Recent updates

Recent updates

Under the usual code revision, I sorted ut with a small modification of the training set that seems to have a large impact on the stability of the neural networks in the model. And also in our trading behaviors. I was able to find some interesting patterns in the data, that show that it is possible to reduce a bit of profitability for more reliable information This is why we need to make sure that the training set has enough accuracy.

As I wrote, the difference is tiny, just 1 bar. All training positions have been adjusted. We now have a more reliable set of predictions and the most affected indicator is probably the rV.Target. It was estimating the maximum extension of the move. It now represents the level that when cleared gives a start to the close position procedure.

There is a small (averaged) loss in presumed profitability, compensated by what should be a more reliable set of previsions.

As you know, I do not backtest anything, so let’s see how it preforms in the real world.

Posted by Luca in free, generics, indicators, model insights

Weapons for resolute traders

If you occasionally read this blog, you may have noted that I often say that r.Virgeel is not a trading system. I want to warn the newcomers that they will not find any automatic fount of wealth here.

Any serious trader has matured its activity in a deeply constructed attitude: call it a plan, or a set of rules, or a set of indicators or all these things together. Traders hate losses like cats hate water: sometimes you need some, but better avoid. So, they build their framework, each one different, each one influenced by the history of each trader itself.

When I first designed the model that will become r.Virgeel, my trading experience was at the “trade-with-technical-analysis-the-fundamentally-chosen-stocks” stage. Many experiments started with sets of t.a. oscillators and were largely unsatisfactory. It took time to understand that I might ask to the model “impossible” answers.

What I understood is that I must ask the model “impossible” answers, otherwise better use the t.a. methods an go on with the traditional analysis. With “impossible” I mean not available using traditional programming techniques. All t.a. is computer-based nowadays, so code is the key to performance. But traditional code cannot perform certain tasks in a manageable reasonable way, like forecasting next bars as the weather channel forecasts the temperatures for the next days. The model, neural networks based, can. Now, consider that saying “tomorrow low will be at XXXX.XX” involves a certain responsibility, bearable, in my case, by the long term performance of the model.

I’ve developed various indicators, during the never-ending development of r.Virgeel, and many have disappeared, leaving an affordable set of unique information. To best fit into everyone’s set of weapons, you have t.a. mimicking indicators, as rV.Target or rV.Stop, and some “impossible” indicators, as rV.Future Bars or rV.ExpectedTurn (which evaluates how many bars to the next turn) or rV.ColorBars (which evaluates at which stage inside the ideal position is the market and shows it as an easy to read colour code).

At a certain point, I started to develop the rV.Position indicators: they are many, all derived by the same learning process that reads the S&P 500 index flow into positions, long and short, picking always the best market position. Now, you may say, this IS a trading system and yes, in some way it is. In the middle, there is the behaviour of the model, that sees and detects a huge amount of patterns and correlates dozens of different inputs. Experience has taught to my faithful subscribers and me that r.Virgeel is very responsive, sometimes too much (it is still young, you know), rarely it gets blind for one bar (this behaviour has been drastically reduced by latest improvements), and it is correct most of the time.  I do not consider rV.Position indicators as a trading system, so I do not follow blindly its entry/exit signals; instead, I search for correlations between all the indicators to confirm any trading activity. Of great importance is the Weekly analysis, that has demonstrated to be well integrated with the Daily analysis.

Since few months, I have introduced an automatic summary: r.Virgeel writes a brief summary evaluation on the daily report and this is intriguing: it is a small text and it is working well, opening the road to new possibilities in the model output presentation.

more on the indicators…


Posted by Luca in free, generics, indicators, r.Virgeel, 0 comments

rv.Signal and rv.Position

I often receive questions about rv.Signal and rv.Position indicators and supposing they generate a bit of confusion, I hope the following may help.

