Are you a trader or an active, self-directed investor who has tried different strategies with little success? Are you tired of the emotional rollercoaster that comes with making trading decisions? Or do you find it difficult to monitor the markets and execute trades effectively due to a busy schedule? If you answered yes to any of these questions, it may be time to consider a new approach. Cloud-based automated trading systems use sophisticated algorithms to analyze market data in real time, identify trading opportunities, and execute trades without human intervention. This can eliminate the emotional bias that often plagues manual trading and help you achieve more consistent results. Additionally, cloud-based automated trading programs can operate 24/7, 365 days a year, allowing you to take advantage of more trading opportunities if you have a busy schedule, without having to install or manage complicated software. This innovative trading approach can also leverage advances in technology, like AI, with statistical backing. 

Let’s take a deeper dive into automated, cloud-based trading systems and how you can incorporate them into your investment approach.

What Are Cloud-Based Trading Systems?

Cloud-based trading systems are software applications that are hosted in the “cloud” (via an Internet server farm like those offered by AWS (Amazon) or Microsoft) and managed over the Internet by the system developer.  They are not installed on an individual’s PC or computer.  The trading systems use sophisticated algorithms to analyze market data and identify trading opportunities.  When a market condition meets pre-determined rules and parameters, the algorithms send trade signals to the broker’s signal execution software and execute trades without human intervention. 

Cloud-based, automated trading systems can offer several benefits. However, it is not without risks, and self-directed investors should carefully consider their goals, risk tolerance, and investment capital before using an automated trading program.

How Are Fully Automated Trading Systems Different From Other Investment Strategies?

Fully automated trading systems are different from other investment strategies in that they rely on pre-programmed rules and algorithms to execute trades, rather than relying on human decision-making or analysis. These rules can be adaptive based on recent market performance and changing conditions and even driven by advanced machine-learning and AI technology to find opportunities that would not be found otherwise.  Automation also improves execution speed (minimizing missed opportunities) and removes emotion from the trading process, helping to improve consistency and trading results.

Traditional investment strategies, such as those based on fundamental or technical analysis, involve a trader making subjective decisions based on their analysis of market conditions, news events, and other factors. This can be influenced by cognitive biases (such as anchoring, loss aversion, and gamblers’ fallacy) and other emotions and ultimately lead to poor trading results. Fully automated trading programs can also operate 24/7, without the need for human intervention, which can allow for more opportunities and even take advantage of movements in multiple markets simultaneously.

Fully automated trading programs are complex to build and maintain, but when built properly by trading professionals, can offer many benefits to investors.

What Are The Benefits Of Cloud-based, Fully Automated Trading Systems?

Cloud-based, fully automated trading systems offer several benefits to new and experienced traders, and investors alike, including:

• Consistency: One of the key benefits of using fully automated trading systems is consistency. Unlike human traders who can be influenced by emotions and cognitive biases, an automated trading program follows pre-programmed rules and parameters, leading to more disciplined and profitable trades.

• Efficiency: Automated trading programs can save traders time by analyzing market data and executing trades much faster than a human trader. This can allow traders to take advantage of more trading opportunities, particularly in fast-moving markets. Moreover, automated trading programs can operate 24/7, meaning traders can benefit from trades that occur outside of regular trading hours.

• Backtesting: Automated trading systems can be backtested and optimized on historical data, allowing traders to identify strategies with the best odds of success. This can lead to better trading results and help traders avoid costly mistakes that may have been made through trial and error.

• Risk Management: Automated trading software can help traders manage risk by setting stop-loss orders and other risk-management parameters. This can help prevent large losses and preserve capital, particularly in volatile markets

• Scalability: Automated trading programs can be scaled up to handle larger trading volumes, which can be difficult for human traders to manage. This can allow traders to take advantage of more trading opportunities without sacrificing performance.

• Diversification: Automated trading solutions can allow traders to diversify their trading portfolios by using multiple strategies simultaneously. This can help to spread risk and potentially increase returns.

How Do I Get Started With a Cloud-Based Automated Trading System?

