selected primer

Gamification

If you think that the trader’s activity is similar to a game, I would like to first say it’s not. For many reasons. What makes to someone the trading activity similar to a game is a misconception of the bet. The novice tends to see a buy of a stock share as a bet, and, well, it somehow is a bet if you know nothing of what you are doing. Because it’s not a game.

But staying with the game analogy, I would prefer, to much adrenaline-driven action games, the more time related Virtual Regatta Offshore, a provider of oceanic regattas simulators in real-time with real conditions, here in the current RORC 2019 where I participate as minushabens. In this case, it is a 16/17 days ride from the Canarias to St. George’s Island. We are about 4 days from the arrival and I’m placed quite well: I was lucky, indeed!

 

Let me explain: the player have to decide its route considering the present condition of the wind and the future evolution of the wind, based on some known performance of the boat we are racing with (known as the polars of the boat, simply the speed of the boat at different wind speed at all angles). So, the player relies on the weather forecasts to evaluate its alternatives. While in real-world regatta you may apply a wide sort of tactics against your opponents, here you just race against the wind. No need to know the real sailing (it helps), we race against a worldwide huge number of participants. Here, at the RORC 2019, we are 37.000 and counting.

Now, I can guarantee you that my choices are not bets. Sometimes, as it is now, the choice has been more favorable, others are not so exciting, but if you want to appear in the first third of the ranking you cannot trust the simple bet. You must change your mind: you are challenging a force of nature, much bigger than you and good forecasts for 5 or 8 days ahead may easily change in 2 or 3 days, not much certainty around. Is anything sounding familiar? Now, if you substitute the word wind with the word stock market (the S&P 500, in this case), is it clear the analogy of the behavior of the player of the regatta and the position trader on the index?

If you see the game as a be-there-at-that-time-to-be-elsewhere-at-another-time dynamic, it’s not difficult to place yourself in the first 700, possibly between 300 and 500, where I often find myself at the arrival. A bit of luck today is appreciated. Obviously, you bet, there is a number of route calculators available as apps and websites. Every service is based on one of the available forecasts, then provides different best paths, but the game platform has often slightly different conditions and there you are gaming. You must be well placed in the space and time of the game to fully take advantage of the suggestions from the routing software. Here, as well, a bit of luck is largely appreciated. To remain once more in the game analogy, you are requested to dominate space and time, always need to consider the two as a whole. This is a common analogy with adrenaline games.

End of August. r.Virgeel is already positive for two days and gives a projected rv.Target around +3%. Great time to jibe!

The target was then reached at around 3000 in 10 days.

 

PS. Update – The RORC 2019 finished with me at 787th / 39101

 

 

Posted by Luca in educational, free, generics, performance, psychology, selected primer, 0 comments

r.Virgeel’s trading model

 

The r.Virgeel’s model is stable since enough to let me say it is now entering its early maturity. I’m working in the refinement field to gain speed, affordability, stability. Less, and this is my fault, I work in the field of communicating how to read and use the model’s output. This is obviously useful to newbies (to the website and also to trading), but also to experienced traders and investor, and even to long term subscribers, that already know the mechanics of the forecasts.

The global goal of r.Virgeel is to detect the best S&P 500 market position available: better stay long or short? Then it provides indicators to detect the incoming market waves projecting targets, stops,  with the support of confirmation indicators. r.Virgeel was not conceived to be a trading system, but it sorted out to be a sort of. I do not push it, I always suggest to get the suggestions and verify inside your framework.

Let’s take the Long Position and its dynamic: r.Virgeel detects a deteriorating downward move and warns the short end is near. Signals that mark the bottom are fired. r.Virgeel confirms the long position. Occasions to add to Position are detected, to let you enter/add with margins of safety. Warnings are fired when the position is detected weakening. Next inversion is detected/confirmed and so on.

The previous is the ideal path that resides on the learning side of the model, then when applied to the real day by day market, some signal may be missing, some turn may be a bit bumpy, some uncertainty arises here and there, usually sniffing incoming turbulence.