In origin, it was Signal. It was the first attempt to generate inversion warnings. Its model was hand trained. Then, with various steps, it has developed into the first version of the Position indicator. It was not just trying to catch inversions, but to recognize an “open-hold-close” sequence, that for sure is often coincident with the inversion sequence of the Signal indicator, but being able to provide much more complex information. The present rv.Position indicator is the development of the original and has demonstrated long term reliability. It has grown to a group of indicators that work together in reciprocal confirmation.

  • The basic rv.Position, it evaluates both long and short positions, splitted in
    • the rv.+Position, it evaluates long positions only,
    • The rv.-Position, it evaluates short position only
  • the rv.Target, the extreme to be reached by the current position, calculated as close and high/low
  • the rv.Stop, the value that must not be broken on close to validating the position.
  • the rv.PositionColor, a colour code that visually feedbacks: light green for accumulating, light red for distributing.

Here a sample of the training screen for the rv.Position indicator. r.Virgeel learns to take and hold a position until the reversal occurs. rvPositionColor, rv.Targets and rv.Stops are set as consequences.
All these indicators are calculated and evaluated independently, without knowledge of each other. The process is now partly handmade, partly algorithmic and supervised. Hundreds of positions concur to setup r.Virgeel’s pattern recognition, in many different market conditions. And every day a new bar adds to its knowledge.

After rv.Position has been developed, the Signal indicator was temporarily dismissed. After a while, I decided to revive it and make it another confirmation tool. r.Virgeel is like a son to me, but I cannot trust one single indicator. Even if rv.Position gives an articulated insight in the market position, I always search for confirmations from a different logical approach.

Now, rv.Signal is composed of hand taught signals, plus other signals generated by a cyclical analysis (here a sample of the minimum detector) at four different levels (short term, medium term, long term, extra long term). Cyclical analysis is not yet complete, but working. It sorts out that rv.Signal is a sort of freestyle turning point detector, that works also for short term swings and mainly as a confirmation for the rv.Position system.

The ideal final charting of the mix of  rv.Signal and rv.Position indicators is something like this. A complex of bars evaluation, target, stop and triangles that mark the relevant turning points, mostly in the direction of the underlying position. My attitude is to limit as much as possible to take position against the current trend, even if sometimes the sudden corrective move holds some real value.

rv.Signal ideally fires +1/-1 values. In the real world, the values range from +1/-1 to a fraction of them, and, even if the .3 or .4 values means a very weak warning, I prefer to chart also smaller values to have the visual feedback.

rv.Position ranges from +1/-1 to zero. Ideally, a +1/-1 (Open Long/Short) warning is fired, then its value slides down to a +0.5/-0.5 (Hold) value, and in the final bars of the position, the value goes toward zero, that marks the “Close. Out of the Market” position. In the real world, it often happens the same.


Posted by Luca in free, indicators

Update to D-FT historical

Following a subscriber’s hint, I have re-brewed the D-FT historical values, with all the four values that are daily provided and for a longer time span, 60 bars instead of 30. Also, there is the date for every record, to make it easier for you to check out past values (please, remember the D-FT is always calculated in anticipation, for the next bar).

Just a final reminder: the D-FT is a very sensitive indicator and I think it is more indicated to provide a frame to intraday to short term traders, unlike the other indicators from r.Virgeel, that are more directed to position traders and investors.

This is a sample of the file format. Fields are:

date, resistance1, support1, resistence2, support3, bars back from day of calculation (in this case 2019-05-08)

11/02/2019, 2721.241, 2703.527, 2722.993, 2701.337, 60
12/02/2019, 2755.813, 2721.446, 2748.868, 2736.403, 59
13/02/2019, 2764.75, 2746.467, 2760.096, 2746.55, 58
14/02/2019, 2746.093, 2730.176, 2754.552, 2732.229, 57
15/02/2019, 2786.192, 2773.074, 2784.98, 2761.81, 56
18/02/2019, 2787.897, 2766.648, 2784.827, 2761.917, 55

D-FT historical files are provided for:

  • S&P 500
  • Dow Jones Industrial Average
  • Nasdaq Composite
  • DAX Frankfurt
  • SHC Shanghai
  • GOLD
  • 10Y US Bond Yield



Posted by Luca in checkouts, free, indicators

How r.Virgeel is trained

Following the requests coming from some users that were initially confused about how to interpret the signals coming out from r.Virgeel, I think that nothing is better than to explain how the indicators are produced. I have never done it before so extensively.

