🔍 Understanding Crypto & Equities Correlation [Market Analysis]
There have been some interesting developments in the crypto market recently. As long-time readers probably know, we write market analysis posts every once in a while. This time around, we decided to focus on a topic that we haven't seen well covered in the mainstream media: the nature of BTC's correlation to equities.
Not too long ago, in 2018-2019, Bitcoin was virtually uncorrelated with equities. Its correlation oscillated between -0.2 and 0.3, frequently transitioning between positive and negative zones. This lack of correlation was a key factor in Bitcoin's appeal as a diversification tool. The primary investors in Bitcoin at that time were early adopters and retail investors, not the institutional investors who typically invest in the S&P 500. This explains the absence of correlation during these early years.
During the initial phase of the pandemic, there was a flight to liquidity, with investors selling off assets across the board to raise cash. This behavior caused simultaneous declines in both Bitcoin and equities, which were quite predictable. This also led the systems, which now evolved into the Algocrat AI portfolio, to have several very good months in a row. Basically, every time there is a 'fight or flight' event on the markets, there are good trending movements to capture significant profits.
However, even a few months after that, the correlation remained positive. Initially, this likely resulted from massive monetary stimulus measures by central banks around the world. Both the stock market and Bitcoin benefited from these measures, leading to rising prices and increased correlation. Subsequently, the main factors in play have been the trend of institutional investment, integrating Bitcoin more closely with traditional financial markets, and broader economic factors, such as inflation expectations, interest rate changes, and fiscal policies, impacting both equities and cryptocurrencies.
Interestingly, we saw an upward spike in correlation after the BTC ETF approval in January of this year. Given current macroeconomic trends, continued institutional adoption, and the market integration of cryptocurrencies, it's plausible that we will see a higher correlation between these assets in the coming months and years.
What does this mean for the Algocrat AI portfolio? Since it is designed to work well with Bitcoin during periods of both high and low correlation with equities, it doesn't mean anything specific. We have considered various correlation metrics when developing the systems comprising the portfolio and haven't found anything that can increase their edge.
Still, the Algocrat portfolio scored good gains on our public Algocrat AI account during recent months, and recent Binance results are even better than that (and they are, on average, better since Binance is still the biggest crypto exchange out there). Algocrat AI is designed specifically to take advantage of crypto market trends "on autopilot," regardless of the market context.
Best regards,
The Algocrat AI Team
There have been some interesting developments in the crypto market recently. As long-time readers probably know, we write market analysis posts every once in a while. This time around, we decided to focus on a topic that we haven't seen well covered in the mainstream media: the nature of BTC's correlation to equities.
Not too long ago, in 2018-2019, Bitcoin was virtually uncorrelated with equities. Its correlation oscillated between -0.2 and 0.3, frequently transitioning between positive and negative zones. This lack of correlation was a key factor in Bitcoin's appeal as a diversification tool. The primary investors in Bitcoin at that time were early adopters and retail investors, not the institutional investors who typically invest in the S&P 500. This explains the absence of correlation during these early years.
During the initial phase of the pandemic, there was a flight to liquidity, with investors selling off assets across the board to raise cash. This behavior caused simultaneous declines in both Bitcoin and equities, which were quite predictable. This also led the systems, which now evolved into the Algocrat AI portfolio, to have several very good months in a row. Basically, every time there is a 'fight or flight' event on the markets, there are good trending movements to capture significant profits.
However, even a few months after that, the correlation remained positive. Initially, this likely resulted from massive monetary stimulus measures by central banks around the world. Both the stock market and Bitcoin benefited from these measures, leading to rising prices and increased correlation. Subsequently, the main factors in play have been the trend of institutional investment, integrating Bitcoin more closely with traditional financial markets, and broader economic factors, such as inflation expectations, interest rate changes, and fiscal policies, impacting both equities and cryptocurrencies.
Interestingly, we saw an upward spike in correlation after the BTC ETF approval in January of this year. Given current macroeconomic trends, continued institutional adoption, and the market integration of cryptocurrencies, it's plausible that we will see a higher correlation between these assets in the coming months and years.
What does this mean for the Algocrat AI portfolio? Since it is designed to work well with Bitcoin during periods of both high and low correlation with equities, it doesn't mean anything specific. We have considered various correlation metrics when developing the systems comprising the portfolio and haven't found anything that can increase their edge.
Still, the Algocrat portfolio scored good gains on our public Algocrat AI account during recent months, and recent Binance results are even better than that (and they are, on average, better since Binance is still the biggest crypto exchange out there). Algocrat AI is designed specifically to take advantage of crypto market trends "on autopilot," regardless of the market context.
Best regards,
The Algocrat AI Team
📈 June 2024 [Monthly Performance]
Hello everyone,
As we close out another month, we're eager to share the latest performance results from Algocrat AI.
June was solid, with our high-risk setting achieving an account growth of 6.41%.
On the flip side, we also experienced a maximum drawdown of 11.01%.
As always, for a comprehensive overview of our performance, you can visit our verified MyFxBook track record:
🔗 Click Here To Access Our MyFxBook Track Record
Best regards,
The Algocrat AI Team
Hello everyone,
As we close out another month, we're eager to share the latest performance results from Algocrat AI.
June was solid, with our high-risk setting achieving an account growth of 6.41%.
On the flip side, we also experienced a maximum drawdown of 11.01%.
As always, for a comprehensive overview of our performance, you can visit our verified MyFxBook track record:
🔗 Click Here To Access Our MyFxBook Track Record
Best regards,
The Algocrat AI Team
🚀 How We Made 37.8% In 5 Days [Performance Analysis]
Recently, Algocrat AI's proprietary trading system did what it does best: it caught a large trend in the crypto market, outperforming most investors who primarily hold BTC and ETH, achieving an account growth of 37.8% in just 5 days.
Let’s take a closer look at what happened:
First, a quick note: we will be discussing the Algocrat AI portfolio results on this public Pepperstone account. Due to the varying crypto quotes, execution, and expenses across different brokers and exchanges, results will differ between platforms. However, long-term performance and overall trends remain consistent. Accounts on Binance and other Forex brokers we work with have also seen substantial profits recently. Those using the same broker (Pepperstone) achieved results almost identical to ours.