Please, note that these warnings are to be used inside your framework: your trading and investing style must not be rebooted, just may integrate the r.Virgeel’s suggestions. It may need some time to adapt, but the utility of a totally unbiased a.i. robo-advisor is out of doubt.

Here a visual representation of the Long Position as detected by r.Virgeel. For the opposite Short Position, just reverse the rules.

We have the three main indicators rV.Stop, rV.Target and rV.Position that defines the global situation. Some confirmation indicators are needed because sometimes the main indicators diverge and generate uncertainty. (see bifurcation to approach the topic)

In the real world, here you may see the Alpha Chart generated on 28th of August 2019: it summarizes .Virgeel’s opinion for the incoming wave, well confirmed by recent market action.

 

 

 

Posted by Luca in educational, free, selected primer, 0 comments

spxbot limits

Different trading and investing styles

I’m fully aware of the basic fact that every trader and investor has it’s own style. Many school of thinking, but everyone is really different, particularly in the private sector. If a private trader survives the first 18 months without being wiped out, then she/he may have the possibility to play on. It’s a sad and real statistics: 95% of traders are wiped out in the first 12-18 months of activity. So, if you are a private trader since years, you are in the 5% and you have built your skills with iron and steel, it’s not easy to approach a new language.

In effect, a.i. tools are very comprehensive: the result is there, fast, precise, direct. You just have to pay attention, when required, then to act if necessary. The whole decision process that makes the foundations of a trading system is questioned. It’s not an easy process, it will not be.

 

Mind changer about traditional tools as t.a.

Artificial Intelligence tools, not only r.Virgeel, implies that you change your mind about the instruments of analysis. Are you there with any of the technical analysis tools, or with a realtime CFD, you plot your oscillators, you backtest an optimal setting and decide, based on a unique line of data and a monodimensional analysis. A.I. can analyze many different correlations concurrently, sorting out with surprising results. It is obviously different, it is much different.

If you are totally unaware of a.i.. and neural networks, you do not need to read huge books to understand. You use Excel, for sure. Read this, then it will be easier. Made simple, supercharge and megapower a spreadsheet and you have a neural network. Then you have all the a.i.: image recognition, diagnostic, speech recognition, text recognition, and you name it. Once you understand the brick, then the wall makes sense.

The fact is that an a.i. robo-advisor makes the dirty work for you. Collects data, builds tables, generates logic, connects correlations, normalizes the resulting cloud of data and generates the output data. Whooo! All in one. And it’s fast!

Low adrenaline, stress reducer

People love adrenaline, excitement and, basically, confusion. In the long term, this attitude generates deep stress, that reflects into bad behaviours. If you are a few minutes ticker trader, r. Virgeel is not for you, probably. Well, as it  gives a daily trend, it may help, but…

Once you have a good robo-advisor, you need less to have opinions about everything. It monitors the data, it makes the loops, it builds the report. You must trust it, follow the suggestions and pull the triggers. Stress is highly reduced. Instead of needing to have an opinion about everything, you just have to evaluate a very well documented “opinion” generated by the a.i. model. You know, I like to say, it’s different.

For what I can see, robo-advisory is taking shape as large (and expensive) premium sites with a large choice of instruments, with applied different forms of analysis and previsions. I argue that the neural analysis is often simplified and this can be a good thing, overall. In other words, these sites offer a large set of instruments and an automated training.

Here at spxbot it’s a completely different music (well, it’s a premium site, but it’s cheap). First, just one instrument – the S&P 500 – here. Then, the correlated instruments are hundreds, to represent the global finance world. All for one, we may say 😉 More, r.Virgeel is highly deparametrized, meaning that it work by brute force and not by rules. Finally, r.Virgeel is trained “personally”, bar by bar. Total human supevision on the training of the model. You know, it’s always the same old story: you put rubbish in, you get rubbish out.

