Turing and the price graphs

Alan Turing was a mathematician who lived in the twentieth century and which is considered the father of theoretical computer science and artificial intelligence. In 1950 he wrote an article in Mind (1) in which he formulated the basics of his test, a criterion for deciding whether a machine is able to think or not. A computer can mimic human thought and deceive a person?

Turing wrote: "I propose to consider the following question. ‘Can machines think?' […] You can describe a new form of the problem in terms of a game which we call the 'imitation game'. It is played in three, a man (A), a woman (B) and an interrogator (C) […]. The interrogator is in a separate room apart from the other two. The goal of the game for the interrogator is to determine which of A and B is the man and who is woman. He only knows them as X and Y, and at the end of the game can say 'X is A and Y is B' or 'X is B and Y is A' ". The interrogator is allowed to put questions to A and B. To avoid that the interrogator could help himself by listening to the tone of voice or handwriting, the responses of A and B should be typewritten. "Now let's make the question: what would happen if a computer take the place of A? The interrogator would be wrong with the same error rate when the test is performed between a man and a woman? These questions replace the original question: the machines are able to think? ".

In the simplified version of this test at least 30% of the testers must be convinced that they had discussed with a person of flesh and bones. According to the latest and more complex versions, the test has not yet been passed, while according to others, he was overtaken by Eugene Goostman, a system developed in Petersburg that looks like a 13 year old Ukrainian (2).

It is interesting to note that the Turing test has also been used in the financial field in a study of the price charts. In 2010 a group of researchers at MIT, published a research based on the verification whether a human being is able to distinguish between a price chart generated with real data and one created with a random function, generated by a computer (3). The test team used a video game in which are shown two sets of side by side prices graphs, in a dynamic manner with the curves updated every second. One of the graph shows a real historical series of price data, while the second graph is constructed in random manner and then artificial.

It is asked to the subject, to press a button to indicate which is for him the real graphic of price data. The subject is immediately informed of the correctness of his choice so he can also generate a certain self-learning. The result is that all subjects of the test are able to distinguish between graphs of real prices of financial assets and those generated randomly. To date, it seems that the computer has not yet been able to confuse those who were tested.

The conclusions of these researchers, push the idea that new information systems should be created to allow, through human-computer interfaces, to systematically exploit the human capacity in this field to be used in financial trading (4). For example, with the right interfaces, it might be possible to translate the eye-hand coordination of experienced video-players to intervene in real time when they recognize predictive models related to price. Operations in trade could then be advantaged by greater speed and accuracy in the identification and execution, compared to a computer algorithm, which currently lacks these innate associative capabilities of the eye and the human brain.

To this we must also add that the younger generation prefer the visual channel in a much more considerable way than the past generations. The information and communication technologies of wider use among boys (video games, cell phones, the web, but also television, used in zapping mode, which anticipates the interactive TV), are exalting in new generations some cognitive abilities (read in particular Sebastiano Bagnara’s article, Professor of Psychology and Cognitive Ergonomics (5) ).

These are not entirely new skills, rather faculties that were available but not fully utilized. Today's teens have grown up in an environment that encouraged some cognitive abilities such as visual thinking and readiness to grasp and deal with the unexpected, responding smoothly and in an appropriate manner, mainly thanks to the increasingly frequent visual stimuli, such as having to deal the multiple situations of a video game.

It is reasonable to think that the future research in the field of the development of trading and technical analysis must take in to account what has emerged from these studies. If we will increase the visual part of the financial information, as indeed it already is doing precisely videogame technology from which you can draw on, we could have more efficiency in terms of results in trading operations.

But for us as readers, how can this be useful? Surely now we know that we have the innate ability which, after an appropriate training, will allow us to draw from the charts a series of information that sometimes even an algorithm of a computer could identify with difficulties. A new edge for the field of technical analysis.

(1) http://www.csee.umbc.edu/courses/471/papers/turing.pdf

(2) http://www.repubblica.it/scienze/2014/06/09/news/test_turing-88475517/

(3) http://web.mit.edu/~alo/www/Papers/arorassrn.pdf

(4) A. W. Lo & J. Hasanhodzic – The Evolution of Technical Analysis – Bloomberg Press – 2010 – Chapter 6;

(5) http://www.treccani.it/scuola/tesine/comunicazione_le_nuove_forme/bagnara.html

Mario Valentino GUFFANTI CFTe – SAMT Vice President – Swiss Italian Chapter – mario.guffanti@samt-org.ch

Disclaimer: the above article is for general information and educational purposes only. It is not intended to be investment advice. Seek a duly licensed professional for investment advice.