From d4352284dc9049fa0d954b562ebb4632b34f4aee Mon Sep 17 00:00:00 2001
From: zyy3 <zyy3@zy.com>
Date: Mon, 13 Oct 2025 20:51:34 +0800
Subject: [PATCH] 1
---
trading-order-huobi/src/main/java/com.yami.trading.huobi/data/job/AbstractGetDataJob.java | 112 ++++++++++++++++++++++++++++++-------------------------
1 files changed, 61 insertions(+), 51 deletions(-)
diff --git a/trading-order-huobi/src/main/java/com.yami.trading.huobi/data/job/AbstractGetDataJob.java b/trading-order-huobi/src/main/java/com.yami.trading.huobi/data/job/AbstractGetDataJob.java
index 9144f87..77050f9 100644
--- a/trading-order-huobi/src/main/java/com.yami.trading.huobi/data/job/AbstractGetDataJob.java
+++ b/trading-order-huobi/src/main/java/com.yami.trading.huobi/data/job/AbstractGetDataJob.java
@@ -63,10 +63,11 @@
if (delayValue != null) {
-
+ if (delayValue.getValue().compareTo(BigDecimal.ZERO) == 0 || delayValue.getSecond() <= 0) {
+ cleanUpKLineCache(symbol); // 清理缓存，跳过后续计算
+ return;
+ }
// K线场景专属参数（可根据周期动态调整）
- //int kLineCycle = getKLineCycle(symbol); // 获取K线周期（如1min=1, 5min=5）
- //double baseFluctuation = kLineCycle <= 1 ? 0.05 : 0.08; // 短周期（1min）±5%，长周期（5min）±8%
double baseFluctuation = 0.1;
int trendConsistencyRate = 70; // 70%概率保持与前一个值的波动方向一致（模拟趋势）
int maxAdjacentFluctuation = 5; // 相邻值波动不超过前一个值的5%（避免视觉跳变）
@@ -75,7 +76,6 @@
Integer frequency = AdjustmentValueCache.getFrequency().get(symbol);
List<BigDecimal> preAllocationList = AdjustmentValueCache.getPreAllocationList().get(symbol);
Integer currentIndex = AdjustmentValueCache.getCurrentAllocationIndex().get(symbol);
- // 新增：记录前一个值的波动方向（用于趋势一致性）
List<Boolean> upDownTrend = AdjustmentValueCache.getUpDownTrend().getOrDefault(symbol, new ArrayList<>());
if (frequency == null) {
@@ -84,83 +84,97 @@
if (frequency > 1) {
preAllocationList = new ArrayList<>(frequency);
- BigDecimal totalValue = delayValue.getValue();
- // 虚拟币精度高，中间计算保留decimal+4位（避免精度丢失）
- BigDecimal average = totalValue.divide(new BigDecimal(frequency), decimal + 4, RoundingMode.HALF_UP);
+ BigDecimal totalValue = delayValue.getValue(); // 支持正负值
+ // 核心修改1：用绝对值算平均值（避免负数波动范围反向），最后补回原符号
+ BigDecimal totalAbs = totalValue.abs();
+ BigDecimal averageAbs = totalAbs.divide(new BigDecimal(frequency), decimal + 4, RoundingMode.HALF_UP);
+ BigDecimal average = averageAbs.multiply(totalValue.signum() == 1 ? BigDecimal.ONE : BigDecimal.ONE.negate());
BigDecimal sum = BigDecimal.ZERO;
// 优化1：最后k个值分散偏差（k=频率的2%，最少5个，确保最后一根K线无异常）
int lastK = Math.max(5, frequency / 50);
int normalCount = frequency - lastK;
- // 优化2：前n-k个值——模拟真实行情波动（截断正态分布+趋势一致性）
+ // 优化2：前n-k个值——模拟真实行情波动（兼容正负）
for (int i = 0; i < normalCount; i++) {
BigDecimal randomValue;
if (i == 0) {
- // 第一个值：在基础波动范围内随机
+ // 第一个值：基于带符号平均值波动，保留原符号
randomValue = generateTruncatedGaussianValue(average, baseFluctuation, decimal + 4);
} else {
- // 非第一个值：70%概率保持与前一个值的波动方向一致
boolean lastUp = upDownTrend.get(i - 1);
boolean keepTrend = Math.random() * 100 <= trendConsistencyRate;
if (keepTrend) {
- // 保持趋势：上涨则继续涨（或小跌），下跌则继续跌（或小涨）
+ // 核心修改2：按前值绝对值算波动幅度，避免负数趋势误判
+ BigDecimal lastVal = preAllocationList.get(i - 1);
+ double fluctRange = lastVal.abs().multiply(new BigDecimal(baseFluctuation * 1.2)).doubleValue();
+
if (lastUp) {
- // 前一个上涨：本次波动范围 [0, +baseFluctuation*1.2]（允许小回调）
- randomValue = generateDirectionalValue(average, 0, baseFluctuation * 1.2, decimal + 4);