 

 

 

 

Posted by Luca in a.i., educational, free, psychology, selected primer, 0 comments

Spxbot robo-advisory performance

(this post was originally published in the newsletter no.1 in mid January. Probably I will not publish any performance related data in the future, mainly beacause r.Virgeel is not a trading system and also because real performance depends on a lot of factors, depending on your location, tax burden, investment strategy, etc. Anyway, the first two years of activity are here summerized, to show how the the robo advisor is performing in the real world)

I’ve always been reticent to publish the performance of the Position trading system: I’ve even dismissed the record table for the subscribers, without any complaint from them. It should be complex to explain why, it’s something intuitive, but it is related to my distrust in backtesting. First, I’ve always tested forward, not behind. It’s slow, for sure. The model, or as I call it now: r.Virgeel has taken shape during four years and is performing well. It is still under development: new ideas are passing as clouds at the moment. r.Virgeel correlates dozens and dozens of markets and is trained to be a prudent trader, preferring the long term run to the frequent short term trading. r.Virgeel warned us that the market was heading to 2730 many months before, and, honestly, I couldn’t believe it. r.Virgeel is trained to take the best position available in any single moment and it knows the market since a long time. It is not biased, it is responsive and adaptive, it’s huge (the brain is now around 15-17 Millions of neurons). It’s not something that you can backtest, you know (even if it is remotely possible), and I cannot guarantee that at a certain point it doesn’t go completely nuts. At the moment, r,Virgeel is well fit.

Anyway, I understand well that performance is a good starting indicator for evaluating any investment strategy: we have a bottom line and our mental model is arranged to appreciate rankings.

So, this is the update to the daily Position performance: the system started it’s first recorded operation (long) on Feb. 12, 2016 with the index at 1857. Two years may seem a short time and it is, but, as I wrote before, r.Virgeel is unbiased, it doesn’t take in account its previous evaluations. Since inception the Position system has completed 14 positions, 12 long and 2 shorts. Holding the position has lasted from 6 to 74 days, with an average around 37 days. Three positions were negative, respectively -0.28%, -0.84% and -0.04%. The total gain sums up to 823 points, or 44.32% with an annualized rate of 23.14%. A buy and hold strategy should have won, as the S&P 500 has gained 831 points in the same time window. This is mainly due to the fact that the model is trained to be conservative: it exits the market when the short term profits are too risky and recent market conditions made it difficult to re-enter at a lower price.

All calculations are made on gross trading the index value, without taking into account transaction costs and fiscal payments. A reasonable slippage is applied. All transaction are evaluated at the opening of the following day, after signal generation. Personally, I manage my whole personal capital under r.Virgeel advisory. Only, I select the ETFs in a range of preferred sectors.

 

 

 

Posted by Luca in free, model insights, performance, selected primer, 0 comments

A brief history of SPXBOT

In the late 80s, I crossed with BrainMaker, a suggestive piece of software that let you play with neural networks. I was working as an architect and I was self taught in the theory of patterns as formulated by Christopher Alexander. On one side pattern recognition, on the other side patterns in reality. Nice field of research.

At a certain point, let’s say beginning 90s, I was ready to take off with a language and code my own tools. Much easier to say, I finally got through a wonderful library that manages back-propagation networks. Straight, fast, error prone, wow! I’ve built many many versions of a tool, that was always showing the same definitive fault, paying the necessity to tune parameters and entering self referral loops.

Mid 90s, big turmoil: in Italy, in Florence, where I lived, in work, in my life. I gave up. I saved everything, backuped orderly, and closed. In mid years zero, let’s say 2005, I was living and working in Milan, working hard building a villa in the outskirts of Moscow for a russian wealth family. It was like having another son, well, a daughter. My love.

It was around 2012 that I begun thinking to the necessity to develop a plan B. Put your skills under short circuit and your plan B will materialize. In the spring of 2013 the design begun to take shape. About one year to collect the data, build the database management, and generate the skeleton of a possible model. The most of the following two years of development are documented in the Market Mind View free blog, already available to snoopies.

The model has been developed since then and I think that it has achieved a stable mature configuration in latest months, mid 2017. The result of four years of work is a model that correlates simultaneously dozens and dozens of inputs, consisting of financial and economic indices as stock markets, currencies, bonds, rates, commodities, metals, energy and more. The largest of the active neural network models has more than 17 million neurons or nodes. The model is heavily deparametrised, as it is set up, since design, to enhance the generalization ability of neural networks, in other words their ability to see, to recognize, to classify. Are you surprised? Software can see? Are we really into Minority Report or Matrix? Can software really see into the future? Well, no. And yes.

