FAQ – Cycles-Trader

How does Cycles-Trader’s approach to stock market forecasting differ from traditional methods?

Here are some of the ways in which Cycles-Trader’s approach to stock market forecasting differs from traditional methods:

Cycles-Trader uses neural networks to identify cycles in stock market price movements. This is different from traditional methods, which may rely on technical analysis, fundamental analysis, or a combination of both.
Cycles-Trader’s approach is empirical, meaning that it is based on historical data. Traditional methods may also be empirical, but they may also be based on theoretical models.
Cycles-Trader’s algorithms are probabilistic and non-linear. This means that they do not provide precise predictions, but rather a range of possible outcomes. This differs from some traditional methods, which may aim to provide more deterministic predictions.
Cycles-Trader’s software is designed to be used as a decision assistant tool for traders, not as a replacement for human judgment. Traditional methods may also be used as decision support tools, but some traders may rely on them more heavily than others.

How does Cycles-Trader utilize neural networks to forecast stock market price movements?

Cycles-Trader uses neural networks to identify cycles in stock market price movements and project them to the future. The technology was researched for 15 years and tested on hundreds of stocks, FOREX, commodities and Crypto tickers. The neural networks use probabilistic, non-linear functions, and results are dependent on the starting point of the prediction and the forecasting horizon. The correlation between the price and the projections is verified visually on the timingsolution.com platform.

It is important to note that:

The algorithms do not predict exact price levels.
This is not an algo-trading formula and will not trade for you or provide trading suggestions.
The algorithms are not linear. In rare cases, inversions may occur, meaning the projection goes up while the price goes down.
This is not an AI agent.
Past performance is not always indicative of future results.

While these results have not been scientifically or statistically proven, the consistent results over time and on hundreds of price instruments make this a promising tool to assist stock market traders. You can try the software on any ticker to see how the algorithms have performed in the past.

How does Cycles-Trader verify the accuracy of its stock market forecasts?

Cycles-Trader verifies the accuracy of its stock market forecasts visually. This involves checking the correlation between the price and the Neural-Networks projection lines. It’s important to remember that the software’s development platform, timingsolution.com, is designed for visual analysis of market cycles and timing.

Cycles-Trader acknowledges that its results are not “scientifically proven” or “statistically proven”. The software doesn’t use traditional statistical methods to validate its forecasts. Instead, it argues that “consistent results over time on hundreds of price instruments and the improvement of the algorithms and their results over time” offer a good basis for its reliability.

Additionally, Cycles-Trader encourages users to “try before buy” to see how the algorithms have performed in the past on their chosen ticker. This allows potential users to assess the software’s accuracy for themselves.

What types of financial instruments does Cycles-Trader analyses?

Cycles-Trader analyses stocks, FOREX, commodities, and Crypto tickers. The software was researched and tested on hundreds of these financial instruments.

What are the key limitations of Cycles-Trader’s forecasting methodology?

Here are some key limitations of Cycles-Trader’s forecasting methodology:

Reliance on visual correlation: Cycles-Trader verifies the accuracy of its forecasts by visually checking the correlation between price movements and the neural network’s projection lines. This subjective method lacks the rigor of statistical validation, making it difficult to objectively assess the accuracy and reliability of the forecasts.
Lack of statistical proof: The sources explicitly state that Cycles-Trader’s results are not “scientifically proven” or “statistically proven”. This means the software doesn’t rely on established statistical methods to validate its forecasts, which might raise concerns about its robustness and reliability compared to other forecasting methods that use statistical verification.
Probabilistic and non-linear nature of neural networks: Cycles-Trader acknowledges that its neural networks are probabilistic and non-linear, meaning they provide a range of possible outcomes rather than precise predictions. While this approach may be suitable for identifying potential price cycles, it doesn’t offer definitive price targets, which may be a limitation for traders seeking precise entry and exit points.
Potential for rare inversions: Cycles-Trader states that in rare cases, inversions might occur where the price moves in the opposite direction of the projection. This unpredictability adds an element of risk, as the software’s projections may not always align with actual price movements.
Dependence on historical data: As an empirical approach, Cycles-Trader’s methodology relies heavily on historical data. While past data can offer insights into potential future cycles, it’s not always a reliable predictor of future market behavior, especially in unprecedented situations or black swan events.
Inability to predict price levels: The sources explicitly state that Cycles-Trader’s algorithms do not predict specific price levels. This limitation means the software might not be suitable for traders who require precise price targets for their trading strategies.