Getting started withInvestiQuant's fully automated trading programs is a great way to take advantage of volatility and put advanced technology to work for you. iQ Autotrading offers traders a range of robust, statistically-based, systematic trading strategies that are designed to generate attractive returns, regardless of the direction of the stock market. The best part is that these turnkey solutions can be enabled to autotrade your account at an approved execution broker in a matter of days, without having to install or maintain any software whatsoever.

By utilizing a wide range of strategy inputs, including alternative data, technical patterns, volatility, market profile, seasonal events, and multiple advanced machine-learning techniques,iQ Autotrading offers a diversified approach to algorithmic trading. InvestiQuant's autotrading is a powerful, hands-free solution for traders and investors of all types, offering strong, verified returns, potential for outsized growth, emotion-free, statistically-based trading, low correlation with stock trading strategies, a turnkey, hands-free solution, and aligned interests.

Ready to see how cloud-based, automated trading can transform your investment portfolio? Request info to learn about the performance of InvestiQuant’s automated trading programs and how your account could be enabled for automated trading in a matter of days. 

Due diligence is critical when selecting an Autotrading solution. Why? Because these days just about anyone with a little coding and trading knowledge can create a seemingly profitable automated trading solution. But subscribing based on attractive results is simply not enough.  It takes a well-funded, fully-committed team of highly skilled developers and veteran traders to build and support automated trading strategies that can generate real profits in live trading over the long term. By conducting autotrading due diligence, you can better understand the risks, make a more informed decision, and increase the likelihood of achieving your financial goals.

The purpose of this article is to streamline some of the more important questions with some straightforward answers. InvestiQuant is a trusted partner of our clients with AI-driven automated solutions to guide clients in the diversification and growth of their wealth. Our objective is to help you decide if autotrading is right for you and to arm you with the information needed to make the optimal investment allocation decision for your financial situation and risk tolerance.  If you have any other questions not covered in this blog, just reach out to us – we are here to help. 

Does the iQ Team Trade the Same Programs?

Yes! We risk our own capital and rely on the very same strategies and programs as those traded by our clients.

Is The Company Financially Stable? 

Yes. InvestiQuant is a profitable company that has been serving clients since 2008 and is backed by a large group of private investors. These shareholders (professional investors, friends and family, and about 20 of our earliest clients) invested over $3 million to help scale and automate the company’s innovative machine learning technology and strategies. With their backing, a strong balance sheet, and highly scalable business model, clients can rest assured that iQ is a company they can count on. 

Are The Principals Trustworthy, Qualified and Accessible? 

InvestiQuant’s principals, Scott and David, are highly experienced traders and software development professionals. They met while attending the United States Military Academy (West Point) and were subsequently stationed at Fort Bragg, NC (Scott served with the 18th Aviation Brigade and David with the 7th Special Forces Group.) After leaving the Army, they earned Masters degrees and led the development and launch of Jaggaer (formerly known as SciQuest) - one of the first B2B software-as-a-service pioneers and a global leader in e-procurement with over 1,000 employees today. With Scott at the helm, they took this cloud-based software company public on the NASDAQ exchange. 

Following Jaggaer, they applied their passion for data to the financial markets and built InvestiQuant.  Along the way, they became professional traders with Series 3 Commodities and Futures licenses. To earn their licenses and manage money professionally, they had to pass the rigorous National Futures Association (NFA) and Commodities Future Trading Commission (CFTC) background checks and derivatives qualification exams. (Note: the company is now registration-exempt so their licenses have expired.) 

As CEO of InvestiQuant, Scott speaks with clients and prospects, and responds to emails on a daily basis. He can be reached at Scott @ investiquant dot com. 

Are The Published Performance Results Real? or Hypothetical? 

Unlike many 3rd party developers, we don’t hide behind hypothetical results and disclaimers which can be incredibly misleading and dangerous.  Every InvestiQuant program’s live net trading results are shared from inception, typically along with simulated (hypothetical) returns for a few years prior, so that a more complete picture of how a strategy would have performed in other market environments can be assessed. 

Please know that relying solely on hypothetical results - without live trading confirmation - is <highly> risky as simulated results are often over-optimized and rarely account fully for real world execution slippage. If the program trades frequently, live trading variances of 50% or more are possible. When evaluating other signal developers, buyer beware!

