There's not an institution out there - hedge funds, mutual funds, insurance companies, super funds - that doesn't employ investment algorithms. In fact, the biggest investing entities employ algorithms every day.
And yet, time and time again when I speak to individual investors I discover two things…
- They've never heard of an investment algorithm and don't know what it means.
- They're not working with money management professionals who employ investment algorithms.
This knowledge gap leaves individual investors at an extreme disadvantage. Especially because a fundamental underlying problem for the individual investor today is that most brokers and investment advisors are salesmen. They continue to sell the way they always have - they talk about valuations and P/E ratios, etc.
The problem: Algorithms are designed knowing that that's the subject of so many conversations. They count on the fact that you're still hearing the old key words and they take advantage of the incited emotions, whether they be greed or fear.Investment Algorithms and the Individual Investor
To be fair, the brokers aren't solely to blame. Fundamental research worked well for several decades. Now, however, its value has decreased in direct proportion to the rise of the machines. In the past three to five years the same brokers and advisors who saw success with valuations now can't figure out what's wrong, or why they're not seeing the financial gains they've come to expect. To us, it's simple:
If you're not employing investment algorithms to direct your investing you are at a direct disadvantage in the world we live in today.
For further thoughts listen to the podcast below, or continue reading…
Prefer to listen rather than read? Check out the investment algorithm podcast....How Investment Algorithms Take Advantage of the Individual Investor
There are pain points in a portfolio; algorithms are designed to sniff out those pain points and take advantage of them. Further, investment algorithms are designed to take advantage of human emotion - whether that be on a top-day trade, or over a series of days and weeks.
Essentially, if you're not using investment algorithms to direct how you put money to work then you're bringing old tools to a new battle. The best analogy is that you're bringing a knife to a gunfight. Naturally, this approach will only lead to confusion and disappointment.
If you don't employ algorithms to help direct your capital then you're at risk of being manipulated.
The New Way Capital Is Put To Work
In response to how events of 2008 devastated investors' portfolios (and the subsequent manipulative response by central banks) we've focused on portfolio rehabilitation via investment algorithms. This represents a part of our effort to fill the gap between institutions and individuals.
Another part of that effort lies in demystifying the trading landscape. We do that by sharing how investment algorithms have changed the financial investing process. Shedding light on that specific subject is the reason we decided to do the series of podcasts that begins with the one posted above.Things Have Changed Since 2007-2008
Over the past ten years we've witnessed a paradigmatic shift in the way capital is put to work, and in the manner in which debt markets, currency markets, etc., behave. This has impacted all of us, and the shift has left behind a number of individual investors who don't understand what's happening. Instead, they find themselves confused, frustrated and afraid.
(If that sounds familiar, sit tight: You're not alone. A lot has changed since the crisis of 2008.)
Our goal here is to explain exactly how things have changed and help you learn the disciplines required to succeed in the new environment.
To begin, here are three critical things you need to know - that your financial advisor most likely hasn't yet discovered.#1 Investment Algorithms Rule Today's Markets
A year ago Greenwich Associates estimated that electronic trades represent about 55% of U.S. equity trades. Around the same time Reuters suggested that "automated trading accounts for about 75 percent of all financial market volume."
Those of us deeply engaged in and following industry trends suspect these statistics to be much higher. It's reasonable to guess that 90% of trades today are executed by computer investment algorithms.
In the trading realm investment algorithms operate in a variety of ways. For example…
A popular algorithm for institutions is an execution algorithm. (We're all familiar with the bastardization of these investment algorithms by high frequency traders.) Often employed by insurance companies and super funds these investment algorithms process their orders by relying on execution operations to gradually parse large orders into smaller amounts. The objective here is to reduce transaction costs and achieve best prices. By posting updated quotes these types of algorithms automatically respond to changing market conditions.
Smarter and faster than humans, execution algorithms replace human market makers. A major outcome of this shift: it allows machines - that have no obligation to create stable markets - to impact the trading environment (i.e. by immediately pulling out when the market gets shaky). Since the proliferation of these investment algorithms we've seen a rise in potential for "flash crashes," a quick drop and recovery in securities prices.