So, what happened? In 2014, hackers breached the now-famous and defunct Mt. Gox cryptocurrency exchange, which at the time handled about 70% of the total trading volume. They stole 850,000 bitcoins, which the exchange has been trying to recover ever since.
Mt. Gox recovered 141,868 bitcoins, which it will distribute among its clients. The total value of the returning BTC is $7.7 billion. For comparison, inflows into Bitcoin ETFs, one of the main drivers of the crypto bull market, amounted to $14.6 billion.
Market participants fear that the exchange's clients will sell the cryptocurrency, as Bitcoin has risen by 12,100% since then. Combined with the large volume of funds being returned, this could create strong downward pressure on the price.
Consequently, BTC fell by about 7% over the last week, dragging the entire market down with it. Almost all altcoins, including Ethereum, experienced even steeper declines, as is typical in such scenarios.
Was this unexpected? Not really. It was known in advance that Mt. Gox would start repaying its customers. So why the market reaction? Typically, such volatility arises from unexpected news.
The crypto market is still immature and, therefore, susceptible to manipulation. Large market participants often use such events to create volatility, allowing them to capitalize on the panic. By triggering a sell-off, they can profit from the downward movements. Additionally, the start of payments was likely to push the market even further down. This is precisely what has happened over the last few days and weeks.
By looking at the charts, one can understand that some large market participants likely positioned themselves ahead of this movement. This pattern of manipulation and exploitation is something Algocrat AI anticipated and strategically navigated, thereby outperforming the broader market. And while we are not whales by any metric, we can align our positions with some of these whales, capturing robust profits as a result.
We hope this was interesting and insightful.
Best regards,
The Algocrat AI Team
PS - 57% of all Algocrat AI's capital availability has already been taken. If you'd like to secure your spot as an Algocrat AI client before it's too late, click here and apply right now.
Recently, Algocrat AI's proprietary trading system did what it does best: it caught a large trend in the crypto market, outperforming most investors who primarily hold BTC and ETH, achieving an account growth of 37.8% in just 5 days.
Let’s take a closer look at what happened:
First, a quick note: we will be discussing the Algocrat AI portfolio results on this public Pepperstone account. Due to the varying crypto quotes, execution, and expenses across different brokers and exchanges, results will differ between platforms. However, long-term performance and overall trends remain consistent. Accounts on Binance and other Forex brokers we work with have also seen substantial profits recently. Those using the same broker (Pepperstone) achieved results almost identical to ours.
So, what happened? In 2014, hackers breached the now-famous and defunct Mt. Gox cryptocurrency exchange, which at the time handled about 70% of the total trading volume. They stole 850,000 bitcoins, which the exchange has been trying to recover ever since.
Mt. Gox recovered 141,868 bitcoins, which it will distribute among its clients. The total value of the returning BTC is $7.7 billion. For comparison, inflows into Bitcoin ETFs, one of the main drivers of the crypto bull market, amounted to $14.6 billion.
Market participants fear that the exchange's clients will sell the cryptocurrency, as Bitcoin has risen by 12,100% since then. Combined with the large volume of funds being returned, this could create strong downward pressure on the price.
Consequently, BTC fell by about 7% over the last week, dragging the entire market down with it. Almost all altcoins, including Ethereum, experienced even steeper declines, as is typical in such scenarios.
Was this unexpected? Not really. It was known in advance that Mt. Gox would start repaying its customers. So why the market reaction? Typically, such volatility arises from unexpected news.
The crypto market is still immature and, therefore, susceptible to manipulation. Large market participants often use such events to create volatility, allowing them to capitalize on the panic. By triggering a sell-off, they can profit from the downward movements. Additionally, the start of payments was likely to push the market even further down. This is precisely what has happened over the last few days and weeks.
By looking at the charts, one can understand that some large market participants likely positioned themselves ahead of this movement. This pattern of manipulation and exploitation is something Algocrat AI anticipated and strategically navigated, thereby outperforming the broader market. And while we are not whales by any metric, we can align our positions with some of these whales, capturing robust profits as a result.
We hope this was interesting and insightful.
Best regards,
The Algocrat AI Team
PS - 57% of all Algocrat AI's capital availability has already been taken. If you'd like to secure your spot as an Algocrat AI client before it's too late, click here and apply right now.
💰When To Join Algocrat AI For Maximum Returns [Entry Point Strategies Analysis]
After our last post, we received many questions about the best point of entry. After all, Algocrat AI just reached an all-time high, and it's usually not the best time to start investing, right? Well, as usual, financial reality is a little more complicated than that.
There are two equally valid ways of thinking to tackle this question. First, if there was a straightforward way to maximize profits, such as through more precise market timing or refraining from trading after reaching an all-time high, Algocrat AI would have already adopted it. This is why its equity curve appears random to an outside observer. In other words, it's nearly impossible to predict whether there will be a drawdown or another really good month after reaching an all-time high.
Secondly, since Algocrat AI's performance is not really predictable in the short run, it's very similar to the age-old question of market timing: When is it best to enter the S&P 500? Market theorists have studied this question extensively for decades and have concluded that it is best summarized by a well-known Chinese proverb: "The best time to plant a tree was 20 years ago. The second-best time is now". On average, it’s usually more profitable to invest everything at once.
That said, just like with stocks, a drawdown sometimes occurs after reaching an all-time high with the Algocrat AI portfolio. If you encounter this drawdown soon after starting to invest, it may mean nothing from the system's standpoint, but it can be psychologically challenging. If you decide to invest a certain amount, you can invest a part of it now while saving a part for later to reduce psychological discomfort in case of encountering a drawdown soon after joining the Algocrat AI.
Additionally, you may start by thinking about what you want to maximize: your overall potential returns or your psychological comfort. Due to loss aversion embedded in our psyche, one of the best ways to minimize psychological discomfort is to wait for a drawdown. This is not the most profitable decision, as you will often miss good returns by doing so, but if you are seeking comfort first and foremost, you can invest a part now and wait for a drawdown to invest the rest.
So, that’s it — a quick overview of popular ways to time your investments.
