William jet

William jet (also WJ , the "reactive" Williams 'algorithm , English Larry Williams' Jet Strategy ) is a mathematical and technical algorithm that determines the state of the fundamental position of the price in conjunction with the technical characteristics of the market and global analysis of the extremum of 137 indicators of the banking terminal for previous periods.

Content

Authorship

Some authors attribute the creation of this algorithm to after publishing information about it in the book “ How I made one million dollars last year trading commodities ” ^[1] . Considered ^{[by whom?} ^] that after the success of the Williams% R indicator, the Larry Williams team for seven years developed an algorithm that would ideally fit in trading currencies, stocks, goods, and would also become a unique algorithm in the growing binary options segment. However, other researchers question this fact, claiming that its true developer was , known for developing a stochastic oscillator . However, even the latter recognize the significant work of Larry Williams in interpreting and popularizing this indicator.

The creation of William jet

When using classic indicators in technical analysis, traders are faced with the need to choose the optimal indicator for their calculations and opening positions. In the general case, this is a non-trivial task that spawned a whole branch of technical analysis, and therefore a proposal arose to automate the selection of this parameter. In 1992, Tushar Chande developed the Adaptive Moving Indicator Model (IIDYA), in which the width of the window depends on price volatility , and in 1995 Perry Kaufman proposed his version of a similar technical indicator. The main message of Kaufman was the desire to implement a conservative trend direction, while quickly receiving a signal in a dynamic market and timely closing positions when the market becomes non-directional. But repeated unsuccessful attempts suspended work on the “ideal” indicator, and only in 2004 a group of world-famous programmers and traders led by Larry Williams resumed work on an algorithm that would be unique in its own way and could perform thousands of logarithmic operations every second to find the ideal entry points. In 2008, in the midst of the global crisis, the first tests of a new digital algorithm began, which could not be called an indicator, since in its work in analyzing the market, it immediately used 73 market indicators and 16 advisers. But, due to the tense economic situation in the world, in particular, in the exchange sector, indicator trading lasted a little over a year and a half, after which the Larry Williams group suspended the practical part in order to wait for an improvement in the economic component of the exchange sector. At the same time, some financial institutions during the period of economic decline bought several licenses for the William jet algorithm for a period of 10 years to stabilize their own situation. As stated by Larry Williams himself, giants such as Goldman Sachs , Bank of Amerika , CitiGroup and others, managed to survive the period of the global crisis only thanks to the support of the Williams group and a number of nominal indicators, including William jet.

In mid-2012, the William jet algorithm received a new life and was massively used by the financial giants of the United States, which once again confirmed its ambiguous role for the US stock and banking sectors during the global crisis. But three years were not in vain and the updated William jet in 2012 was already processing 137 different market indicators every second! In the first quarter of 2014, the UKTraders financial institution ( London ) purchased the right to distribute the William jet algorithm in Europe and the CIS. The algorithm was officially named William Jet Strategy and, in accordance with the EU exchange legal legislation, gained the status of “Indicator William Jet”.

Nationalization and Internationalization

The period of nationalization of William jet can be considered the year 2008, when the algorithm first fell into third hands and was put into practice. It can be said with accuracy that it was the crisis time and interaction with such large financial giants as Goldman Sachs , UBS , HSBC , JPMorgan, and others that served as the foundation for the further nationalization of the algorithm in the United States.

Since 2014, the period of internationalization began. First of all, internationalization affected western Europe and continued on its eastward path. Within a year and a half, about 2000-3000 licenses were sold. First of all, small informative and online advertising is associated with the orientation of licensing for the most part of large financial institutions, and secondly, the content of individuals with the indicator.

Today, the William jet indicator is present in the markets of the USA, Europe, CIS, Asia Minor and the Middle East. But since the end of 2015, the UKTraders product internationalization policy has adopted certain changes and the introduction of the indicator in the private sector is increasing. From the point of view of international practice, nationalization and internationalization (the period from 2008-2014) is an indicator of the rapid dynamic growth of both the popularity of the product and its effectiveness.

Trading Strategies

There is no single universally accepted strategy for using the William jet indicator. On the other hand, the techniques for applying the algorithm are numerous and sometimes contradictory. However, researchers agree that the William jet algorithm can be used both as a trend indicator, and as an oscillator, and even as an indicator that indicates global periods of long-term growth.

Depending on the settings, the William jet indicator characterizes the market as a whole - therefore, positions should be opened using the indicative tools of the algorithm; or it evaluates the current state of the market, directly at the moment, as a result of which the opening and closing of positions follows from the internal orientation of the indicator.

In most cases, experts recommend relying entirely on the William jet algorithm and solely on indicator performance. This situation is justified by the use of 137 market indicators at a time, which, in turn, is beyond the power of the human brain, but with which the William jet algorithm perfectly copes.

Link to other indicators

Based on the fact that the William jet indicator simultaneously uses 137 indicators of market assessment, one can observe an ambiguous relationship with most of the known indicators. On the other hand, it is equally possible to declare the dependence of other indicators on William jet. And for the most part this is due to the inability of other indicators to make a market assessment and relevant conclusions, relying on indicators other than their own. And this is one of the many features that distinguish the William jet algorithm from all existing indicators and indicators.