How Can I Verify The Performance of Your Autotrading Programs?

InvestiQuant reports the live trading results from its accounts each month. Due to the broker’s “Average Price System” every client receives the same net results for each trade. As such, the simplest way to verify InvestiQuant’s published returns is to ask the broker representative to verify our published figures. (Note: results can vary slightly by broker.) 

Do Your Employees Have Access To My Funds?

No. InvestiQuant serves as the 3rd party signal developer and focuses its efforts solely on developing, maintaining and improving advanced algorithmic trading strategies. No iQ employee ever has access or visibility to clients’ funds or trading accounts. 

A professionally licensed and registered brokerage firm, with algorithmic trading expertise, supports clients by assisting them with opening and funding their account with another highly regulated entity: a Futures Commissions Merchant. The broker serves as the support representative and liaison between the client and the merchant. The broker also maintains trading desk personnel to oversee and ensure proper algorithmic trade execution of all InvestiQuant signals within each client account. The futures merchant serves as the custodian of the client funds and safeguards them in segregated accounts.

Is There “Key Man” Risk?  What Steps Are in Place to Ensure Error-Free Execution?

Many algorithmic investment solutions are entirely dependent upon one or two individuals (typically founders) for their research, coding, and trade operations and most only have 2 or 3 employees. However, redundancy of personnel is crucial for autotrading companies. 

What happens if the person who oversees signal generation is on vacation or out sick or leaves the company? What if the data feed breaks or is corrupted? Are there other employees who understands the ins and outs of the algorithmic code and, most importantly, is qualified and trained to make the appropriate decisions and take corrective action if needed? 

The InvestiQuant team is a diverse, highly collaborative, cross-functional team consisting of traders, full time software engineers and data analysts. We have the financial wherewithal, personnel and processes in place that ensure critical operations within our company structure will continue in a streamlined manner, no matter the circumstances. Why? Because we risk our money side-by-side with our clients in the exact same trading programs each day. 

Are Your Trading Operations and Algorithms Backed-Up With 24/7/365 Power?

All critical InvestiQuant trading signal software and data are safely and securely stored, and backed-up, in cloud-based hosting centers located near the exchange using Amazon Web Services (AWS). Our development team maintains backup power supply in the event of any power outages that sometimes do occur in North Carolina. (Hurricanes are not uncommon.) And, we have systems in place to facilitate and assure that all our trade operations continue, despite inclement weather conditions and situations. 

Have additional questions? Reach out to info@investiquant.com. 

InvestiQuant takes great pride in helping clients invest smarter using institutional quality, automated hedge fund strategies based on advanced machine learning and statistical edges. Whether you are a self-directed investor or a trader, you can be assured that your hard earned capital is being treated with the same care and diligence as our own. 

You know the saying: if it sounds too good to be true, then it probably is. 

Artificial intelligence (AI) is all the rage these days as tech giants race to capture market share. The promise of new and accessible technology has everyone trying to come up with the next greatest idea, and identifying market opportunities with AI is just one facet of this AI boom.

Recent advances, often demonstrated by generative AI leaders like OpenAI’s ChatGPT and  Google’s Bard, are making impressive strides in automating workflows, creating code, and churning out articles for the web. But these capabilities have yet to become readily applicable to the financial markets. 

Can You Ask ChatGPT to Predict Stocks? 

There’s no comparison: asking a chatbot to write an essay on the fall of Rome is hardly on the same playing field as asking ChatGPT the best trading strategies or to predict the S&P 500’s performance. In fact, generative AI tools like ChatGPT provide a disclaimer that they may provide inaccurate statements, or that they stopped collecting data nearly two years ago.

So, can you ask ChatGPT or Google Bard to predict stocks? Well, technically you could ask the chatbot, but should you is perhaps the better question. 

The Pitfalls of Relying on ChatGPT and Generative AI to Predict Market Performance

When it comes to recounting well-documented history, the task is relatively straightforward because there are few variables and assumptions involved. This is because the events have already taken place and most of the related information is known and recorded. 