Hope you find it useful.
Best regards,
The Algocrat AI
After our last post, we received many questions about the best point of entry. After all, Algocrat AI just reached an all-time high, and it's usually not the best time to start investing, right? Well, as usual, financial reality is a little more complicated than that.
There are two equally valid ways of thinking to tackle this question. First, if there was a straightforward way to maximize profits, such as through more precise market timing or refraining from trading after reaching an all-time high, Algocrat AI would have already adopted it. This is why its equity curve appears random to an outside observer. In other words, it's nearly impossible to predict whether there will be a drawdown or another really good month after reaching an all-time high.
Secondly, since Algocrat AI's performance is not really predictable in the short run, it's very similar to the age-old question of market timing: When is it best to enter the S&P 500? Market theorists have studied this question extensively for decades and have concluded that it is best summarized by a well-known Chinese proverb: "The best time to plant a tree was 20 years ago. The second-best time is now". On average, it’s usually more profitable to invest everything at once.
That said, just like with stocks, a drawdown sometimes occurs after reaching an all-time high with the Algocrat AI portfolio. If you encounter this drawdown soon after starting to invest, it may mean nothing from the system's standpoint, but it can be psychologically challenging. If you decide to invest a certain amount, you can invest a part of it now while saving a part for later to reduce psychological discomfort in case of encountering a drawdown soon after joining the Algocrat AI.
Additionally, you may start by thinking about what you want to maximize: your overall potential returns or your psychological comfort. Due to loss aversion embedded in our psyche, one of the best ways to minimize psychological discomfort is to wait for a drawdown. This is not the most profitable decision, as you will often miss good returns by doing so, but if you are seeking comfort first and foremost, you can invest a part now and wait for a drawdown to invest the rest.
So, that’s it — a quick overview of popular ways to time your investments.
Hope you find it useful.
Best regards,
The Algocrat AI
🧪 The Science Behind Timing The Markets [Market Theory Deep Dive]
The last two posts attracted attention, and we’ve received requests asking for details about market timing, as our proprietary trading systems shorted Bitcoin with perfect precision, getting out at the very end of the movement, achieving an account growth of 37.8% in just 5 days.
This is a very important question that applies equally well to stock market, crypto, and Algocrat AI investments. That’s why we decided to make a more in-depth continuation of this post.
First of all, it’s well-known that phrasing the question in a meaningful way is often the most difficult part of any research. So, let’s phrase the question correctly first. Suppose we have a portfolio of growing assets to invest in — stocks, bonds, crypto, and effective trading strategies. What’s the best way to do it on average?
The most important thing here is what exactly we are trying to maximize. We have not clearly stated what “the best way” means above, and that’s for a reason. When designing a trading system, a trader can optimize various metrics: maximize overall return, Sharpe ratio, Sortino ratio, minimize drawdown, and so on. By choosing the metric to optimize, we decide what is the most important thing for us.
This should be easy — just maximize returns, right? Well, not quite. As it turns out, for many people, psychological comfort is actually more important than the returns they see per se. Since most people perceive losses to be more painful than the satisfaction from returns of the same magnitude, people often prioritize their psychological comfort over gaining more money. Another important metric to consider is whether the proposed solution is easy to manage. If it needs constant attention and frequent calculations, investors are less likely to consider it.
Having all of this in mind, let’s go through the different options:
💰 Lump-sum investing: Studies have shown that, historically, lump-sum investing tends to outperform dollar-cost averaging (DCA) about two-thirds of the time. This is because markets generally trend upward over time, so the sooner the investment is made, the more time it has to grow. This is confirmed by a Vanguard study conducted in 2023 and similar studies by other researchers over the years. Vanguard analyzed U.S., U.K., and Australian markets and found that lump-sum investing outperformed DCA in 68% of cases over a 10-year period. That said, this paper also compares these two strategies using 10,000 simulated-return scenarios that tested various types of portfolios and CA period lengths. Consistent with findings from the historical analysis, LS in most cases yielded greater wealth after one year than CA, but also greater losses in some of the worst market environments. So, if we aim at maximum returns on average and the easiest solution (keeping in mind the Occam’s razor principle), we should choose LS investment. However, if we optimize for the psychological comfort of the investor, DCA can actually be more advantageous since it does not produce such losses as LS would in falling markets
💸 Dollar-cost averaging (DCA): As mentioned above, DCA is often recommended for investors who are risk-averse or who are concerned about market volatility. By spreading out the investment, the investor reduces the risk of entering the market at a peak. DCA can help mitigate the psychological impact of market volatility. It prevents the regret associated with investing a lump sum right before a market decline. At the same time, it is also a way to get a risk-averse investor into the market, as markets tend to outperform cash about 70% of the time. Apart from the above-mentioned Vanguard study, Leggio and Lien (2003) found that while DCA might reduce risk, it also often results in lower returns compared to lump-sum investing due to the market’s general upward trend. For people willing to have a sound but unorthodox view on this subject, we highly recommend reading the “Explaining the Riddle of Dollar-Cost Averaging” paper by Simon Hayley
The last two posts attracted attention, and we’ve received requests asking for details about market timing, as our proprietary trading systems shorted Bitcoin with perfect precision, getting out at the very end of the movement, achieving an account growth of 37.8% in just 5 days.
This is a very important question that applies equally well to stock market, crypto, and Algocrat AI investments. That’s why we decided to make a more in-depth continuation of this post.
First of all, it’s well-known that phrasing the question in a meaningful way is often the most difficult part of any research. So, let’s phrase the question correctly first. Suppose we have a portfolio of growing assets to invest in — stocks, bonds, crypto, and effective trading strategies. What’s the best way to do it on average?
The most important thing here is what exactly we are trying to maximize. We have not clearly stated what “the best way” means above, and that’s for a reason. When designing a trading system, a trader can optimize various metrics: maximize overall return, Sharpe ratio, Sortino ratio, minimize drawdown, and so on. By choosing the metric to optimize, we decide what is the most important thing for us.