Since early 90s, I’m used to chart my modified DMI indicator, here in the Pascal version for the CFD platform. The indicator separates positive (blue) and negative (red) action of the market, as DMI does, using averages as input, instead of the plain data H/L/C. Can’t live without.

Let’s look at it in another way: the neural network always provide the less improbable result, chosen from the archive of possible results it has recorded. It’ a complex relationship: as these data, this possible diagnosis. This classification. This signal. Neural networks learn from the experience you provide them. They do not calculate the result: they know the result, if someone has taught it to them. Otherwise, they guess, in a reverse statistics, the less improbable result. Not the precise result of a calculation, but the less improbable result from it’s experience database. If you teach rubbish to a network, you get… guess? You get the less improbable rubbish.

In mid 2015, I realized that probably the architecture work, in Italy, was over and the neural works were worth the development. I also realized that the information I was producing  was getting sensitive and that induced me to hide from large public, giving life to this premium website. I mean, I wanted to continue my research and to have interaction with selected interested people, because this interaction is precious. It’s real fuel in the development process. So the site is available under a cheap annual fee, because I prefer a selected small club to a vast messy audience.

 

 

 

Posted by Luca in educational, free, generics, model insights, selected primer, 2 comments

Riding the wave and then… splash!

 

Following my previous post, I would like to point out that approaching the a.i. advisory, you have to change your mind. With most probability, you are trained in technical analysis, various techniques to train your eye and numbers to correlate the stream of data. With an extended application to chart reading and some discipline, it’s not hard to avoid largest mistakes and trade with some results.

What happens is that your carefully brewed technique, a certain day, blows up. You where riding the wave and … splash! All technical analysis let you ride one wave, if well set up, but you are bound to splash as soon as the new wave comes in.

Try to experiment with volatility and then you begin to see how impredictable are the consequences of human behavior. And that is just one dimension. So, if you are so expert to radically change your trading attitude and timely, no need to read further.

I have to say, I’m not in the group. I tend to stick to that particular solution and trust and be deluded. And lose money. I do not really trade with t.a. any more, except a minimal account where I experiment and keep updated the relation from the a.i. model output and t.a. charting. There, I trade using the a.i. daily forecast as a long term preview and I use a 2h bars chart with my beloved modified DMI plus Parabolic and Hi-Lo Activator. In other word, these are momentum and stops. I activate them manually, but following indicators notifications. Shaking all information, it’s not hard to catch good opportunities, always in the direction of predominant trend. If in doubt, stay out. The account is growing.

So, if the use of a robo-advisor is in your future, prepare to radically change your trading and investing behaviour. Sit down, try to imagine all the things that you can do in your spare time and start. Yes, you will have a lot of spare time, embarrassing lots. You need to fill that time and with periodicity, every day, or even every week, maybe every 4 hours? (it will depend on the advisory you will adopt, there are many around, they are popping out massively), you will just peep, take note and check and take few, very few triggering decisions. Than, fast back to your gardening, to your fitness training, to your passion with motors, to reading as there is no tomorrow. In my spare time, I develop the spxbot a.i. engine and this website.

Just a final note: anytime I tried to use t.a. indicators (and I tried many) inside the model, the result were disastrous. The one dimensional constraint that they introduce conflicts with network correlation ability. In effect, I’ve earned from my really first experiments in neural networks modelling with BrainMaker down in the late ’80s, neural networks work good with the data as raw as possible. Any transformation introduces a field of possible wrong solutions and divergencies proliferate. The neural networks do not need to be perfect, they need to see just a little bit better than you and to discriminate using details that you cannot even imagine exist. That’s not perfection, that’s sharpness.

Keep in touch.

 

 

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Posted by Luca in a.i., free, model insights, psychology, selected primer, 0 comments

Psychological consequences of a.i. advisory

If you are a happy trader, you can avoid reading this post. You have your instruments and techniques and take home your living. You are in the 5%.

