How to Invest in 2017 Stock Market Volatility [PODCAST]: A Step-by-Step Example of How investment algorithms help guide investment strategy in 2017 stock market volatility.

A Step-by-Step Example:

How investment algorithms help to protect capital and still capture upside

How to invest in the 2017 stock market is a question experts and individual investors have been asking since before the year began. For example, in early December 2016 three financial advisors sat down with the Wall Street Journal specifically to discuss how to invest in 2017. Their advice began by predicting volatility:

“[We] think the bull market is getting long in the tooth,” one explained.

Unintended consequences of Trump’s policies and investor complaisance with valuations were cited as reasons to expect stock market volatility in 2017.

At the end of January Bloomberg Markets echoed this stock market forecast in the aptly titled piece, “2017 Is Shaping Up as a Volatile Year for Markets.”

While suggesting that “Volatility is likely to trend higher through the course of the year as markets react to a range of unknowns” the very next paragraph concedes that despite Trump policy disruptions January 2017 was still less volatile than its two predecessors.

The Collapse of U.S. Stock Market Volatility

Throughout the first quarter 2017 markets continued to define themselves. While everyone was expecting it the much-touted volatility …. did not materialize. According to CNN Money at the end of the first quarter “…market volatility remain[ed] low. The VIX volatility gauge [was] sitting at just 12, down from 22 right before the November election and north of 40 amid the turmoil of August 2015.”

In fact, according to Jason Goldberg’s research at Pimco, “U.S. equity volatility, as measured by the simple average of volatility of the top 100 current stocks in the S&P 500, is at multi-decade lows.”

Why Has U.S. Stock Market Volatility Collapsed?

Goldberg deliberately points out that the decreased volatility directly coincides with the increased uncertainty about the current administration’s political agenda. Even so, Goldberg, too, expects that 2017 stock market volatility could increase – specifically, when policy advances (i.e. related to tax code or healthcare reform) occur.

Now we’re at the end of May, about a week after CNN Money reported that the VIX (one of the market’s measures of volatility) had spiked nearly 40%.

U.S. Stock Market Volatility on the Rebound?

Where we go from here is anyone’s guess. What remains very clear from the above summary, however, is that the predictions for this year’s volatility are, themselves, volatile and unpredictable.

In the face of the collective political and financial uncertainty the individual must make many decisions. What investment strategy does he choose for how to invest in 2017? Stock market volatility will, at some point, arrive. How does an individual investor protect his nest egg assets while also achieving growth?

To learn a part of the answer listen to the podcast and read on….

The Benefit of Investment Algorithms for the Individual Investor

by Bret Rosenthal

In this step-by-step analysis straight from the Rosenthal Capital Management trading desk, Head Trader and Principal, Bret Rosenthal, explains how algorithms can help protect capital and still capture the upside.

Have questions about what you hear on the podcast or read in the investment algorithm article? We love answering follow ups: Call or email us.

How to Invest in 2017 Stock Market (Volatility or Not)

The fact is, we live in a world driven by algorithms. (So much so that the Schwab perspective partially “blames” algorithmic trading for suppressing volatility.) Which means, algorithms offer an essential ingredient in deciding how to invest money in stocks. Any decision for how to invest in 2017 stock market (volatility present or absent), then, must incorporate the presence of algorithms in some way.

This is especially true since investment algorithms have evolved to a high degree of efficacy. To capitalize on 2017 investment opportunities one must utilize these important post-2008 institutional investing tools in the individual investor’s portfolio.

At Rosenthal Capital that’s exactly what we do. Specifically, we have developed proprietary investment algorithms to help direct our investment into the major indexes (S&P500, NASDAQ100, Small Cap Index and 20+ Year U.S. Treasuries). Since three out of four stocks follow the S&P500 the information from these algorithms lends itself to a wide range of applications.

Using ETFs in Your Investment Strategy

In addition, we use exchange traded funds (ETFs) to invest in those indexes. This makes it easy for individual investors to participate. Rounding out our platform, we have specific algorithms designed for chosen groups in the stock market.

