The Markets Speak: The Great Flood Of Liquidity

Summary

• Those who get their "knowledge" from rumor and opinion, rather than from data, have paid a very high price.
• Financial markets have undergone a tremendous shift in the past two decades.
• Large herds of investors quickly herd in and out of popular indices at the click of a button.
• These movements create large statistical footprints and exhibit classic herding behavior. However, separating signal from noise is difficult without cutting edge technology.
• Valuable fundamental information is imperfectly distributed. Therefore, prices move before all competitors in the market have the complete fundamental picture, or before they have processed it accurately.
• Looking for a helping hand in the market? Members of ZOMMA Algorithms get exclusive ideas and guidance to navigate any climate. Get started today »

My service signaled a move to cash for our subscribers on Feb. 21 at 9:55am, within 1.6% of the all time high for the S&P 500. It was satisfying to signal an exit an the all time top. But the subsequent flood of Fed liquidity can created whiplash inducing market moves that terrify most investors.

Here is a useful empirical framework that guides a rational algorithmic approach:

First, fundamental data is widely reported. However, market prices react to both fundamental data, and increasingly, to central bank liquidity injections.

Second, heavy-handed central bank moves to inject and to withdraw liquidity often override economic fundamentals in the short to medium term.

Third, markets react to economic fundamentals, to corporate fundamentals, and to central bank gambits to inject and to withdraw liquidity.

Remember that, although market participants focus on explicit Federal Reserve policy decisions, day-to-day open market operations, in which the Federal Reserve buys and sells bonds on the open market, are just as important.

Fourth, Federal Reserve open market operations create trends, or serial autocorrelation, in the direction of asset classes.

Over time, the interplay of these variables creates the winners and the losers of the game.

Algorithmic methods can often sniff out important statistical footprints. I use my Zomma Directional Algorithm to take advantage of trends created by the flow of investment dollars reacting to the interplay of these variables.

The algo does not use form fitting. It uses the same settings on every market. Here's how to understand the results:

1. When the yellow line crosses above the green cloud, it signals a buy.

2. When the yellow line crosses back into the top of the green cloud, it signals a sell and a move to cash.

Note: The algo is not designed to create short signals.

When my VXX (VXX) algo gave a long signal on Feb. 21, I was terrified. Since late March, it has settled down nicely. The trending behavior of equity volatility is one of life's greatest pleasures.

This is a completely natural looking chart of the S&P 500 (SPY). Move along people. No manipulation or liquidity driven moves here.

The pipeline stocks (AMLP) are fascinating. They were in their own Great Depression, hit yields of almost 20% in some cases, and found a bottom. Like Netflix (NFLX), the natural gas-focused pipelines bring their product right in to your home.

For now, the move higher in Russian equities (RSX) reflects that realpolitik is prevailing in the oil patch. It is always an uneasy truce. There is a book which perfectly captures the value capture debate called The Myth of Market Share. Highly recommend it. I would give it ten stars if I could.

The 20+ Year U.S. Government Bond Index (TLT). You get charts like this when the Fed hires traders for the explicit reason to move markets.

The old equal-weighted CRB Commodity index (GCC) looks confused, battered and tired, but trying to get up off the mat.

The machines love speculative stocks, or stocks that are surrounded by popular interest and controversy, like Tesla (TSLA).

There's so much speculative interest in Apple (AAPL) that it trends better than the indices. The machines love this stock. And if you're swing trading in and out, that can cut both ways. You are competing, literally, against machines. You can feel the whiplash of the big waves of up/down/up moves.

In an age of unprecedented governmental intervention, stock prices largely reflect the flow of liquidity around the world, and the over and under reaction to macro phenomenon as the herd of index and ETF investors stampede in and out of markets en-masse, creating large trends.

Central bank gambits to inject and to withdraw liquidity create trends, or serial autocorrelation, in the direction of asset classes. These trends are then accentuated by a herd of index investors. Algorithmic methods can often sniff out important statistical footprints created by the interplay of these variables. Investors ignore the trends unearthed by algorithmic analysis at their own peril.

Analyst’s 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.

Hypothetical performance results have many inherent limitations, some of which are described below. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown; in fact, there are frequently sharp differences between hypothetical performance results and the actual results subsequently achieved by any particular trading program. One of the limitations of hypothetical performance results is that they are generally prepared with the benefit of hindsight. In addition, hypothetical trading does not involve financial risk, and no hypothetical trading record can completely account for the impact of financial risk of actual trading. For example, the ability to withstand losses or to adhere to a particular trading program in spite of trading losses are material points which can also adversely affect actual trading results. There are numerous other factors related to the markets in general or to the implementation of any specific trading program which cannot be fully accounted for in the preparation of hypothetical performance results and all which can adversely affect