This post is written for the other 95%. Yes, 95% of traders go broke, in the first 12-18 months of activity. The market is merciless with the fool and his money. Being in large company does not help.

It’s not easy to manage a losing position. Taking position requires a lot of opinions and more your position is on the loss side, more opinions are required, in conflict with the original ones. It soon becomes a mess. The psychological stress then goes wild and compromises not only your account, but also your relationships and your social attitudes.

Many famous book writing traders say that you must plan your trading activity and strictly stick to the plan. This undoubtedly reduces errors, but requires a very rational attitude that not everyone has. Usually, a plan is related to technical analysis (t.a.) indicators that nowadays are largely insufficient to guarantee you from errors. Some are better than others, but market is ever changing and the analysis of a single price line on a single time frame is unable to catch the full complexity of what’s going on. Whenever you back test a t.a. system, you are enclosing in such a number of constraints that soon the system will go broke. Maybe some exception is running out there.

Financial markets are complex, being the sum of a huge number of actors. What sorts out is that market is moved by anticipation of future events, through counter opinions and this phenomena globally unfolds in trends. And you see the trends follow one another. Where there is repetition, often you have patterns in action and pattern are generated by interacting frequencies. As a trader, in front of charts, you soon develop the ability to recognize repetitive graphic patterns and maybe you also have some tools that helps you classify the patterns. Charts are fantastic for a fast global opinion and worth nothing for suggesting the correct intervention. The chart is just a slice in the ham of the market: for as good as it is, you are missing the most.

Now, suppose that you have near a good relaxed trader, one in the 5%, and you do not understand very well how he acts, but you see him opening and closing positions, earning money and reducing losses to ridiculous phisiological amounts. You will just follow his steps, soon stepping aside of you opinions, recovering self esteem, reducing stress. It is now much easier to manage losing positions: sometimes hedging, sometimes holding, sometimes taking the (small) loss.

I have begun to build the robo-advisor long before the word was even coined, in early ’90 with the first experiments and in early 2013 with the actual running model. The model is pure brute force pattern recognition and it is under evaluation, by my subscribers and me, no back testing of any sort, since two full years and it is acting nicely. It is a much better trader than I am, so I seat behind and peep. I see it may occasionally be blind or wrong, sometimes late and sometimes early, but, you know, nothing is perfect in this world. It recovers very fast, it is adaptive, it is unbiased, it is responsive and a bit conservative. It keeps you on the sunny side of the road. Stress is over. I see to the charts and it’s easy to recognize the opportunities, manage the positions and trigger the orders. Since long without a name, I now call my robo-advisor r.Vergeel.

PS. a kind reader has made me note that, out there, the number of websites offering a.i. advisory is exploded: I just want you to be aware about many very superficial analysis. Please, make your due homework and consider that single data line analysis is available through well known software and largely insufficient to represent the complexity of the market.

 

 

 

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Posted by Luca in a.i., free, psychology, selected primer, 1 comment

The Lazy Investor and A.I.

 

Artificial intelligence is for lazy investors and this for two orders of reasons: it reduces the frequency of trading actions and it relieves you from the necessity of having an opinion.

Any of our action requires an opinion and, in trading, our opinions are, usually, like TNT in the hands of a chimp. It’s a big problem. A lot of opinions to have, on gold, on oil, on the stocks, on the banks, on EVERYTHING!! A Correct Opinion!

I Must Have A Correct Opinion On EVERYTHING!
Otherwise I Will Lose Money!

In fact, it ends up that we lose money, confidence, respect, with rising tensions and crisis of any kind around, and still we  have a very confused opinion on something, ignoring all the rest. Our frequency of trading rises to syncopated and the crash is near.

