Indicator
Relative Normalized VolatilityThere are plenty of indicators that aim to measure the volatility (degree of variation) in the price of an instrument, the most well known being the average true range and the rolling standard deviation. Volatility indicators form the key components of most bands and trailing stops indicators, but can also be used to normalize oscillators, they are therefore extremely versatile.
Today proposed indicator aim to compare the estimated volatility of two instruments in order to provide various informations to the user, especially about risk and profitability.
CALCULATION
The relative normalized volatility (RNV) indicator is the ratio between the moving average of the absolute normalized price changes value of two securities, that is:
SMA(|Δ(a)/σ(a)|)
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SMA(|Δ(b)/σ(b)|)
Where a and b are two different securities (note that notation "Δ(x)" refer to the 1st difference of x, and the "||" notation is used to indicate absolute value, for example "|x|" means absolute value of x) .
INTERPRETATION
The indicator aim tell us which security is more volatile between a and b , with a value of the indicator greater than 1 indicating that a is on average more volatile than b over the last length period, while a value lower than 1 indicating that the security b is more on average volatile than a .
The indicator use the current symbol as a , while the second security b must be defined in the setting window (by default the S&P500). Risk and profitability are closely related to volatility, as larger price variations could potentially mean larger losses (but also larger gains), therefore a value of the indicator greater than 1 can indicate that it could be more risked (and profitable) to trade security a .
RNV using AMD (top) volatility against Intel (bottom) volatility.
RNV using EURUSD (top) volatility against USDJPY (bottom) volatility.
Larger values of length will make the indicator fluctuate less often around 1. You can also plot the logarithm of the ratio instead in order to have the indicator centered around 0, it will also help make values originally below 1 have more importance in the scale.
POSSIBLE ERRORS
If you compare different types of markets the indicator might return NaN values, this is because one market might be closed, for example if you compare AMD against BTCUSD with the indicator you will get NaN values. If you really need to compare two markets then increase your time frame, else use an histogram or area plot in order to have a cleaner plot.
CONCLUSION
An original indicator comparing the volatility between two securities has been presented. The choice of posting a volatility indicator has been made by my twitter followers, so if you want to decide which type of indicator i should do next make sure to check my twitter to see if there are polls available (i should do one after every posted indicator).
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Distribution BlocksThis idea has been created by the combination of the two existing systems as a result of my efforts to create a distributional buying and selling guide that has plagued my head for a long time.
1st idea is Accumulation / Distribution Line :
2nd idea is Distribution Day :
These two ideas, the intellectual assistance of professional brokers, and my observations of cot data played a role in the formation of this idea.
Let's start.
No matter how often we divide our risk, both our minds are not comfortable and our capital may end at any moment, and if we do not use professional systems, our chances of success are 50 percent.
If we take this system as an aid to our classic systems, we can determine the amount of risk with those predictions and gradually trade.
If we don't use leverage and we have a little predictive ability, our chances of success go above 50 percent.
But for the first time, we can keep our first lot very low and increase the number of positions in the same order of orders (example: buy and buy and buy).
If we keep the first amount low, the folds won't hurt us.
When we catch up with the trend, purchases with larger position sizes than lower prices lower our average price, so that we can make a good profit when the rising trend starts.
By accepting the zone changes as the reset point just like in the martingale system, we enter the folds in the new zone with our first lot weight.
Although we cannot catch the trend, we determine the stoploss level by adding the first point we entered or the first point we entered and the commission cost.
In fact, this method is the method of buying and selling very large traders and producers, banks, pro-brokers, hedge funds and in other words the new popular phrase "whales".
Because if he trades otherwise, he cannot find buyers because his goods are too big.
I like the comfort of mind in this way.
Finally, your methods separating the negative and positive regions (macd, rsi, interpretation observation etc.)
the stronger you are, the higher your success rate.
I think the Accumulation Distribution method is very successful, but it can be adjusted for the period.
I can't wait to integrate my relativity system on this.
And when my deep learning series is over, I will integrate them on ANN series and share them publicly.
To start with, I can say briefly.
If your capital is 100:
(first lot + (increase multiplier * first lot) + (increase multiplier * increase multiplier * first lot) + .....) = 100
I tell you that you can have the same position in this series 10 - 15 times,
this will help you decide how small a position size is to be used as the starting rate and choose a low increment multiplier!
I think that this idea cannot be converted into strategy, because when our expectations come true, we may want to free all positions and start again.And I think that's better.
And in sudden movements and developments we take action with different expectations.
I'm going to talk about this script's calculations and profits on educational ideas.
Regards , Noldo.
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