What specific limitations are acknowledged by Cycles-Trader regarding the accuracy of its stock market forecasts?

Here are the specific limitations acknowledged by Cycles-Trader regarding the accuracy of its stock market forecasts:

Lack of Scientific and Statistical Proof: Cycles-Trader clearly states that its results haven’t been “scientifically proven” or “statistically proven”. The software relies on visual correlation for verification, rather than rigorous statistical validation methods.
No Guarantee of Future Predictive Accuracy: Cycles-Trader acknowledges that past results are not always indicative of future performance.
Potential for Inversions: While rare, Cycles-Trader acknowledges that its projections might be inverted, meaning the projected price direction might contradict actual price movements.
No Price Level Predictions: Cycles-Trader’s algorithms are designed to identify cyclical patterns and trends, not to predict specific price levels. The software won’t pinpoint exact prices for potential trades.

What specific aspects of the algorithms used by Cycles-Trader have been improved over time?

While the sources mention that the algorithms used by Cycles-Trader have been improved over time, they do not provide specific details about what aspects of the algorithms have been enhanced. The sources focus on the general principles and limitations of the forecasting methodology, emphasizing the use of neural networks, empirical research, and visual correlation for verification.

How long has Cycles-Trader been researched and tested?

Cycles-Trader’s underlying technology has been researched for 15 years. The research involved using neural networks to identify and project cycles in stock market price movements. This research was empirical, meaning it was tested on data from hundreds of financial instruments, including stocks, FOREX, commodities, and cryptocurrencies.

What specific types of financial instruments have Cycles-Trader algorithms been tested on?

Cycles-Trader algorithms have been tested on stocks, FOREX, commodities, and Crypto tickers. The research, which spanned 15 years, was conducted on hundreds of these financial instruments.

How is the Cycles-Trader software intended to assist stock market traders?

Here’s how the Cycles-Trader software is intended to assist stock market traders:

Cycles-Trader is designed as a decision assistant tool for traders, not a replacement for human judgement. It aims to provide traders with insights into potential market cycles and trends to support their trading decisions.
The software identifies and projects potential price cycles in financial markets. It uses neural networks to analyse historical price data and identify recurring patterns and cycles. This information can help traders anticipate potential market turning points and adjust their trading strategies accordingly.
Cycles-Trader offers a visual representation of potential price cycles. By visually comparing the projected cycles with actual price movements, traders can assess the software’s accuracy and incorporate the insights into their analysis.
The software covers a wide range of financial instruments. Cycles-Trader has been tested on hundreds of stocks, FOREX, commodities, and cryptocurrencies, making it a potentially versatile tool for traders involved in various financial markets.
Traders can evaluate the software’s performance before committing to it. The “try before buy” option allows users to test Cycles-Trader on their chosen tickers and see how the algorithms have performed historically. This feature enables traders to assess the software’s suitability for their trading style and risk tolerance.

It’s important to remember that Cycles-Trader acknowledges its limitations. The software doesn’t predict specific price levels and relies on visual correlation for verification, without relying on rigorous statistical validation. Additionally, the probabilistic nature of its algorithms means it provides a range of possible outcomes rather than definitive predictions. Therefore, traders should use Cycles-Trader as a supplementary tool alongside their own analysis and risk management strategies.

How does Cycles-Trader’s reliance on visual verification of its projections compare to other methods of evaluating forecasting accuracy?

While the sources describe Cycles-Trader’s use of visual verification for evaluating the accuracy of its projections, they do not explicitly compare this method to other approaches for evaluating forecasting accuracy.

