Hello and welcome to the latest issue of One Button Capital’s Monthly Report. After weeks of downward movement and negative news, July came as a massive relief for all investors. As we enter the new month, we want to highlight the most important things from the Industry.
Here is what we covered:
Now, it is time to go in-depth on each of the topics and see where are we at in crypto as of August 04, 2022.
We finally come to a point when the crypto markets are not bleeding. Ethereum shocked the industry with an astonishing +58.66% ROI in July, while BNB, Solana, and Bitcoin followed the asset on the way up.
Global cryptocurrency market capitalization:
After losing more than $2T of its market capitalization, the crypto markets have not been the same. The spotlight of July was the swings below and over $1T of the total market cap. The lowest point was Jul 13 at around $950B. The highest point was reached on Jul 31 at just above $1.14T.
Bitcoin’s price action
During May and June Bitcoin struggled a lot and recorded one of its worst periods since 2010 when the assets became publically traded. In July the streak was broken, as the BTC currency recorded periods of green price action and prosperity. In total Bitcoin gained +21.23% and closed the month at $23,336.90.
In our June Report, we wrote a section on Inflation and its effect on the crypto markets. In reality, we opened a bigger topic — the correlation of Bitcoin and DeFi to traditional markets and global events in general.
With barely 2% mass adoption according to various sources, there is no looking around that crypto for now is just a small part of the World’s economy.
The current reality is that global events like the recent record-breaking inflation and interest rates will undoubtedly have their toll on crypto, just like every other risky asset. Let’s see how traditional investments reacted to the economic environment in July.
In July the S&P500 index traded at a classical uptrend, consisting of “higher tops and higher bottoms”. Overall, the asset returned +9.4% which was really good after several months of struggling.
Other indices like Dow Jones and NASDAQ grew slightly in a similar fashion as well. The current correlation between technological stats and crypto is evident, and predicting how long it will continue is speculative at best.
That being said, Bitcoin still has all features to be an excellent inflationary hedge just like Gold. If we look at a bigger timeframe, the performance of BTC is thousands of percent better than any other investment.
In July we had several major economic indicator updates, including:
We predicted increased volatility in the week after Jul 11 - Jul 17 in expectation of the Economic calendar. The results were a very increase in traded volume in both BTC and ETH and a sharp increase in price.
As of July 2022, we can conclude that global events play a role in crypto’s price action, but the direct correlation with tech stocks is an unreliable indicator as it may get broken at any given moment.
The six-day collapse of the Terra(LUNA) stablecoin and token began one of the most devastating cryptos crashes in recent years. Terra’s foundation's attempt to stabilize its algorithmic stablecoin price by selling out its Bitcoin reserves was enough to throw the whole industry into a panic.
Couple that with the companies that got exposed directly from the $60B erase in less than a week, and you got yourself a Domino Effect. First, we had Celsius, a crypto lender freeze all actions for their users, causing yet again another stroke of fear across all crypto communities. And so it continued with the downfall of other firms that were connected to the Dominoes chain.
July was different. The chain reaction continues sending companies into Bankruptcy, and other firms cutting out staff members, but the total impact got weaker each time. The effects on the price charts were also less noticeable with each following negative news.
Has the Crypto Domino Effect come to an end? As much as we are concerned about the series of events following the Terra collapse, we would say that the chain is cut.
One of the most pleasant surprises came from the second-largest digital asset - Ethereum (ETH). At one point the cryptocurrency was at a +58.66% gain over a 30D period.
Still far from its all-time-high (ATH) from November 2021 at $4,878, but it gave us a couple of valuable lessons:
So what is all the excitement for?
The Ethereum merge is important because it will allow the Ethereum network to move from a proof-of-work consensus algorithm to a proof-of-stake consensus algorithm. This will improve the scalability and security of the Ethereum network, as well as lower gas fees which is one of the biggest issues of the network currently.
If all goes to plan it is expected to have a completely operating Ethereum 2.0 somewhere in mid-September. If just the news of an upcoming merge can boost the prices by 50% in a week, there is no thinking about what the real event can bring to the whole crypto scene.
According to the founder of Ether - Vitalik Buterin, the real price of the asset will be shown after the merge.
For this month our research team has gathered data on several key topics that will give us a better understanding of the importance of using Mathematics in investing.
Furthermore, we will analyze how robots became so efficient in finding their own solutions for problems, that they need just a few hours to become world-class at anything.
We will also touch on a very current topic on regulations and decentralization, and examine if there are more positives or negatives in the government actions for the future of DeFi and crypto.
Mathematics is the language of the universe, and those who understand it can harness its power to make incredible fortunes. The world's richest gamblers are those who have mastered the art of probability and used it to their advantage. Whether it's playing poker or investing in the stock market, these individuals have used their mathematical skills to make billions of dollars. And in many cases, they have done it without any inside information or influence on the economic scene.
So what makes mathematicians so powerful? It's the ability to see patterns and relationships that others can't. And in the world of gambling, those who can see these patterns and relationships are often the ones who come out on top. Let us look at a couple of examples of success stories:
Chris Ferguson
Chris Ferguson, a professional poker player and winner of over $9.6M in prize money, is something of a legend in the casino world. But what many don't know is that Ferguson is also a math genius, using his skills to calculate the odds and make the right moves to win big.