However, making a trade or investment recommendation requires predicting the future state of the markets, and despite how advanced AI technology has become in the past year, these AI algorithms are only as good as the past data they have collected. Predicting future market performance requires these machines to make countless assumptions regarding the economy, government actions, and geopolitical events that may or may not ever occur - and this hardly scratches the surface! These stock market predictions also demand that AI considers the available capital, risk tolerance, and timeline of the inquiring investor.

Striking a Balance Between AI and the Trader for a Successful Investment

One of the appeals of autotrading is how it incorporates AI-powered algorithms to reduce the risk, volatility and flawed biases that human involvement may introduce into the equation. Naturally, you’d expect that an AI bot would be the shiny new solution for making investment decisions. But there’s a careful balance that must be struck here; AI chatbots like ChatGPT exist in a vacuum somewhere in the digital sphere. The human element may not seem necessary to execute a data-backed strategy, but in reality it is essential.

The generative AI widely available to the everyday person with an Internet connection was most certainly not devised to handle the complexities required to assimilate and normalize the vast and varying data required to make a forecast regarding future market behavior, or account for the many hidden risks of trading and investing. 

Of course, the dream AI-powered technology that many investors desire from AI bots like  ChatGPT is likely already available to the Wall Street elite, but what about the mainstream investor? 

Well, we believe generative AI is far more likely to be used for its glittering sex appeal than to be a holy grail solution for generating profits for the investing masses.

Alternatives to Stock Market Trading with ChatGPT, Google Bard, and Others

Over the past few years, countless firms have exhausted an array of artificial intelligence techniques to build investing models designed to conquer the markets. Unfortunately, success stories are rare, and some have even blown up in the process. 

So, how has InvestiQuant managed to successfully and profitably implement AI-driven  autotrading solutions while so many have failed? 

The Keys to Successful Autotrading with AI: iQ’s Stock Market Success 

1. Our focus is extremely narrow. Instead of trying to “boil the ocean,” we’ve chosen to focus on a narrow subset of markets (index futures) and the intraday time frame only.  When pursuing statistical edges, it pays to go deep - not wide. Our AI stock trading is designed with very specific risk constraints. Finding an edge in the markets that occurs regularly and with a high degree of certainty is worthless if the risk required to capture it is too high. InvestiQuant’s advanced machine learning algorithms don’t just identify if there is a significant probability of a directional bias in the market. Rather, they answer the more important question: “Is there a clear historical bias today, with attractive profit potential, that can be traded without exceeding our maximum risk tolerances?”

2. We started early and leveraged our trading experience. InvestiQuant was launched in 2008 as a statistical trading service. Our strategies were based upon thoroughly researched - but rigid - rules using market factors that had historically demonstrated an edge. As the markets evolved and some of our edges waned, we struggled to incorporate new factors and improve our signals.

In 2013, we made a conceptual breakthrough and created our Machine Learning 1.0 engine. It allowed us to expand our strategy inputs tenfold by organizing them into categories that we, as traders, believed to be uniquely predictive for the intraday session. The ML engine was engineered to auto-update the factors nightly to adapt to changes in market conditions, as well as their historical performance for each market environment. By ensembling the different factor groups and making them market-adaptive, we were able to create a powerful directional bias indicator that dwarfed the best results of any single indicator, or group of indicators. 

To refine our innovative approach, we collaborated with Duke University's Center for Quantitative Modeling in 2015 (the Director subsequently became a Board member and investor in our company). Though we tried, it took seven years to improve upon this first-generation approach. In fact, iQ’s Machine Learning 1.0 engine continues to drive many of our best trading strategies today. 

3. We are nuts about data and continuous improvement. Artificial intelligence is only as good as its data. As the saying goes: "garbage in, garbage out." With the incredible horsepower afforded by advances in machine-learning technology and generative AI, this concept is especially true. 

Over the past two decades of observing markets and their behaviors, we have accumulated a massive proprietary database of market factors. And we don’t just buy 3rd party data and plug it in. Nor do we outsource the tedious and laborious processes of data checking, correcting, scrubbing, and formatting. We manage our data completely in-house using our own data scientists who follow strict protocols. Why? Because we risk our own capital with the same InvestiQuant algos and strategies that we license to our clients and bad data = bad results! 

