Short-Term is Not Trend Following

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This summary is written by Rich based on a conversation in our CTA series between Roy Niederhoffer, Founder and President of R.G. Niederhoffer Capital Management, and the podcast hosts, Niels and Alan.

About Niederhoffer Capital Management

Niels and Alan were joined by Roy Niederhoffer, Founder and President of R.G. Niederhoffer Capital Management. They discussed the successful investment strategy of trend following, short-term trading, and managed futures in 2022. 

Roy shared the background of his firm, which is celebrating its 30th year in business and manages around $1 billion in assets. 

He highlighted their focus on short-term, primarily contrarian trading and the positive impact of high volatility since COVID. 

Alan asked Roy about the reasons behind his firm's focus on short-term trading. Roy explained that his background in neuroscience inspired him to quantify human behaviour patterns and their impact on historical price data, leading to the discovery of non-random patterns in short-term price patterns. Additionally, there was a business reason: they could provide an alternative to the dominant trend-following strategies and be negatively correlated to equities.

Roy mentioned that his approach targets both strong emotional responses in market participants and broader inefficiencies. By focusing on emotionally charged situations, they can predict subsequent behaviour more accurately. Roy emphasized the importance of treating the search for strategies scientifically and avoiding spurious correlations and non-causal relationships that do not generalize well.

Alan asked Roy about the ups and downs of short-term trading strategies in the past 30 years and whether certain market environments are more favourable for these strategies. 

Roy explained that there is a correlation between short-term trading approaches and realized market volatility, which was significantly reduced by central banks' quantitative easing measures until 2019. This led many investors to abandon short-term trading in favour of more profitable strategies during that period.

Niels then asked Roy what kept his confidence in short-term trading strategies during challenging times. Roy credited his belief in the models, his philosophy based on human behavioural patterns, and his conviction that these patterns are unlikely to change. However, he also acknowledged that luck could have played a part in his decision to stick with the strategy.

The discussion highlighted the importance of staying committed to a well-founded trading philosophy, even during difficult periods, but also recognized the potential role of luck in successful outcomes.

Concerns about the Sharpe Ratio

Niels raised a question about whether investment managers should be concerned about their own Sharpe ratio or the Sharpe ratio of their clients' overall portfolios. 

Roy shared his experience of running a hedge fund with a negative beta to stocks and bonds, which resulted in significant annualized alpha but wasn't easily appreciated by investors who didn't look at it from a portfolio basis.

Roy referenced his collaboration with Danny Kahneman on a presentation about the challenges investors face in maintaining negatively correlated strategies like CTAs in their portfolios. They found that a CTA with the same Sharpe ratio as other managers in a portfolio would appear at the bottom of monthly sorted performance tables four times as often, even though it might provide the most significant portfolio benefits.

The issue lies in the strategy's skew; negative skew strategies are easier to maintain in a portfolio than positive skew strategies like CTAs. People tend to prefer negative skew strategies because they provide many small bursts of happiness, whereas CTAs can be more frustrating due to periods of small losses, despite their potential for significant benefits in the long run.

The Effectiveness of Trend Following when Interest Rates Rise 

Niels brought up a discussion from 2014 when Roy wrote a paper questioning the effectiveness of trend following in fixed income when interest rates rise. Now that yields have risen, Niels asked if Roy is surprised by how well trend following performed in the rising yield environment.

Roy acknowledged that his theory didn't hold up in some instances, such as when the Barclays Global Ag total return index declined 14% and CTAs made 26%, proving his idea incorrect. However, he noted that his theory didn't account for an inverted yield curve environment, which has been the case in recent years. In such an environment, being short actually pays, making it hard to determine if his theory has really been tested.

Niels suggested that since back adjusted prices are used in trend following models, the signal strength may be impacted by the roll yield, potentially adjusting the position size accordingly. Roy reiterated that his theory focused on a positively sloping yield curve and that it may take many years to see if his theory holds true. Ultimately, both Roy and Niels agreed that it's great for the industry when everyone makes money.

The Role of Short-Term trading in a Broader Portfolio

Alan asked Roy about the role of short-term trading in a portfolio compared to other strategies like volatility and tail risk trading. 

Roy explained that options strategies can become very expensive once markets get volatile, making it challenging to enter those strategies. In contrast, short-term strategies that trade futures can perform better in such environments.

Roy believes that a variety of strategies, including short-term, trend following, long vol, and tail risk, each have their own benefits. He highlighted the importance of diversification in a CTA allocation, including having a range of strategies with different durations. Roy emphasized that his firm is explicit about the role they play in a portfolio, the correlations they provide, and when they expect to make or lose money.

He acknowledged that explaining short-term trading to investors can be more challenging than explaining trend following, as the reasons for gains or losses are more complex. However, Roy believes that the burden for short-term managers is to provide clients with the necessary understanding and comfort, which is a higher bar than for other strategies.

Market Regimes that are Favourable and Unfavourable to Short Term Trading

Niels asked Roy about the differences between periods when short-term trading performs well and periods when it does not, such as during Volmageddon and the Omicron event. Roy explained that it depends on the specific strategy and allocation. He highlighted that there are substantial differences within the short-term trading space, with variations in trading duration and asset mix.

Roy noted that some short-term managers are more correlated to the CTA index and others less so, which can be attributed to their strategy's duration and asset mix. He emphasized that understanding the drivers of each strategy is essential for investors. 