Chris Ferguson, a professional poker player and winner of over $9.6M in prize money, is something of a legend in the casino world. But what many don't know is that Ferguson is also a math genius, using his skills to calculate the odds and make the right moves to win big.
Ferguson began playing poker while studying at UCLA and quickly realized that he had a talent for the game.
Ferguson's biggest win came in 2000, when he took down the first-ever World Series of Poker Main Event, earning a massive $1.5M payout. Since then, he has continued to rack up winnings and is now widely considered to be one of the best poker players in the world.
What makes Ferguson special is his contribution to implementing GTO (Game Theory Optimal) strategies in poker. His methods removed all emotion from the game and focused purely on game theory and statistics, which resulted to be quite profitable for him.
Jim Simons
In the world of finance, there are few figures more legendary than Jim Simons. A former codebreaker for the U.S. Department of Defense during the Cold War, Simons is now a billionaire hedge fund manager who has used his mathematical genius to achieve unparalleled success in the markets.
Simons is the founder of Renaissance Technologies, a hedge fund that uses complex algorithms to trade in financial markets. Since its inception in 1982, Renaissance has generated incredible returns for its investors, averaging around 30% per year.
Simons is a true math whiz, with a remarkable ability to solve complex problems. The most profitable fund under Renaissance Technologies - The Medallion Fund is legendary in the investment world. During the 2008 financial crisis, the fund posted a gain of +82% net of fees, while the S&P 500 lost -37%.
There is no doubt that Jim Simons is one of the smartest investors in the world. His success in using math to earn billions is a testament to his genius. He has been able to attract some of the brightest minds in the world to work for his hedge fund company which further enhances the development of new profitable investment methods.
Simons has also made contributions to the fields of mathematics and physics. He and his team developed numerous quantitative analysis systems that have dominated the hedge fund world for over twenty years.
Edward O. Thorp
Edward O. Thorp is an American mathematician, professor, and hedge fund manager. He is the author of 1962 “Beat the dealer”, which outlined various card counting techniques for winning at blackjack. He is also the author of the 1968 “Beat the market”, which proposed the first systematic model for using arbitrage and hedging principles to beat stock market indexes.
In the early 1970s, Thorp became the first person to successfully employ a market timing strategy for mutual funds, earning him the title "the father of the mutual fund." In 1976, Thorp founded the first hedge fund to employ a quantitative approach to investing, which he called "the convertible arbitrage."
This strategy, which Thorp called "the most powerful in the world," generated incredible returns for its investors for over a decade. Thorp's hedge fund, Princeton-Newport Partners, was one of the most successful hedge funds of the 1980s, earning its investors an average of more than 20% per year.
More hall of fame names:
A common belief is that only short-term traders rely heavily on technical analysis, while long-term investors use a more fundamental approach. The reality is that both methods work and a certain combination of both is best for the highest precision when investing.
From the history of wealth management firms that rely mostly on technical analysis, we can see that when it is done right it can be one of the most lucrative ways to exploit the market. This is contrary to the widespread lie that “technical analysis is astrology for men” or “technical analysis is just gambling”.
What people rarely mention in the discussion of fundamental investing on the other hand is that the largest institutions in the world have two key things that give them an edge over the rest of the market:
1) Influence on the economic scene:
There is a reason why many people dislike the investment approach of George Soros and wealth management firms like BlackRock. They have a large amount of capital to leverage, which gives them the power to influence markets and create wealth on a scale that few others can match, but that is not everything.
Additionally, it is common knowledge that institutions from that height have a huge influence on the mass media, so as soon as they decide to move in or out of an investment sector, all other investors have to follow suit.
BlackRock alone controls more than $10T and has a stake in most major financial institutions and economies in the world. Even if you are not directly invested in them, your bank, government, or pension fund is likely to be.
BlackRock is frequently criticized for funding climate destruction by supplying fossil fuel companies with a steady stream of capital leading to exponential risks for the planet, both environmental and financial.
A famous story about George Soros is from 1992 when the British pound was in crisis, and he single-handedly "broke the Bank of England" and made $1B in a single day by betting against the value of the British pound.
On September 16, 1992, George Soros made history by successfully executing a short sale of $10B worth of Pound Sterling, earning him a profit of $1B in a single day. By doing so, he effectively "broke" the Bank of England, which was forced to devalue the English Pound in order to avoid complete financial collapse. To this day, Soros is considered one of the most successful (and controversial) investors in the world.
Takeaway: big players can build an economic architecture that suits their needs and empowers them, no matter what the consequences may be to the rest of the population.
2) Insider trading:
Insider trading is a type of securities fraud that occurs when a person uses non-public information about a company to make trades in its stock.
This can be done by buying or selling the stock, or by recommending that others do so.
There are two primary types of insider trading: legal and illegal
Legal insider trading happens when directors of the company purchase or sell shares, but they disclose their transactions legally.