Now, what A.I. provides is the possibility to setup an environment that classifies data autonomously, large bunches of data without human intervention. You can say that it “learns”, that it “recognises”, that it “sees”. Sometimes, these pieces of code do something that seems magic, as the possibility of reading and forecasting the bars of the S&P 500 into the future.

spxbot.com does this. Far from being perfect, I manage the art of being approximately correct. Neural networks does a reverse reasoning: they find the result as the less improbable value from the data it has been fed with. So, if you can manage a nicely huge amount of data and you can setup the code environment to accomplish the analysis and you have some years to spend on research, I guarantee that you may get some very interesting results. Or, you may subscribe to spxbot!

The brain has passed more than four years of development and it is now nicely working since a while. Signals have a validation sequence, then acting is suggested. Always, it is suggested the day before, to act on next day market. I record market opening as the execution price, just for having a fixed schema. You may act as you prefer, following your trading habits and indicators and even timeframes.

I consider our portfolio having two components: a part dedicated to long term investments and a part for playing trading. Signals from the a.i. indicators should cover both. I say should, because the “brain” is running since less than two years, so it’s behaviour in a falling market is still to be seen. Long Term speaking, the model is still long at the moment.

Since it’s inception, dating back to 02/12/2016, the DTS has taken 12 closed positions, 9 positive and three negative. The three negative position where closed at -0.28%, -0.84% and -0.04%. The global performance of these twelve positions amounts to +34.52%, compared to the SPX +30.80%, during the same period.

 

 

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Posted by Luca in a.i., free, psychology, selected primer, 0 comments

Artificial Intelligence is different

Almost one month ago, this daily forecast was correctly warning of the incoming A-B-C wave. Does your tools do something even similar?

Trading is one of the easiest activities around: few seconds and you are in position, few seconds and you are out of your position. Making it profitable is a totally different discourse. Libraries are plenty of technical and fundamental analysis books and the internet is plenty of websites that offer amazing returns. All of them (except some you can count on one hand’s fingers) do the same one dimensional analysis, based on the tape, the fluctuating price of the chosen instrument. The variety of tools available is confusing, but basically they all work on moving averages and momentum, sometimes volatility. So, you have, basically, one dimensional analysis based on momentum. And you lose money.

Two very common profitable trading techniques are insider trading and front running. Both are illegal, and you must be inside the financial business to be able to put them in practice. And if you are not, are you aimed to be stripped? Probably, yes.

Today, artificial intelligence offers an edge for common investors and traders: opposite to the plethora of tech analysis software, it makes a totally different analysis, it needs years to be developed proficiently, it sees things that the human eyes cannot see.

Here at spxbot, I have taken this totally different approach: the model crunches long term data from dozens of different inputs, and when I say dozens I really mean an approach that is impossible for a human to even imagine. The daily model, that forecasts the daily time frame, has 87 basic inputs, at the moment, that cover almost every aspects of the financial markets: stocks exchanges, commodities, rates, bonds, metals, currencies. The world spins and the data gets in, then the data is prepared for the model, trained, tested, verified… well, it’s a long process, but computers are fast and after years of development the code is well fitted. After data preprocessing, we are talking of a “brain” with millions of neurons at work.

What sorts out is stunning, something that makes momentum trading appear as old as a sumerian cuneiform clay tablet. Artificial Intelligence is able to recognize real patterns inside the market hidden (and evident) disorder and give back an unbiased, unemotional reading of the future events. Believe it or not, A.I. can snoop incoming events, in advance. The spxbot model is designed to be adaptive and responsive, and built to accomplish its tasks without any human opinion intervention.

 

 

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Posted by Luca in a.i., free, model insights, psychology, selected primer, 0 comments

Artificial Intelligence core explained

It’s not my aim to explain how Artificial Intelligence works and I never tried to, just sometimes I’ve discussed the media approach on the topic.

I’ve seen this video and it explains quite well how the core of this technology works. We are speaking about back-propagation neural network, the pattern recognition engine that works at the core of r.Virgeel and that makes the magic.

 

 

My first experiments with neural networks were back in the early 90s using Brainmaker. It was not 4 minutes, but in maybe half an our you could have a quite complex network running. Then training time was hours. In 2013 it took me three years to build the spxbot.com model and it’s under continuous development. Large part of the work really stands in maintaining the data base, formed by tables that have hundreds of fields and thousands of records that must be aligned and updated, always. Without exception. Now the network size has reached the remarkable dimension of a maximum over twenty millions of neurons. It is not the positronic brain, yet. It is just a single complex table that offers the possibility to correlate a large number of inputs and some experimental training ideas for the output side.