Another (increasingly popular) type of investment algorithm is deep learning, i.e. artificial intelligence. These algorithms contain connected layers of inputs and outputs. Typically, there are three layers:
- Input receives data related to information about factors that are expected to drive the returns of a security.
- Hidden adjusts the weighting of inputs to continually reduce error.
- Output can consist, for example, of buy/hold/sell classifications.
Another largely employed type of investment algorithm is the proprietary investment algorithm. This is the kind we use here at Rosenthal Capital. Technically, these investment algorithms are designed around probability and statistics. Specifically, they help us statistically understand where the correct entry points are from a potential reward versus risk standpoint.
Just this quick overview of investment algorithms reveals the enormous size of the institutional trading footprint. Such a scenario dramatically decreases the ability of the individual investor - operating without investment algorithms - to achieve significant trading and investing success.#2 Central Bank Intervention Manipulates Capital Markets
Massive central bank intervention in capital markets explains why the decades-old practice of valuation has significantly lost relevance. In fact, this relatively new central bank practice marks a major shift in the investing playing field.
Pre-2008 we had a long history of valuations. This led to a clear understanding of when things were undervalued or overvalued. In the pre-2008 era these indicators were often accurate and very useful.
However, the past three to five years have been so difficult (and led to much fear and confusion) because valuations have lost their worth. The actions of central banks have shifted the playing field.
Here's an example of what I mean:
Rather than updating their processes many financial advisors still use valuations to decide when to buy the market or individual stocks. In our current market they often think that (based on the past fifty years) valuations look obscene today. However, today central banks are directly participating in equity markets.
What does that mean? A central bank prints money. In fact, a central bank can print as much money as it wants. Then, it pours that capital into, for instance, Facebook. According to Reuters the Swiss National Bank (SNB) - the world's eighth biggest public investor - "owns more publicly-traded shares in Facebook than Mark Zuckerberg, part of a mushrooming stock portfolio" that includes many U.S.-based companies as the chart below illustrates.
(Source: Zero Hedge)
Another compelling recent example: The Central Bank of Switzerland bought four million shares of Apple in the last three months. This enormously built on the number of shares that had already been amassed by Q4 2016.
(Source: Zero Hedge)
Furthermore, in the first three months of 2017 central banks have committed equivalent to $1 trillion of capital to equity markets and debt markets in the Western hemisphere.
With this kind of unlimited capital coming into the market it's impossible for valuations to make sense. Suddenly, the last ten/twenty/forty years worth of valuation statistics means zero.
Naturally, this creates frustration. You or your investment advisor might think, "I can't put money in that. The valuation's not right." Or worse, the frustration leads to contrarian investing and you begin shorting into the face of a tidal wave of central bank capital flows.
You're using a knife in a gunfight.
This scenario illustrates exactly why it has become essential to work with someone who can use investment algorithms.
On our trading desk we extensively (and on a daily evolving basis) develop, write and code proprietary investment algorithms using our personal capital, time and experience.#3 Institutions (Still) Have More Access to Information Than You Do
In conclusion, let's crystallize what's going on:
Institutions and individuals are always at odds. Historically, the institution is always perceived as having more information than the individual.
Pre-2008, what everyone focused on, cared about and opposed was how institutions use their wealth, influence, etc., to gather information on a company and then invest in it. And doing all of this while the individual didn't have access to the same information.
Because this scenario is so unfair many rules and regulations have been developed to try to level the playing field. In the big picture, this is a good thing. It is only fair for everyone to get the same information at the same time.
But guess what? The playing field of how institutions gather information has shifted. Investment algorithms now offer that new piece of information that institutions have always sought.
While processes and practices may have changed the truth is that today's world contains many similarities to earlier times. As a matter of fact, the divide between institutions and individual investors echoes the same type of problem that existed in earlier decades:
Institutions continue to use capital to their advantage. Today, that means they build algorithms to gain edge. (Or, what we call, "alpha.") This allows institutions to access that new information while individual investors still cannot. Consequently, the individual investor experiences frustration, confusion and fear.
Avoiding these uncomfortable feelings is why it's so important to work with investment advisors who use investment algorithms. In the end, that's the answer to the old tools/new world predicament.
If you want to be on the same playing field as institutions - if you want there to be equality between institutions and individuals - then you've got to have access to institutional quality investment algorithms. That's the world we live in today.
Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.