The process is very different from the calculations for a technical indicator as RSI or MACD, which involves the direct extraction of values from the price historical data.

Using neural networks follows a different logic: what to I want to know?  Think to a medical sample: doctor, I have these symptoms, which is the disease? Ideally, if I have a database of symptoms associated to various diseases, querying the database can give an easily probable range of possibilities, if not the correct reply. This happens now in many major hospitals around the world.

If you have ever used a spreadsheet (who doesn’t?), think to a table made of columns of homogeneous data, each line a single “experience”. You may add one or more columns and associate to each experience a characteristic, a category, a value, a disease, something that give sense to the line of data.  Great, you have created an a.i. model. It is a table, where some columns are input data that represent an event or an experience, and other columns that represent a meaning that we want to associate to each event or experience.

Usually, by habit, input columns are placed left in the spreadsheet and associated values are placed right.

r.Virgeel left columns does NOT include any data from the S&P 500 index. All the inputs come from dozens of other market indices, that covers all main stock markets, commodities, forex, metals, yields, bonds, etc.

I may say that r.Virgeel evaluates the S&P 500 as a consequence of all other markets. The influence of each market is directly related to its dimension, so the bond market and the forex are the most relevant.

At the moment the daily model has 74 indices on the input side and the weekly model has 123 inputs on the input side.

At this point, how the r.Virgeel indicators are built? What is placed in the right side columns?

I will cover the main indicators, the rv.Stop, rv.Target, rv.Position and rv.Signal indicators.

First, the market action is broken in “positions”, either long and short. Here you may see a sample of a long position, from the training program. This code is one of the three legs that support r.Virgeel (the others being the data maintenance and the number cruncher): here is where the “experience” is transferred into the model.


The position is marked by the thick white line.

rv.Stop (red dots) is placed to accommodate the whole movement. This is a traditional stop, a value that, if perforated, does invalidate the position.

rv.Target is calculated from the highest high and from the highest close of the final bar of the position.

Two series of signals are placed at significant bars (let’s call them “arrows”): the rv.Position puts arrows at the first and second bar of the move, to mark the entry points, and at the second-last and at the last bar, to mark the close of the position. Then it marks all the other bars of the position with a “Stay long” marker.
The same signals are placed in the rv.Signal indicator, except for the “Stay long” markers, plus other arrows are placed at meaningful bars, to highlight minor corrective movements and new entry points available, as the main position is holding.

These four indicators work in accord almost always. Almost. When they point in different directions, it’s a nice warning that something crucial is happening. Big attention is suggested then. After recent improvements, it seems that indecision/uncertainty usually last one/two bars, then r.Virgeel returns under normal conditions.

In the background, you may see coded the rv.PosColor: bright red at major long entry points, bright red at major short entry points, a gradient in between. It is a confirming tool.

All indicators are calculated separately and r.Virgeel is totally unaware of its own past outputs. Every time it produces an output, let’s call it a forecast or a diagnosis, it evaluates present values on the left side against the archive of experiences it has recorded. It is called PatternRecognition and is produced by applying a reverse logic algorithm. The less improbable result is output.

This is how neural networks work. Now you may understand better when I’ve written “A.I. is different“, it has nothing to do with technical analysis by any means.

One recent improvement has been the introduction of the FastTrack indicator. It is the first indicator that has been suggested directly by r.Virgeel. The model has a strange behaviour, probably depending on the fact that I’m not a mathematician I cannot explain it, that produces exaggerated forecasts under defined conditions. Leveraging on this defect, I verified extensively that the output was a fantastic trend follower: false signals are near to nil, considering that even if when they occur, usually you may return on the correct side with a minimum loss.  The FastTrack output is a series of four levels. What matters are the two levels that define the central neutrality area.

