Investment Algorithms

Computers have become an integral part of the financial market, not just as tools for investors and traders but also as a way to autonomously determine investing strategies or even carry out transactions. For example, CARL gives you unprecedented access to sophisticated quantitative hedge funds which make their investment decisions based on data-driven algorithms. This strategy is incredibly effective, and our quants have 15%+ targeted returns. Investment algorithms have clear advantages over traditional decision-making processes in the financial world.

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There Are Two Ways of Approaching Algorithms in Finance and Trading

Before examining how algorithms can positively impact investment success, we need to understand the term "investment algorithm". There are two related but sufficiently distinct ways to use them in a trading context.

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Algorithmic Trading

When a trader engages in algorithmic trading, this usually means they are using computer systems to automate their trades to a significant degree.

For example, they may use AI-driven systems to buy and sell stock at the time of maximum profit or use them to exploit minor inconsistencies in stock prices (arbitrage). Their trading software typically uses market simulations to predict price changes which then automatically executes whichever orders might benefit you most.

High-frequency trading relies heavily on trading algorithms making automated decisions. This is because human traders simply wouldn't be quick enough to take advantage of the many small opportunities which high-frequency trading aims to exploit.

Let's use a simplified example: Using machine learning, we have taught artificial intelligence how seasonal changes affect the price of commodities such as grain. We then set our trading system the task of buying and selling grain stock in such a way as to create maximum gains. The system will have learned that the price of grain peaks in certain months and dips to its lowest point in other months, so it will buy and sell according to this seasonal model.

Most modern algorithmic trading systems aren't that simplistic, of course. They often take into account market trends, macro-scale events, or even the behavior of other traders – all in real-time. This has led to some criticism, as the trading software may start selling stock as soon as it realizes a large number of other investors are also selling (since this may cause the price to drop significantly). This could create a cascading effect that could send stock prices plummeting. That's why some algorithmic traders may choose to exercise a certain amount of human oversight over their otherwise fully automated system.

The Quantitative Approach

A similar way of using algorithms for trading is quantitative analysis, as used by the quants to which CARL can give you access.

Quantitative analysis uses algorithms, machine learning, computer-generated market simulations, etc., to guide investment decisions – though importantly, the actual trading may still be done by humans. This has the effect of creating some measure of oversight, limiting the risk of using automated systems. That way, quants can avoid sudden short-term buying or selling sprees created by fully automated systems – if they choose to employ human oversight.

The main difference between quants and traditional hedge funds lies in their respective decision-making processes. Standard funds typically have one or more high-profile investment managers who collate data (such as an asset's value and volatility), their own experience, and a measure of intuition to decide which investment vehicle the fund's portfolio should focus on. Quants use algorithmic trading strategies which rely solely on data – but they typically draw from a more comprehensive selection of data points. For example, if a quant's algorithm notices that the GDP of a country on the verge of industrialization has been rising over the past few years, it might decide that investing in assets such as entertainment products in that country may be a wise decision, as the population will soon have more disposable income for such "luxuries".

The great benefit of quantitative funds is that they significantly limit the risk of human error by taking fund managers out of the decision-making process – without eliminating the human element. The traders and computer scientists at the helm can still decide which information to feed the trading system and how to train the machine learning algorithms. This is why quants whose algorithms have been fed useful information have consistently outperformed most traditional hedge funds. This is particularly true in very volatile market environments, in which human managers tend to be more prone to overvaluing or undervaluing assets.

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Why Investors Can Benefit Significantly From CARL’s Quants

Quants are still a relatively new thing in the trading world, even among savvy investors. This is mainly because using trading algorithms seems like a daunting proposition at first. Many investors – new ones in particular – find it easier to relate to human fund managers than to a trading software supervised by computer scientists and mathematicians. Which is why they often open their portfolios to the possibility of bad calls made by a manager instead.

Recent history has shown that mistrust in algorithmic trading strategies is wholly unjustified, as even during market crashes and recessions, quants have typically performed better than traditional funds. This is no surprise to those in the know, as financial algorithms are rigorously backtested before they're employed. "Backtesting" means an algorithm is put in a sandbox environment and fed data on a historical market situation. The system is then asked to make investment decisions in this sandbox. The results are compared to actual market developments from that historical point onward. Only if the algorithm managed to beat the market in this historical sandbox environment can it even be considered ready to be employed for actual decision-making. Such backtests are done frequently during the development of the algorithm to ensure the final version of the software will be as refined and as accurate as possible.

In short: The algorithmic systems used by quants are typically highly reliable, and they tend to outperform other hedge funds. For example, CARL's quants feature 15%+ targeted returns, which provides your investment with significantly greater growth potential than most other investment opportunities – including alternative and traditional investments such as mutual funds, exchange-traded funds (ETFs), the stock market, etc.

How to Spot a Reliable Algorithm

Even if you have already spent years actively investing in the market, you likely won't know how to assess quants. This is because their financial decisions are made by anonymous trading software. This software is being programmed by people who might have made a name for themselves in the information technology sphere – but probably not in the financial world. All you have to go on are:

  • Computer or data science credentials
  • A proof of concept using the algorithm
  • Information from the quant's prospectus

You might think that it's a daunting task for someone not well-versed in the IT world to identify reliable quants. And you'd be right – but that's where CARL comes in. All of the quants in our portfolio go through our due diligence process to determine whether they are a promising and trustworthy investment vehicle for you.

That's not a guarantee of success – all hedge fund investments naturally carry a certain amount of risk. But it does mean you're not on your own when it comes to figuring out your investment options. You won't need to spend time and money researching which funds are currently open to investors and which of those are feasible based on their trading strategy, the talent involved, etc.

All you need to do is qualify as an accredited investor, set up your CARL account, and you're good to go. The CARL app provides you with all of the relevant information, from annualized volatility to historical performance, making your investment decision much easier.

Making Algorithm-Based Funds Part of Your Strategy

Sometimes, you may not want to invest all of your money into algorithmic trading vehicles. Perhaps you're not aiming to get the greatest profit possible. Maybe you prefer to put some of your money into funds that don't use trading algorithms because you think supporting them is a worthy cause.

Quants trading via algorithms don't need to be the focus of your portfolio – they can also be used for diversification.

In that case, you can use algorithmic funds like CARL's quants to diversify your portfolio. As they're entirely data-driven and use hedging strategies as a risk control method, quants offer significant gains at manageable risk. While they're not risk-free, this does allow you to control the overall risk that your portfolio is exposed to. So if, for example, you're putting a significant amount of money into a worthy cause that may be highly volatile or doesn't offer great returns, you can use quants to pick up the slack.

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3 Easy Steps to Start Investing With CARL

Investing in quants is as easy as pie if you've got CARL on your side. Investors can set up an CARL account quickly and easily.

Set Up Your Account

Quickly and securely connect your CARL account to your bank and transfer investment funds.

Analyze Investments

Using the tools within the CARL app, determine which strategies at what allocations are right for your investment goals.

Fund Your Investment

Simply save your portfolio settings and on the next strategy funding cycle your investment will be live!

Enjoy the Benefits of Investing Algorithms

With the CARL app, you can access to sophisticated quants and benefit from investment opportunities based almost entirely on data. Avoid human-induced trading errors and profit from 15%+ targeted returns at a minimum investment of only $20,000, with built-in risk controls. Add CARL to your portfolio today.

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