This should be easy — just maximize returns, right? Well, not quite. As it turns out, for many people, psychological comfort is actually more important than the returns they see per se. Since most people perceive losses to be more painful than the satisfaction from returns of the same magnitude, people often prioritize their psychological comfort over gaining more money. Another important metric to consider is whether the proposed solution is easy to manage. If it needs constant attention and frequent calculations, investors are less likely to consider it.
Having all of this in mind, let’s go through the different options:
💰 Lump-sum investing: Studies have shown that, historically, lump-sum investing tends to outperform dollar-cost averaging (DCA) about two-thirds of the time. This is because markets generally trend upward over time, so the sooner the investment is made, the more time it has to grow. This is confirmed by a Vanguard study conducted in 2023 and similar studies by other researchers over the years. Vanguard analyzed U.S., U.K., and Australian markets and found that lump-sum investing outperformed DCA in 68% of cases over a 10-year period. That said, this paper also compares these two strategies using 10,000 simulated-return scenarios that tested various types of portfolios and CA period lengths. Consistent with findings from the historical analysis, LS in most cases yielded greater wealth after one year than CA, but also greater losses in some of the worst market environments. So, if we aim at maximum returns on average and the easiest solution (keeping in mind the Occam’s razor principle), we should choose LS investment. However, if we optimize for the psychological comfort of the investor, DCA can actually be more advantageous since it does not produce such losses as LS would in falling markets
💸 Dollar-cost averaging (DCA): As mentioned above, DCA is often recommended for investors who are risk-averse or who are concerned about market volatility. By spreading out the investment, the investor reduces the risk of entering the market at a peak. DCA can help mitigate the psychological impact of market volatility. It prevents the regret associated with investing a lump sum right before a market decline. At the same time, it is also a way to get a risk-averse investor into the market, as markets tend to outperform cash about 70% of the time. Apart from the above-mentioned Vanguard study, Leggio and Lien (2003) found that while DCA might reduce risk, it also often results in lower returns compared to lump-sum investing due to the market’s general upward trend. For people willing to have a sound but unorthodox view on this subject, we highly recommend reading the “Explaining the Riddle of Dollar-Cost Averaging” paper by Simon Hayley
🕒 Wait for a drawdown: This strategy means that investors are trying to actively time the market. Research shows that investors are usually very bad at this, and most of the time, they tend to miss good opportunities by staying out of the market. The research outlined in J.P. Morgan's Guide to the Markets suggests that trying to time the market can lead to missed opportunities. Missing just a few of the best days in the market can significantly impact long-term returns. This applies equally well to Algocrat AI investments as well as investments in market index ETFs. That said, while not being effective in terms of returns, this approach still provides psychological comfort to people as they are much less likely to have a really bad entry point. This approach is also more difficult than LS and DCA, as it requires constant attention to the market’s up and down moves
📊 Value averaging (VA): Value averaging is an interesting and relatively new approach to investments. It basically means investing more when prices are low and less when prices are high, aiming for a target value increase each period. While there is some research suggesting that it outperforms DCA and even LS in some scenarios, there are also studies arguing that the apparent outperformance of VA in some studies may be due to a bias in how performance is typically measured rather than actual superior returns. However, the main disadvantage of this method is its complexity. It requires a disciplined approach, frequent calculations, and adjustments. This makes it impractical for most investors who are not active traders and usually prefer spending less time on their investments
📚 A Summary for Those Who Prefer Fewer Words:
Efficient Market Hypothesis (EMH) suggests that markets are generally efficient, meaning that it is difficult to consistently outperform the market through timing or selection. Therefore, a lump-sum investment, which gets you into the market immediately, is often recommended by proponents of EMH
Behavioral Finance acknowledges that investors are prone to cognitive biases. DCA and value averaging can help mitigate some of these biases by promoting disciplined investing and reducing emotional responses to market volatility
📊 General Recommendations:
Lump-Sum Investing: If you are comfortable with market volatility and have a long investment horizon, lump-sum investing might offer the highest potential returns
Dollar-Cost Averaging: If you are concerned about market timing and prefer a more gradual entry into the market, DCA could be a suitable strategy
Value Averaging: For those who are willing to actively manage their investments and adjust contributions based on market performance, value averaging may offer a balanced approach
And, needless to say, joining Algocrat AI and becoming part of the exclusive circle of traders making the most out of the crypto markets, year after year, since 2019:
🔗 Click Here To Join Us Now
Best regards,
The Algocrat AI Team
📊 Value averaging (VA): Value averaging is an interesting and relatively new approach to investments. It basically means investing more when prices are low and less when prices are high, aiming for a target value increase each period. While there is some research suggesting that it outperforms DCA and even LS in some scenarios, there are also studies arguing that the apparent outperformance of VA in some studies may be due to a bias in how performance is typically measured rather than actual superior returns. However, the main disadvantage of this method is its complexity. It requires a disciplined approach, frequent calculations, and adjustments. This makes it impractical for most investors who are not active traders and usually prefer spending less time on their investments
📚 A Summary for Those Who Prefer Fewer Words:
Efficient Market Hypothesis (EMH) suggests that markets are generally efficient, meaning that it is difficult to consistently outperform the market through timing or selection. Therefore, a lump-sum investment, which gets you into the market immediately, is often recommended by proponents of EMH
Behavioral Finance acknowledges that investors are prone to cognitive biases. DCA and value averaging can help mitigate some of these biases by promoting disciplined investing and reducing emotional responses to market volatility
📊 General Recommendations:
Lump-Sum Investing: If you are comfortable with market volatility and have a long investment horizon, lump-sum investing might offer the highest potential returns
Dollar-Cost Averaging: If you are concerned about market timing and prefer a more gradual entry into the market, DCA could be a suitable strategy
Value Averaging: For those who are willing to actively manage their investments and adjust contributions based on market performance, value averaging may offer a balanced approach
And, needless to say, joining Algocrat AI and becoming part of the exclusive circle of traders making the most out of the crypto markets, year after year, since 2019:
🔗 Click Here To Join Us Now
Best regards,
The Algocrat AI Team
✨ Two New Brokers Now Supported [OxSecurities & Eightcap]
Hello everyone!
We are thrilled to announce the addition of two new brokers to our platform:
- OxSecurities
- EightCap
These brokers were in high demand from our clients and potential investors.