Exploring how to invest in 2017 stock market fluctuations engenders many approaches. Today I’m focusing on our investment strategy related to:

  • Gold and gold stocks (GDX is the relevant symbol)
  • 20+ Year U.S. Treasuries (with the ETF: TLT)

A single quest drives the development of our investment strategies:

To employ proprietary institutional-quality investment algorithms to preserve capital while still capturing the upside. 

For example, we have developed many proprietary algorithms specifically designed for the volatility of each asset listed above. The interplay between these investment algorithms helps protect capital and still capture upside. Thus, an investment strategy becomes very flexible and dynamic.

Managing Unpredictable Markets

To see how effectively this works I’m going to walk you through a step-by-step example from the week of May 15th. (If you’re a student of the stock market then you know: This particular week equities had a significant sell-off on Wednesday, May 17th).

In our cockpit we were very prepared for that Wednesday sell-off. Why? Not because we were guessing what the market was going to do – and not because there were news stories about President Trump that made us take action – but because of the signs we received from our investment algorithms.

Quick disclaimer: It’s important to remember that algorithms are not crystal balls. They’re not guessing the future. They’re not witchcraft.

What we’re by employing investment algorithms doing is very simple:

We’re using statistics and probabilities (based on extensive back-testing over the last decade) to tell us when risks are elevated or when reward is so significant that it’s worth taking risk.

While investment algorithms can’t predict the future, they can help you better manage it.

Algorithms Impact Choices in Stock Market Investing

There are many ways that investment algorithms can have a huge impact in how to invest in stocks. Two of our favorites and most utilized are:

First, algorithms reduce the emotions that can interfere with disciplined investing. Guesswork and news-related reflex decisions usually fail. Certainly, they don’t succeed over an extended period of time. (We’ve all experienced that “lucky once or twice” phenomenon. However, over an extended period of time emotions like greed and fear just eat away at your profits.)

What algorithms can do is dramatically reduce dependence on emotions and begin to increase your assets with reduced draw downs. We want to preserve capital but still capture upside – when investment algorithms suppress the effects of emotions they help you do that.

Second, algorithms use statistics and probability to assess the risk vs. reward. When that equation is optimal it’s time to put money to work. The aggregated data that algorithms provide dramatically alter and inform how an investor perceives the reward vs. risk potential of every stock market investment. Understanding each investment’s location in this matrix can intelligently guide how to invest in 2017 stock market volatility.

Let’s walk through a step-by-step analysis of why in our individually managed accounts and hedge funds were prepared for the move lower in the markets on Wednesday, May 17th.

Step #1: Signs From the Major Indexes 

At the end of April (4/19-21) all three of our algorithms on the major equity ETFs – S&P500 (SPY), NASDAQ100 (QQQ), Small Cap Index (IWM) – were telling us to be long all three of those indexes.

When all three go positive at one time that basically tells us that the reward from here is worth the risk that we’re going to be taking. We use this investment strategy in our portfolios in two ways:

  1. You can either directly trade the ETFs and actually go long those assets following the algorithms.
  2. You can infer that: If three out of four stocks follow the indexes then if the indexes are saying, “Now is the time take risk,” you can go into your favorite basket of individual equities and start putting those positions into your portfolio.

So, directly trading the ETFs or investing in favorite equities were the two choices at the end of April.

Subsequently, coming into Friday of last week (May 12th) a number of things happened. The interplay of our algorithms told us that instead of going long it was actually time to protect capital.

In summary at this point:

  • At the end of April reward was worth the risk.
  • By the middle of May risks had risen so dramatically it was time to protect capital.

Step #2: Signs From Precious Metals and U.S. Treasuries

The first algorithm to indicate that something in the market had changed in mid-May was our algorithm on precious metals stocks.

