Tag Archives: simulation

Software

Addaptron Software Releases New Stock Market Software SMT1

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Addaptron Software announced a software release, SMT1 (Stock Market Tools, release 1), a new advanced software system for End-Of-Day (EOD) traders. One of new advantages is all-in-one output forecast signal. This signal (number) is the result of processing data by Artificial Intelligence (AI) Forecast Module. The set of data consists of technical indicators, waves prediction, pattern filter, and cycles extrapolation. Based on Machine learning results, AI decides how to interpret all relevant data and express the conclusion in a single number.

SMT1 is intended for EOD traders with intermediate or advanced knowledge in the Stock Market and computer software. The software consists of four major functionalities: Forecast, Backtest, Simulation, and Tracking. SMT1 is provided with User’s Manual which helps to understand the general structure of the software, connections between functional modules, and how effectively utilize all features.

The software uses EOD historical prices data as input. SMT1 includes a free Downloader that allows downloading EOD historical quotes files of selected symbols (some of most traded leveraged ETFs) from Addaptron Software server for free. Optionally, users can use own input data files. User’s Manual explains how to use own input files.

The main concept of the software is to work (i.e., predict, simulate and optimize trading performance) with the group of well-traded leveraged ETFs to maximize overall return. Each ETF has inverse counterpart and represents different industries that allows finding a potential winner every day. Although the software is suited to a specific niche, users can try to use own group of symbols.

Stock Market traders use different types of sell signal to exit position. Since exit signal cannot be reliable enough, some traders use stop loss and profit target to exit position. Addaptron Software has done numerous computer simulations to learn if adding more exit conditions can improve trading return. The research discovered that a better trading return in the long run can be achieved by using as many as four conditions for exit. This multi-trigger exit concept has been implemented in SMT1 as a new 4-Way Exit Method. This is another SMT1 advantage.

The software also includes an extra feature to record buy-sell transactions, analyze a current position, recommend the action, and measure trading performance. Since AI is able to optimize many settings parameters, the number of user-defined parameters is minimized so that users can save time.

Downloading and installing SMT1 is a very easy process and explained step-by-step on download page . All retail traders are eligible for free fully-functional version during initial 30-day period.

The example of SMT1 user interface: tab-page Simulation (back testing)
The example of SMT1 user interface: tab-page Simulation (back testing)
General, Research, Software

Pre-Release Announcement

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Addaptron Software has been making steady progress with the development of the next generation of high quality software tools for investors/traders. Although there is still a lot of work ahead, Addaptron Software is getting ready to deliver a new software product, SMT-1 (Stock Market Tools, version 1.0). Its first (beta) release is scheduled for October-November 2018.

One of the achievements is all-in-one output forecast signal. This signal is combined from technical indicators, waves, and cycles data by Artificial Intelligence (AI) module. Also based on prediction accuracy, AI decides what time-frame signals to include. There are three types of output: (1) positive numbers for up trending symbols, (2) negative numbers for down trending ones, and (3) zero numbers for uncertain prediction (when AI is unable to provide a reliable prediction result).

In short, SMT-1 has the following benefits:

  • Its comprehensive AI forecast output is combined into a single list of ranked symbols. Such a simple concept enables most investors/traders to use the software easily.
  • Since AI is able to optimize many settings parameters, the number of user-defined parameters is minimized so that users can save time.
  • The software recommends entry/exit prices that allows users just to place a limit buy or limit sell order for the next market day.
  • The software has a back-test simulation functionality that allows users to try different trading strategies.
  • Except a calculated sell signal, the software has an ability to maximize trading profit by optimizing additional sell-trigger parameters.
  • The software includes an extra feature to analyze a current position, recommend the action, track buy-sell transactions, and measure trading performance.
A screenshot of SMT-1 alpha version, main interface
A screenshot of SMT-1 alpha version, main interface

The SMT-1 release will represent a leap forward in usability, functionality, performance and value for Addaptron Software product users. Visit our website addaptron.com at the end of 2018 to download a beta version of SMT-1 and take advantage of this huge upgrade and promotional deal.

