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如何使用 OsMA 指标进行交易?

MACD Cross Prediction Indicator MT4

The moment when the MACD line crosses the signal line often leads to a significant price movement and trend changes.

MACD Cross Prediction is an indicator that uses OSMA(MACD oscillator) and a red line. You can change the level of the red line on the indicator setting popup(and the red line moves up and down). The alerts(email, mobile push, sound, Alert Box) will be sent when the MACD histogram touches the red line, which means the alerts can be sent just before/around the time when the MACD line crosses the signal line.

This indicator works for all pairs including Gold and Oil etc.

This Demo version works only on USD/CHF

What is MACD(OSMA)?

MACD, short for moving average convergence/divergence, is a trading indicator used in technical analysis of stock prices, created by Gerald Appel in the late 1970s.[1] It is designed to reveal changes in the strength, direction, momentum, and duration of a trend in a stock's price.

The MACD indicator (or "oscillator") is a collection of three time series calculated from historical price data, most often the closing price. These three series are: the MACD series proper, the "如何使用 OsMA 指标进行交易? signal" or "average" series, and the "divergence" series which is the difference between the two. The MACD series is the difference between a "fast" (short period) exponential moving average (EMA), and a "slow" (longer period) EMA of the price series. The average series is an EMA of the MACD series itself.

A "signal-line crossover" occurs when the MACD and average lines cross; that is, when the divergence (the bar graph) changes sign. The standard interpretation of such an event is a recommendation to buy if the MACD line crosses up through the average line (a "bullish" crossover), or to sell if it crosses down through the average line (a "bearish" crossover).[6] These events are taken as indications that the trend in the stock is about to accelerate in the direction of the crossover.

OsMA is an abbreviation for the term oscillator of a moving average (MA). The OsMA is a technical indicator that shows the difference between an oscillator and its moving average over a given period of time. The MACD is most common oscillator used in the OsMA indicato

Support for Osmo Mobile 2

The Osmo Mobile 2 supports mobile phones measuring from 58.6 mm-85 mm width. This covers most of the smartphones currently available. Please note that actual compatibility might be affected by accessories attached to your phone (including the phone case, external camera lens, or side button).

Step 1: Ensure that the battery is charged enough. If the battery level is low, connect the charging port on the right side of the handle with a USB cable to charge the Osmo Mobile 2.
Step 2: 如何使用 OsMA 指标进行交易? Mount and balance the mobile device to the Osmo Mobile 2.
Step 3: Activate your Osmo Mobile 2 via DJI GO. Power on the unit and pair it with your mobile device. Instructions will be shown in DJI GO automatically to guide you through the activation process.

The Osmo Mobile 2 utilizes Bluetooth 4.0 to communicate with mobile phones. Though Bluetooth 4.0 has become a standard 如何使用 OsMA 指标进行交易? for current phones, we suggest you check your mobile phone’s specifications for compatibility.

Loosen the Holder Lock Knob, follow the indicated directions and rotate the mobile phone holder for 90 degrees to mount your phone horizontally or vertically, then tighten the Holder Lock Knob. Please remove your phone before rotating the mobile phone holder.

When the Osmo Mobile 2 is turned on, press the Trigger once to switch between SmoothTrack Mode and Lock Mode. In SmoothTrack, the Osmo Mobile 2 anticipates the handle’s movement to smooth out pan and tilt transitions and reduces the shakiness from natural arm movements.

When the Osmo Mobile 2 is powered on, and Bluetooth is connected, tap the Power/Mode Button three times to switch between the mobile phone’s front and rear cameras.

DJI GO

1. Can I use ActiveTrack, Timelapse, and Panorama when the mobile phone is mounted vertically to the Osmo Mobile 2?

Tap the metering button in the lower left corner of the screen to switch to 如何使用 OsMA 指标进行交易? ActiveTrack. Mark an object on the screen to track it as it moves.

4. What are the differences between Timelapse, Motion Timelapse and Hyper Timelapse and when to 如何使用 OsMA 指标进行交易? use them?

For Timelapse, the Osmo Mobile 2 can be mounted to the bottom base or Tripod when shooting from a fixed angle.
For Motion Timelapse, the Osmo Mobile 2 moves between the preset positions and captures scenes from different angles.
For Hyper Timelapse, you can hold the Osmo Mobile 2 and capture views while walking.

Yes. You can set parameters manually in the Camera Settings menu. This 如何使用 OsMA 指标进行交易? function is only supported by iOS devices.