To ensure they meet our standards, we conducted extensive tests with real accounts using our proprietary Algocrat AI trading system to evaluate their trading conditions.
After weeks of comprehensive research and testing, we have determined that both brokers offer favorable conditions.
🇺🇸 If you are in the United States, we are pleased to inform you that OxSecurities accepts US traders, making it a viable solution for you.
Are you part of Algocrat AI & have an OxSecurities/Eightcap account?
🔗 Click Here To Learn How To Connect Your Account
Not part of Algocrat AI yet?
🔗 Click Here To Join Us Now
Best regards,
The Algocrat AI Team
Hello everyone!
We are thrilled to announce the addition of two new brokers to our platform:
- OxSecurities
- EightCap
These brokers were in high demand from our clients and potential investors.
To ensure they meet our standards, we conducted extensive tests with real accounts using our proprietary Algocrat AI trading system to evaluate their trading conditions.
After weeks of comprehensive research and testing, we have determined that both brokers offer favorable conditions.
🇺🇸 If you are in the United States, we are pleased to inform you that OxSecurities accepts US traders, making it a viable solution for you.
Are you part of Algocrat AI & have an OxSecurities/Eightcap account?
🔗 Click Here To Learn How To Connect Your Account
Not part of Algocrat AI yet?
🔗 Click Here To Join Us Now
Best regards,
The Algocrat AI Team
📉 Why Most Algorithmic Traders Fail [Curve Fitting Explained]
Today, we'll discuss one of the main reasons why algorithmic traders are often unsuccessful in actual trading, even though their test results are perfect: curve fitting.
In this post, we will take a quick dive into what curve fitting is and how it is manifested, looking at one particular example for additional clarity on the matter.
First things first – definitions.
What is curve fitting?
It’s basically the process of creating a trading strategy that is overly optimized to fit historical data. This involves tweaking a trading model to the point where it performs exceptionally well on past data but fails to generalize to new, unseen data.
Curve fitting is often associated with backtesting, where traders test their strategies using historical market data to evaluate their potential effectiveness.
Why does it happen?
The answer is diverse, as curve fitting comes in all shapes and sizes. There are countless ways to curve-fit the algorithm to past data so that it will only perform well on the data it has seen, but there are only a few ways to get it right.
One of the most frequent ways it happens is by having too many core parameters and optimizing all of them together. The solution to this is to have simpler models that are complex just enough to capture the essence of existing market inefficiencies but not too complicated to avoid curve fitting. It may be counterintuitive, but often, a simpler system is a better one.
The gist is that each part of your trading model should capture real, existing market inefficiencies. A good trader should understand how each part of the trading system connects to the underlying market effects it is designed for. If some part of your system captures noise instead, it will lead to curve fitting.
How can one avoid curve fitting?
The simplest answer is that each part of the trading system should capture an existing market inefficiency in a robust way. Let’s clarify this with a simple example.
Suppose we are designing a simple recommendation system that tells us when to buy the S&P 500 index and when to sell it. We’ve taken the last 10 years of data and noticed one particularity – in 8 years out of 10, June closed at a loss. Suppose the probability of closing the month at a loss is 50%. In this case, the probability of having 8 negative months out of 10 is 45/1024, or about 4.4%. If we have a 95% probability threshold to consider something an inefficiency, we satisfy it as 100-4.4=95.6>95%
The calculation is correct, but the main mistake here is that we have also looked through each other month, and only June had 8 negative years out of 10. If we consider the fact that we studied data from all 12 months, the probability of having 8 negative months out of 10 increases significantly to 1-(1-0.044)^12=41.7%. So, we can have 8 negative months out of 10 simply by chance! And the “not trading in June” criteria will likely capture random noise, not an existing market inefficiency.
In reality, even having 10 Junes or Octobers closed at a loss in a row is not that improbable. Almost always, taking a particular month out of trading hurts more than it helps. But that’s just an illustration of a more general case. In trading, there are all kinds of “random noise” mistakes one can make, and very often, using logic, reason, and common sense is the best way to avoid them
There are various ways of dealing with curve fitting: cross-validation, out-of-sample testing, walk-forward analysis, regularization, and many other complicated trading terms.
The most important one, at least from our point of view, is using sound logic when developing the system to make sure that each part of it captures an existing market tendency.
For example, the logic used when developing the Algocrat AI proprietary trading system.
Hope you find this helpful!
Best regards,
The Algocrat AI Team
Today, we'll discuss one of the main reasons why algorithmic traders are often unsuccessful in actual trading, even though their test results are perfect: curve fitting.
In this post, we will take a quick dive into what curve fitting is and how it is manifested, looking at one particular example for additional clarity on the matter.
First things first – definitions.
What is curve fitting?
It’s basically the process of creating a trading strategy that is overly optimized to fit historical data. This involves tweaking a trading model to the point where it performs exceptionally well on past data but fails to generalize to new, unseen data.
Curve fitting is often associated with backtesting, where traders test their strategies using historical market data to evaluate their potential effectiveness.
Why does it happen?
The answer is diverse, as curve fitting comes in all shapes and sizes. There are countless ways to curve-fit the algorithm to past data so that it will only perform well on the data it has seen, but there are only a few ways to get it right.
One of the most frequent ways it happens is by having too many core parameters and optimizing all of them together. The solution to this is to have simpler models that are complex just enough to capture the essence of existing market inefficiencies but not too complicated to avoid curve fitting. It may be counterintuitive, but often, a simpler system is a better one.
The gist is that each part of your trading model should capture real, existing market inefficiencies. A good trader should understand how each part of the trading system connects to the underlying market effects it is designed for. If some part of your system captures noise instead, it will lead to curve fitting.
How can one avoid curve fitting?
The simplest answer is that each part of the trading system should capture an existing market inefficiency in a robust way. Let’s clarify this with a simple example.
