advanced-algorithmic-trading

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By definition a mean-reverting series will occasionally deviate from its mean and then eventually
revert. Bollinger Bands provide a mechanism for entering and exiting trades by employing
standard deviation "thresholds" at which trades can be entered into and exited from.
To generate trades the first task is to calculate a z-score (also known as a standard score)
of the current latest spread price. This is achieved by taking the latest portfolio market price,
subtracting the rolling mean and dividing by the rolling standard deviation.
Once this z-score is calculated a position will be opened or closed out under the following
conditions:
• z score < −z entry : Long entry
• z score > +z entry : Short entry
• z score ≥ −z exit : Long close
• z score ≤ +z exit : Short close
Where z score is the latest standardised spread price, z entry is the trade entry threshold and
z exit is the trade exit threshold.
A long position here means purchasing one share of ARNC and shorting 1.213 shares of UNG.
Clearly it is impossible to trade a fractional number of shares. Hence such a fraction is rounded
to the nearest integer when multiplied by a large unit base quantity, e.g. 10,000 "units" of the
portfolio traded.
Thus profitable trades are likely to occur assuming that the above conditions are regularly
met, which a cointegrating pair with high volatility should provide.
For this particular strategy the lookback period used for the rolling moving average and the
rolling standard deviation is equal to 15 bars. z entry = 1.5, while z exit = 0.5. All of these
parameters are arbitrarily picked for this chapter, but a full research project would optimise
these via some form of parameter grid-search.
27.4 Data
In order to carry out this strategy it is necessary to have daily OHLCV pricing data for the
equities and ETFs in the period covered by this backtest. Table 27.4 outlines the required asset
prices.
Ticker Name Period Link
ARNC Arconic Inc. (prev
Alcoa Inc.)
11th November 2014
- 1st September 2016
Yahoo Finance
UNG
United States Natu-
11th November 2014
Yahoo Finance
ral Gas ETF
- 1st September 2016
This data will need to placed in the directory specified by the QSTrader settings file if you
wish to replicate the results.