at the end of August and at the September high.
The above is based on historical data from closed candles. It doesn’t indicate what will happen next and isn’t investment advice. If you also wait for the lows of two days to come close together before buying, would you care about missing the gains during those 27 days after selling?