Suppose we are designing a simple recommendation system that tells us when to buy the S&P 500 index and when to sell it. We’ve taken the last 10 years of data and noticed one particularity – in 8 years out of 10, June closed at a loss. Suppose the probability of closing the month at a loss is 50%. In this case, the probability of having 8 negative months out of 10 is 45/1024, or about 4.4%. If we have a 95% probability threshold to consider something an inefficiency, we satisfy it as 100-4.4=95.6>95%
The calculation is correct, but the main mistake here is that we have also looked through each other month, and only June had 8 negative years out of 10. If we consider the fact that we studied data from all 12 months, the probability of having 8 negative months out of 10 increases significantly to 1-(1-0.044)^12=41.7%. So, we can have 8 negative months out of 10 simply by chance! And the “not trading in June” criteria will likely capture random noise, not an existing market inefficiency.
In reality, even having 10 Junes or Octobers closed at a loss in a row is not that improbable. Almost always, taking a particular month out of trading hurts more than it helps. But that’s just an illustration of a more general case. In trading, there are all kinds of “random noise” mistakes one can make, and very often, using logic, reason, and common sense is the best way to avoid them
There are various ways of dealing with curve fitting: cross-validation, out-of-sample testing, walk-forward analysis, regularization, and many other complicated trading terms.
The most important one, at least from our point of view, is using sound logic when developing the system to make sure that each part of it captures an existing market tendency.
For example, the logic used when developing the Algocrat AI proprietary trading system.
Hope you find this helpful!
Best regards,
The Algocrat AI Team
📈 July 2024 [Monthly Performance]
Hi there,
As we wrap up another incredible month, we're thrilled to share the latest performance results from Algocrat AI.
July has been outstanding, marking our best month so far this year with an impressive account growth of 37.8%!
Additionally, we managed to keep the maximum drawdown to just 6.84%.
We want to extend our heartfelt congratulations to the 177 accounts on our network who benefited from this month's profits.
As always, for a comprehensive overview of our performance, you can visit our verified MyFxBook track record:
🔗 Click Here To Access Our MyFxBook Track Record
Best regards,
The Algocrat AI Team
Hi there,
As we wrap up another incredible month, we're thrilled to share the latest performance results from Algocrat AI.
July has been outstanding, marking our best month so far this year with an impressive account growth of 37.8%!
Additionally, we managed to keep the maximum drawdown to just 6.84%.
We want to extend our heartfelt congratulations to the 177 accounts on our network who benefited from this month's profits.
As always, for a comprehensive overview of our performance, you can visit our verified MyFxBook track record:
🔗 Click Here To Access Our MyFxBook Track Record
Best regards,
The Algocrat AI Team
💰$12,500,000 in Assets Under Management [Milestone]
We're excited to share that Algocrat AI has reached a new milestone with over $12,500,000 in assets under management (AUM), just a few months after our official launch.
This remarkable growth underscores the trust you place in our cutting-edge crypto trading solutions and reaffirms our commitment to delivering exceptional results.
We are immensely grateful for your ongoing support, which drives us to achieve greater heights.
As we look ahead, it's important to note that our AUM limit for Q3 of 2024 remains at $20,000,000.
With more than 60% of our availability already taken, now is the perfect time to join Algocrat AI.
To ensure you don't miss out on being part of our growth, link your Binance, MetaTrader, or ByBit accounts today.
Here’s how you can connect:
- Binance: Connect Your Binance Account
- MetaTrader: Connect Your MetaTrader Account
- ByBit: Connect Your ByBit Account
If you haven't joined us yet, don't wait any longer. Apply now and secure your spot in the future of crypto trading:
🔗 Apply Now and Secure Your Spot
Best regards,
The Algocrat AI Team
We're excited to share that Algocrat AI has reached a new milestone with over $12,500,000 in assets under management (AUM), just a few months after our official launch.
This remarkable growth underscores the trust you place in our cutting-edge crypto trading solutions and reaffirms our commitment to delivering exceptional results.
We are immensely grateful for your ongoing support, which drives us to achieve greater heights.
As we look ahead, it's important to note that our AUM limit for Q3 of 2024 remains at $20,000,000.
With more than 60% of our availability already taken, now is the perfect time to join Algocrat AI.
To ensure you don't miss out on being part of our growth, link your Binance, MetaTrader, or ByBit accounts today.
Here’s how you can connect:
- Binance: Connect Your Binance Account
- MetaTrader: Connect Your MetaTrader Account
- ByBit: Connect Your ByBit Account
If you haven't joined us yet, don't wait any longer. Apply now and secure your spot in the future of crypto trading:
🔗 Apply Now and Secure Your Spot
Best regards,
The Algocrat AI Team
📈 August 2024 [Monthly Performance]
Hello,
Once again, we're beyond excited to share August's performance results from Algocrat AI.
This month, we achieved a solid account growth of 15.2%, demonstrating consistent performance across the board.
Said growth came with a maximum drawdown of 11.24%.
Congratulations to the 200+ investors on our network who are enjoying the profits this month!
As always, for a detailed overview of our performance, you can visit our verified MyFxBook track record:
🔗 Click Here To Access Our MyFxBook Track Record
Best regards,
The Algocrat AI Team
Hello,
Once again, we're beyond excited to share August's performance results from Algocrat AI.
This month, we achieved a solid account growth of 15.2%, demonstrating consistent performance across the board.
Said growth came with a maximum drawdown of 11.24%.
Congratulations to the 200+ investors on our network who are enjoying the profits this month!
As always, for a detailed overview of our performance, you can visit our verified MyFxBook track record:
🔗 Click Here To Access Our MyFxBook Track Record
Best regards,
The Algocrat AI Team
💰 $15,000,000 in Assets Under Management [Milestone]
We’re thrilled to announce that Algocrat AI has now surpassed $15,000,000 in assets under management (AUM) as we continue our rapid growth in the crypto trading space.
This significant achievement, coming so soon after our last update, reflects the trust you place in our advanced trading solutions and motivates us to push for even higher performance.
As always, we deeply appreciate your support and commitment to Algocrat AI’s journey.
Looking ahead, our AUM limit for Q3 of 2024 remains at $20,000,000.
With more than 75% of our capacity already filled, time is running out to join us.
To ensure you don't miss out on being part of our growth, link your Binance, MetaTrader, or ByBit accounts today.
