2. Theory and Literature Review
2.1 Technical Trading Indicators
A technical trading system comprises a set of trading rules that can be used to generate trading signals. In general, a simple trading system has one or two
parameters that determine the timing of trading signals. Each rule contained in a trading system is the results of parameterizations. For example, the Dual Moving Average Crossover system with two parameters (a short moving average and a long moving average) may be composed of hundreds of trading rules that can be generated by altering combinations of the two parameters. Among technical trading systems, the most well-known types of systems are moving averages, channels (support and resistance), momentum oscillators, and filters. These systems have been widely used by academics, market participants or both, and, with the
exception of filter rules, have been prominently featured in well-known books on technical analysis, such as Schwager (1996), Kaufman (1998), and Pring (2002).
Filter rules were exhaustively tested by academics for several decades (the early 1960s through the early 1990s) before moving average systems gained popularity in academic research. This section describes representative trading systems for each major category: Dual Moving Average Crossover, Outside Price Channel (Support and Resistance), Stochastic Oscillator and Alexander’s Filter Rule.
Dual Moving Average Crossover
Moving average based trading systems are the simplest and most popular trend-following systems among practitioners (Taylor and Allen 1992; Lui and Mole 1998). According to Neftci (1991), the (dual) moving average method is one of the
few technical trading procedures that is statistically well defined. The Dual Moving Average Crossover system generates trading signals by identifying when the short-term trend rises above or below the long-term trend.
Specifications of the system are as follows:
A. Definitions
Next to moving averages, price channels are also extensively used in technical trading methods. The fundamental characteristic underlying price channel system is that market movement to a new high or low suggests a continued trend in the direction established. Thus, all price channels generate trading signals based on a comparison between today’s price level with price levels of some specified number of days in the past. The Outside Price Channel system is analogous to a trading system introduced by Donchian (1960), who used only two preceding calendar week’s ranges as a channel length. More specifically, this system generates a buy signal when the close price is outside (greater than) the highest price in a channel length (specified time interval) and vice versa.
Specifications of the system are as follows:
A. Definitions
1. Price channel = a time interval including today, n days in length.
2. The Highest High = , where is the high price at time t-1.
)
(
HH
t max{Pth−1,...,Pth−n+1} Pth−12. The Lowest Low (
LL
t)=min{Ptl−1,...,Ptl−n+1}, wherePtl−1 is the low price attime t-1.
The stochastic oscillator(SO) is a momentum indicator used in technical analysis, introduced by George Lane (1956) to compare the close price of a
commodity to its price series over a given time span. The idea behind this indicator is that price tends to close near their past highs in bull markets, and near their lows in bear markets. Generally, trading signals can be spotted when the stochastic oscillator crosses its moving average. Two stochastic oscillator indicators are typically calculated to assess future variations in prices: fast (denoted by K) and slow (D). Comparisons of these statistics are a good indicator of speed at which prices are changing or the Impulse of Price. Some analysts argue that K or D levels above 70 and below 30 can be interpreted as overbought or oversold. On the theory of price oscillating, George Lane, recommend that buying and selling be timed to the return from these thresholds. In other words, one should buy or sell after a bit of a reversal. Practically, this means that once the price exceeds one of these
thresholds, the investor should wait for prices to return through those thresholds (e.g. if the oscillator were to go above 80, the investor waits until it falls below 80 to sell)
Specifications of the system are as follows:
A. Definitions
1. Stochastic oscillator Value(
SOV
t) = [Ptc-(LL
t)] / [(HH
t)-(LL
t)]c
Pt , (
LL
t), (HH
t) are the same definitions in Outside Price Channel.2. = = , i.e. K is the s-days moving average of SOV, and D is the l-days moving average of K
K
t∑
C. Parameter:
n, s, l
There are two items about
Stochastic Oscillator
to explain here. First, the parameter are default generally set as (9,3,3) in worldwide financial website, such as Bloomberg, MarketWatch, yahoo finance and CnYes. In the “Reflexivity” section, we will deeply discuss the commonly used parameter in the SO indicator. Second, the reason why we add a rule on holding our position of threshold value 25 and 75 is that whenK
value keeps going above 75 as price series moving forward means the price series are in a strong bullish trend or better than 3rd-Quartile in statistical way. Since that reason, we should not unwind our long position as theK
value higher than 75 and vice versa.
.
Alexander’s Filter Rule
This system was first introduced by Alexander (1961, 1964) and exhaustively tested by numerous academics until the early 1990s. Since then, its popularity among academics has been replaced by moving average methods. This system generates a buy (sell) signal when today’s closing price rises (falls) by x% above (below) its most recent low (high). Moves less than x% in either direction are
ignored. Thus, all price movements smaller than a specified size are filtered out and the remaining movements are examined. Alexander (1961, p. 23) argued that “If stock price movements were generated by a trendless random walk, these filters could be expected to yield zero profits, or to vary from zero profits, both positively and negatively, in a random manner.”
Specifications of the system are as follows:
A. Definitions and abbreviations
1. High Extreme Point (HEP) = the highest close obtained while in a long trade.
2. Low Extreme Point (LEP) = the lowest close obtained while in a short trade.
3. x = the percent filter size.
B. Trading rules
1. Go long on the close price, if today’s close rises x% above the LEP.
2. Go short on the close price, if today’s close falls x% below the HEP.
C. Parameter: x.