Let’s make an example. Today’s D-FT (Daily FastTrack) is the sequence 2837.79, 2797.362 | 2808.145, 2788.749

  • The ordered sequence is 2837.79, 2808.145, 2797.362,  2788.749
  • The central neutrality area is defined by the numbers 2808.145, 2797.362
  • Above 2808.145, we have confirmation of a rising dynamic under development,
  • Under 2797.362, we should have confirmed of a declining action under development.

The FastTrack is an end of day indicator, it is very sensible and I find it useful placed on the short term intraday real-time chart. Actually, using the r.Virgeel’s framework, the D-FT levels, some rudiments of Elliott’s Wave’s theory and a couple of moving averages seems a good setup. I’m testing it at the moment with a certain satisfaction and I will report the experience when it will be mature. Simply said, I’m moving the first steps towards a wealth building machine, using intraday action, based on a weekly staircase. Each week target is based on a stable compound capitalization model. In a few month I will go bankrupt (on the CFD account) or the machine will be snorting and puffing and chugging.

r.Virgeel’s indicators somehow mimic some traditional t.a. indicators and this may generate confusion or misunderstanding. It’s my fault: as the model construction has developed, I’ve got from my previous experience of investor and trading scholar, fishing ideas trying to shape r.Virgeel. Many indicators have been developed and few survived.  Some brilliant ideas have been demonstrated them dumb, others have a long track of solidity and sharpness. The quest is not over.


Posted by Luca in a.i., free, indicators, model insights

The new FastTrack indicator

UPDATE 2018/12/14

Today I’ve closed the free alpha testing of the FastTrack. It is fantastic! All the spxbot readers have seen in real time it’s performance.  Now, to be clear, the numbers.

[table id=6 /]


Operations were simulated on a CFD platform. I have stopped the last (virtual) operation today in the morning (CET), with the SPX at 2623. Prices subject to a bit of slippage and to personal triggers. This was not an automatic testing, it was, as usual, a real time testing. No account for expenses or taxation. Even if your apply your  more pessimistic view and consider a wider slippage, there is a huge margin for a very consistent profit.

This is the performance during the first month and a half, during development. Stellar! Now, development has completed, and subject to the refine process. Subscribers have access to daily reversal D-FT levels for the following markets:

  • S&P 500
  • Dow Jones Industrial Average
  • Nasdaq Composite
  • DAX Frankfurt
  • SHC Shanghai
  • GOLD

The FastTrack indicator, an r.Virgeel artificial intelligence tool, is a totally de-parametrized neural indicator composed of price reversal levels that confirm or deny the short term trend in action. The basic assumptions are:

  1. that the market may go any direction any time,
  2. that exceeding the traced levels is a clear sign of continuation or reversal of the trend
  3. the area inbetween the levels is a sort of “neutral” area that does not give any relevant indication.

Let’s see the simpler version in action, to better understand it’s behavior:

Here you see the levels for the latest days, from the top of Oct. 3rd to Oct. 19th., 2018
Levels are generated for the next day/bar. We can easily identify three key days, in the chart:




(Please note, the above images are from the very first development stage)

In the shown days, the coming reversals are clearly oulined by the relative levels: as next day the S&P 500 crosses the levels, then the reversal is stated.

As shown in the last chart, for two consecutive days, the FT supports and resistences the FastTrack is calculated under two different conditions and so we actually have two levels that show the less improbable path of the coming bar.

I have sampled the FT all around the data (it’s a nicely long recording of the S&P 500) and the behavior of the new indicator seems very attracting. The FT indicator is not exempt from some false signals, but following strictly its action should reduce drawdowns to virtually meaningless.

The FT is also applied to weekly time frame. Follow the blog for updates.

