Mid-Term Indicator Strategy — Full Breakdown & Transcript

中线指标行业与个股共振策略介绍与回测

0h 03m video Published Apr 1, 2026 Transcribed Sep 18, 2026 数分魔  🌍: DataAnalysisModel 数分魔 🌍: DataAnalysisModel
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Intermediate 2 min read For: Quantitative traders and investors interested in technical analysis and systematic strategies.
AI Trust Score 65/100
⚠️ Average / Some Fluff

"Title promises a mid-term indicator strategy and delivers exactly that, though the performance claims are based on a specific backtest period."

AI Summary

The video presents a mid-term quantitative trading strategy that combines industry-level and individual stock indicators, focusing on capital flow (OBV) and price momentum (DEA). The strategy backtest from January 1 to February 28 shows a maximum drawdown of about 17% from March to June, but later outperforms the CSI 300 index, ending with roughly 70% cumulative returns and an annualized return of about 60%.

[00:00]
Strategy Performance Overview

The backtest period starts January 1, 2025, and ends February 28. The strategy underperforms from March to June with a drawdown of about 17%, then surpasses the CSI 300 index, ending with ~70% cumulative returns and ~60% annualized.

[00:50]
Strategy Logic: Industry First, Then Stocks

The strategy first analyzes industry-level indicators, then selects individual stocks that meet specific conditions. This top-down approach is similar to a previously introduced strategy.

[01:04]
OBV Indicator Explained

OBV (On-Balance Volume) accumulates volume: if the stock closes up, volume is added; if it closes down, volume is subtracted. The MA of OBV (MAOBV) shows the trend of capital flow strength.

[01:29]
Capital Flow Trend Detection

The strategy detects industries with capital inflows. For example, in December, it captured inflows into sectors like commercial aerospace, contributing to a ~20% gain in that period.

[02:10]
DEA Indicator Explained

DEA is a price momentum signal line derived from MACD. It is calculated by smoothing the DIF (difference between short-term and long-term moving averages). A DIF crossing above DEA indicates upward short-term price momentum.

[02:38]
Combining Volume and Price

MAOBV tracks volume (capital flow), while DEA tracks price momentum. The strategy first identifies industry trends, then selects stocks within those industries.

[03:06]
Backtest Assumptions

The backtest uses data from the presenter's database, removes look-ahead bias (future functions), and applies specific buy/sell rules. The overall performance is considered good.

The strategy effectively combines capital flow and price momentum indicators to identify industry trends and select stocks, delivering strong returns with manageable drawdowns. It demonstrates a systematic approach to mid-term trading.

💡 Key Takeaways

🔧

Capital Flow Detection

Explains how the strategy captures sector inflows, leading to significant gains.

01:29
⚖️

Volume and Price Combination

Shows the core logic of combining volume (MAOBV) and price (DEA) indicators.

02:38
📊

Backtest Integrity

Emphasizes removing look-ahead bias for realistic backtest results.

03:06

[00:00] 最近实在是太忙了,没工夫录视频 今天给大家介绍一个中线指标公正策略 我们先来看一下这个策略回撤的收益 这个回撤区间是从2025年1月1号开始的

[00:12] 一直到2月28号 我们看到这个策略呢 它在有一段 大概从3月到6月表现不是太好 差不多17%到这个回撤吧

[00:25] 然后从6月份之后 就超过了沪深300指数了 到结束的时候 大概有70%几的收益 年化的话大概在60%几吧

[00:37] 我们整体这个策略呢 市场好的时候 它会超越指数 但是如果市场不太好的时候呢 它有一定的回撤 但是整体回撤幅度也还可以 下面我们来看一下 这个策略的主要逻辑

[00:50] 它的逻辑跟上一次 我们介绍的策略类似 它是先看行业的指标 再看个股的指标 个股的选择呢 也是满足于这几个条件 那这几个指标什么意思呢 给大家介绍一下 OBV这个指标是怎么算出来的呢

[01:04] 它是如果这个股收盘的时候涨的 它的成交量即为流入 如果当天收盘是跌的 成交量就即为流出 然后不断累积得到这么一个指标

[01:16] 那我们看这是我们这个蓝色 这个是指标的一个波动的情况 那MA呢是移动平均的意思 对这个OBV求它的均线 就得到了一个移动平均的一个线 这个线代表一个什么样的趋势呢

[01:29] 这个线代表说 资金流向的趋势有没有变强 就是所以呢我们这个策略的逻辑呢先看这个行业有没有资金流入为什么我们这个策略在去年12月份的时候有一个特别高的增长就是这个策略因为捕捉到

[01:44] 比如像商业航天这样的板块 这样的行业有资金流入 所以我们在这个里面是有收益的 所以在去年这个里头 大概有20%几的收益 这就是这个策略的逻辑

[01:57] 除了这个OBV代表资金流入的 这个逻辑之外 还有一个DEA 这个DEA什么意思呢 它是一个价格动量的信号线

[02:10] 它是来自于MACD的体系 先由短期均线和长期均线做X 得到DIF 然后再对DIF进行平滑 得到一个趋势线

[02:22] 那这个DEA呢 它其实是一个价格动量的信号线 如果我们说DIF上穿 上穿DA说明价格短期动能是向上的

[02:38] 所以说我们这两个指标 MAOBV是看量的 DA是看价的 所以这个策略逻辑就很简单 它其实先找出行业变化的一个趋势

[02:52] 然后在中间找个股 然后这下面是一些买卖的规则 包括我们进行策略回测的时候 做的一些假设 数据是来源于我们的这个数据库的

[03:06] 在这个里头呢 我们也注意了 就是把这个未来函数都给它去掉了 得到这么一个收益 这个策略看起来整体来讲还是不错的 好 今天分享就这么多 谢谢大家

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