 

 

Posted by Luca in a.i., free, model insights, selected primer, 0 comments

The Dark Side of the Spreadsheet

I have read the following https://www.technologyreview.com/s/604087/the-dark-secret-at-the-heart-of-ai/ and, again, I thought about the misinterpretation that Artificial Intelligence is going through.

Do your remember Visicalc? Probably not. Visicalc was the first spreadsheet, 20 rows by 5 column (!) by Dan Bricklin with Bob Frankston. It was 1978. The Spreadsheet! The tools that makes the world go around… You have a world before 1978 and a world after 1978. And the world after 1978 has transposed in the spreadsheet programs (now thousands of rows by thousands of columns, and in the cloud!) what they were used to do by hand.

Neural networks (the logical and computational engines of AI systems) are not so different from a spreadsheet. In effect, they are spreadsheets! And as spreadsheets, they get in raw data to output a result. Simply, neural networks contains the data and a relational tool that correlates the data, and this engine (the dark box) apply a reverse logic. Visical and all its children and nephews apply algebra to raw data and calculate the result. The neural networks do not calculate the exact result, they calculate the less improbable result, in the range of the previously given results. The two, often, coincide. It is, anyway, a statistic tool.

The logic of “less improbable” has demonstrated to be very effective in solving very complex problems, like image analysis, categorization of large amount of data, correlation of many different inputs. Neural networks are a powerful diagnostic tool: given symptoms, a range of possible deseases is restricted; or think to recognizing elements in an image, here they do real the magic: the neural networks can see. They can recognize fingerprints, faces, animals …

In the case of trading, the neural networks can provide an unbiased unique reading of the market.

 

 

Posted by Luca in a.i., free, selected primer, 0 comments

Performance chart update

I know that every new reader of the blog, and older too, has one and just one question to ask: what about performance? Show us tables, comparisons, benchmarks, charts!

I tried to explain many times that working with Artificial Intelligence shifts the approach, opens a completely new way of thinking to trading and/or investing and makes very complex to prepare ex-post (made on past data) performance: more than complex, it is about meaningless.  I prefer to measure performance ex-ante (or in real time) and collect data about the forecasts, as they unfold.

 

 

The chart shows the real (in blue) and forecasted (in pink) close for latest 248 trading days. You may note that around mid chart, something happens and the forecast is then less volatile and more fitted to real data. It was late summer and I made some crucial improvement to the model, that is under continuous development. The result was a better “vision”, sharper and more reactive to market mutable conditions. Then, during late fall and early winter, the model has been completely revised since roots and this is reflected into an even better matching of real and forecasted data.

 

 

 

Posted by Luca in free, model insights, performance, selected primer, 0 comments

Trading opinions

Every trader and investor has her/his own framework of opinions that pilot the triggers. It is a mix of experience, knowledge and emotions. As your decisions are worth a gain, you have an euphorical sensation that you are mastering the forces that drive the market, but on the other side if your decisions take you on the losing side, you are bound toward depressions and your trading decisions gets worser and worser.

Every trader or investor has passed through these two extremes of the maniac-depressive syndrome and it is crucially importante to learn to manage its effects.

First, never blame someone else for your faults. Try to recognize your errors and learn to manage your money with realistic expectations. We need to study, not just install a charting software. But there is always a weak point in the process and it is our opinions. Opinions are strictly tied with sentiments and none of us is able to separate the actual objective facts from our perception of them, and this is inevitable.

As traders or investors, we need  tools that help us stay away from emotions and from opinions. It may seem strange, but the less opinions you have, the better trading decisions you take. I have learned it developing the artificial intelligence model that powers the forecasts: you do not need to have opinions to make good trading decisions – more, it’s better you do not have opinions at all. No opinions, no stress. No stress, better trading decisions.

