From our inception in 1997, the NAOI taught the use of Modern Portfolio Theory (MPT) to design and manage portfolios - this was, and still is, the unquestioned industry standard methodology. But after watching the MPT portfolios we had taught our students to create melt-down during the market crash of 2008-2009, I suspended all NAOI education classes. I had to realize that MPT, introduced to the market in the 1950’s, could not cope with modern market volatility. At that point I opened the NAOI Research and Development Division to find an alternative approach to MPT; one designed to thrive in modern markets.

Following a multi-year R&D project using significant input from the investing public we found it in the form of Dynamic Investment Theory (DIT). This page provides a short overview of our development process and presents the content of the new theory we developed.

Starting with Investor Goals for a New Approach to Investing

As the NAOI R&D Division began a search for an updated approach to portfolio design and management, I was adamant that it be designed based on input from the investing public, not on a decades-old academic theory as is the case with MPT. So our first task was to ask our students what they wanted and needed to in this new approach to investing. Their top goals were as follows:

1. Simple to understand, implement and manage, with or without the assistance of an advisor

2. Higher returns with lower risk than the MPT portfolios they are given today

3. Absolute protection from significant market dips and crashes

4. Eliminate or reduce the “human-risk” element that is the source of so much that is wrong the way investing works today

It was immediacy obvious to us that MPT met none of these goals. So we began our research with a blank slate, as if MPT didn’t exist.

NAOI Design Goals and “Thinking-Differently”

To meet the goals set for us as listed above we had to think differently about how portfolios could be designed and managed. By doing so, we determined that the following fundamental changes were needed. These were are design goals:

1. A Better Portfolio Goal. Today’s MPT portfolios are designed to match a “guesstimate” of each investor’s risk profile. And a low-risk rating greatly inhibits a person’s ability to take full advantage of the market’s wealth creation potential. A better portfolio goal would be to maximize returns and minimize risk in all economic conditions. This is a universal goal that works for all investors regardless of their risk tolerance and the need for customization, and its associated risks, goes away.

2. A Buy-and-Sell Management Strategy. MPT portfolios are meant to be held for the long-term regardless of market price movements. This buy-and-hold management strategy makes portfolios dangerously vulnerable to market crashes. A better management approach would use a buy-and-sell strategy that makes portfolios market-sensitive; capable of detecting and buying into market price uptrends while avoiding market price downtrends and crashes.

3. A Built-In, Objective Trading Plan. MPT provides no guidance for making changes to a portfolio once designed other then, perhaps, a periodic rebalancing to revert to original allocations.Equity purchases and trades for MPT portfolios are thus based on subjective judgments and this injects a massive “human-risk” element into the investing process. A better approach would be to build in to each DI a standardized trading plan that signals trades based on objective observations of empirical market data.

4. Eliminating the “Human-Risk” Factor. To eliminate, or to at least dramatically reduce, the risks related to subjective human judgments in today’s portfolio design and management process, we saw the need to base equity trades on objective observations of market data as discussed just below.

To meet these goals we did a deep dive into field of equity market Quantitative Analysis.

Taking Advantage of Quantitative Analysis

As we began to explore the massive world of market data analysis, the following question was posed to our group: What do we know about market price behavior with a high degree of confidence?

One would think that we know a lot. But we found only three equity price behaviors that we could use in a new approach with confidence. They are as follows, with a related premise:

1. Asset Classes and Market Segment prices are cyclical, moving up and down at regular intervals. This observation leads to the premise that patterns exist in past price movements that have predictive value for future price movements.

2 Asset Classes and Market Segments prices move up and down at different times. This observation leads to the premise that at all times, in any economic conditions their will exist positive returns somewhere in the market.

These two points are illustrated diagram, below; showing that the Stock and Bond asset classes tend to move in opposite directions.

3. Price Trends are persistent - each lasting for an extended period of time - The chart presented below shows that up-trending, Bull Markets, last an average of 14 months and down-trending, Bear Markets, last an average of 14 months.. This leads to the premise that if a price-trend is sampled at relatively short intervals, e.g. monthly or quarterly, the chances of the trend direction detected continuing until the next periodic sampling is high.

Significant testing and data analysis showed each of the above premises to be true with a high degree of confidence. This enabled us to create a new approach to investing that we called Dynamic Investment Theory (DIT) that is presented below.

What Dynamic Investment Theory Says

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“At all times, in any economic environment, there exist in equity markets areas of uptrending prices. And equities that have moved up in price for a significant time in the past have a high probability of continuing to move up in price for at least a relatively short time period in the future.

A simple, dynamic and internally-intelligent investment type, hereafter referred to as a ‘Dynamic Investment’ (DI), can be created that is capable of automatically finding equities trending up in price and capturing their positive returns potential while also detecting equities moving down in price and avoiding their loss potential. And these actions will be based on observations of historical equity price data with no subjective, human-decisions involved.

It is projected with a high degree of confidence that a Dynamic Investment so designed will be able to produce returns that are consistently and significantly higher than those of virtually any MPT-based portfolio, over the same time period, and with lower risk. It is further projected that Dynamic Investments can be designed that are so simple to understand, implement and manage that individuals of all investing experience levels will be able to take full advantage a DI’s higher performance with minimal education and training required.”

This is the Future of Investing

How Dynamic Investments work is explained at this link.