34 Pages Posted: 12 Sep 2012 Last revised: 1 Oct 2012
Date Written: June 15, 2012
This paper challenges H. Markowitz’s Portfolio Theory due to its narrow focus upon market risk. It identifies 6 risks and presents a long only active investment process whose principles are supported by five year beta trials 2003-2009 & the performance of current portfolios. The DigitalInvest process uses interaction between the price of a stock and its moving averages to trigger signals that drive: asset allocation, portfolio choice and risk management. Passive investment is seen as sub optimal in our age of bubbles and crashes since it requires you to hold stocks that have slipped below their falling 200 day moving average.
Our inspiration lies in the investment theories of David Ricardo, Charles Dow and others. We assert that a high price premium paid to a stock's annual moving average price is the key risk to the investor since it exposes him to reduced reward and a greater risk of losses.The 8 asset sectors (sovereign bond, corp. bond etc) are each measured against their performance hurdles and review perspectives. These sectors mirror IMA sectors where possible but to optimise total returns we hold equities or bonds (during downturns) not equities and bonds.
We propose that a growth stock’s price performance can be split into its: persistent relative performance trend and less persistent absolute performance trend. Relative performance places top decile stocks into our watch list of “champions” for each sector. Absolute trends then drive the timing of our buying and holding of the sectors with attractive coefficients of investment and the sale of sectors whose coefficient falls out of range.This goes against orthodox teaching that trends are not persistent.
This paper introduces an equation for analysts: Investment Coefficient= M- (R plus C squared), where M is the year-on-year rise in the moving average price, the stock’s Momentum, R is the price premium payable to this moving average at purchase -risk of overpaying- C represents the drag on returns from future price volatility (seen as a secondary risk).
Our process ranks our sectors by their Coefficient of Investment to optimise asset allocation decisions each month and ranks each watchlist stock for portfolio choice. It adds value by providing clear rules and tools for micro managing investment under uncertainty.
Three later papers cover: The Quality Sieve, Asset Allocation and Risk Management.
Keywords: price, premium, diversification, CAPM, inverse correlation, portfolio, profit share, Charles Dow
JEL Classification: G11
Suggested Citation: Suggested Citation
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