Here’s how you can connect:
- Binance: Connect Your Binance Account
- MetaTrader: Connect Your MetaTrader Account
- ByBit: Connect Your ByBit Account
Haven’t signed up yet? Now’s your chance! Apply today and become part of the future of crypto trading:
🔗 Apply Now and Secure Your Spot
Best regards,
The Algocrat AI Team
We’re thrilled to announce that Algocrat AI has now surpassed $15,000,000 in assets under management (AUM) as we continue our rapid growth in the crypto trading space.
This significant achievement, coming so soon after our last update, reflects the trust you place in our advanced trading solutions and motivates us to push for even higher performance.
As always, we deeply appreciate your support and commitment to Algocrat AI’s journey.
Looking ahead, our AUM limit for Q3 of 2024 remains at $20,000,000.
With more than 75% of our capacity already filled, time is running out to join us.
To ensure you don't miss out on being part of our growth, link your Binance, MetaTrader, or ByBit accounts today.
Here’s how you can connect:
- Binance: Connect Your Binance Account
- MetaTrader: Connect Your MetaTrader Account
- ByBit: Connect Your ByBit Account
Haven’t signed up yet? Now’s your chance! Apply today and become part of the future of crypto trading:
🔗 Apply Now and Secure Your Spot
Best regards,
The Algocrat AI Team
📈 September 2024 [Monthly Performance]
Hi,
As we close out September, we're pleased to share Algocrat AI's performance for the month.
Despite a more conservative month, we still delivered a respectable account growth of 3.79%, while managing a maximum drawdown of 12.22%.
We want to congratulate the 200+ investors on our network who continue to profit alongside us!
As we move into the final quarter of the year, we’re excited to keep building on this momentum and working towards even more success.
For a detailed breakdown, don’t forget to check out our verified MyFxBook track record:
🔗 Click Here To Access Our MyFxBook Track Record
Best regards,
The Algocrat AI Team
Hi,
As we close out September, we're pleased to share Algocrat AI's performance for the month.
Despite a more conservative month, we still delivered a respectable account growth of 3.79%, while managing a maximum drawdown of 12.22%.
We want to congratulate the 200+ investors on our network who continue to profit alongside us!
As we move into the final quarter of the year, we’re excited to keep building on this momentum and working towards even more success.
For a detailed breakdown, don’t forget to check out our verified MyFxBook track record:
🔗 Click Here To Access Our MyFxBook Track Record
Best regards,
The Algocrat AI Team
Hi there,
As we wrap up Q3 (July to September) of 2024, we're excited to reflect on our best quarter of the year at Algocrat AI.
Throughout Q3, we achieved a remarkable account growth of 62.78% and managed a maximum drawdown of 15.06%.
Our assets under management (AUM) surged from $10M to over $15M at its highest point, a strong signal of the trust and growth in our network.
Looking ahead, we're eager to build on this success as we approach the year's final quarter.
For more insights and a detailed breakdown, feel free to explore our verified MyFxBook track record:
🔗 Click Here To Access Our MyFxBook Track Record
Haven’t you signed up yet?
Apply today and become part of the future of crypto trading:
🔗 Apply Now and Secure Your Spot
Best regards,
The Algocrat AI Team
Please open Telegram to view this post
VIEW IN TELEGRAM
🚀 Bybit MT5 Accounts Now Supported
We’re excited to announce that Algocrat AI now officially supports Bybit MT5 accounts!
In June of this year, Bybit announced their transition from MT4 to MT5, retiring MT4 accounts entirely.
As a result, we had to discontinue support for Bybit MT4 accounts.
However, we acted quickly—connecting our own Bybit MT5 accounts as soon as the platform became available and conducting intensive testing to ensure it met our standards.
After a couple months of rigorous evaluation, we are pleased to confirm that Bybit MT5 offers solid trading conditions, making it a good option for Algocrat AI clients.
If you’re already part of Algocrat AI, you can now seamlessly connect your Bybit MT5 account:
🔗 Click Here To Learn How To Connect Your Bybit MT5 Account
Not a client yet?
Join us today and take advantage of our powerful trading solutions:
🔗 Apply Now and Secure Your Spot
Best regards,
The Algocrat AI Team
We’re excited to announce that Algocrat AI now officially supports Bybit MT5 accounts!
In June of this year, Bybit announced their transition from MT4 to MT5, retiring MT4 accounts entirely.
As a result, we had to discontinue support for Bybit MT4 accounts.
However, we acted quickly—connecting our own Bybit MT5 accounts as soon as the platform became available and conducting intensive testing to ensure it met our standards.
After a couple months of rigorous evaluation, we are pleased to confirm that Bybit MT5 offers solid trading conditions, making it a good option for Algocrat AI clients.
If you’re already part of Algocrat AI, you can now seamlessly connect your Bybit MT5 account:
🔗 Click Here To Learn How To Connect Your Bybit MT5 Account
Not a client yet?
Join us today and take advantage of our powerful trading solutions:
🔗 Apply Now and Secure Your Spot
Best regards,
The Algocrat AI Team
With the increased likelihood that Trump may emerge as the winner in the 2024 U.S. presidential election, we saw a rally in Bitcoin that brought it close to all-time highs.
The Binance spot high on October 29 was 73,620, just slightly below the all-time high of 73,777 by a margin of a bit more than 150 dollars.
Here's how Algocrat AI handled these events:
First, a small disclaimer: we'll examine the results of Algocrat AI's verified, public track record, available here.
Results from individual trades on other brokers may vary due to differences in quotes, fees, and execution, although the long-term results remain comparable.
Now, why the rally?
Markets never give us all the answers, but the primary reason appears to be the increased likelihood of Trump winning in key swing states.
Trump has publicly advocated for the crypto industry, which could lead to increased U.S. investment in Bitcoin, potentially triggering a significant rally or even a new bull run.
Consequently, it’s reasonable for the market to price this in advance.
How did Algocrat AI systems perform during this rally?
They timed entries and exits with precision. Positions were entered above 69k, just before the rally past 70k.
Some exited early, locking in profits, while others continued to ride the trend, exiting close to the peak at 72,900.
As a result, the Algocrat account reached an all-time high, surpassing the previous peak achieved a week earlier on October 23.
