Edition

IFTA JOURNAL
2017 EDITION
Research Objective
The objective of this paper is therefore to examine the
efficacy of using the RSI (14) as a trend trading indicator that
could be used in a systematic way to improve profits and
reduce risk compared with pure buy and hold, by reducing the
portfolio’s exposure to the market during more turbulent and
volatile bear market periods.
Materials and Methods
Methodology for RSI (14) Trend-Trading Identifier
Backtest
To test the hypothesis that the RSI (14) can be utilized as a
trend-trading indicator, and whether its readings provide an
investment approach that increases profitability and reduces
risk, the strategy is backtested against the S&P 500 Index—the
U.S. stock market index of the 500 leading companies by market
capitalization.
The following criteria allow this model to be simple, yet
emotion-free and objective.
1. The model uses purely mathematical logic.
2. The same model and parameters can be used for various time
periods (e.g., minute, daily, weekly, monthly) based on the
user’s time horizon.
The RSI (14) trend-trading methodology includes the
following:
Initial Entry
BUY RULE: Enter long when the RSI (14) line closes above the
9-period SMA and above the 45-period EMA.
SELL RULE: Enter cash when the RSI (14) closes below the
9-period RSI (14) SMA and below the 45-period RSI (14) EMA.
Ongoing
A. If long, enter cash when the RSI (14) closes below both the
9-period SMA and 45-period EMA.
B. If cash, enter long when the RSI (14) closes above both the
9-period SMA and 45-period EMA.
Additional rules:
• For the purposes of this report, the test data analysis only
considers this model as a long-cash model. It is important to
note that the model can also support a long-short strategy.
• The data analysis is based on a weekly period; this is targeted
for intermediate-term (9–12 month) time horizon investors.
Some mechanics of the model are as follows: If the RSI (14)
closed above both 9- and 45-period moving averages on
a Friday, then due to the weekly frequency, the following
Friday’s close is when the trade would be entered/exited,
thereby creating a time lag in processing in order to simulate
real-time trade processing requirements.
• For the secular bear market 2000–2009, the data output are
total return series that include dividends.
• For the secular bear markets 1929–1942 and 1966–1978, the
data output are price return series.
• For the secular bull markets 1942–1966 and 1978–2000, the
data output are price return series.
• Cash returns were not calculated; the assumption was that
the investor was out of the market.
• Taxes are excluded.
• Transaction costs are included.
• RSI (14) weekly closing data are obtained through FactSet
Research Systems and Bloomberg, L.P. Data are analyzed
using Microsoft Excel 2007.
The backtest for each secular trend scenario was made with
a theoretical starting balance of US $1 million. This would be a
reasonable amount for a registered investment advisor to invest
in as a large cap asset allocation to a portfolio.
The overall time period for backtests include three secular
bear and two secular bull markets applied to the S&P 500 Index
from 1929–2009. The specific dates for each backtest scenario
are as follows:
Secular bear trend scenarios:
9/6/1929–4/28/1942
1/14/1966–11/17/1978
1/14/2000–3/6/2009
Secular bull trend scenarios:
4/28/1942–1/14/1966
11/17/1978–1/14/2000
Transaction Costs
For each scenario backtest, transaction costs are included to
represent the variable friction in trading U.S. equities over the
past 80 years. Transaction costs including bid-ask spreads plus
commissions going from 1900–2000 are represented in Figure 3.
Figure 3. Estimated annualized trading costs of NYSE
stocks 1900–2000 (= turnover * [bid-ask half spread +
one-way commission]) (Adapted from Charles M. Jones 10 )
Results
RSI (14) Model Backtest Results: Three Secular Bear
Markets
The test results of the RSI (14) trend-trading model applied
within a secular bear market are compelling. Not only does the
timing model outperform buy and hold for each time period
studied, but it also protects the investor from a significant
drawdown due to an extreme market event.
The first test case analyzes the results of all three secular
bear markets combined (a total of 34 years). Figure 4 illustrates
the test results, which include annual performance of the RSI
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