Illegal insider trading occurs when a person trades stock based on material, nonpublic information. This type of trading is a violation of securities laws and can be punished with fines and jail time.
Here are three examples of insider trading:
1. One of its employees was taking part in an NFT-related insider trading scheme on the NFT platform OpenSea
2. Owner and principal of investment fund sentenced to three years in prison for insider trading and investment fraud that yielded more than $7 million in criminal profits by trading securities shortly before the company’s earnings announcements were publically available.
3. Trader at large Canadian Asset Management Firm was charged with insider trading for engaging in a front-running scheme where he gave out private information to relatives in order to make profitable trades.
When not caught, insider traders can have a huge financial impact and an edge over the rest of the population. And while it is true that predicting economic trends is a must in investing, it is those that have the information before anyone else who make the biggest buck with this method.
Using mathematics, statistics, and pattern recognition is a lot more than “astrology for men” and the most successful hedge fund managers and gamblers in the world have used these analytical methods to earn up to billions of dollars across their lifespan.
While the world is also full of great fundamental investors like Warren Buffet, there is also a dark side to big financial firms that are rarely talked about. Trying to predict economic changes based on the limited information that is publically available can be as hard as trying to figure out what the latest candlestick indicates.
The goal of this research is not to make you choose one investment philosophy over the other, but rather to appreciate both and take the most out of them.
In recent years, decentralized finance (DeFi) has emerged as one of the most promising sectors in the cryptocurrency space. DeFi projects are built on decentralized protocols and offer a wide range of financial services, including lending, borrowing, and trading.
However, the DeFi sector is currently facing regulatory challenges. In particular, there is a risk that regulations could stifle innovation in the space and prevent DeFi projects from reaching their full potential.
There is a debate raging within the DeFi community about whether regulations will ultimately kill or save the sector. On one side, there are those who believe that regulations are necessary to protect investors and ensure the stability of the space. On the other side, there are those who believe that regulations will stifle innovation and prevent DeFi from reaching its full potential.
Fiat-backed stablecoins have been gaining popularity in the decentralized finance (DeFi) space in recent months. However, the recent Terra LUNA crash has highlighted the risks associated with these types of tokens.
Government regulators have been quick to react to the crash, with South Korea’s Financial Services Commission banning the trading of Terra LUNA on exchanges. The US Securities and Exchange Commission has also launched an investigation into the matter.
These actions by government regulators could have a chilling effect on the DeFi space, as they may be seen as an attempt to clamp down on this nascent industry. However, it is also possible that these actions could help to protect investors and prevent future crashes. Only time will tell how this situation will play out.
In recent years, we have seen a trend of centralized exchanges becoming highly regulated. Coinbase and Binance are two examples of this. While this may be seen as a negative by some, it could actually be a positive for decentralized finance.
With more regulations in place, decentralized finance has a chance to flourish. These regulations could help to prevent scams and other illegal activities. They could also help to ensure that there is more transparency in the industry and better convenience for new users.
At present, regulations are easier to implement when the percentage of the population involved in crypto is still relatively low. However, as more people begin to adopt crypto, it will become increasingly difficult to regulate.
This is because cryptocurrencies are decentralized by nature, and there is no central authority that can be held accountable. governments may be able to get more control over crypto in the future. While it is still too early to say definitively, it seems likely that regulations will have a positive impact on DeFi in the long run.
By providing more clarity and certainty, they will help to attract more users and businesses to the space. In addition, by making it more difficult for bad actors to operate, they will help to create a more stable and sustainable industry.
Regulations are usually monitored as something negative within the cryptocurrency world but the recent events and billions of dollars in losses prove that regulations to some extent can have their benefits. Providing a more secure environment will be key to attracting more people to crypto.
At the same time, it is important to monitor what kind of regulations exactly are governments trying to issue, as the border between what is useful and what is excessive to decentralized finance is pretty thin. The biggest drawback of too many regulations is that people may give out too much of the control of crypto to centralized institutions - destroying the whole purpose of DeFi. With the current growth of the industry that is unlikely to happen as the sector may explode at any given moment, similar to the Internet in the early 2000s.
Wealth management is a process that helps individuals invest their money in a way that meets their financial goals. It includes creating a financial plan, investing in crypto, stocks, bonds, and other assets, and monitoring progress to make sure the plan is on track.
For most people, wealth management is something they delegate to a financial advisor. But what if there was a better way? What if robots could do a better job of managing your money than humans? It may sound farfetched, but it's not as crazy as it sounds.
In fact, there are already a number of ways in which robots are outperforming humans when it comes to managing money. For example, robots are much better at analyzing data and making investment decisions.
They can process large amounts of data much faster than humans can, and they're not subject to emotions or other biases that can lead to bad investment decisions.
Now, let us look at the history of chess robots as the development of technology there is really relatable to that of wealth management. What it took humans centuries to develop, computers did in a couple of years. And after that neural networks came into the scene and dominated everything within several hours of training time.
The history of chess computers is a long and complicated one. It took humans centuries to develop chess theory, and the first computer that beat a world champion didn't come along until the 1990s. Since then, chess computers have come a long way.
The first fully-working chess computers were created in 1950. They were called mechanical chess players, and they were nothing more than simple robots that could make basic moves.
