ETF Investing According To Market Climate: With The IM Best2 MC-Score System

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Includes: EMB, GLD, SH, SPY, USMV, VNQ, XLP
by: Georg Vrba

Summary

Investors should structure their investments according to prevailing stock market climate. It does not make sense to have the same bond and stock allocation when market climate changes.

This system provides investment selections according to stock market climate. During up-markets it is long equity ETFs and switches to bond- and gold ETFs during neutral and negative markets.

Four different approaches are used to assess market climate which are based on economic, momentum and sentiment indicators. This results in five different market climate segments.

For each market climate segment only two ETFs are selected, and held until the climate segment changes, on average for six months. This is a low turnover model.

A backtest from Jan-2000 to Jul-2016 shows an average annual return of 16% with a maximum drawdown of -17% and only 61 realized trades during this 16.5 year long period.

Investors desire to beat the market, but not even most professional fund managers are able to achieve this. However, the simple strategy described here, namely investing according to market climate with the MC-Score System, should always provide better returns than buy-and-hold, and perform better than most equity funds.

The key is to define market climate in a sensible way, so that periods of market weakness can be identified, and investment in stock ETFs avoided during those times. There are many different ways to define market climate and it is not suggested that the method used here is the only one having merit.

The backtest described below is not alone showing good returns. For example, one can set up a model which always has five stock/bond ETF positions and vary the portfolio composition according to market climate. A backtest from Jan-2000 to Jul-2016 shows an average annual return of 17.2% with a maximum drawdown of -17% and only 230 realized trades, and a low portfolio turnover of about 3-times a year.

Market climate measurement:

The measurements of market climate are in some respects similar to Fred Piard's system. The system described herewith uses following economic indicators:

  1. Russell 1000 Index.
  2. S&P 500 earnings per share estimate (SPEE), based on the time weighted analyst's estimates of current year and next year.
  3. Short Interest Percent of Float for the S&P 500 (SPSI).
  4. The Aggregate Spread, similar to the Enhanced Aggregate Spread, is a recession indicator with a long lead time, which uses:
    1. 20-year US Treasury bond yield (Y20),
    2. Target Federal Funds Rate (FFR),
    3. Consumer Price Index (CPI),
    4. Unemployment Rate (UER).
  5. The Hi-Lo Index of the S&P 500 measures the excess of the number of shares reaching new 3-month highs versus the number of shares forming new 3-month lows.

These five indicators are used in four models which indicate a weak market climate when:

  1. The unemployment rate is on the increase: UER now > UER 3-mo ago.
  2. The earnings estimate of the S&P 500 declines: SPEE now < SPEE 20-wks ago.
  3. The markets are declining: Short moving average (MA)< long MA of the Russell 1000 Index.
  4. The three following conditions are true
    1. Recession indicated: (Aggregate Spread 10-mo ago < 150 bps) and
    2. Negative market sentiment: (short MA < long MA of the Hi-Lo Index) and
    3. Negative market sentiment: (short MA > long MA of SPSI).

Market Climate Score:

Summing above four market climate models (1. thru 4.), results in the market climate score (MC-score)

MC-score = 0 (best market climate)

MC-score = 1 (positive market climate)

MC-score = 2 (neutral market climate)

MC-score = 3 (negative market climate)

MC-score = 4 (worst market climate)

See the Appendix for the performance of SPY during the five MC-score defined market climate segments. The performance charts of SPY clearly illustrate the futility of being long the market when the MC-score is 3 or 4.

The iM MC-Score System:

Using the market clime score, a trading system is devised that selects from following ETFs:

ETF Description
XLP Consumer Staples Select Sector SPDR Fund ETF
USMV iShares Edge MSCI USA Minimum Volatility ETF
VNQ Vanguard REIT ETF
EMB iShares JPMorgan USD Emerging Markets Bond Fund ETF
SH ProShares Short S&P 500 ETF
GLD SPDR Gold Trust ETF
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The system always uses two ETFs (equal dollar weighted), and invests in alternative market segments during different market climate segments. The performance charts of SPY clearly illustrate the futility of being long the market when the MC-score is 3 or 4.