4. When trading intraday, robustness and speed are king. In 2020, we realized that to take full advantage of our ever-growing database and IP, we needed to utilize the most advanced AI technology available. So, we embarked on a nearly 2 year R&D project. And in late 2021, we launched the iQ Machine Learning 2.0 engine. It was a significant upgrade to the ML 1.0 engine, in that it could process the real-time state of every factor in our database (nearly 1,000) and generate statistically robust predictions every minute (faster if needed)—something not remotely possible using our first-generation engine and approach. 

The Future of Trading Stocks with AI 

If it sounds like we have it all figured out, we don’t. However, we do have well-established AI machine-learning technology and proven processes for finding and trading real, statically-based edges using our autotrading programs. Most importantly, our strategies have stood the test of time and are not based on fanciful, over-optimized backtesting aberrations created by an amateur programmer or inexperienced quant researcher. Like all things in trading, and perhaps even more so with artificial intelligence: buyer beware!

Introduction

There is much more to autotrading than meets the eye. Despite the sound of “auto,” there is an abundance of hard work that goes on behind the scenes to deliver a powerful, trustworthy investment solution that has the greatest probability of achieving the investor’s financial objectives. 

The client, the broker, and the algorithmic developer each play a vital role in ensuring the automated trading solution is properly enabled and successful. Each is a part of a whole that works together. 

• The client licenses the desired autotrading program(s), provides and maintains appropriate funding levels, and monitors their account balances. 

• The broker facilitates the process by connecting clients’ accounts with the appropriate autotrading solution, oversees trading execution and provides personalized support. 

• The developer creates the adaptive trading algorithms and maintains seamless integration with the broker’s systems for optimal trade execution.

The collaborative relationship between these three parties creates an environment in which investors can maintain control and visibility, while enjoying the most hands-free investment experience possible. 

When considering automated trading solutions with IQ, it is crucial to understand the different parties involved in the autotrading process. In this blog post, we will explore the roles and responsibilities of clients, brokers, and ourselves in operating algorithmic trading programs.

What Are Your Responsibilities as the Client?

As a client, your tasks are limited, yet essential. The first step is to select and license the iQ Autotrading program best suited for your desired investment amount, financial goals, and risk tolerance.  InvestiQuant will then connect you with one of our approved execution brokers who will assist you with submitting the required information for opening and funding a private investment account.  Most investors’ accounts are established in their own names and are typically approved for trading within 24-48 hours.  Entities and individual retirement accounts are a bit more involved and take longer. 

Once your account is set up, it will be automatically enabled for trading alongside the accounts of InvestiQuant’s principals and our many other clients. When trading commences, your responsibility shifts to simply monitoring your account balance from time to time. (Daily is probably too frequent and monthly is typically about right for most.) 

Important: If at any time you wish to pause the trading of your account, or you need your funds for another purpose, simply notify the broker. Note: InvestiQuant, as a professional signal developer, has zero visibility or access to your funds and accounts. We focus solely on creating, maintaining, and transmitting the best quantitative trading signals possible. You maintain total control of your account and funds at all times. 

What Are the Responsibilities of the Broker?

Brokers play a pivotal role in supporting your algorithmic trading journey. They assist you in setting up your account at one of InvestiQuant’s approved futures merchants (also known as “FCMs”). FCMs are highly secure and regulated firms (by the NFA and CFTC) that act as the custodian of your funds and facilitate the trading of your account via the Chicago Mercantile Exchange (CME) using index futures contracts. 

Index futures are derivatives of the S&P 500 - a stock market index comprised of 500 of the largest companies traded on the New York stock exchange in the United States. Futures contracts are ideal instruments for algorithmic trading (long and short) and provide a superior leveraged trading opportunity, while minimizing cash requirements and taxes.  Their many advantages make opening a futures account at an authorized broker well worth it!  (Note: trading involves risk and is not suitable for everyone. Please consult a registered futures broker for more information.)

