💰Over $8,000,000 in Assets Under Management [Milestone]

While we're diligently processing the hundreds of applications received, we're thrilled to share a significant milestone achieved.

Thanks to the trust you've placed in us, and the speed with which some of our new clients have connected their accounts, we've witnessed a remarkable growth in our assets under management (AUM):

From an approximate initial $5,000,000 at launch, today, we proudly announce that our AUM has soared to over $8,000,000.

This +50% increase in just two weeks is a testament to the confidence and excitement surrounding Algocrat AI.

Your support fuels our commitment to delivering the exceptional crypto trading experience Algocrat AI intends to, and for that, we're deeply grateful.

Please remember our AUM limit for Q2 of 2024 is set at $20,000,000.

With only approximately $12,000,000 left available and the current pace of growth, we could be reaching our full capacity within weeks.

If your application has been accepted, we encourage you to secure your place in the Algocrat by connecting your Binance, MetaTrader or ByBit account without delay.

If you haven't applied yet, there's still a chance to join us this quarter. Submit your application now, and we'll endeavor to process it as swiftly as possible:

🔗 Click here to apply now and secure your spot

Best,
The Algocrat AI Team

P.S. - The future of crypto trading is happening now, and it's happening here. Don't miss your chance to be a part of it.

📈 April 2024 Results [Monthly Performance]

Hello!

April has flown by, and it's time to reflect on another successful month at Algocrat AI.

We're excited to share our latest performance figures and what they could mean for your trading journey.

This April, our high-risk setting yielded a robust account growth of 9.87%, accompanied by a maximum drawdown of 12.83%.

These figures aren't just numbers – they represent our commitment to driving strong results while managing risks effectively.

Check out our verified MyFxBook track record to see the details of this month's results:

🔗 Click Here To Access Our MyFxBook Track Record

Best,
The Algocrat AI Team

💰$10,000,000 in Assets Under Management [Milestone]

Just one month after our official launch, we're thrilled to announce that Algocrat AI has crossed a significant milestone, reaching over $10,000,000 in assets under management (AUM).

This swift increase in AUM is a clear indicator of the trust you place in our capabilities and the effectiveness of our crypto trading solutions.

We are deeply grateful for your support, which continues to inspire our commitment to excellence.

As we progress, remember that our AUM limit for Q2 of 2024 is set at $20,000,000, meaning more than 50% of our availability has been already taken.

To ensure you don't miss out on being part of Algocrat AI's 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're not yet on board, now is the time to apply and secure your spot in the future of crypto trading:

🔗 Apply Now and Secure Your Spot

Best regards,
The Algocrat AI Team

📈 May 2024 [Monthly Performance]

Hey there,

As we wrap up another month, we're excited to share the latest results from Algocrat AI.

May has been remarkable, with our high-risk setting achieving an account growth of 10.18%.

However, we also faced a maximum drawdown of 20.05%.

For a detailed look at our performance, visit our verified MyFxBook track record:

🔗 Click Here To Access Our MyFxBook Track Record

Best regards,
The Algocrat AI Team

✍🏼 Clear All Your Doubts Here [Frequently Asked Questions]

Hi,

Since Algocrat AI's launch over two months ago, several important questions have come up repeatedly. Most of these have been covered in our help center, but some haven't. Let's go through them in detail:

1. What happens if I close trades manually?

Over time, manually closing trades often results in lower profits. Approximately 90% of our clients who intervene manually achieve lower returns compared to those who do not intervene manually over the course of a year. The remaining 10% might succeed occasionally, but this is largely due to chance. After evaluating hundreds of algorithms for closing trades, we have selected the most effective one for each system.

Frequent underperformance due to manual interventions might lead us to disconnect your account, as continued trading under these conditions often results in minimal profits, which are not viable for either party since our compensation is tied to profit sharing, not fixed fees or management charges.

Regarding potential technical issues, these depend on the platform you use. If you trade using MT4 or MT5, you shouldn't encounter technical problems. However, Binance operates differently, handling positions instead of trades. For instance, if you decide to close a 1.0 BTC buy trade, you would place a corresponding 1.0 BTC sell order. When our systems later determine it's optimal to close the trade, another 1.0 BTC sell order will be issued, leaving you with an open 1.0 BTC sell position until you close it manually. If you're prepared to manage this, then it should not be an issue.

Please note that we only factor in the profits from Algocrat's trades when calculating the performance fee. Any manual trades are solely your responsibility. Even if manual trades result in losses, but Algocrat's trades end the month profitably above the previous high watermark, you will still be required to pay the performance fee on the profits.

2. Why did I get different results from yours last month?

As you already know, the crypto market, as well as the Forex market, isn’t centralized. There is no single data source for it (unlike stock exchanges, as Nasdaq). That’s why quotes, trading conditions, and execution are often very different across brokers and exchanges. Plus, there are various server-side issues that we have no control over. Just recently, we experienced a brief Binance server outage (the first time in the last 2 years), which affected execution. For a few minutes, we could not send any orders. This also happens with all brokers, as no server has a 100% uptime. Due to these factors and the various differences between exchanges and brokers, it is impossible to have the same results across different brokers and exchanges. That’s why your results will always be at least a little bit different. If you want to have almost exactly the same results as our public Pepperstone track record, you should use the same broker. If you wish to have the best risk-adjusted return in the long run, you should use Binance, as it offers the best liquidity with the lowest expenses on the market, which generally results in better performance.

3. I just had a negative month. Is it normal?

Yes, it is normal. As you can see on our public Algocrat account, having 4-5 negative months in a year is a normal part of our strategy. Our main goal is not maximizing the number of positive months (which can be optimized, but it’s a completely different optimization criterion) but optimizing returns in the long run. After all, long-term profits are what a sensible trader should care about. We understand that this may be a concern, but it's a natural part of the trading process.

Hope you find this useful,

Best regards,
The Algocrat AI Team

🔍 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

📈 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

💰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

🧪 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

🕒 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

✨ 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

📉 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

📈 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

💰$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

📈 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

💰 $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

📈 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

🚀 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