如何计算股票价格的趋势线

How to calculate the trendline for stock price

我正在尝试计算和绘制股票价格的趋势线。搜了搜,想了一天,也没有什么好主意。

我有每日价格历史,想找到趋势线和价格线之间的交叉点。

您能提供一些想法或指导吗?

非常感谢!!!

import pandas as pd
import quandl as qdl
from scipy.stats import linregress

# get AAPL 10 years data

data = qdl.get("WIKI/AAPL", start_date="2007-01-01", end_date="2017-05-01")

data0 = data.copy()
data0['date_id'] = ((data0.index.date - data0.index.date.min())).astype('timedelta64[D]')
data0['date_id'] = data0['date_id'].dt.days + 1

# high trend line

data1 = data0.copy()

while len(data1)>3:

    reg = linregress(
                    x=data1['date_id'],
                    y=data1['Adj. High'],
                    )
    data1 = data1.loc[data1['Adj. High'] > reg[0] * data1['date_id'] + reg[1]]

reg = linregress(
                    x=data1['date_id'],
                    y=data1['Adj. High'],
                    )

data0['high_trend'] = reg[0] * data0['date_id'] + reg[1]

# low trend line

data1 = data0.copy()

while len(data1)>3:

    reg = linregress(
                    x=data1['date_id'],
                    y=data1['Adj. Low'],
                    )
    data1 = data1.loc[data1['Adj. Low'] < reg[0] * data1['date_id'] + reg[1]]

reg = linregress(
                    x=data1['date_id'],
                    y=data1['Adj. Low'],
                    )

data0['low_trend'] = reg[0] * data0['date_id'] + reg[1]

# plot

data0['Adj. Close'].plot()
data0['high_trend'].plot()
data0['low_trend'].plot()

一些想法和指导:

Based on your statement (cit.:)
I did some searches and thought for a whole day, there is no a really good idea on how to do.

I can make you sure, there is no universally good idea, how to solve this, but this should not make you nervous. Generations of CTAs have spent their whole lives on doing this to their individual horizons of the best efforts they could have spent on mastering this, so at least, we can learn on what they have left us as a path to follow.

1) 定义趋势:
作为最初的惊喜,人们应该将趋势视为外系统驱动的(外部)特征,它与 意见 的关系比与 TimeSeries 数据(可观察的)历史的关系更大。

换句话说,一旦意识到有关趋势的信息根本不存在于 TimeSeries 数据集中内部,事情就会开始明显明朗。

2) 如果一个人对 her/his 趋势识别方法有足够的信心,
我们只能 扩展这种趋势-指示,作为一种信念,进入 FUTURE(一个猜想)

3) MARKET & 只有 The Market VALIDATES (or ignores) 这样的"accepted"-信念。

4) 共享 信念重新确认 这样的信念线作为大多数人尊重的趋势指标(由市场衡量风险暴露的股权,而不是通过大众投票,通过人群喊叫或 CTA 的自我推销尖叫声更少)


它有用吗?

上面的 USDCAD 示例屏幕 ( zoom-out into a new window for a full-scale indepth view ) 反映了所有这些,并添加了一些基本事件实例,这些实例被引入 "across" 技术起草的 (定量支持 ) 主要吸引子,显示了称为 FX 交易的河流流动的真实生活的一部分。