In addition, the broker's team is responsible for connecting your account to the desired  autotrading program and ensuring error-free execution of the iQ algorithmic strategies. They also assist clients with adding and withdrawing funds as needed and managing any margin-related issues. Additionally, brokers provide daily and monthly statements to keep you informed and updated at all times.  In return for their many critical tasks, brokers are compensated via a low cost commission structure that we’ve pre-negotiated on behalf of our clients. 

What Are the Responsibilities of the Developer?

As algorithmic strategy developers, we are akin to the builders and maintainers of a jet airplane upon which your hard-earned capital will fly in—integral and crucial to the entire autotrading process. 

Our responsibilities involve developing, maintaining, and monitoring the markets, data, strategies, and execution network that support autotrading from start to finish.  Using our decades of professional trading and software development experience, we create and deliver the statistically-based signals that the broker’s software uses to trade your account.  Our team is focused on ensuring that our algorithmic trading system operates smoothly, efficiently and flawlessly every trading day of the year.  Because we also risk our own capital and rely upon the very same autotrading programs as our clients, you can rest assured that we are highly motivated to do our absolute best in maximizing profits and minimizing risks every step of the way. 

Conclusion

In the world of automated investment strategies, success hinges on institutional-quality software and the highly synchronized, collective efforts of the client, broker, and developer.  Just about anyone can create an algorithmic strategy, but it takes a diverse, veteran team of trading and software professionals to deliver autotrading solutions that you can count on, day in and day out, 252 trading days a year. 

Contact us today if you’d like to learn more about InvestiQuant and how we might be able to help you better diversify and grow your wealth. 

If you’ve followed InvestiQuant for a while, you’ve probably heard us quote Ray Dalio’s mantra that diversification is the holy grail of investing. But actually, it’s not. Diversifying one’s wealth across investments that move in tandem with one another is of little value to an investor. The key to unlocking the benefits of portfolio diversification lies in the concept of low or no correlation. 

Correlation refers to the statistical relationship between different assets or investment strategies. It can be positive, negative, or zero. Positive correlation means that two assets tend to move in the same direction, while negative correlation suggests they move in opposite directions. Zero correlation means there is no apparent relationship between their movements. Non-correlated (a.k.a. uncorrelated) strategies have a correlation between -.1 and .1.  The closer the value is to +/- 1.0, the more positively correlated / negatively correlated the strategies are to one another.  Why is this important?  Because diversification alone is not enough when investing.  

Diversification is the practice of spreading one’s wealth across different assets or strategies with the aim of reducing risk. However, diversifying across highly correlated instruments, for example Apple and QQQ, does not reduce one’s risk since they will rise and fall in near lock-step with one another due to their values being driven by the same market factors. However, by diversifying with low-correlated investments, investors can minimize the odds that all of their investments will underperform at the same time. The inclusion of unrelated assets helps smooth out the overall performance of the portfolio and cushion against losses incurred by any single investment or segment.

When assets and investment strategies perform independently of one other, they provide two significant advantages to investors: 

• Less Risk - When investments are lowly correlated, the risk of a ‘perfect storm’ of market factors (think Dot Com crash of 2001 or the Great Recession of 2008) causing a financially devastating (or emotionally unbearable) reduction in one’s net worth, is much lower. 

• Less Volatility - By combining multiple non-correlated strategies in a portfolio, investors can improve their risk-adjusted returns and increase the likelihood of capturing positive returns during all market environments — without increasing their overall portfolio risk. In layman’s terms, the investor can realize more consistent, less stressful growth of their wealth over time.

The real holy grail? Diversifying with investments that are proven to be lowly correlated in both good and bad economic times. 

(Tip: Many stock related investments can appear to be lowly correlated in bullish markets, but in reality be highly correlated in bear markets. This concept is called “crisis correlation” and savvy investors should carefully consider this dangerous phenomenon when constructing their portfolios.)

Appropriate non-correlated investments will vary for each investor based on the components of their portfolios. However, most traditional stock investors can benefit from the low correlation between iQ Autotrading and equities: Here’s a table of the iQ programs and their correlation to the S&P 500.