+ // 前一个上涨（无论正负，比前值大即为涨）：波动范围[0, fluctRange]
+ randomValue = generateDirectionalValue(lastVal, 0.0, fluctRange, decimal + 4);
} else {
- // 前一个下跌：本次波动范围 [-baseFluctuation*1.2, 0]（允许小反弹）
- randomValue = generateDirectionalValue(average, -baseFluctuation * 1.2, 0, decimal + 4);
+ // 前一个下跌（比前值小即为跌）：波动范围[-fluctRange, 0]
+ randomValue = generateDirectionalValue(lastVal, -fluctRange, 0.0, decimal + 4);
}
} else {
- // 反转趋势：正常基础波动
+ // 反转趋势：基于带符号平均值波动
randomValue = generateTruncatedGaussianValue(average, baseFluctuation, decimal + 4);
}
- // 优化3：强约束相邻值波动——不超过前一个值的5%
+ // 核心修改3：相邻波动约束——用前值绝对值算最大波动，超限时按符号截断
BigDecimal lastValue = preAllocationList.get(i - 1);
- BigDecimal maxAdjacent = lastValue.multiply(new BigDecimal(maxAdjacentFluctuation / 100.0))
+ BigDecimal maxAdjacent = lastValue.abs()
+ .multiply(new BigDecimal(maxAdjacentFluctuation / 100.0))
.setScale(decimal + 4, RoundingMode.HALF_UP);
- BigDecimal adjacentDiff = randomValue.subtract(lastValue).abs();
- if (adjacentDiff.compareTo(maxAdjacent) > 0) {
+ BigDecimal adjacentDiff = randomValue.subtract(lastValue);
+
+ if (adjacentDiff.abs().compareTo(maxAdjacent) > 0) {
randomValue = lastValue.add(
- adjacentDiff.divide(randomValue.subtract(lastValue), decimal + 4, RoundingMode.HALF_UP)
- .multiply(maxAdjacent)
+ adjacentDiff.signum() == 1 ? maxAdjacent : maxAdjacent.negate()
);
}
}
preAllocationList.add(randomValue);
sum = sum.add(randomValue);
- // 记录当前值的波动方向（与平均值对比）
- upDownTrend.add(randomValue.compareTo(average) > 0);
+ // 核心修改4：涨跌趋势改为“与前值对比”（而非平均值），兼容正负
+ boolean currentUp = (i == 0)
+ ? randomValue.compareTo(average) > 0
+ : randomValue.compareTo(preAllocationList.get(i - 1)) > 0;
+ upDownTrend.add(currentUp);
}
- // 优化4：最后k个值——极小波动+偏差分散（确保最后一根K线平滑）
+ // 优化4：最后k个值——兼容负数总和
BigDecimal remaining = totalValue.subtract(sum);
- BigDecimal avgLastK = remaining.divide(new BigDecimal(lastK), decimal + 4, RoundingMode.HALF_UP);
+ // 用剩余值绝对值算平均，补回符号
+ BigDecimal remainingAbs = remaining.abs();
+ BigDecimal avgLastKAbs = remainingAbs.divide(new BigDecimal(lastK), decimal + 4, RoundingMode.HALF_UP);
+ BigDecimal avgLastK = avgLastKAbs.multiply(remaining.signum() == 1 ? BigDecimal.ONE : BigDecimal.ONE.negate());
+
for (int i = 0; i < lastK - 1; i++) {
- // 最后k-1个值：波动范围缩小到基础波动的1/3（±1.7%~2.7%）
BigDecimal smallFluctValue = generateTruncatedGaussianValue(avgLastK, baseFluctuation / 3, decimal + 4);
preAllocationList.add(smallFluctValue);
sum = sum.add(smallFluctValue);
- upDownTrend.add(smallFluctValue.compareTo(avgLastK) > 0);
+ upDownTrend.add(smallFluctValue.compareTo(preAllocationList.get(preAllocationList.size() - 2)) > 0);
}
- // 最后1个值：仅承担剩余微小偏差（波动≤基础波动的1/5）
+
+ // 最后1个值：兼容负数偏差
BigDecimal finalValue = totalValue.subtract(sum);
- BigDecimal maxFinalFluct = avgLastK.multiply(new BigDecimal(baseFluctuation / 5))
+ BigDecimal maxFinalFluct = avgLastK.abs()
+ .multiply(new BigDecimal(baseFluctuation / 5))
.setScale(decimal + 4, RoundingMode.HALF_UP);
+
if (finalValue.abs().compareTo(maxFinalFluct) > 0) {
+ // 超限时按符号截断，保留原方向
finalValue = maxFinalFluct.multiply(finalValue.signum() == 1 ? BigDecimal.ONE : BigDecimal.ONE.negate());
- // 若超出范围，反向微调前一个值（确保总和正确）
BigDecimal prevLastValue = preAllocationList.get(preAllocationList.size() - 1);