How is the FastTrack built? r.Virgeel projects extreme levels into the coming bar. It makes a double projection, under two different (opposite?) conditions. His projections are usually quite precise and so the FT generate a sort of trend following channel. But the market is a wild beast and it is alive and loves to play sudden reversals. Let mr. Market play his game, and he will break the FT, either in the direction of the trend or reversing, because he is always exagerating and pushing over its limits. In some way, the FT is built around the psychopathological behaviour of the market. The FT has been suggested me by r.Virgeel and was unexpected. I nean, I did not designed it, I just refined the code to have a stable output.

Even if it has some occasional (and inevitable) false signal, the other r.Virgeel’s indicators are there to help confirm the trading action.

The FastTrack has been published for free during the first month and a half of development, from late October to mid December 2018, during alpha development and testing, to let us evaluate it’s performance and solidity, and it is now available only  to subscribers.


Thank you for following and supporting!



[pt_view id=”7a3b622qrv”]


Posted by Luca in free, indicators, r.Virgeel

Going Forward

For many months, I’ve tried to put together the pieces to have a long term database, monthly based and with a huge history. I was moved by the progress of the monthly forecast, that I see sharper than before. No way. Data is largely unavailable. Very few series of mayor commodities and indices are out there, but very few indeed. r.Virgeel works well with more data. More data. No way.

Then I started to look at my beloved weekly forecast and I soon realized that I could enlarge the weekly database in time reducing its components. To make it simple, more data for less symbols. Mmh…

I hoped that data could go back some decades more, but I now have a new weekly database about 75% longer in time than the standard one. It needs a new whole ecosystem of code to work and the basic part is in beta development and running. More work is needed, but I’m very curious of all new code output, when it will come.

So, I’m rewriting the code once again and with a new database (DBMS), it’a game of traps and bugs. The new DBMS is slower than the standard one, but its tameness is great. Being slower, I have to rewrite the code optimizing every step, and this is good. It will take time, but then we will have a brand new weekly brain. Worth the effort.



This chart is the very first captured from the development. It is the training process feedback. the color code seems to work well. One of the enhancements is a better visual evaluation of r.Virgeel learning, an evolution of the Colored Bars. I try to be as impartial as possible and help r.Virgeel detect bottoms and top and generate optimal signals for operative triggers. Working on the past, it is not difficult, but sometimes tricky.

Another enhancement at the horizon is that r.Virgeel will no more be restricted to the S&P 500, but it will open to a batch of sperimental new subjects: EUR/USD and Gold will be the first. Before it was not impossible to obtain a forecast of other symbols, but it was quite complex, being the original project very SPX centric. Now it will be easier to test some new entries and see how they work out.

I wanted a huge monthly database and I will have a not-so-huge-but-larger new weekly model.  At work, now.





Posted by Luca in free, indicators, model insights

Daily forecast accuracy sample

I wish to stick to showing you samples of the r.Virgeel activity, in (almost) real time. There is no other way to test r.Virgeel than real time. Also, to avoid the “well chosen sample” effect.

Here, on the left, the forecasted bars evaluated on May 17th, on the right the chart of the actual bars until yesterday close, May 30st.


Left: forecast of May 17th Right: actual bars at May 30th


I show you the forecasted bars because it is by far the most difficult indicator to calculate, bars come in from the future squishly jigsawing and with modulated velocity.  So whenever I want to evaluate r.Virgeel model, I first look at the future bars. Also, the future bars are a totally unattended calculation, meaning that there is no human intervention at all, just the correlation of a huge number of factors is taken in account.

Looking at the forecast, when it was issued, you might argue that a choppy period was to begin, that should not exceed the last high and that might break the last low.  Two down days, followed by a reaction that flattens and returns slightly negative. You ‘d have known all this in advance, various days in advance. Either you are an investor or a trader or even a daytrader, you might take advantage in various ways from the forecast, but you are psychologically prepared to what is coming.

From the comparison ot the two sequences, I point the attention on the fact that the incoming wave is demonstrating to come in faster than expected by the forecast. This is a fact I’m long pondering. Almost all r.Virgeel forecast show this reverse lag, but I’m still detecting. One possible reason is the fact that the databases of r.Virgeel goes back to an era when everything, in trading activity, was slower: no internet, no direct instant execution, non continuous markets, just newspapers and a phone to pass your orders to your broker or bank. The ever accelerating time implicit in the trading activity is an interesting subject of research. Another possibility is that time in itself might be an accelerating media, but here I can’t go further.