It wasn't until the end of the 20th century that a chess computer was able to beat a world champion. In 1997, the computer Deep Blue beat the then reigning WC, Garry Kasparov, in a six-game match.
Since then, chess computers have only gotten better. The latest generation of chess computers is powered by neural networks, which makes them far superior to traditional chess robots. Neural networks are able to learn and improve upon themselves, which means that they can get better at playing chess by studying the moves of grandmasters and other successful chess players.
In 2017 Deepmind, an AI research laboratory announced the first chess engine that runs on neural network programming.For each move, AlphaZero searches only a small fraction of the positions considered by traditional chess engines. In a 100-game match against Stockfish (the best traditional chess engine), AlphaZero won 28, drew 72, and lost ZERO games.
Algorithmic Chess Engines
Chess computers have come a long way since the early days of Deep Blue. The traditional chess computer relies on a brute force approach of trying every possible move and evaluating the position to see if it is good or bad. This is a very effective way to play chess, but it is also very slow.
AI Chess Engines Powered By Neural Networks
Newer chess computers are using neural networks to try to improve on this. Neural networks are a way of teaching a computer to recognize patterns. The machine learning technology allows modern chess engines to adapt to different types of play, and compute the highest accurate moves at a much faster pace.
AlphaZero for example trains entirely through reinforcement learning and self-play to avoid outside dependencies.
Another great feature to some AI Chess engines is that they can use natural language processing (NLP) to learn to perform more humanlike moves. Something that traditional chess engines are often criticized for.
Difference
One of the biggest differences in understanding between older and newer engines can be found in strategic middlegames which involve long-term improvements by one side. As shown in many of the AlphaZero – Stockfish games, the older engines sometimes fail to see dangers due to their limited foresight.
Relying solely on move-by-move calculation is not always enough to solve problems against the strongest opponents. This is because neural network engines excel at slowly building up pressure, making small improvements to optimize their winning chances, before gradually preparing the decisive breakthrough.
Final Thoughts On Chess Engines
When chess engines became a powerhouse that could take out even the strongest grandmasters with no problem they were widely hated. One main reason for that is the fact that despite making highly accurate moves, their style of play was so off from what a human would play. The 2013-2023 world chess champion Magnus Carlsen even said that “playing against an engine is like playing an idiot, and then he wins.”
In spite of that, chess computers became an inseparable part of every top player’s toolset and the constant development of new engines only improves the aspect of the sport as well. The most modern engines rely either on 100% neural network architecture or a hybrid of it with some traditional algorithms.
The biggest impact that AI made in chess is probably in efficiency. In a game where there are more than 10^120 possible games (more than the atoms in the universe), having a method to effectively and efficiently find the best moves is everything.
The most modern AI engines are also able to learn to imitate the human style of play, so they can be a good partner to play against as well (opposite to old engines that just make you feel stupid.)
In June 2022, Google made a breakthrough in Sentiment. Google says The Language Model for Dialogue Applications (Lamda) is a breakthrough technology that can engage in free-flowing conversations. But engineer Blake Lemoine believes that behind Lamda's impressive verbal skills might also lie a sentient mind.
The fact that Google denied the later claims by their work and even fired him in July 2022, rises more questions and conspiracy theories than ever. We are wondering how far has AI reached in sentiment analysis exactly.
Other Breakthroughs In 2022 In AI And ML Include:
If sentiment analysis keeps developing at this pace, soon it can become an addition to wealth management firms that use AI for investing purely based on price action analysis (eg. One Button Capital). Adding a market sentiment AI on top will give the trading robots a whole new dimension of decision-making.
A.I Timeline or Understanding Artificial Intelligence. Source: David Alayon
Now that we know where we are at the development of AI technology it is time to look at how the wealth management industry has used the available tools in order to tame the market in its favor. At the time of research, the best AI trading firms rely solely on neural network architectures that analyze price data.
From our paper on the “Richest Gamblers (Investors) In The World That Used Nothing But Math” we know that this can be a very effective way of investing.
A.I. in finance is already providing huge benefits to banks and other financial institutions. It is being used to automate the tedious and time-consuming tasks of financial analysis, including the identification of trends, the assessment of risks, and the generation of predictions.
This is freeing up human resources so that they can be deployed to more strategic tasks, such as developing new products and services or providing better customer service. A.I. is also being used to develop new financial products and services. For example, it is being used to create "Robo-advisors" that provide personalized investment advice to individual investors.
Robo-advisors are able to provide this advice because they have access to vast amounts of data and can analyze it quickly and efficiently. They can also provide their services at a lower cost than traditional human advisors. In the future, A.I. is likely to play an even bigger role in finance and wealth management. It will help financial institutions to become more efficient and to better serve their customers.
The Edge Of AI Robo-Advisors
The concept of an automated trading system was first introduced by Richard Donchian in 1949 when he used a set of rules to buy and sell funds. Then, in the 1980s, the concept of rule-based trading became more popular when famous traders, and in the mid-1990s, some models were available for purchase (sounds familiar?).