Calculation Method

In his work, Martin Pring recommends the following meanings:

The number of periods to calculate ${\textit {RoC}}\ (x):x_{1}=10,x_{2}=15,x_{3}=20,x_{4}=30.$ ${\ displaystyle {\ textit {RoC}} \ (x): x_ {1} = 10, x_ {2} = 15, x_ {3} = 20, x_ {4} = 30.}$
Lengths of Exponentially Smoothed Moving Averages ${\textit {EMA}}\ ({\textit {avg}}):{\textit {avg}}_{1}=10,{\textit {avg}}_{2}=10,{\textit {avg}}_{3}=10,{\textit {avg}}_{4}=15.$ ${\ displaystyle {\ textit {EMA}} \ ({\ textit {avg}}): {\ textit {avg}} _ {1} = 10, {\ textit {avg}} _ {2} = 10, { \ textit {avg}} _ {3} = 10, {\ textit {avg}} _ {4} = 15.}$
Summing Weighting Factors $(W):W_{1}=1,W_{2}=2,W_{3}=3,W_{4}=4.$ ${\ displaystyle (W): W_ {1} = 1, W_ {2} = 2, W_ {3} = 3, W_ {4} = 4.}$

After substituting these values, the formula takes the form:

{\textit {WJS}}_{t}=1\cdot {\textit {EMA}}_{t,10}(RoC_{i,10})+2\cdot {\textit {EMA}}_{t,10}(RoC_{i,15})+3\cdot {\textit {EMA}}_{t,10}(RoC_{i,20})+4\cdot {\textit {EMA}}_{t,15}(RoC_{i,30}).

{\ displaystyle {\ textit {WJS}} _ {t} = 1 \ cdot {\ textit {EMA}} _ {t, 10} (RoC_ {i, 10}) + 2 \ cdot {\ textit {EMA}} _ {t, 10} (RoC_ {i, 15}) + 3 \ cdot {\ textit {EMA}} _ {t, 10} (RoC_ {i, 20}) + 4 \ cdot {\ textit {EMA}} _ {t, 15} (RoC_ {i, 30}).}

Some analysts recommend weighing the obtained value ^[2] :

{\textit {WWJS}}_{t}={\frac {W_{1}\cdot {\textit {EMA}}_{t,{\textit {avg}}_{1}}(RoC_{i,x_{1}})+W_{2}\cdot {\textit {EMA}}_{t,{\textit {avg}}_{2}}(RoC_{i,x_{2}})+W_{3}\cdot {\textit {EMA}}_{t,{\textit {avg}}_{3}}(RoC_{i,x_{3}})+W_{4}\cdot {\textit {EMA}}_{t,{\textit {avg}}_{4}}(RoC_{i,x_{4}})}{W_{1}+W_{2}+W_{3}+W_{4}}},

{\ displaystyle {\ textit {WWJS}} _ {t} = {\ frac {W_ {1} \ cdot {\ textit {EMA}} _ {t, {\ textit {avg}} _ {1}} (RoC_ {i, x_ {1}}) + W_ {2} \ cdot {\ textit {EMA}} _ {t, {\ textit {avg}} _ {2}} (RoC_ {i, x_ {2}}) + W_ {3} \ cdot {\ textit {EMA}} _ {t, {\ textit {avg}} _ {3}} (RoC_ {i, x_ {3}}) + W_ {4} \ cdot {\ textit {EMA}} _ {t, {\ textit {avg}} _ {4}} (RoC_ {i, x_ {4}})} {W_ {1} + W_ {2} + W_ {3} + W_ {four}}},}

or with initial parameters:

{\textit {WWJS}}_{t}={\frac {1\cdot {\textit {EMA}}_{t,10}(RoC_{i,10})+2\cdot {\textit {EMA}}_{t,10}(RoC_{i,15})+3\cdot {\textit {EMA}}_{t,10}(RoC_{i,20})+4\cdot {\textit {EMA}}_{t,15}(RoC_{i,30})}{1+2+3+4}}.

{\ displaystyle {\ textit {WWJS}} _ {t} = {\ frac {1 \ cdot {\ textit {EMA}} _ {t, 10} (RoC_ {i, 10}) + 2 \ cdot {\ textit {EMA}} _ {t, 10} (RoC_ {i, 15}) + 3 \ cdot {\ textit {EMA}} _ {t, 10} (RoC_ {i, 20}) + 4 \ cdot {\ textit {EMA}} _ {t, 15} (RoC_ {i, 30})} {1 + 2 + 3 + 4}}.}

From the formulas it is seen that the largest weight - 4 is given to the longest value $RoC_{i,30}$ ${\ displaystyle RoC_ {i, 30}}$ smoothed using the slowest: ${\textit {EMA}}_{t,15}$ ${\ displaystyle {\ textit {EMA}} _ {t, 15}}$ .

Number of periods to calculate Lengths of exponentially smoothed moving averages Weighting factors for summation

Notes

↑ Larry R Williams. How I made one million dollars last year trading commodities - Windsor Books, Jun 1, 1979. 130 pages. ISBN 0930233107
↑ Colby Robert. Encyclopedia of technical market indicators. - 2nd ed. - M .: Alpina Business Books, 2004. - 837 p. - ISBN 5-9614-0031-X .

Literature

Larry R Williams. How I made one million dollars last year trading commodities - Windsor Books, Jun 1, 1979. 130 pages. ISBN 0930233107 .
Stephen B. Akelis. Williams percent range (William's% R) // Technical analysis from A to Z. A complete set of trading tools ... from Absolute Width Index to Japanese Candles = Technical Analysis from A to Z: Covers Every Trading Tool ... from the Absolute Breadth Index to the Zig Zag / Per. from English M. Volkova, A. Lebedeva. - M.: Diagram, 1999. - S. 246-247. - 376 p. - ISBN 978-5-902537-13-7 , 5-900082-05-09, GRNTI 06.73, LBC 65.526.
LeBo Ch., Lucas D.V. Computer analysis of futures markets: Per. from English - M.: Publishing House "ALPINA", 1998-304s. ISBN 5-89684-002-0 (Russian) ISBN 1-55623-468-6 (English).
Colby Robert. Encyclopedia of technical market indicators. - 2nd ed. - M .: Alpina Business Books, 2004. - 837 p. - ISBN 5-9614-0031-X .