Let’s look at GDX:

On Wednesday, May 10th our algorithm on GDX told us to get long the gold stocks. In and of itself that doesn’t tell us to start reducing positions on equities. However, because this asset is negatively correlated to the equity markets (S&P, NASDAQ, Small Cap Index) it tells us that risk could be rising. So, if one were to get long there you’d want to realize that risk may be elevated in the big equity indexes.

On Friday, May 12th, our algorithm designed to invest in 20+ Year U.S. Treasuries (we use the ETF: TLT as our tool for that) indicated that it was time to get long.

Collectively, our algorithms were suggesting to put on positions in two negatively correlated assets (that go up when equity prices come down).

This naturally reduces risk and allows the protection of capital. One could still be long the major indexes — but now also long the indexes that will go up if equities roll over. Again, risk dramatically reduces.

Step #3: Signs From the Small Cap Index

On Friday, May 19th, our algorithm designed for the Small Cap Index (the ETF we use is IWM) indicated to be 100% cash.

This Small Cap signal meant a lot to us. We interpreted it through more than thirty years of experience working together. During those decades we’ve seen this happen over and over again: Small Caps are the canary in the coal mine. They almost always lead on the downside for equity markets. The reason is simple:

Big institutions – and we now have to include central banks in that category – focus their capital flow into Big Cap stocks. They don’t, however, support the Small Cap arena.

For example, the Central Bank of Switzerland now owns more public shares of Facebook than Mark Zuckerberg. Yet they don’t own shares of LogMeIn. (Never heard of it? That’s because it’s a Small Cap.) The institution of the Central Bank of Switzerland does not support Small Cap stocks. So, when things start to unravel in the equity market in general they first unravel in Small Caps.

By Friday, May 12th, then, our algorithms looked like this:

  1. Long position in GDX (counter to the market)
  2. Long position on long-dated government bonds (TLT); another warning sign that something could be wrong with equities
  3. 100% cash Small Cap allocation

Those are three major strikes against the stock market. What all of this tells us is that risk is elevated. Consequently, it’s time to start thinking about how to protect capital.

Again, there are two ways to do this:

  1. Directly invest in these assets (and so your portfolio could be long Treasuries and gold stocks to match it against your favorite Big Cap stocks, for instance).
  2. You could start selling off some of your equities and booking profits from the run that you’ve had since the end of April.

Step #4: Signs From the S&P500 (SPY)

The S&P is our favorite index to use and our most sensitive algorithm. The more data you have, the more volume you have, the better and more effective your algorithmic information.

(Note: There are few things that trade more liquid than the SPY. So, we have a high degree of probability when we trade this index.)

Picking up our analytical thread…

On Friday, May 12th we had already gotten the signals to:

  1. Go long gold stocks
  2. Go long 20+ Year U.S. Treasuries
  3. Sell Small Cap stocks

Then, the SPY algorithm gave us what we call our “Profit Protection Exit” signal. It told us that risk was dramatically increased at this point.

The correct response: Reduce exposure in the positions that were bought on April 24th.

Following this investment strategy your portfolio would have been already protected on Wednesday, May 17th. Such protection would be critical when the following three things occurred:

  1. Dow dropped 350 points
  2. S&P dropped 1.75%
  3. Small Caps dropped 2.5%

Algorithms Offer A Systematic Approach to Stock Market Investing

In conclusion, all four of the major steps outlined above happened between mid-April and mid-May. Viewed collectively they reveal a prime example of how algorithms can protect capital but still allow you to experience upside in your portfolio.

In this example the highlighted steps relate to a specific, short time frame. However, the illustrated process for how to invest money in stocks remains evergrene:

  • Markets behave erratically.
  • Algorithms interpret compiled data.
  • Investors respond to algorithmic information.

Collectively, these bullet points offer a road map for how to invest in 2017 stock market volatility — and beyond.

Want To Learn More?

Read about the power of investment algorithms and how they can benefit the individual investor. 

The Rosenthal Capital Management blog explores how algorithmic trading strategies help individual investors get better returns.

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