Now in the 2020s, we got AI Robo-advisors. What gives them the edge against humans and even traditional algorithmic automation tools is reinforcement learning. With its help, the most modern trading bots are capable of not only using historical data to create unique strategies but also swiftly adapting to the constantly changing environment and finding patterns that no one has ever thought of before.
A New Way To Invest:
One Button Capital is the first company to provide a wide range of crypto investing strategies that are 100% based on machine learning and neural networks. Since its creation in 2020, the firm has outperformed the market by a steady +3.62% monthly and is currently working on adding two more investment vehicles (first in their class).
A new way to invest:
One Button Capital is the first company to provide a wide range of crypto investing strategies that are 100% based on machine learning and neural networks. Since its creation, the firm has outperformed the market by a steady 4% every month and is currently working on providing two more investment vehicles that are the first of their kind. Read more about the company here.
One Button Capital uses tested investment management frameworks from traditional finance and combines them with big data, artificial intelligence, and machine learning technology to gain an edge in cryptocurrency investing. The platform is:
Fully Automated: asset management is fully managed by AI-driven tech with ZERO human intervention.
Scientifically Driven: developed by a team of technologists, scientists, and product managers, the firm uses a scientific approach to investing.
Consistent Alpha: contrary to the majority of crypto funds, we generate both absolute and relative returns higher than the market for our investors since 2020.
Read the full presentation.
How It Works
All the trading and portfolio management is done purely by the AI-backed models. The models are using recurrent neural networks and reinforcement learning for maximizing returns while trading cryptocurrencies.
Architectures used in the models include the ones also used by major tech companies Amazon, Google, and Facebook for data processing and analytics, such as LSTM, GRU, Performer (Transformer), GMLP, Filter, and others.
All the models are developed in-house by the One Button Capital research team.
Read the full Whitepaper.
Artificial Intelligence has come a long way and has already impacted countless industries. The real scope for the wealth management sector is yet to be seen, but we can safely look at the history of chess computers to see where we are at, and what we can expect to happen in the future.
While it took about 50 years for a chess computer (since the first one) to beat a world champion, it only took 20 more years for a neural network chess engine to take over the crown. In finance, the concept of an automated trading system was first introduced around the same time and the development since is pretty consistent with that of chess engines. The 2020s will undoubtedly be the turning point for AI-driven wealth management.
The Impact Of Inflation On The Cryptocurrency Market
Time In The Market Vs. Timing The Market: Why Even Long-Term Holders Lose Money In Crypto
Investing During A Bear Market: How To Not Lose Your Money In Crypto
Can Bitcoin Solve The Money Problem? Why Money Is Dead.
DeFi Trends In 2022 Web3. Is The Future Of Finance On The Blockchain?
Should You Invest In Funds? Real State Of Wealth Management Market in 2022.
Making Money In Crypto: 10 Proven Tactics For Effective Cryptocurrency Investing.
AI/ML In 2022. Why investing in tech projects will set you apart for a lifetime.
AI In Cryptocurrency Trading: The Big Picture
July was a great month for both Bitcoin and Ethereum. The events that we discussed in the market performance section led to both assets regaining some of their losses from recent months. Ethereum is the big winner in this month’s rally. One Button recorded a very good result of +20.96% ROI, making a better return than Bitcoin, which gained +17.24% in July.
Unsurprisingly, the Performer v2 strategy made huge net returns during the micro bull market in July. But what was not expected was to see the newest AI strategy - Explorer take on first place in its debut month. With a net return of +28.47% against +28.26%, this opens the room for an upcoming rivalry in which strategy will take the crown for best-performer in 2022.
Net Return Of The Other Strategies
Ethereum made it in most of July’s headlines but there were other great winners in the altcoin department. The trading AI at One Button captured several of the micro bull runs and returned great profits on a couple of them.
Taking advantage of the short-term pumps on specific alternative crypto pairs can serve as a good strategy for increasing one’s gains. It is really important to note that altcoins carry an even higher volatility risk than Bitcoin and Ethereum.
No investor should go all-in into such type of investment without measuring the risk and his loss tolerance. A common practice for crypto investors is to allocate the majority of their investments in BTC and ETH and maybe some other Top 10 coin (measured by market cap).
Outperforming The Market Over The Long Run
One Button Capital’s long-term results against Bitcoin.
OBC: +38.05%
BTC: -44.93%
The above graph focuses on the overall averaged performance of all BTC trading strategies on One Button Capital. The AI-boosted BTC outshines the number one crypto by over +80%
One Button Capital’s long-term results against Ethereum.
OBC: +269.4%
ETH: +39.34%
No, there is not a spelling mistake in the above results. The AI-Boosted Ethereum strategy outperformed ETH by more than +300% over the course of 18+ months. In absolute terms, this is almost 7x times more ROI in less than two years when compared to a buy-and-hold strategy for the same investment period.
Last month we introduced our latest AI trading strategy - Explorer. In July the trading bot made its debut and it absolutely dominated both the markets it traded on and its ancestor bots. In the community feedback section, we will review the exact trading history of the strategy and how it ranked #1 last month as the most profitable AI under One Button Capital’s assortment.