Posted by Luca in accuracy samples, educational, free, indicators, 0 comments

The Indicators

Sample chart from May 7, 2018

This post explains the main website feature: the indicators that form r.Virgeel vision of the market.

The indicators are:

Bars ahead – neurally calculated – H/L/C is forecasted for the next 24 bars
Target– neurally calculated – where the current move is heading
Stop – neurally calculated- a value that confirm the trend and generates alerts of reversal
Position – neurally calculated – a simple, but detailed, as a neural swing system, Position is calculated in three fashion: the positive attitude, the negative attiture and an overall attitude. In moment of uncertainty this help to have confirmation of the reading.
Color Bars – neurally calculated – an evaluation of market’s potential energy through color code. It has integrated the old Stamina indicator.
Signal – neurally calculated – top/bottom pattern recognition. It’s the simplest original version of the Position indicator: it fires probable tops and bottoms detection.

FastTrack – The standard report integrates now the FastTrack levels, from daily, weekly and monthly  models for SPX. The daily D-FT is available for:

  • S&P 500
  • Dow Jones Industrial Average
  • Nasdaq Composite
  • DAX Frankfurt
  • SHC Shanghai
  • GOLD


All indicators are calculated indipendently from one another, giving the opportunity to let them reciprocally confirm.

The text on the left of the chart summarize the relevant numerical data, more numerical data in the body of the mail/post.



Coloured bars. It’s a glimpse into the future: they represent the less improbable path the market is supposed to follow, for the next 24 bars. In the background, the latest monthly and weekly forecaste bars give a more complete and synchronical view of the coming events.



Blue dots, blue lines. It’s a glimpse into the future: the Target is an evaluation of the price level that the S&P is bound. More the price nears the Target, higher the probabilities of an imminent turn.


Red dot, red lines. It’s a reading of the present. The Stop is the value that, if broken at close, suggests that the position has come to an end. It works either for long or short positions. The Stop is free to fluctuate and, by experience, the descending Stop is a sign of strength of the long position (and reverse), usually occurring during choppy phases.

Also, the weekly Stop is present on the chart (darker red band).


It’s a reading of the present. The Position indicator is the most evolute and mimicks a complete trading system, with entry signals, position confirmation and exit signals. It is calculated separately for the long and for the short positions.

The Position indicator provides the following signals:

  • Open Position – generates signal triangle
  • Add to Position – generates signal triangle
  • Stay in Position
  • Reaching Top/Bottom – generates signal triangle
  • Close Position – generates signal triangle

that follow the ciclical activity of investing and trading.



It’s a reading of the present. The Signal indicator is the parent of the Position indicator and it was, at a certain point, removed from the charts and dismissed. It has the aim to detect the market turning points. Lately, I decided to revive it and use it the signal generation: you may see, usually near the extremes of the chart, there are some small colored triangles. These triangles are generated from the Position indicator and from the Signal indicator and they usually coincide. The triangles should mark the extremes, but more often they generate a cloud of signals around the reversals.


Posted by Luca in a.i., educational, free, indicators, r.Virgeel, 0 comments

A brand new Signal indicator

Signal was the very first indicator that I developed for the A.I. model: it used to fire a +/- 1 value at market extremes, marking top and bottoms. I never did touch it again, but in the meantime the model has evolved quite a lot.

The first consequence of the ongoing research on cyclicality has been that I have now a new categorization of the market extremes, so I have different values for each bottom and top bars. Using these different values makes the new Signal now range from -11 to +11, with any value from +0.70 to 11 marking a potential bottom and -0.70 to -11 marking the potential top. As the number rises, the top/bottom should be considered “stronger” and last longer.

As any indicator in the arsenal, the new Signal will be tested ex-ante, meaning that it will be put at work and evaluated as time goes by.



