The Essence of Backtesting
Backtesting is a strategy used by traders to test their trading strategies using historical data. It allows traders to simulate a trading strategy using past data to see how it would have performed. By analyzing these simulations, traders can identify patterns and conditions that have historically led to successful trades. This process is akin to John’s methodical approach to finding the best routes to the grocery store, where he used his past experiences to plan his future journeys more effectively.
TradeMachine: Your Financial GPS
Much like how GPS technology has revolutionized the way we navigate physical spaces, TradeMachine offers a sophisticated way to explore the financial landscape, leveraging hundreds of millions of opportunities and patterns to uncover those with historical success.
The Magnificent Seven: A Case Study
In this traders can see how TradeMachine facilitates the discovery of trading opportunities. This process underscores the importance of not just understanding historical patterns but also applying this knowledge to craft strategies that can navigate future market conditions effectively.
Leveraging AI for Enhanced Prediction
TradeMachine doesn’t just stop at historical data; it incorporates proprietary artificial intelligence to anticipate and adapt to new market conditions. This AI functionality mirrors John’s evolving understanding of traffic patterns, highlighting the tool’s ability to learn from the past. This innovative approach ensures that traders are equipped with a dynamic and responsive tool that can adjust to the ever-changing financial market.
A Practical Example: Spread the Sell-off Strategy
The video mentions a specific AI strategy known as “Spread the Sell-off,” which focuses on stocks that have experienced a significant drop. The criteria for this strategy are clearly defined, demonstrating Trade Machine’s capability to not only identify specific trading opportunities but also provide alerts to traders, ensuring they are always informed of potential trades. This example serves as a testament to the power of combining historical backtesting with AI to navigate the complexities of the stock market successfully.
Conclusion: Navigating Success with Backtesting
Just as John ultimately found his best routes to the grocery store, traders can navigate the stock market more effectively with the aid of backtesting with TradeMachine. By learning from the past and leveraging technology to anticipate the future, traders can uncover patterns and strategies that lead to success. Whether you’re a seasoned trader or just starting, the journey of backtesting offers a path to more informed and strategic decision-making in the world of stock trading.
Transcription of both videos:
Ophir Gottlieb (00:04):
John got great news. He just bought a new house and he’s in a whole new neighborhood. Now that he’s all moved in, he realized he has to figure out the best way to get to the grocery store. Little did John know his quest for the best grocery route was about to offer him insights into something much bigger, much like the world of stock trading. On his first trip, he figured the fastest way to get there would be a straight line, and he tried that way first. Pretty confident he was all set, but it turns out that way has a 10 mile per hour limit, and even worse, it’s a speed trap. His 10 minute drive turned into a 20 minute problem, so then John tried the next shortest route. After all, you can’t get unlucky twice, right? He went west and then he went north.
(00:46):
This will work, he thought, and that was a really good route. He was all set, but later in the week, he faced a new challenge. A school at the corner meant unpredictable traffic patterns during weekdays, much like unforeseen market fluctuations, and that meant every Monday through Friday, both early in the morning when school started, or in the afternoon when school got out, this was just as bad as the slow speed trap. This route worked once, but when conditions changed, it didn’t work at all. So then John thought he would take the path that went north and then west, and that would be the way he got to the grocery store. He could just take this route every time and not worry about changing conditions or days of the week. Well, that route worked fabulously well on the weekdays, but John soon discovered that on the weekends this route had massive traffic jams.
(01:37):
Months later, anyone watching John could see why he was so happy. He knew which route to take on which day and what time to get to the grocery store. Now he gets to the grocery store easily now that he has a plan, a plan that is based on his experience in the past, his failures and his successes. Ultimately, John reaped his goal when he learned from history. It took a lot of drives to the grocery store for John to figure it out, but now he’s happy. Now he knows exactly how to get to the grocery store and exactly when and exactly which roads not to take. But in reality, there’s many homes and there’s many grocery stores and they’re all over. And it’s not just grocery stores, it’s every other store and his friends’ houses and work. And there are many paths to take, many times on different days in different seasons in different weather, freaking out what route to take on which day and at which time.
(02:28):
Then also understanding which routes not to take and which places not to go on certain days and times. Well, this is all called a back test. John used the past to help him decide what to do in the future to get from his house to the grocery store. Imagine for a moment, these everyday destinations, homes, grocery stores, workplaces as stocks in the market and instead of roads, think of these routes as different ways a stock can move. Just like John’s routes, the stock market has many paths. A stock can be above the 200 day moving or below the 200 day moving average. It can be above the 200 day moving average, but below the 50 day moving average, but above the 10 day moving average all at the same time. Stocks, much like roads, have their ups and downs. They can be on an upward trend or experiencing a downturn affected by seasons, market events and earnings reports.
(03:19):
There are hundreds of millions of different patterns in the stock market for just a single stock, and there are tens of thousands of stocks in the market each moving together and separately at the same time. Just as choosing the wrong road at the wrong time can lead to delays. Choosing the wrong stock at the wrong time can lead to financial setbacks. So how do you navigate this complex network? Enter trade machine, your financial GPS, it’s a backtester designed to identify the most promising patterns. It tests hundreds of millions of different opportunities and patterns and shows you historically which ones did the best. And then we layer on our proprietary artificial intelligence on top of it. Our proprietary AI goes a step further. It doesn’t just learn from historical patterns. It anticipates adapting to new market conditions. A bit like John’s evolving understanding of his neighborhood’s traffic flows, because when it all comes down to it, while option trading can be very complex, all we really want to know is how to get from home to the bank.
(04:28):
Today, we will look at a pattern in the seven largest stocks in the market. They’re called the magnificent seven, and then we’ll take the next logical step. We’ll identify and test an option strategy that has benefited from that pattern. As we do this together, you will inherently see how easy it is to identify these patterns with trade machine on the one hand, and on the other hand, how it’s virtually impossible to do so without trade machine. Let’s learn, have some fun, and create a trading plan to profit, but it’s not as simple as some people would like it to be. You can’t just buy calls and pray. It takes a little bit of finesse, a little bit of ai, but it’s really easy in trade machine. We’ll go to our saved back tests and we’ll load one of our AI strategies called Spread the Sell off, and we’ll load it.
(05:14):
We’ll select the magnificent seven from our built-in portfolios, and here you have it. Over the last three years, the technical conditions have triggered 15 times and 14 of those 15 have been wins, and this one month trade has averaged 37%. And what exactly are these technical conditions? It’s when the stock has been down by at least 10% in the last 30 days, so the stock is incorrection, the stock is below its 200 day moving average, so the stock is in technical failure. And finally, two of our proprietary AI indices must read below zero and you get this trade. You can do this in the NASDAQ 100 and the financial sector as well. This is the power of trade machine prebuilt strategies, prebuilt technical conditions, prebuilt portfolios so you can find your trades fast. And how do you know when this technical condition is triggering? It’s pretty easy. Simply click add alert. It takes you to the alerts tab, click the add alert button, and you’ve now added seven alerts. You’re going to know when this strategy happens and it’s going to come to your phone in a text or your inbox in an email. We discuss our AI below. In fact, immediately upon joining Trade Machine, you’ll get 140 alerts, which include this strategy and three others with AI ready to go. Welcome to Trade Machine, and imagine all the other strategies we’ve already got built in
(06:45):
For all the other portfolios. Thanks for watching.