For MC-score = 0 : USMV and XLP.

For MC-score = 1 : USMV and XLP.

For MC-score = 2 : VNQ and EMB.

For MC-score = 3 : GLD and EMB.

For MC-score = 4 : GLD and SH.

Notes:

  1. The model was backtested using the on-line portfolio simulation platform Portfolio 123, which also provides extended price data. for ETFs prior to their inception dates calculated from their proxies.
  2. USD Emerging Markets Bond Fund EMB is used, because according to BlackRock and Research Affiliates USD EM debt is expected to produce much higher returns than US Bonds and Treasuries.

Trading:

ETFs are bought and sold on the first trading day of the week after a signal is generated.

Transaction slippage and brokerage fees were assumed to be 0.1% of each trade amount. The model is rebalanced weekly, but portfolio turnover is low, about 2-times a year on average, or about 4 buy- and sell-trades per year.

The only buy rule specifies the two ETFs for each of the five MC-score defined market climate segments. There is only one sell rule to ensure a minimum holding period of about three weeks. There is no ranking system needed.

Historic performance of the iM MC-Score System:

In the Figures-1 and 2 the red graph represents the model and the blue graph shows the performance of the benchmark SPDR S&P 500 Trust ETF (NYSEARCA:SPY).

Click to enlarge Figure-1: Simulated Performance 2000-2016: Annualized Return= 16.0%, Max DD= -16.9%. The backtest period was from Jan-2000 to Jul-2016.

Click to enlargeFigure-2: Simulated Performance 2009-2016: Annualized Return= 16.3%, Max DD= -12.5%. The backtest period was from Jan-2009 to Jul-2016.

Rolling 1-year Returns:

Over any 1-year period, starting Jan-2000 and 1 week offset intervals, this model showed returns ranging from -6% to +56%, whereas SPY returns ranged from -39% to +60% over the same periods. There were only 13 sample periods out of 813 which had small negative returns, whereas for SPY there were 238 sample periods with negative 1-year returns.
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Risk Measurements:

Table-1 lists the annualized returns, maximum drawdowns, and various risk measurements for the trailing three years and for the full backtest period.
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Trading Statistics:

This model assumes a starting capital of $100,000, and trading costs/slippage of 0.10% of each trade amount. Note, that the total amount of all Losers is only about 7% of the total amount of all Winners. This model has a high win rate of 81% of all realized transactions.

Number of days invested from 1/3/2000 to 7/29/2016 (6,052 days) in:

XLP 4,498
USMV 4,491
VNQ 586
EMB 1,374
SH 217
GLD 938
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Performance Statistics:
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Following the Model:

The backtests indicate that a successful strategy would be to invest in ETFs having styles that are applicable to prevailing market climate as defined by the MC-Score System.

This model can be followed live at iMarketSignals, where it will be updated weekly starting end of August 2016.

Appendix: Performance of SPY during various market climates

MC-score = 0 (best market climate)

MC-score = 1 (positive market climate)

MC-score = 2 (neutral market climate)

MC-score = 3 (negative market climate)

MC-score = 4 (worst market climate)

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Disclaimer:

One should be aware that all results shown for the MC-Score System are from a simulation and not from actual trading.

All information for this model is back-tested, based on the methodology that was in effect on the launch date. Back-tested performance, which is hypothetical and not actual performance, is subject to inherent limitations because it reflects application of a methodology and selection criteria in hindsight. Actual returns may differ from, and be lower than, back-tested returns.

All results are presented for informational and educational purposes only and shall not be construed as advice to invest in any assets. Backtesting results should be interpreted in light of differences between simulated performance and actual trading, and an understanding that past performance is no guarantee of future results. All investors should make investment choices based upon their own analysis of the asset, its expected returns and risks, or consult a financial adviser.

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. I have no business relationship with any company whose stock is mentioned in this article.