The last 30 days were a complete blast for the AI that trades on BTC: USDT. The AI managed to buy in exactly before the pump on Jul 27–28 and utilize all the upside. The trade history shows it all; I’m not going to comment on it.
This AI’s total ROI for the last 30 days is +34.69% against +20.76% of BTC.
Each investment strategy on One Button Capital utilizes machine learning technology. This gives a superior AI edge to the trading bots, as they are capable to analyse the market like a professional trader, rather than following set-in-stone rules that do not work forever.
Before becoming available to investors, every trading robot undergoes a series of tests that includes prototype experiments, backtest runs, and several months of trading on the live market. Once a strategy is approved to be profitable it can go into the OBC assortment of trading bots.
That is what we call “training” a bot. It is important to note that the AI is not only trained during the creation of the strategy but also every time a new bot is launched under a given strategy. And it is very noticeable when we observe the performance on the charts. Here are several patterns that we commonly observe.
If we take the BTC chart from above, we can see that during the ten days the Performer v2 AI mimicked the movement of the assets almost perfectly. This is the “in-field” training period during which the bot gets used to the current market condition and prepares for higher frequency trades.
When a trading bot detects a potential crash in the traded market pair it will immediately convert most or all of the investor's capital into fiat money. This can be observed on the chart above with the straight lines between Jul 11 - Jul 17 and later between Jul 22 - Jul 28.
Finally, after an AI has completed its preparation period and avoided all traps it is time to earn money. In the shadowing phase, we observe a very similar trend-following line to the “sticking” pattern, but thanks to the clever “folding” periods there is a margin between the real asset’s performance and that of the bot’s performance. Between Jul 28 - Jul 31 we see a demonstration of the real beauty of AI trading - once a bot is fully-trained there is no stopping it.
AI was also spot-on to buy in before the ETH pump. It has been completely dominating the market for the last month. Again, the trade history shows it all.
Overall, this AI returned +13.50% since it was activated on December 3, 2021, vs. -62.42% of Ethereum it has been trading on.
It is hard to look at the Ethereum graph since December when we know what kind of performance it made in the last month. Many long-term fundamental investors lost up to -80% of their investments from Q4 last year. The buff in July healed some of the wounds, but there is a lot more to climb until we reach the previous ATH.
On the other hand, by looking at the Performer v2 performance (yellow line), it is evident that the AI caught every single uptrend opportunity since its creation. In the last ten days of Jan 2022, the bot shadow followed the price action of Ethereum, and reached a peak of ~30% ROI, while the asset was down by around the same percentage.
The Clipper AI Strategy is popular for its ability to clip profits during uptrends. And this is very visible in the BNB case study from above. During August and September of 2021 Clipper was stuck closely to the asset's movement, but once BNB started trending up between October and late November, clipper made sure to lock in profits before eventually folding in December when the market crash began.
The AI was very quiet during December 2021 and January 2022, but it eventually began to mimic the price movement of BNB and is currently up by more than +70% against the digital asset.
The trading history of the Endeavour AI against the same BNB market is quite intriguing.
It was passive in “fold” mode between May 19 and June 10 while the market was slowly trading down.
The AI entered a buy position about a week earlier than the optimal time but still managed to outperform the market by +37.78%.
And here goes my favorite: Ethereum Classic. Due to recent fundamentals, this coin has been pumping particularly actively. Guess who was there to capture all the upside? (hint: it starts with A and ends with I)
Overall, this AI returned +117.39% since it was activated on November 18, 2021.
Do you know how much you would’ve made if you just “buy-and-hold” ETC for the same period? -23.01%!!!
We can also look at the chronology of this AI.
We have demonstrated time and time again that the best results with OBC are achieved when the bots are run for at least 3+ months. At the same time, it is insightful to observe how a strategy performs in a given month. For that purpose, some of our investors, like Mr. Noidea from above launch several trading robots at the beginning of each month and let them trade throughout the whole 28-31 days.
Letting AI manage your finance is a big leap if you have never done something like this before.
But if we look at this investor’s case study and compare it to an investor that would have chosen to buy some BNB in November when everyone had the FOMO (Fear Of Missing Out) syndrome, he would have lost at least -60% of his money from his impulsive decision.
Our trading robots on the other hand do not care about headlines or market sentiment. They invest solely based on price action and neural network signals.
And while it may not sound sexy as that new NFT project, at least the AI bot has a much larger chance to protect your money when an unexpected crypto winter season begins.
The new trading strategy Explorer showed very promising results at the beginning of July. One of OB Capital’s VIP investors ran one trading bot for Litecoin (LTC), Ethereum (ETH), and Bitcoin (BTC) each.
His results ten days into the month say it all.
Another investor saw great ROI in the first half of July on three of his 26-day running bots.
The Performer v2 strategy outperformed ETH, BNB, and LINK, while two of the three assets were trading in the red zone.
What is more impressive is the improvement of two of the older trading bots of the investor. While they did not perform horribly, they seemed to be lagging behind some of the other trading robots. In July they finally “un-sticked” from the market and started trading at a nice “shadow” margin of about ~12%.