Technical analysis is based on opinions, Elliott’s wave theory is based on opinions, Gann’s theory is based on opinions, even fundamental analysis is based on opinions: all these instruments takes your emotions out of control, sooner or later.

Technical analysis, in its various forms, can be very useful: it may provide you with valuable information and can trigger signals in quite an objective way, but only if you use it inside a wider framework that provides you with a deeper reading of the market. Otherwise, it just will take your emotional side out of control.

Having a tool that shows how the market will act in near future is a powerful opinion deleter. No tool is perfect, of course, but if you trade with an unbiased vision of the future, your decisions are free from emotions and your rational expectation are stress free. This is the real and objective power that rises from artificial intelligence applied to trading or investing.

 

Posted by Luca in a.i., educational, free, selected primer, 2 comments

New attitude for new market

It is almost one year that the spxbot.com site is on and three and a half years since I begun developing the model. Well, many previous experiences have built the necessary skills, but this is the timing.  No, it’s not time to draw conclusions, the work is still going on – will it ever last? –  as I’m now developing a new weekly model, pretty different from the one that is active at the moment, so to have not one, but two readings  and a better vision of the market.

Snooping around I see a lot of bearish attitude and I remember that about four years ago I was very bearish and the market was continuously rising. My incapacity to be well tuned was obvious. The results of the model did surprise me: I have to be sincere, I wouldn’t have bet a dime on its success – market is unpredictable is the mantra we have grown with and it is difficult to reset the way we think.

Technical analysis is almost unuseful, otherwise it would be plenty of millionaires around. Maybe you know, 95% of market private traders lose the capital and the shirt in 12/18 months and they usually trust technical analysis tools. I’ve been subscribed to “T. A. of Stocks and Commodities” for years and it gives you a lot of ideas and strength and good attitude, but then I realized that digital technical analysis is about half a century old and it must have been outmoded. Really do you think that with a line of data and a bunch of indicators you can get rich?

We need instruments to manage market noise and dig inside complex ever changing relations, as society itself is deeply changing, now faster than ever. We need an indipendent view on the market, abstract and unbiased, opposite of the continuously manipulated  information we are subject.

PS: Years ago, I used to think that market is where opinions are transformed in profit (or more often, in losses). Now I do not let my opinions hinder my investments, as the model is so much smarter than me.

 

Posted by Luca in a.i., educational, free, selected primer, 1 comment

Responsive and adaptive

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Forecast charts from May 05, 2016

The forecast charts are the output of the Amodel. All the work, all the code, all the information that is produced here it is put in there, in the chart. The model is designed to be adaptive and responsive, so that it adapts to (chaotic) ever changing markets.

Under specific circumstances, let’s say today, it outputs a response pattern that delineates how the market will behave in the future. When the the model is in its optimal “viewing” conditions, the pattern flows, for some time and the wave of the future flows though the present in synchronicity, then sometimes completes and sometimes, after some bars, changes and start develop a different pattern (that may be a totally different view of the market or just an expansion or contraction of something similar to the previous forecasted pattern).

The code that parse the model is in real time: every time it fires, it is totally unaware of what it did yesterday or the day before and on. It looks at the situation right now and produces the opportune output.

Under normal working conditions, the Amodel, as the final part of the wave is performing, stabilizes the output and you have some more bars to get confirmations of the imminent top or bottom.

 

Posted by Luca in a.i., educational, free, model insights, selected primer, 0 comments

The Realm of Imprecision

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Shown in the chart: 1 daily bar forecast comparison with actual close. I get confirm that there is a widespread one day lagging in computations. Need to work on it.

Except bars projection, all other indicators read the realtime status, now. They do not project future values, they just get a reading of the edge.

But bars projection goes further, goes into the future and project latest price into next bars. Something impossible happens: you see the wave coming in. You see it, in advance.

As future bars are calculated by the neural networks, it is impossible to know what really happens. It does not depend on the sequence of experiences you submit to the network, it does not take in account the rumor, the huge amount of rumor that lies inside the market. It works as Pattern Recognition. The model is set up to see and it recognizes.

 

Posted by Luca in a.i., free, psychology, selected primer, 0 comments