Shark 7.0 EA review

This is a review by a trader of the Shark 7.0 EA.

Pros:

+ Though I didn’t figure out what activates the logic, I like the idea behind. As it places orders only when the market moves quickly, there is a great probability given that either a sell or a buy order will close in profit.

(It is not possible to figure out the logic if it uses Artificial intelligence algorythms)

+ It uses pending orders only. I consider it to be an advantage, as it decreases slippage greatly.

(That is not necessary some brokers still have slippage on pending orders.)

+ trades two currency pairs.

+ It does not open more than one trade at a time.

                                               Cons:



- As SL is placed very close to the market price, dishonest brokers may play dirty games.

(That is important as it is about very close orders to the price. Choose carefully the broker and always always monitor the execution. That is why you need to backtest with your broker tic by tic.)

(And of course you can't have something for nothing everything has its cost, here as thestrategy seeks for the tightest stop loss, that necessarily comes with costs: extra care and control over the execution).



- I am certain that Shark 7.0 will not work with market makers, and results will vary from broker to broker.

(I agree on this, but I would add some market makers not all market makers, I think if you play with 0.01 lots as basic lot instead of 0.1 lot you may have less problems in the first time)



- The final version input parameters are limited to money management settings only. Other parameters are not accessible by the user and can’t be changed. To my mind that’s a bad thing for experienced traders as they don’t have much “space” to maneuver with their settings. Who knows, maybe they change that after seeing this post.

- The user manual does not include any information regarding broker and VPS requirements. That’s not a big deal for experienced traders but clearly, a disadvantage for newbies.



That EA has potential but extreme care need to be used when implemented.

I would add that the quality of the code is guaranteed as the EA is done by experienced traders and programmers.



We would negotiate for EA Shark 7.0 discount coupons for our members even one evaluation copy may be available to one of the most serious contributors on www.beathespread.com.

It is recommended to buy this EA (is someone is interested) and not to search free copies because of the support. The support is a critical feature and without support do not even think to let it trade for you. (Personnal opinion).

PNN for metatrader using Parzen window classification version 2 with kernel smoothing of inputs

This is the PNN using Parzen window classification version 2 with kernel smoothing of inputs. You need to have the PFE indicator.

Here you will file the standard PNN called version 2. And the PNN with money management and kernel smoothing of inputs.

Nevertheless this is a beta version, because I am not sure that the integration of the kernel smoothing with the PNN code is correctly executed.

So this is what we have for now. Anyway the idea is interesting.

In the normal PNN Eric we have as input the difference between:


b[bar]= Close[bar]-Open[bar+AmoutOfForecastBars-1])

The idea was to replace this piece of code with something else and to see how it would affect the EA.

So I replaced this by the kernel smoothing of PFE.


b[bar] = kernel()

So this is the idea. However the number of bars of parameters is still an important parameter because it affects the initial period for training:


TrainingStartTime = Time[0] + Period()*60*AmoutOfForecastBars

Of course we can replace this piece of code by Numbars_for_Training as a parameter, but I chose not to touch this for the moment.


TrainingStartTime = Time[0] + Period()*Numbars_for_Training

Any wise look in the code would be welcome as there is not many native mql code for neural implementations.

DOWNLOAD from here

Linear regression technical analysis

http://www.fao.org/docrep/W5449E/w5449e04.htm

As for me the main model of the technical analysis is the linear regression. The oscillators are not intended to measurecycles, they are intended to measure the deviation from the central line of the linear regression. and yes, when you deviate from those center line there is an increase probability that you will reverse to the center line of the linear regression.

That is the true reason why oscillator tend to work (of course according to the theory).

That theory is completely different from the Ehlers theory of trend mode and cycle mode.



I am not sure that I am really clear, that is why I am giving to the introduction to the video of linear regression.

And yes that is the basic model. Imagine: trend lines, Andrew's Pitchfork theories (look here it is very revelative how he defines the linear regression manually).

The second important model is the heteroscedasticity of the volatility. All the patterns of the technical anlysis are driven by this phenomenon, it is related also with the market state analysis.
Definition of 'Heteroskedasticity'

In statistics, when the standard deviations of a variable, monitored over a specific amount of time, are non-constant. Heteroskedasticity often arises in two forms, conditional and unconditional. Conditional heteroskedasticity identifies non-constant volatility when future periods of high and low volatility cannot be identified. Unconditional heteroskedasticity is used when futures periods of high and low volatility can be identified.

Read more: http://www.investopedia.com/terms/h/heteroskedasticity.asp#ixzz1swlH5Cfh


Investopedia explains 'Heteroskedasticity'

In finance, conditional heteroskedasticity often is seen in the prices of stocks and bonds. The level of volatility of these equities cannot be predicted over any period of time. Unconditional heteroskedasticity can be used when discussing variables that have identifiable seasonal variability, such as electricity usage.

Read more: http://www.investopedia.com/terms/h/heteroskedasticity.asp#ixzz1swlOdQge



The Third important thing is coming from the chaos thoery by measuring the fundamental properties of the price time series. Fractal dimension and Lyapunov exponent.

Those measurements matters because imagine the third window when you are using a limit order. Knowing the fractal dimension will save you to prevent your stop to be hit when the limit order is activated.



So here we are. We can explain most of the common technical analysis by some mathematical models.

By this theory it is clear that the oscillators may be adapted according to the volatility arround the central tendancy.

Do you see really what they are doing ? They measure how far we are going away from the central tendancy. If the central tendacly is going up we are saying up trend, if the central tendancy is going down (down trand), and if it is horizontal we say (range).



Those posts are a little bit long but they are related to the general theories underlying the technical analysis.

We are looking for a kinf of unifiying theory. Why those efforts? Well that is because we see how the linerar regression together with the volatility models are expaining so much of the technical analysis.

We ask ourself what the creators of this or that technical method really see. What is the mathematical underlying reality of what the technical authors really see.

To this we can add the psychology we have seen how the psychology is creating an accumulation of orders at specific places. Then in turn those places act as attraction points and are activated.

All this is forming a very complex soup.

We can observe this but our knowledge as a speculative knowledge is limited.

Nonetheless, speculative knowledge is not perfect knowledge of the phenomenon under inquiry, on the contrary, speculative knowledge is precisely imperfect, partial, fragmentary, as such a knowledge is rooted in the necessity of contingency, which implies the knowledge that perfect knowledge is illusory (not in an epistemological sense but in an ontological one).
Read more: http://fractalfinance.blogspot.de/2011/04/possibility-of-cognition.html