Roy concluded that there is more diversity in the short-term space, and investors need to ask more detailed questions to gain insights into different strategies.

Importance of Execution with Short Term Trading

Niels asked Roy about the importance of execution in short-term trading strategies. 

Roy disagreed that execution is the most critical aspect, arguing that it plays a smaller role. He believes that a strategy should work even with relatively naive execution, as long as it is smart. Roy maintains that execution won't make or break a trading strategy, and that factors like diversity, trading size, and alpha are more important.

Roy clarified that he is referring to short-term trading, and while he doesn't suggest that a naive person will have the best execution, he believes that being thoughtful and having experience should be enough. 

Research and Enhancements

Alan asked Roy about balancing the multi-strat approach, including machine learning, and how they handle difficult months like February 2018 (Volmageddon) from a research perspective. 

Roy explained that such months are exogenous periods and they didn't change their approach after that. 

However, his macro view changed with inflation and the unprecedented debt to GDP situation. Roy believes there is a risk of the dollar being debased, leading to nominal appreciation in financial assets. This requires hedge funds and alternative investments to keep up with the stock market, which might involve taking leveraged positions.

Alan inquired about research projects driven by macro views and how they unearth new sources of alpha. Roy shared that they have spent years figuring out how to be consistently downside protective for stocks and bonds, making it relatively easy to adapt their strategy based on macro views.

Alan then dug deeper asking Roy about their process for developing new trading strategies and insights. Roy shared that they've hired neuroscientists and people with non-traditional finance backgrounds, and everyone in the firm is involved in both research and trading. They believe thinking like traders rather than researchers is crucial to their success.

Regarding machine learning, Roy views it as a dangerous tool due to the risks and potential for overfitting data. Although they've had success with machine learning, they don't let computers analyse data and find features autonomously. 

Roy expressed concern over the use of machine learning in their trading domain because certain unpredictable factors, such as sudden market changes, can be challenging for these systems to handle. These factors can stem from external forces, such as an unexpected comment from a key figure, like a central bank's chairman, which can drastically influence market behaviour in a matter of seconds. Machine learning systems may struggle with these nonlinear dynamics and convergence when faced with such events.

However, Roy highlighted that not all aspects of machine learning are problematic for their domain. While the initial step of letting computers autonomously analyse data and find features can be dangerous, subsequent steps in the machine learning process can be quite useful. By leveraging these later steps, Roy's team has been able to achieve success with machine learning, while avoiding the pitfalls of relying too heavily on the technology for decision-making in their trading strategies.

Capacity and Liquidity of Short-Term Strategies

Niels asked Roy about his view on capacity and liquidity for short-term strategies in trading.

Roy addressed three aspects: whether investors should have the strategy, capacity, and liquidity.

1. Investors should have the strategy: Roy believes that the strong correlation between various markets and assets, along with the fact that most strategies are short volatility, makes a strong case for managed futures and short-term trading strategies. He argued that these strategies should have a higher allocation in portfolios.
2. Capacity: Roy acknowledged that short-term trading strategies have limited capacity, which means they cannot accommodate an unlimited amount of investment. For his firm, the maximum capacity is around $3 to $4 billion. He mentioned that each manager must address this question individually and find ways to diversify or grow.
3. Liquidity: Roy explained that liquidity varies across different markets, with the short end of the fixed income duration being more affected than the long end. He emphasized that the key metric for liquidity should be the cost of getting into a position relative to the market volatility and the position size, rather than just focusing on the bid or offer size.

Misconceptions of Short Term Trading

Roy addressed misconceptions about short-term trading:

1. It is not trend following: Short-term trading is distinct from trend following and offers diversification when combined with other strategies.
2. Long volatility vs. long premium: People often confuse being long volatility with being long premium. In reality, short-term trading is long realized volatility, not long premium.
3. Track records: People put too much emphasis on historical performance without considering how much a manager has evolved and improved their strategies over time. It's essential to focus on the manager's research process and the validity of their current strategies instead of relying solely on their track record.

"Long volatility" and "long premium" are terms used in trading, particularly in options trading. They refer to different positions that traders can take based on their expectations of market volatility. However, people sometimes confuse the two concepts, which are distinct.

Long volatility: Being long volatility means that a trader expects market volatility to increase. In the context of short-term trading, being long volatility means that the trading strategy profits from higher market volatility, as the realized volatility (actual market fluctuations) increases. In this case, the more the market moves, the more the strategy can potentially benefit.

Long premium: Being long premium, on the other hand, refers to owning options. In this case, the trader is buying options, which are contracts that give them the right to buy or sell an asset at a specific price within a specific timeframe. The options themselves have a price (premium), which the buyer pays to the seller. When you are long premium, you expect the market to move enough to overcome the premium you paid for the option, and you benefit from the increase in the option's value.

The confusion arises because both positions can profit from increased market volatility. However, being long volatility in the context of short-term trading means profiting from realized market fluctuations directly, rather than by owning options and paying premiums. In other words, short-term trading strategies seek to benefit from actual market movements, while being long premium involves profiting indirectly through the value of options as volatility increases.

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This is based on an episode of Top Traders Unplugged, a bi-weekly podcast with the most interesting and experienced investors, economists, traders and thought leaders in the world. Sign up to our Newsletter or Subscribe on your preferred podcast platform so that you don’t miss out on future episodes.