Posted by Luca in free, indicators, model insights, 0 comments

Enhancement to indicators

All indicators have been enhanced to a new adaptive behaviour, so that the indicators, when calculated, are never aware of any bars of the current move.

This was already partly true, but now this has been stated peremptorily.

The charts are much more interesting now, because Targets and Stops, for example, tend to form clouds of values that are self confirming.

The A model outputs at the moment five AI indicators:

  • Top / Bottom recognizer is a market excess locator, marks turning points
  • Position works on a deep learning base, provides the basic set of signals to enter and exit positions
  • Target estimates the goal of the acting wave
  • Stop puts a protective value : if a bars closes behind the Stop, well, something is going wrong and better get out soon.
  • 24 Bars ahead gives you a visual feedback

When indicators confirms each other a turn is promptly recognized.
The system always considers the execution of the orders at the opening of the next bar. This makes it perfect for part-time distributed investors.

I never thought, when working on the first experiments about S&P 500 forecasting, to create a trading system. It generated itself, maybe six months ago, once I completed the Stop and Target indicators: all the number crunching and training were ready and data could be extracted easily.

The Position trading system can be used as a swing/ position/ investing/ trading tool relative to how you set your entry/exit strategy and your preferred time frame.

Position trading system works on daily, weekly and monthly time frame, to provide a complete framework  of evalutions.


Posted by Luca in free, indicators, model insights

Enhancement to Signal

SPX-da-am-20160707-225903-914E63B3-ECBB-4429-AD03-03EE136D4636-3500-24Please note, this is just a part of a larger chart and it shows three indicators calculated by the A model. As the set has been trained, results are perfect. Last 8 bars are excluded from training and are guesses of the model bots. The image was produced few minutes ago.

We have the Target, the Stop and the Signal: Target points to trend exhaustion (cyan dots), Stop places the stoploss (yellow circles).

I introduced a modification to the Signal indicator. The original Signal marked the extremes with a triangle, either red (tops) or green (bottoms). Just the extreme. (And this, I believe, was the origin of many false signals).

Now, for any day marked as a top or a bottom, the day before and the day after are marked as well, with different values.

The behaviour of the indicator is as follow: the appearence of a first triangle must be considered as a warning. A second triangle is to be taken in consideration for position opening. I always consider that execution will be placed the next day, at opening, following the market and serching for a favorable entry point.  (Personally, I often look at hourly CFD rates of S&P500 to trigger easy exit or entry point).

For sure, the triangles may now be in overnumber and I will monitor that they do not invade the screen, but I feel interesting pushing the limit of the system to be as much confortable as possible. Now we should have a possible warning 2 days before the event and 1 day before the top or the bottom, plus a recurring confirmation of the flowing move, and I think it will make easier trading decisions.

For prudence, I always invite to check reciprocal confirmation from the various indicators before operating.

Posted by Luca in free, indicators, model insights

About targets

[su_column size=”1/1″]target_sample

[T]he target is an instant reading of the price potential energy. When the price serie is trained, the best possible trades are marked with a start and an end, that generates the arrows  that signal market extremes. Then taking the average of the last day of the position and the successive day, the difference for every day of the position  from this value is calculated: for every day there is a percentage af value that still has to be gained until the position has to be terminated. The chart is quite simple, isn’t it? The main idea is that whenever the price is above (or below) or even very near to the target, the movement has finished it’s energy. This is for the ex-post and the training phase.


[su_column size=”1/1″]

Now, what about realtime readings? Here is the sample from today. Undoubtly the cyan dots (the targets) are quite confused, but it’s just what the model reads from the never seen before data. Generally speaking, we may note that:


  1. usually the target stands on the side of the movement, over the price during the uptrends and below the price during downtrends
  2. targets tend to “converge” toward the reversal areas
  3. by construction the scattered dots marks the most sensible support/resistance areas

In conclusion, the target is a confirmation tool that add an interesting information that can be read from price action inside the model.





Posted by Luca in free, indicators, model insights