Here’s a summary of what the sources do say about Cycles-Trader’s approach to evaluating its accuracy:

Visual Verification: Cycles-Trader primarily relies on visual verification to assess the accuracy of its forecasts. This method involves visually comparing the correlation between the price of a financial instrument and the projection lines generated by its neural networks on the timingsolution.com platform.
Emphasis on Consistent Results: The sources emphasize that Cycles-Trader’s methodology has produced consistent results across hundreds of financial instruments over time. This consistency, rather than rigorous statistical proof, is presented as a key indicator of the software’s reliability.
User Evaluation: Cycles-Trader offers a “try before buy” option, enabling users to evaluate the software’s past performance on their chosen financial instruments. This approach allows potential users to assess the software’s accuracy based on their own visual inspection and judgement.

However, the sources do not discuss or mention any alternative methods of evaluating forecasting accuracy, such as statistical analysis or backtesting. Therefore, a direct comparison of Cycles-Trader’s reliance on visual verification with other methods is not possible based solely on the provided sources.

What specific factors influence the results of Cycles-Trader’s Neural Networks?

Here are the specific factors that influence the results of Cycles-Trader’s Neural Networks, according to the sources:

Starting point in time of the prediction: The results of the Neural Networks depend on the starting point in time of the prediction. This suggests that the software’s accuracy may be influenced by the specific historical data used as the basis for its projections.
Forecasting horizon: The results of the Neural Networks are also influenced by the forecasting horizon, meaning the length of time into the future the prediction is being made for. This implies that the software’s accuracy might vary depending on whether it is used for short-term or long-term forecasting.

How can I experience this method as a trader?

Here are some ways you can experience the Cycles-Trader method as a trader, based on the information provided in the sources:

Utilise the “try before buy” option: Cycles-Trader offers a “try before buy” option for any ticker you choose. This allows you to visualise how the algorithms have performed on your chosen ticker in the past and evaluate their potential usefulness. This hands-on experience can provide insights into the software’s accuracy, the types of cycles it identifies, and how well those cycles align with historical price movements.
Visualise the projections: Cycles-Trader relies on visual correlation for verifying its projections. By visually comparing the projection lines generated by the neural networks with the actual price movements of your chosen financial instrument, you can assess the software’s accuracy for yourself. This visual approach can help you understand how the software identifies potential cycles and turning points in the market.
Focus on the insights, not specific price levels: Remember that Cycles-Trader does not predict specific price levels. Instead of expecting precise price targets, focus on understanding the potential cyclical patterns and trends indicated by the software. Use these insights to support your own analysis and decision-making process.
Combine with your own analysis: Cycles-Trader is designed as a decision assistant tool, not a replacement for your own judgement. Integrate the insights from Cycles-Trader with your own technical analysis, fundamental analysis, and risk management strategies. Consider the software’s projections as one piece of the puzzle, alongside your existing trading methodology.
Experiment with different timeframes: The accuracy of Cycles-Trader’s neural networks can vary depending on the forecasting horizon. Test the software on different timeframes to see how its performance changes over shorter and longer periods. This experimentation can help you determine the timeframes where the software’s projections align best with your trading style and risk tolerance.

Remember, Cycles-Trader acknowledges that its results are not “scientifically proven” or “statistically proven.” The software’s reliance on visual correlation and the probabilistic nature of neural networks mean that it’s crucial to approach its projections with a critical eye. Use the “try before buy” option, experiment with different settings, and combine the insights with your own analysis to form a comprehensive view.

Here is a summary of the Cycles-Trader method in 4 bullet points:

Identifies potential market cycles: Uses neural networks and 15 years of research to identify and project potential price cycles in various financial instruments like stocks, forex, commodities, and cryptocurrencies.
Decision assistant, not a replacement for judgement: Provides insights into potential market trends, but does not predict specific price levels or offer trading suggestions. Traders should combine these insights with their own analysis.
Visual and empirical: Relies on visual correlation to verify projections rather than rigorous statistical validation. Offers a “try before buy” option to see past performance and assess suitability for individual trading styles.
Acknowledges limitations: Results are not scientifically or statistically proven, and past performance doesn’t guarantee future accuracy. Neural networks are probabilistic, meaning potential inversions or deviations from projections can occur.