Research, Software

Using Parabolic SAR with Neural Network for Predicting

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Parabolic SAR (SAR stands for Stop-And-Reverse) is a trend-following indicator that has been used by many traders for decades. Its major application is in trading systems to define a trailing stop, i.e., to protect profit when a price trend changes. The term “parabolic” appeared to characterize the indicator parabola shape that is due to using an accelerating factor in the formula. SAR is especially effective in a trending market. To make it more effective in a sideways market, it is often used in conjunction with other indicators.

SAR indicator gives a strong signal when a price trend is about to reverse, therefore, this indicator can be used for prediction. To compare the predictive ability of SAR with other indicators, it has been implemented into the technical analysis module of Fundamental-Technical Analyzer FTA-2. SAR calculations have been used to collect statistics based on the forecast simulations for major indexes and ETFs during August-October 2011 period. As a result, SAR’s position was mostly in “top ten” indicators list.

Using Parabolic SAR with Neural Network for Predicting

The research and presented chart are made by Fundamental-Technical Analyzer FTA-2, one of the software modules that enables composing Neural Network forecasts of many indicators with weights accordingly to each indicator’s predictive ability.

Omitting logical rules for accelerating factor and reversal conditions, a recurring core formula for SAR is the following:

SAR (current point) = AF * [EP – SAR (previous point)] + SAR (previous point)

where:
AF – Acceleration Factor (normally starts from 0.02 and increases by 0.02 if each next point reaches a new extreme, saturates until 0.2);
EP – Extreme Point (lowest low or highest high).

To summarize, Parabolic SAR can be enriched by combining it with Neural Network and successfully used for predicting stock market prices. Combing it with Neural Network allows extracting more statistically stable patterns and, therefore, providing a better accuracy in the forecast. As simulations showed, improved results can be achieved if SAR is transformed into more sensitive indicator by subtracting it from close price (it indicates the degree of SAR and price convergence).

General, Research

New Trading Decision Support Systems Group on LinkedIn

New Trading Decision Support Systems group on LinkedInThe new group Trading Decision Support Systems is intended to be a resource for individual/institutional traders/investors and software developers in stock market area to share ideas, initiate and participate discussions, benefit from the collective intelligence, and to expand network. It will be primarily focused on such topics as:

  • Trading EOD and intraday different asset classes: trading tips, strategies, why, how, and results.
  • Trading systems: algorithms, methods, technologies, human factor, and statistics.
  • Software tools to support traders decisions: forecast methods, simulations, back-testing, and optimization.
  • Technical Analysis: indicators and chart patterns.
  • Fundamental Analysis: financial ratios and predictive models.
  • News: analysis and formalization by converting to measurable variables to automate systems with contributing news factor.
  • Numerical methods, data processing, artificial intelligence, and modeling in stock market areas.

Many things remain unchangeable in a trading world – supply-demand price balance, greed-fear driven mistakes, as well as, ability to think, make right decisions, and find the best solutions. When once winning approaches, strategies, or methods failed, many traders are prone to analyze the reasons why it happened. Then they create new approaches and develop new successful systems. If systems are automated, it is easy and fast to test them, collect and analyze back-testing and live statistics, and then make necessary improvements. That is why it is important to implement the best ideas in software applications that can be also used by others.

The computational technologies are changing. Systems empowered by Artificial Intelligence have self-learning abilities that enable them to adapt to market changes. One of the purposes of this group is to bring together the developers of decision support software and traders-users for mutual benefits: the developers get more ideas about their products’ improvements and make a better progress in developing software for traders, the users arise issues relating to their needs and wants. Hopefully everyone will find something useful participating in this group.

You are welcome to join this newly created networking group. Be the first to start a relevant discussion, promote your product or service. Please join Trading Decision Support Systems group on LinkedIn!