“Improvements during the last 30d of "bad" ADA: BUSD bot:”
“That's the graph of last week's improvement of the "bad" SOL: BUSD bot:” - Hubhub
Below is an exciting catch from one of the sell trades of the investor’s bots. The AI forecasted the red candlestick and sold it just on time in order to keep profits at a maximum.
“Also interesting: Bot screenshots 1-day difference. Look what the market did and how the bots managed to sell on time” - Noidea
Incredible one-month adaptation from Performer v2 which doubled the market’s performance, returning +37.45% against BNB’s 30-day return of +17.47%.
“Lovely! This is my BNB: BUSD running for 1 month:” - Hubhub
On July 18, 2022, our investor Mr. Hubhub shared a testimonial of one of his longest-running bots that underwent the market collapse.
The AI was set to trade on ETH: USDT at the start of 2022.
It managed to save the looping -55.03% from being erased during the Ethereum crash.
Now, when the market is stabilizing the bot has plenty of capital to ride any upcoming uptrend.
A great observation that OBC members and investors saw about the trading strategies is that they favor certain USD Market Pairs more than others. In the below example we can see how both strategies outperformed Chainlink (LINK), but the BUSD bot made +16.51% more ROI.
If we look at the results of the Bitcoin pair there is a slight difference in favor of the BUSD bot. One of the hypotheses we have is that the larger trading volume in
Explorer was an absolute machine in July. In only 26 days after his debut, he gained up to +43.44% profits in its traded markets.
One way to assure that your crypto investing strategy is effective is if it can outperform to top 3 digital assets.
In the case of Explorer both Bitcoin and Ethereum stay in the shadow of the AI.
“Not bad??.. I'd say very good :)” -Noidea
Here comes one of the most groundbreaking trading performances of the year. The LTC: BUSD trading bot of an investor under the username Ezza absolutely crushed it 2022. After a very quick adaptation period in January, the AI quickly gained shadow and managed to mimic Litecoins movement at a significant +100% margin.
If we look at absolute numbers here is what the investment looks like with a $10,000 hypothetical investment:
Invested in January: $10,000
Litecoin at end of July: $4,524
Performer v2 at end of July: $14,268
That is 3.15x better than the asset’s performance or 315% times more money in the investor’s portfolio!
Watching the uptrend in July’s end our investor decided to launch several more bots in order to catch the rally. While the bots typically need several days to accumulate to the market conditions, this time the Performer v2 strategy was ruthless. An average of +17.78% ROI was recorded in just 6 days (with +41.60% in SNX: BUSD), while the assets moved only by +7.44% on average and one of them recorded a drop (NEAR: BUSD went down -7.42%).
At the same time, one of the longest-running bots in the investor's toolset recorded +29.54% ROI over 191 days while the UNI: USDT pair went down -40.91% since the bot’s launch date.
A $5,000 investment would be worth $2,955 from a buy and hold strategy, while this particular bot would be worth $6,477 - a staggering 219% difference!
The icing on the cake for the investor is his July experiment that saw his Explorer and Performer v2 stragies returning incredible results (both in relative and absolute terms). Explorer netted +70.94% on Ethereum and +25.10% on Bitcoin, while P2 gained +21.31% in Elrond (EGLD) and +9.41% on Litecoin.
*Please note that the Litecoin bot’s performance is tracked over a 75 days trading period, and is not part of the July experiment. Nonetheless, it is great a result, as it outperformed the asset over 1.2x times and returned profit while the asset’s price has dropped..
“hey guys - I've been running MATIC: BUSD for 8 days and seeing some good results based on the above query will start posting more in the bot performance section, just fairly new so letting bots run a bit first, I've posted in the bot-performance section the MATIC bot” - Smethersslug
It is amazing when new investors start seeing immediate results. In this case, the user launched a Performer v2 AI against MATIC: BUSD.
We can immediately see that during the first two days his trading bot folded from taking any actions. There was a small trade on July 25, but the AI then returned to fold status as the market dropped sharply in a single day (-21.56%).
On July 27, or five days infield the Performer v2 bot started shadow mimicking MATIC’s movement and over the course of several more days was up by +24.43% since creation, while the asset is up by only +3.86%.
We are looking forward to seeing how the AI will perform in August and the rest of the year.
This wraps up our community feedback section and OB Capital’s July performance chapter of the report. This was undoubtedly one of the most successful months for our investors. Both the short-term and long-term investments made a great profit in the last 30 days and we are expecting to see even better results towards the end of 2022 if the predictions for an upcoming bull market are correct.
In our previous two reports, we highlighted the importance of having a working strategy during bear markets as that is key to both not losing money in crypto but also having free capital for when the prices start going back up again. Now, that we tasted the short uprise in July, we have up-to-date data to prove our thesis.
To join the discussion on the One Button Capital Discord server, click here.
Disclaimer: This is not financial advice. This report is strictly educational and does not provide investment advice, solicit the purchase or sale of any assets, or encourage readers to make financial decisions. Please use caution and conduct independent research.
Practical evidence stands higher than theoretical theses, and the results we shared do the talking by themselves. At the same time, we think that it is valuable for our investors to learn how an AI-driven asset management machine works, as this is an innovative way of investing.
