A Technical Analysis of the factors underlying the price of EU ETS
In this article, we undertake technical analysis of one of the most traded carbon assets- the EU ETS. The idea is to hypothesise a few key macroeconomic indicators that could form the basis for generating a trade in and out of the EU ETS. These strategies are then backtested on the recent historic data to see how each macroeconomic indicator fared.
As opposed to fundamental analyses, technical analysis is solely the way to study past data (of price and volume) to identify meaningful trends for a future trade. Technical analysis offers a complementary set of tools in a trader's arsenal to help them balance their the fundamental research.
This article was inspired by a short presentation from Tim Mccullough, a technical analysis applications specialist at Bloomberg and uses his methodology to sample out the macro indicators chosen to backtest, whether trading in EU ETS based on these would have yielded profitable or losing trades.
Basic Terminology
Source: Bloomberg
Input:
Macro indicator
The macroeconomic indicator based on which a trade in EU ETS is entered or exited for the given strategy
Trigger Values
Defining the values for the macro indicator, which when met would have resulted in a buy or sell trade as defined
Holding Period
Refers to the time for which a particular buy or sell action, based on the suggested triggers, is not reversed.
Source: Bloomberg
Output:
Total Trades
Refers to the total trades predicted by the backtesting strategy, based on the value of the underlying triggers provided.
Basis, whether buy/sell trades based on these triggers were either profitable or loss-making, total trades are further classified into correct and incorrect bets.
Single-period Returns
The average returns generated by the strategy, per holding period
Backtesting 3 strategies with varying macro indicators:
Strategy 1 : Buying ETS when inflation rises
In this strategy, we consider the hypotheses that a rising inflation may be a good trigger to the market.
Assumption:
This is based on the observation that a high inflation penalises the performance of the equities, while rewarding commodities and hence a carbon allowance such as EU ETS.
Input:
a. Macro Indicator
Eurozone CPI (monthly)
b. Trigger conditions
We trade in into the EU ETS when the Eurozone CPI crosses its 5 month historic value. Similarly, we sell an EU ETS when the corresponding CPI value is lower than it was 5 months ago.
c. Holding Period
We assume a holding period of 12 months, following any trade that's executed. This is because of the slowly moving nature of the underlying indicator in this case.
Source: Bloomberg
Output:
As seen in the screen above, the strategy results in 25 trades based on the trigger conditions provided (represented by the green and red signals on the EU ETS graph). Of these 14 resulted in a profit, while 11 lost money during the subsequent holding period.
The strategy resulted in a single period return of 2.69% which is also the annual return in this case (since each holding period equalled 12 months).
It could thus be said that inflation based EU ETS trading could be a useful strategy, given a positive annual ~3% return for over 17 years.
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Strategy 2: Buying ETS when coal prices are rising
In this strategy, we consider the hypotheses that a rising coal price may serve as a trigger to buy ETS in the market.
Assumption:
This is based on the assumption that a high coal price reflects a higher demand of coal, which would need to be accompanied by higher subsequent offsetting.
Input:
a. Macro indicator
Price change in coal price for a 5 day period (Coal 5d %)
b. Trigger conditions
We trade in into the EU ETS when the Coal 5d increases beyond 10% i.e. prices of coal change by more than 10% over a 5 day period. Similarly, we sell an EU ETS when the Coal 5d dips below 10% or the prices of coal fall by over 10% in a 5 day period.
c. Holding Period
We assume a holding period of 21 days, following any trade that's executed. This translates to the no. of trading days in a month, so effectively the holding period is one month.
Source: Bloomberg
Output:
As can be observed, the strategy results in 84 trades for the period starting Jan 2007 to Apr 2022. Of these 32 resulted in a profit, while a higher no. i.e. 48 lost money during the subsequent holding period.
The strategy resulted in a single period return of - 0.40% which translates to an annual return of - 4.80% (since each holding period equals 1 month).
It could thus be said that the price of coal isn't really useful in trading in or out of EU ETS.
Strategy 3: Buy ETS when it has a bullish trend and an underlying momentum
In this strategy, we consider the hypotheses that a consistently rising price may serve as a trigger to buy ETS in the market.
Assumption:
Input:
a. Macro indicator
For trend, we use two moving averages (short term and long term) with 21 and 65 day periods respectively. These basically depict the dynamic average of EU ETS price over the corresponding terms.
Momentum is represented by the RSI (Relative Strength Index), which captures how quickly a particular asset is being bought or sold. A high RSI represents an oversold asset, while a lower RSI represents an overbought one.
b. Trigger conditions
We trade in into the EU ETS when the
c. Holding Period
We assume a holding period of 21 days, following any trade that's executed. This translates to the no. of trading days in a month, so effectively the holding period is one month.
Source: Bloomberg
Output:
As is evident, the strategy results in 50 trades for the period starting Apr 2018 to Apr 2022. Of these 26 resulted in a profit, while 22 lost money during the subsequent holding period (MA (65,0) values not available for last 2 trades to see if they result in profit or loss)
The strategy resulted in a single period return of 1.29% which translates to an annual return of 15.48% (since each holding period equals 1 month).
It could thus be said that the momentum based investing works quite well in case of EU ETS.
Conclusion
Technical analysis helps one uncover the patterns and correlations that might or not otherwise make sense (so far) fundamentally. As much as the efficient market theorists continue to beat down on the technical analysts, hedge fund managers starting with A.W.Jones in the 60s, then Michael Steinhardt and Co. in the 70s followed by the hundred others that followed since, have continued to deploy technical analyses to deliver consistent alphas, through uncovering certain correlations that were yet to be theorized by the fundamental analysts of their times.
The best ones out there however always deployed a combination of the two, covering both their grounds dynamically as and when the price volume action demanded.
P.S. Highly recommend reading More Money Than God by Sebastian Mallaby for an exciting history on the evolution of hedge funds in the 20th century.