preAllocationList.set(preAllocationList.size() - 1, prevLastValue.add(totalValue.subtract(sum).subtract(finalValue)));
}
preAllocationList.add(finalValue);
- upDownTrend.add(finalValue.compareTo(avgLastK) > 0);
+ upDownTrend.add(finalValue.compareTo(preAllocationList.get(preAllocationList.size() - 2)) > 0);
- // 缓存新增：波动方向列表（用于趋势一致性）
+ // 缓存更新
AdjustmentValueCache.getPreAllocationList().put(symbol, preAllocationList);
AdjustmentValueCache.getCurrentAllocationIndex().put(symbol, 0);
AdjustmentValueCache.getUpDownTrend().put(symbol, upDownTrend);
@@ -168,49 +182,45 @@
}
}
- // 后续分配逻辑（不变，仅需在清理缓存时移除upDownTrend）
+ // 后续分配逻辑：兼容正负延时值
if (frequency <= 1) {
- // 单次分配逻辑
+ // 单次分配：直接用带符号值，避免符号丢失
+ BigDecimal delayVal = delayValue.getValue().setScale(decimal, RoundingMode.HALF_UP);
if (currentValue == null) {
- AdjustmentValueCache.getCurrentValue().put(symbol, delayValue.getValue().setScale(decimal, RoundingMode.HALF_UP));
+ AdjustmentValueCache.getCurrentValue().put(symbol, delayVal);
} else {
- AdjustmentValueCache.getCurrentValue().put(symbol,
- currentValue.add(delayValue.getValue()).setScale(decimal, RoundingMode.HALF_UP));
+ AdjustmentValueCache.getCurrentValue().put(symbol, currentValue.add(delayVal).setScale(decimal, RoundingMode.HALF_UP));
}
if (!item.getAdjustmentValue().equals(AdjustmentValueCache.getCurrentValue().get(symbol))) {
item.setAdjustmentValue(AdjustmentValueCache.getCurrentValue().get(symbol));
itemService.saveOrUpdate(item);
}
- cleanUpKLineCache(symbol); // K线场景专属缓存清理
+ cleanUpKLineCache(symbol);
} else {
- // 按预分配列表取值
+ // 按预分配列表取值（列表已兼容正负）
if (preAllocationList != null && currentIndex != null && currentIndex < preAllocationList.size()) {
- BigDecimal currentValue_frequency = preAllocationList.get(currentIndex)
- .setScale(decimal, RoundingMode.HALF_UP);
+ BigDecimal currentValueFrequency = preAllocationList.get(currentIndex).setScale(decimal, RoundingMode.HALF_UP);
- // 更新当前值（K线价格）
+ // 更新当前值：带符号累加
if (currentValue == null) {
- AdjustmentValueCache.getCurrentValue().put(symbol, currentValue_frequency);
+ AdjustmentValueCache.getCurrentValue().put(symbol, currentValueFrequency);
} else {
- AdjustmentValueCache.getCurrentValue().put(symbol,
- currentValue.add(currentValue_frequency).setScale(decimal, RoundingMode.HALF_UP));
+ AdjustmentValueCache.getCurrentValue().put(symbol, currentValue.add(currentValueFrequency).setScale(decimal, RoundingMode.HALF_UP));
}
- // 更新延迟值和索引
- delayValue.setValue(delayValue.getValue().subtract(currentValue_frequency)
- .setScale(decimal, RoundingMode.HALF_UP));
+ // 更新延迟值：带符号减法
+ BigDecimal updatedDelayVal = delayValue.getValue().subtract(currentValueFrequency).setScale(decimal, RoundingMode.HALF_UP);
+ delayValue.setValue(updatedDelayVal);
delayValue.setSecond(Arith.sub(delayValue.getSecond(), Arith.div(this.interval, 1000.0D)));
AdjustmentValueCache.getDelayValue().put(symbol, delayValue);
int nextIndex = currentIndex + 1;
AdjustmentValueCache.getCurrentAllocationIndex().put(symbol, nextIndex);
- // 分配完成，清理缓存
if (nextIndex >= frequency) {
cleanUpKLineCache(symbol);
}
- // 保存K线数据更新
if (!item.getAdjustmentValue().equals(AdjustmentValueCache.getCurrentValue().get(symbol))) {
item.setAdjustmentValue(AdjustmentValueCache.getCurrentValue().get(symbol));
itemService.saveOrUpdate(item);
--
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