Our technology performs two vital tasks in portfolio management:
Portfolio distribution and asset management.
For portfolio management, we use neural networks—a form of narrow AI that can learn to do specific tasks designed by a human.
Portfolio distribution and asset allocation are vital tasks of every portfolio manager. The question here is:
How to allocate capital effectively between various cryptocurrencies?
Our answer:
We use neural networks trained on various baskets of portfolios to optimize the allocation process. The data used to train these models includes billions of combinations of asset buckets tested against billions of different market timeframes.
Using the real-time data received from the market, the models dynamically adjust the portfolio to optimize for better returns.
Additionally, the data from the performance of asset management models is used to optimize allocations.
Ongoing management of a portfolio is another critical task done by a portfolio manager. The question here is:
How to optimize holding the asset to generate returns better than the market?
Our answer:
We use neural networks to trade market pairs on spot and futures to generate returns better than the market. The neural networks are trained on various market pairs using historical market data.
A model can trade a single market pair. The models utilize real-time market data to make decisions to buy, sell, or hold a position.
To explain what One Button Capital trading neural networks are, first we need to understand what they are not.
Neural networks are NOT:
Then what are the characteristics of neural networks?
Neural networks are dynamic, adaptive, and self-learning. They possess the quality of expressivity, which gives an edge to OBC trading AI compared to rule-based algos. In machine learning terms, expressivity is the capacity of a neural network to perform different kinds of computations, therefore, be ready for changes in the environment.
Imagine neural networks as players and the market as a game. The goal of the players is to win the game. And winning the game means scoring the most profit with the least possible drawdown.
That makes it easier to explain the advantages of this technology compared to the alternatives. Since the goal of the models is not necessarily to predict the future price but to actually win the game, the decisions they make might seem unconventional in a moment but give an edge in the long run.
Read the full article.
Following the great event on the Crypto Expo Asia in Singapore, we are looking to extend our reach through other attendances. This time we have two events on our calendar that are Blockchain related.
The development of blockchain technology is vital for the crypto industry, and it is essential that it keeps improving.
The crypto winter is not over yet but there are good indicators that we may be close to greener months.
To further help the digital revolution, I and the team represented One Button Capital at the 2022 Blockchain Week in Singapore in the final week of July.
Thousands of crypto enthusiasts and industry experts from different spheres of work were also present, and we made a great connection with them!
I am excited to share that One Button Capital will be present at this year’s Bali Blockchain Ecosystem Conference.
Our goal is to network with other industry leaders, connect with like-minded investors, and discuss the newest blockchain innovations.
We will have an OB Capital booth at the event and I am invited as one of the speakers. If you are in Bali at this time, you are more than welcome to join us.
Bali Blockchain Ecosystem Conference 2022
15+ Speakers (e.g. CEO Indodax)
20+ Booths Crypto Projects
500+ Participants
$1,000 Bitcoin Giveaway
Free 360 Video
Attendance Certificate on the Blockchain
Bali Blockchain Ecosystem is a Community, Conference, Exhibition networking, and Crypto project ecosystem, sharing opportunities around web3, crypto, blockchain, NFT & Metaverse.
Date: Thursday, August 4, 2022
Duration: 12:00 – 22:00
Location: ParQ, Ubud, Sri Wedari №24, Bali 80571
We have introduced an improved diversification for automated investment portfolio creation.
We have introduced an indicator that showcases whether stop-loss (SL) or trailing stop-loss (TSL) is activated for that AI bot.
We recently introduced USD markets for Kraken in order to support all of our investors outside of Europe. Some of the key markets we support now are BTC, ETH, LTC, LINK + 4 others.
As of the middle of July Performer v2 (one of our most advanced AI strategies) is available to every investor on the One Button Capital app. We introduced it in order to help investors not only on our paid subscription plans to gain a significant edge in the underlying markets.
We have introduced an indicator for each line on the performance chart that showcases the latest value.
Moving forward, we expect that the wealth management sector will rely increasingly on artificial intelligence in upcoming years. With the constant development of new technologies, it is inevitable for big financial firms to upgrade their strategies to meet the challenges of the new economic environment.
Luckily, or should I say, thanks to our eye for innovation, we created the first crypto asset management software that uses exclusively machine learning way back in 2020. We were not just ahead of the curve, but we were also successful in our invention, as our trading AI has consistently outperformed the market by 4% every month.
To have your own AI broker that trades crypto 24/7 on autopilot for you, apply to join the fund here.
If August does not come with unexpected surprises, we are looking for a steady uptrend across the whole market once the Ethereum final testnet before the merge is successful. Subscribe to our newsletter to get updated on the latest news and price changes in crypto, as well as our most recent performance and product updates.
Best regards,
Max Yampolsky, CEO at One Button Capital,
ir@onebutton.capital
Disclaimer: This is not financial advice. This report is strictly educational and does not provide investment advice, solicit the purchase or sale of any assets, or encourage readers to make financial decisions. Please use caution and conduct independent research.
We regularly prepare insightful reports and case studies about crypto trading and the blockchain industry.
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