Aspect Capital on short term trading for alpha generation at the Amsterdam Investor Forum: The skill of capturing ephemeral market alpha
Aspect Capital, one of Europe’s leading CTAs, will be discussing short-term trading at the Amsterdam Investor Forum on 6 March 2018. Dr Constantin Filitti will feature on the panel, along with Nicolas Mirjolet, CIO, Tolomeo Capital.
The Amsterdam Investor Forum is a leading forum for institutional investors and alternative investment managers in the EMEA region.
Gary John-Baptiste (pictured), Sales Director, Prime at ABN AMRO says: “We are delighted to welcome Aspect Capital as one of our experts on the short term trading for alpha generation focus session. We share Aspect’s enthusiasm on the topic and look forward to receiving the wealth of knowledge they bring to the subject.
“We are equally excited about this year’s forum as 2018 has so many absorbing and captivating topics for discussion. We continue to challenge our audience with great debate shared amongst a broad mix of fund managers, investors and industry associates.”
Aspect Capital has evolved in recent years from being purely focused on a single strategy – a traditional medium-term trend following CTA (the flagship Aspect Diversified programme) – to more of a multi-product solutions provider. Part of that initiative was to launch a short-term trading programme, leveraging Aspect’s systematic expertise and research capabilities.
To do this, the firm hired Dr Filitti and Antonio Botelho from Capula Investment Management in July 2014 to develop a new multi-style short-term trading programme, known as the Aspect Tactical Opportunities Programme (ATOP).
The programme is just now approaching its three-year track record and performance has held up well during a tough period for most short-term traders.
“The SG Short Term Traders Index is down over 10 per cent over that period,” comments Christopher Reeve, Director of Investment Solutions at Aspect Capital. “We seeded ATOP with our own capital and earlier this year it received its first client allocation. It now has over USD200 million of institutional money in the programme.”
The ATOP programme trades global liquid futures markets and comprises a set of four sub-strategies or themes, which include: relative value trading; factor premium timing across different asset classes; short-term trading – these are the fastest models in the programme, trading positions over one to three days and are more event-driven or behaviour-driven - and finally momentum trading; effectively a shorter-term directional trading strategy than that used in the Aspect Diversified programme.
The aim is to deliver uncorrelated returns to equity markets, and with a low correlation to traditional CTA indices, which cannot be easily replicated by factor-based investing or alternative risk premia-type investing.
“Combined, these strategies have holding periods that range from one day to one month, with the average holding period typically being five to eight days. It’s not ultra-high frequency, intra-day trading but it is noticeably quicker than your classic medium-term trend following strategy,” comments Reeve.
A key part of any short-term trading strategy is how to best manage and deal with trading costs, giving the higher turnover of the portfolio. The models that the team uses to trade global markets seek to optimise alpha generation in such a way that gains are not adversely eroded by trading costs. Determining the right entry and exit level for each position is highly detailed as the trading models are designed to capture what is, after all, ephemeral alpha.
“You have to make sure your trading strategies are deployed in the most effective fashion. The Aspect Diversified programme takes more medium-term views and is able to leverage its patience premium by spreading trading out over time, whereas the Aspect Tactical Opportunities Programme trades multiple times each day.
“The balance is one where we have to accept slightly higher trading costs, whilst at the same time ensuring the trades are done a bit more aggressively in order to maximise the short-term alpha identified by the model,” explains Reeve.
The team’s research approach is broadly analogous to what Aspect does with its other trading programmes. The ATOP team is supported by Aspect’s wider trade execution, operations and risk team. This includes research technologists who check and code up trading models and software developers who build the trading systems that interface with the markets.
At the same time, the ATOP team constantly engages in research to upgrade or adjust the ATOP programme, which typically happens three or four times a year. As Reeve says, “that’s the typical cycle of idea generation through to building the model, testing it and incubating it with some live trading before switching the model into the strategy”.
One of the main challenges of any short-term trading programme is designing the signals, whose task is to scour the markets, cut through all the noise, and look for the best opportunities.
Even though it is a shorter term programme, ATOP, due to its multi-style approach, isn’t just seeking out price opportunities as one would see with a statistical arbitrage strategy. The models have real behavioural and market participant rationales behind them.
“It’s more than just a signal to noise challenge, it’s also looking for reasons as to why certain people behave in a constrained fashion when they trade, which gives rise to predictable behaviours when market events occur. That is what our models seek to take advantage of.
“It’s hypothesis-based trading as opposed to merely statistical trading,” adds Reeve.
He says that one of the remarkable things about short-term trading strategies is they have, on a pure basis, very high alpha generating capabilities. They are good predictors of the markets but that predictability decays quickly. “The challenge is implementing the models to harvest that short-term alpha in a way that isn’t totally crowded, to the extent that the alpha disappears before you’ve even executed the trade.
“We’ve got some original ideas that we model, which goes someway to avoiding the issue of crowded trades that other systematic models sometimes fall prey to,” says Reeve.
In Q3 2017, slower trading strategies were whipsawed by the markets and lost money in September. By contrast, short-term programmes such as ATOP rode the wave of profitability through August and, when things turned in September, were able to react much quicker. Short-term CTAs are designed to move in and out of markets and avoid the drawdowns that medium-term CTAs often fall victim to.
This is fine when the trading models are able to recognise and capture predictable behaviour in the markets, but it works far less well when black swan events occur. Both Brexit and the Trump presidency nomination are two obvious examples of where short-term CTAs are simply not programmed to make alpha when the markets are thrown into chaos and market participants disagree about the impact of the event.
“A lot of the strategy’s good performance has been over the last five months, as markets have acted in a more predictable way; it’s harder to make short-term alpha when unexpected events scupper the usual market behaviour,” remarks Reeve.
Reeve confirms that the relative value sub-strategy has been the most consistent alpha contributor so far this year, generating profits in global equity futures. “Another area that has been good for the strategy is the energy sector, especially in August and September this year,” adds Reeve.
One of the advantages of shorter-term trading models is that because they make more decisions, one is able to perform historical analysis to get a sense of which parts of the trading model worked better than others. This is harder to do in a medium-term trading strategy as trades may last for six months. The system might get one or two wrong or indeed right, but it takes three or four years of data to gain any degree of statistical confidence as to whether it is working well or not.
Short-term trading allows you to assess trading patterns in more detail, on a relatively quicker basis.
“The tempting thing to do is react to that and change things. You’ve got to remain disciplined, in terms of running your trading models. Everything we do at Aspect is disciplined. It’s about learning from what doesn’t work but also not over-reacting to a particular period that either has or hasn’t worked. That’s the skill; knowing how and when to adjust the model’s behaviour,” concludes Reeve.