v2v Indicators Free Download v2v Indicators Free Download - MT4/MT5 Resources

v2v metrics are uncommon. It doesn't have any directional arrows and no triggered alerts for long/buy or short/sell signals. To do this, one needs to think critically about the one between the keyboard and the chair. Yes, that's you.

This system requires one to do due diligence in order to understand or learn more about the system. Unfortunately due to constant development/updates it may take some valuable time to complete the user manual.

The system includes dozens of indicators.

VWAP bands on this system

This is constructed using the average true range/average range or average daily range, where the moving VWAP band (from the midpoint - the main VWAP line) is calculated based on the statistical z-score. The main starting point for VWAP calculations is based on a talk given by Dr. Paul Levine (RIP) on his MIDAS system.

Statistical z-score values ​​are injected into the algorithm or as an option as part of the probability equation for predicting the end of a trend. The vertical line guides (From and To) on this system are used to draw from price inflection points or timeframes (4-hour, daily, weekly and monthly or 8-hour or 24-hour market ranges). The setup includes a feature to switch from MVWAP (MA-based VWAP) to classic VWAP. MA (Moving Average) is a Hull MA with non-lag fusion using Fulks Matulich calculation method of T3 based MA. Therefore, I call it T3-HMA.

Before adding DSMA filters (Deviation-Scaled MA by John F. Ehlers), the MAs inside the system were mostly linear volume weighting, with Jurik-based MA smoothing filters applied (but some of them were just because the rest used Price's adaptive calculations). Other tools are then integrated into the system...such as a regression analysis tool that can instantly switch between normal price closes and Heiken Ashi – APB closes. The MA period calculation within the system is dynamically calculated/assigned based on the current dominant period period (John F. Ehlers' algorithm).

Dynamic Zones, by Dr. Leo Zamansky and David Standal

The Dynamic Area indicator can show in detail how it solves common trading complexities. Extreme investing uses oscillators to take advantage of tradable trends in the market. This investing style follows a very simple form of logic: enter the market only when the oscillator is well above or below traditional trading levels. However, these indicator-driven systems cannot evolve with the market because they use fixed buy and sell areas. Traders typically use one set of buy and sell zones in bull markets and distinct zones in bear markets.

Herein lies the complexity. Once traders begin to introduce their market views into the trading equation, they negate the mechanical nature of the system by changing zones. The goal is to have the system automatically define its own buying and selling areas to make profitable trades in any market (bull or bear). Dynamic Zones provide a solution to the complexities of fixed buy and sell zones for any indicator-driven system.

Jurik Filter─Phase and Smoothing

This TDI version uses JMA (Jurik Research Moving Average) phase and smoothing calculations. Have you noticed how moving averages add some lag (delay) to your signal? ...especially when there's a big move up or down in price and you're waiting for the moving average to catch up? Don't wait any longer! JMA eliminates these complexities forever and gives you the best of both worlds: low latency and smooth lines.

For example, ideally, a filtered signal might be both smooth and lag-free. Lag causes delays in your trades, and increasing indicator lag usually results in lower profits. In other words, latecomers get what's left on the table after the feast begins. JMA's improved timing and smoothness will blow your mind.
JMA is a powerful adaptive tracker that smoothes time series data with very small hysteresis, no overshoot, and no oscillations. The algorithm is stable and avoids the complexity of neural networks. JMA delivers the best in fluency, accuracy and timeliness across the board.

RSI - Trend Strength Index (RSX) Author: Mark Jurik

RSI is a very popular technical indicator because it takes into account market speed, direction, and trend uniformity. However, its widely criticized shortcoming is its noisy (and nervous) appearance. RSX retains all the useful features of RSI, with one important exception: noise is gone, and no latency is added.

Best formula: Use the average price bar (APB)

Average price bars better describe the current market by eliminating or reducing fluctuations in nominal price action (often referred to as the "bump" of current high, low, and closing price action). In other words, APB removes price-distorting noise.

Using the Hull MA (designed by Allan Hull), but this is a variation from low lag to zero lag

There are many types of moving averages, the most basic of which is the simple moving average (SMA). Of all the moving averages, the moving average lags the price the most. Exponential and weighted moving averages were developed to address this lag problem by placing more emphasis on the latest data. The Hull Moving Average (HMA), developed by Alan Hull, is an extremely fast and smooth moving average. HMA virtually eliminates lag while managing to improve smoothness. Dynamic MyRSI with NET combined with a T3 Hull MA variant with Jurik filter, as well as phase and smoothing finally eliminate lag.

Eller Deviation Scaled Moving Average (DSMA)

The new DSMA was produced by John Ehlers and featured in the July 2018 issue of TASC Magazine. DSMA is a data smoothing technique that acts as an exponential moving average with dynamic smoothing coefficients. The smoothing coefficient is automatically updated based on the magnitude of the price change. In the Deviation Scaled Moving Average, the standard deviation from the mean is chosen as the measure of the magnitude. Even if price changes are small, the generated indicator can significantly smooth the data while quickly adapting to these changes.

RSI and RSX haDelta

haDelta is a simple formula originally developed and published by Mr. Dan Valcu. The idea behind haDelta is to quantify HA candles. One can measure momentum, which is very important when you use haDelta for reversals. It measures the difference between HA off and HA on. NOTE: If using high sensitivity.

Vertical horizontal filter (VHF)

The Vertical Horizontal Filter (VHF) was created by Adam White to identify trending and range markets, similar to the Hikkake Pattern indicator. VHF measures trend activity levels, similar to ADX in orienteering systems. Then, trend indicators can be used in trending markets and momentum indicators can be used in range markets.

(TRIX) Tim Tilson

The reason this moving average was developed was to improve the noise filter and reduce the lag present in most moving averages. The indicator is based on multiple exponential smoothing of prices.

Main cycle (DCP)

The value generated by the DCP is used as the dynamic period parameter value (for dynamic MyRSI with NET).

Homdyne means I use the signal from a bar ago multiplied by itself to produce a zero frequency beat. The beat note carries a single-bar changing phase angle. Still using the basic definition of period, a single phase change rate is the period of the period.

Linear Momentum─aka MomenTicks

Linear momentum is defined as the product of the mass of a system and its velocity. In notation, linear momentum is expressed as p = mv. Momentum is proportional to an object's mass and its speed. Therefore, the greater the mass or velocity of an object, the greater its momentum.

MyRSI with NET (Noise Cancellation Technology)

MyRSI with NET is a technical indicator that uses Kendall correlation to eliminate nonlinear noise. Two main graphs are calculated: MyRSI and NET. Each diagram can be used as a confirmation of the other. NET stands for Noise Cancellation Technology.

MyRSI is a modified relative strength index similar to the one used in RocketRSI. It is calculated as the ratio of the sum of the differences between the closing prices of the most recent bar and the sum of the absolute values ​​of these differences.

NET is calculated as the Kendall correlation of MyRSI. NET plots are less noisy than MyRSI, however, using additional filters may help.