AO;AC;osma指标的含义

SherlockGh 于 2013-04-02 17:28:03 发布 5493 收藏 4

AO;AC;osma指标的含义

Keltner Channel是不是可以把TPrice = (C+H+O+L)/4; 有待验证。

首先总结一些AC的基本观念:
1.AC指标产生的买进信号必为绿棒,卖出信号必为红棒。
2.信号发生后,进场价位为该AC信号棒对应的价格棒最高价上一档买进或最低价下一档卖出。
3.买卖信号产生后,若隔天的AC棒不支持该方向,则该信号立即失效。

AC指标的使用方法

加速和减速震荡指标 — AC

说明:在SAUCER BUY 中,至少需要三根柱状图,而中间之柱(如何使用 OsMA 指标进行交易? 绿色)为最低,而右方之柱(红色)比前一根柱高,如此便构成中间凹陷如同碟子一般之SAUCERBUY。而碟子中,凹陷部份可以有几根柱状图则没有限制。而当信号产生时,我们便找符合条件之条形图,在其最高点加一档作为进场之价位。

双峰买讯(TWIN PEAKS BUY)

说明:当柱状图由左至右产生第二个低点,而第二个低点比第一个低点来的高即产生TWIN PEAKS BUY。须注意图中两个低点之间柱状图皆在零轴以下而信号柱必定为红色。TWIN PEAKS BUY为AO在零轴下唯一之买讯。而在TWINPEAKS BUY发生前一定会先产生一个SAUCER SELL。

降维方法 -简直太全- 附Python代码(Random Forest、Factor Analysis、corr、PCA、ICA、IOSMA

黄饱饱_bao 于 2018-07-01 22:28:39 发布 33800 收藏 335

为什么要降维?

建模初期,我们往往只有几个指标,这个时候不太涉及到降维,但是一个月后你就发现,模型的指标越来越多,从原有的五六个指标一步一步变成 100 个指标。100 个很多吗?不多!但是以后呢?两个月过去可能会变成 500 如何使用 OsMA 指标进行交易? 个,三个月过去就会超过 1000 个,以后还会更多!

降维的好处:

11528 行数据中,第一列是因变量(y_增长率),余下的所有列为自变量(x1. x100),共 100 个自变量。

1.缺失值比例(高:删!)

学校做课题时拿到的数据,缺失值是相对较少的,但是在工作中,缺失值的比例简直让人瞠目结舌,高于 80% 都司空见惯了。当缺失值比例过高时,代表它包含的可用信息太少了,一般会设置一个阈值,缺失值比例高于阈值的特征便删掉。

2.方差(低:删!)

若某一个特征中的数据基本一致,代表这一特征对因变量 y 的解释能力是比较低的,因此我们认为这种特征包含的可用信息也很少。特征中的数据基本一致的直接表现就是方差比较小。

在实际应用中,不同特征的数据范围是不一样的,有 [ 0, 1 ] 的,也有 [ 1, +∞) 的,因此通过这种方法降维之前一定要先对数据进行归一化处理(归一化与标准化不同,具体查看下面链接里的这篇文章)。

3.相关性矩阵(高:保留其一!)

如果两个特征的相关度较高,说明这两个特征携带的信息是高度相似的,过多的相似特征会降低某些算法的性能,比如逻辑回归(Logistic Regression)和线性回归(Linear Regreesion)。因此,一般会设置一个阈值,相关度高于阈值的特征只保留其中一个。

在下例中,因为特征数量较多,不便于展示,所以我们只选取 'x91', 'x92', 'x95', 'x96',' x97' 这五个特征进行相关度计算。

选取的五个特征中,'x91' 与 'x92' 的相关度达0.89,高相关,保留其一即可,其他同理。

4.随机森林(低:删!)

随机森林是一种广泛使用的特征选择算法,RandomForestRegressor 模块中的 feature_importances_ 函数会自动计算各个特征的重要性,因此大大降低了编程的难度。之后再根据特征间的相对重要性选择指标即可。

5. 反向特征消除

获取数据集中的全部 100 个特征和因变量( y_增长率)。

使用特征与因变量训练模型(逻辑回归 or 线性回归 or . )。

删除第 i 个特征后,用剩下的 99 个特征训练模型,并计算模型评价指标。

比较两次的评价指标,若评价指标提高,则删除第 i 个特征。

循环 4 ~ 5 过程,直到模型评价指标不再明显增加。

6. 前向特征选择

将每个特征与因变量 y 训练模型,得到 100 个模型 与 100 个模型评价指标。

循环 3 如何使用 OsMA 指标进行交易? ~ 4 过程,直到模型评价指标不再明显增加。

注意:前向特征选择和反向特征消除需要循环建模,耗时较久,计算成本很高,所以只适用于特征较少的数据,超过 1000 个特征的数据就慎重了。

7.因子分析(Factor Analysis)

能不能找到10种颜色呢?哈哈,100 维到 10 维,没有删减特征,却成功降维啦!

8.主成分分析(PCA)

图中,粉色柱状图一共 25 个 柱子,代表提取的 25 个主成分,其高度代表每个主成分对方差的解释程度。

蓝色折线图代表 25 个主成分对方差的累计解释程度。我们可以看到,25 个主成分对 100 个特征方差的累计解释程度已经达到了80% ,因此这 25 个主成分携带了原始特征中的 大部分信息,成功降维!

9.独立分量分析(ICA)

PCA 和 ICA 之间的主要区别在于,PCA寻找不相关的因素,而ICA寻找独立因素。如果两个特征是独立的,就代表两者之间没有任何关系。例如,今天下不下雨和我工资多少无关。