Timing tools for every investor

Time Trades is a data service designed to add clear timing forecasts to your existing price analysis.

It can be used in a number of different ways:

• Identify patterns of price behavior, and when it changes
• Find the astrological events with the most influence over price
• View forecasts of price behavior based on machine learning models
• Scan 900+ models quickly to find those with the most forecast activity for the coming days

Most traders already have a method to analyze price.

Time Trades focuses on analyzing time.

Instead of learning complex topics like Gann techniques or Astrology, Time Trades simplifies time forecasts to easy-to-understand probabilities.

Every night, 20+ years of daily price data is analyzed to identify 6 different 'behaviors' (or labels for those of you that understand machine learning). These behaviors are:

• Pivot highs
• Pivot lows
• 2 standard deviation up moves
• 2 standard deviation down moves
• Non-directional pivots
• Non-directional moves

Once these 6 behaviors are identified, 6 separate machine learning models are trained, one for each behavior.

These models, while very performant, will never be perfect:

• They are trained on a maximum of 20 years of price data, so longer cycles driven by slow outer planets will not be picked up.
• Stocks with less price history will miss out on more cycles than stocks with more history.
• The models do not detect inversions. Sometimes the predictions will invert where a given cycle may switch from a pivot low to a pivot high.
• Astrological aspects are based on a daily snapshot at 0:00 UTC each day. Influential aspects may happen prior to markets opening or after markets close.

For these reasons, we surface additional visualizations so that you can use your own neural network (your brain) to analyze the forecast.

These additional visualizations include the Cheat Code, Gann Waves, Short Term Waves and Gann Fans.

Future forecasts can and will change from day to day, just like our own personal outlook for the market changes.

Most of the time these changes are minimal. You won't tend to see wild swings from a pivot high next Tuesday to a pivot low.

When the forecasts do change noticeably compared with the prior day. There's a few reasons for this:

As future forecasts transition into the past, the probabilities will change as the system will fit the forecast to align with actual price behavior. This is normal and expected.

• A new price pivot was identified in the price history. Many timing counts are anchored to price pivots, so when these change or move, the forecast will change.
• The prior days move is a big move up or down and influenced the models predictions.
• A new pivot was detected in the price history which changes the future forecasts.
• We are always researching and testing new ways to improve the predictions. We may have added new data points to the model after proving that it has a positive impact on model performance.

To give you a sense of how much variance to expect, see the section called 'Variance' in the Time Trades User Guide

The predictive model is trained on historical price data, up to the prior trading day, and has created a model that aligns to past prices. Historical forecasts will therefore be a very close match to prices.

It's very important that you do not assume historical model performance will continue into the future!

Think of it this way: traditional programming takes data, and rules written by the programmer to generate answers. Machine learning takes data and answers, and generates rules. These rules are then applied to the future to generated predictions. Training a model is the process of generating rules based on the answers (historical price data).

I have not written any code that says "Saturn is bad" or "Jupiter is good". All the rules generated by the machine learning model are inferred from the actual price behavior

If you use TradingView, you can provide your TradingView username. Within 12 hours we will grant you access to an invite only script.

This script includes the Gann Waves feature and an indicator that we call Cheat Code.

This script is part of your Time Trades subscription or trial, and access will end when your subscription or trial ends.

You're free to trade as you wish, but for best results, we don't recommend trading based on the probability forecasts alone.

We recommend combining the forecast probabilities with your existing price analysis and risk management methods. Time Trades is not a silver bullet. You will still need to have good trading execution and risk management.

To put it another way, don't YOLO out of the money 0 DTE puts because Time Trades says there's a 51% probability of an down day.

In general, we do not offer refunds. You will continue to have access for the duration of your subscription term. If you believe your situation warrants an exception, email support@time-trades.com.

You can save 25% by upgrading to a yearly subscription term. Purchasing a yearly subscription if you already have a monthly will result in two active subscriptions. For this reason, please purchase your yearly subscription as close to the end of the monthly subscription as possible. After purchasing your yearly subscription, you can use the Billing Portal under the User Profile to cancel your monthly subscription. Contact support@time-trades.com with any questions.

Behind the scenes, Time Trades creates and generates a machine learning model for each symbol in the system.

In order for the model to have predictive value, it must have at least 3 years of price history.

In addition, the overnight training process takes many hours and we want it to finish before the market opens.

If you'd like to request a new stock or crypto currency, email support@time-trades.com. Please ensure there's at least 3 years of data for the symbol you're requesting.

We will do our best to accomodate your request

We are constrained by what's available from our data providers. For example we don't have access to index data like SPX, but that can easily be worked around by using SPY.

Our data provider currently supports the following indexes: Most American stocks on the Nasdaq and NYSE, London, Toronto, Toronto Venture, Germany XETRA, Germany Frankfurt, Euronext Paris, Euronext Amsterdam, Euronext Lisbon, Euronext Brussels, India BSE and Brazil São Paulo.