Here's how Algocrat’s results with Bitcoin's performance over the last year:
In one year, Bitcoin achieved an impressive growth of over 100% on Binance's spot section, currently up by 108% from a year ago.
The maximum drawdown during this period was 33.6%, calculated as (73,777 - 49,000) / 73,777.
During the same period, Algocrat achieved growth of 226.68%, with a maximum drawdown of 24.47%.
The overall return-to-risk, measured by the Calmar ratio, is therefore (226.68 / 24.47) / (108 / 33.6) = 2.88 times higher for Algocrat AI compared to Bitcoin.
Despite Bitcoin’s impressive growth over the past year, Algocrat surpassed this growth by almost three times in terms of return-to-risk ratio.
Ready to capitalize on the crypto market's volatility?
🔗 Apply Now and Secure Your Spot
Best,
The Algocrat AI Team
Please open Telegram to view this post
VIEW IN TELEGRAM
Please open Telegram to view this post
VIEW IN TELEGRAM
📊 +19.08% - October 2024 [Monthly Performance]
Hi there,
We’re thrilled to share the performance results for October 2024, marking an impressive start to Q4 at Algocrat AI.
In October, we achieved an account growth of 19.08%, making it one of the best-performing months of the year so far.
Our risk management strategies kept the maximum drawdown at 8.98%, demonstrating our commitment to balancing growth with stability.
This month’s results set an excellent tone as we head deeper into Q4, positioning our investors for continued success.
As always, for a detailed overview and to follow our track record, check out our verified MyFxBook:
🔗 Click Here To Access Our MyFxBook Track Record
And if you're ready to join the winning side crypto trading:
🔗 Apply Now and Secure Your Spot
Best regards,
The Algocrat AI Team
Hi there,
We’re thrilled to share the performance results for October 2024, marking an impressive start to Q4 at Algocrat AI.
In October, we achieved an account growth of 19.08%, making it one of the best-performing months of the year so far.
Our risk management strategies kept the maximum drawdown at 8.98%, demonstrating our commitment to balancing growth with stability.
This month’s results set an excellent tone as we head deeper into Q4, positioning our investors for continued success.
As always, for a detailed overview and to follow our track record, check out our verified MyFxBook:
🔗 Click Here To Access Our MyFxBook Track Record
And if you're ready to join the winning side crypto trading:
🔗 Apply Now and Secure Your Spot
Best regards,
The Algocrat AI Team
🧐 Why Algocrat Did Not Trade During The US Elections [Strategies Analysis]
The last few days we saw notable price movements in the crypto market. Algocrat AI’s systems, however, did not take any positions.
Given that Algocrat AI typically trades the major cryptocurrency pairs, many clients have asked why there was no trading activity.
Here’s why:
Algocrat AI operates as a fully automated trading portfolio. There is no manual intervention unless there’s a force majeure event that requires risk management action.
In this case, our systems determined that the potential risk outweighed the benefits, so they remained on the sidelines.
As shown in our verified track record, it’s common for Algocrat to step back in uncertain conditions, and this approach is core to our risk management.
The spike in movement hinted that certain groups might have had an informational advantage, possibly due to early insights into Trump’s lead.
Yet, markets reveal their intentions only in hindsight. The day before the election, even seasoned analysts lacked certainty on the outcome.
There’s limited data on how elections impact markets, so there’s no statistical foundation for trading on these events. Algocrat AI is built on objective systems, not speculation.
In trading, accuracy in predicting the market’s direction doesn’t always translate to profit. Even correct predictions can lead to losses due to volatility triggering stop-losses.
When these risks are high, it’s often more profitable to sit out a trade than to risk unnecessary loss. Our systems are built to measure and mitigate these risks in every decision.
Consistency drives Algocrat AI. Manual trading, by contrast, rarely delivers reliable long-term results.
Over the years, we’ve observed that very few manual traders maintain strong, consistent performance.
Algocrat AI’s automated approach is designed to produce steady, systematic growth over time.
In this instance, we trusted our systems to make the final decision, and they chose to stay out.
While they won’t always make the “perfect” call, they are consistently correct over time.
Real profit in trading comes from a strategy that works again and again, not from lucky guesses.
If you're ready to profit from such strategies, then take action and join us right now:
🔗 Apply Now and Secure Your Spot
Best regards,
The Algocrat AI Team
The last few days we saw notable price movements in the crypto market. Algocrat AI’s systems, however, did not take any positions.
Given that Algocrat AI typically trades the major cryptocurrency pairs, many clients have asked why there was no trading activity.
Here’s why:
Algocrat AI operates as a fully automated trading portfolio. There is no manual intervention unless there’s a force majeure event that requires risk management action.
In this case, our systems determined that the potential risk outweighed the benefits, so they remained on the sidelines.
As shown in our verified track record, it’s common for Algocrat to step back in uncertain conditions, and this approach is core to our risk management.
The spike in movement hinted that certain groups might have had an informational advantage, possibly due to early insights into Trump’s lead.
Yet, markets reveal their intentions only in hindsight. The day before the election, even seasoned analysts lacked certainty on the outcome.
There’s limited data on how elections impact markets, so there’s no statistical foundation for trading on these events. Algocrat AI is built on objective systems, not speculation.
In trading, accuracy in predicting the market’s direction doesn’t always translate to profit. Even correct predictions can lead to losses due to volatility triggering stop-losses.
When these risks are high, it’s often more profitable to sit out a trade than to risk unnecessary loss. Our systems are built to measure and mitigate these risks in every decision.
Consistency drives Algocrat AI. Manual trading, by contrast, rarely delivers reliable long-term results.
Over the years, we’ve observed that very few manual traders maintain strong, consistent performance.
Algocrat AI’s automated approach is designed to produce steady, systematic growth over time.
In this instance, we trusted our systems to make the final decision, and they chose to stay out.
While they won’t always make the “perfect” call, they are consistently correct over time.
Real profit in trading comes from a strategy that works again and again, not from lucky guesses.
If you're ready to profit from such strategies, then take action and join us right now:
🔗 Apply Now and Secure Your Spot
Best regards,
The Algocrat AI Team