Steady success in a volatile world

Martin Estlander, chief executive officer and co-founder of Estlander & Rönnlund, talks to Hedge Funds Review about the firm's flagship er Global Markets Fund, the company's ongoing research programme to maintain profits, and tireless focus on R&D for competitive advantage

Finland's Estlander & Rönnlund has run its Global Markets fund with considerable success, benefiting from trading volatility over a lengthy, 14-year period. Investors have made an annualised geometric return of 10.55% to January 1995, and, equally importantly, made this with a very low correlation to equity indices such as the S&P 500 equity index.

Since launching the Global Markets fund in 1991, Estlander & Ronnlund has also added a global volatility product and global equity arbitrage portfolio. Martin Estlander, chief executive officer and co-founder of the eponymous company, spoke to Hedge Funds Review.

What is the general case for trading volatility as an asset class?

The return characteristics, with volatility as underlying, are so uncorrelated with other types of returns. Also being long volatility, as managed futures typically are, gives a good hedge under market distress.

Could you explain your investment strategy?

The investment philosophy of er Global Markets is to profit from trending markets by exploiting volatility in many time frames. The strategy maintains a global long volatility exposure and, therefore, shows attractive correlation patterns to traditional investments and to other investment strategies. Returns are extracted from markets by well-researched and rigorously maintained quantitative models

The company's prudent risk management, which is conducted on several different levels, includes a dynamic mechanism to ensure true portfolio diversification at all times. Diversification is crucial to achieve as smooth an equity curve as possible for the strategy and the diversification is applied on market-, cluster- and market class level.

Controlling and balancing portfolio exposure controls portfolio diversification. This is the heart of the risk management strategy. Dynamic identification of market clusters based on market behaviour, as well as dynamic allocation of the proper exposure to the various part of the portfolio based on inter-correlations and volatilities of various markets and market segments ensures an optimal balance in the portfolio at all times.

What instruments' and markets' volatility do you trade?

The er Global Markets fund trades on a diversified portfolio of 60 instruments. Only highly liquid instruments are chosen from the following sectors in 14 countries: global foreign exchange, stock indices, short-term interest rate and bond markets, energy, metals and agricultural markets.

Could you explain how backwardation, contango and roll returns play a role in your strategy?

An upward- or downward-sloping term structure of futures prices creates the possibility of 'roll returns'. For backwardation instruments, 'roll returns' come from selling the shorter maturity future higher and buying the longer maturity lower and then rolling up the curve again. For contango instruments, it's the opposite: buying the shorter maturity future lower and selling the longer maturity higher and then rolling down the curve again. As our strategy partly uses trend-following strategies and as backwardation and contango strengthen the trends, our strategy is well suited to make use of these 'roll returns'.

Do particular commodity markets suit your strategy particularly well?

Markets are added on the basis of relative performance to the portfolio as a whole. Risk, return, liquidity and correlation to other assets are main considerations. Especially on correlation, commodities are very important, as they tend to show positive returns at different times to financial markets. Having some of the models more long-term in their trading behaviour and some of the traded commodities less liquid than the traded financial markets, also leads to commodities in general suiting our type of strategy.

What has been the programme's historic correlation to traditional asset classes?

Our correlation to traditional asset classes has been low historically. The correlation to equity markets has been strongly negative during months when returns in equity markets have been negative. The correlation to bonds has been slightly negative when bonds have had negative months. When bonds have had positive months, the correlation to the strategy has been positive, which is also the case regarding correlation to equities.

How have you handled very low equity volatility and do you feel volatility has fallen across the board, or are there markets where it is still high?

Low equity volatility has not changed our approach. Volatility changes, in general, are at the heart of our risk management strategy. We adjust for volatility on position, cluster and overall portfolio level and different models continuously assess the nature of market price action and volatility. Each price action seen is judged against both the most recent history of market behaviour as well as against the longer-term characteristics of the price behaviour of the market. It is mainly in equities that we are seeing lower volatilities now than, for example, five years ago.

In fixed income, currencies and commodities volatility is pretty much on the same level as it has been during the past 10 years. In some commodities, volatilities have, during the last years, been higher than 10 years ago.

What situations are particularly favourable or unfavourable to your strategy?

Most favourable are trending markets and revaluations, when markets are moving in a certain direction. From a volatility perspective, low daily volatility is good, that is, a low cost for gaining a long volatility exposure, then strongly increasing longer volatility. Unfavourable market environments are range markets, sharp market reversals and periods of contracting market volatility.

What time frames do you trade and what holding periods do these produce?

Short-term models have average holding periods of two days. The medium- to long-term trend-following model trade several different holding periods, ranging from 10-120 days. The econometric models are more long term. For the portfolio, the average holding periods are for all trades 50 days, for winning trades 80 days, and for losing trades 15 days.

How often do you trade and what affects your trading frequency?

The trading frequency differs between the different models and markets. In markets in which short-term models are traded (most liquid markets), trading frequency is high, that is, positions are adjusted on average every second day. In less liquid markets with higher trading costs, positions are adjusted more seldom, on average 2-3 times a month. Volatility is also important, due to the fact the program dynamically allocates proper exposure to various parts of the portfolio based on inter-correlations and volatilities of various markets and market segments, ensuring an optimal balance at all times.

How do you diversify and balance your portfolio?

Controlling and balancing portfolio exposure governs portfolio diversification and is the heart of the risk-management strategy - dynamic identification of market clusters based on market behaviour, as well as dynamically allocating the proper exposure to various part of the portfolio based on inter-correlations and volatilities of various markets and market segments, which ensures optimal balance at all times.

Commitments to market clusters vary with market events and the way risk is distributed between market clusters. Portfolio balance and allocation to different markets and market sectors is based on the portfolio as a whole. The process is based on the assumption that market moves may be inter-correlated. Thus, one position is never changed without considering effects on the overall portfolio.

Different models within the portfolio are also overweighed/underweighed based on the market conditions. The key here is understanding when models perform and when they do not. For this purpose, the strategy program uses different kinds of indicators, for instance, volatility, volatility cycles, interest rate differentials, implied volatilities, market trends, value at risk (VaR) and so forth.

How often do you change the models and systems you have?

Financial markets change over time. A key factor to long term success is the ability to adapt the strategy to such change. Therefore, we employ a rigorous and continuous R&D process, to adapt and improve our trading strategy. Important improvements have been introduced as new releases approximately once a year. Improvements are tested with proprietary funds before being introduced to client products. Results and findings have also been presented to key clients before full-scale implementation. Due to the heavy focus on R&D since 2002, during the last 18 months we have seen many major developments and implementations. These are:

• Short-term models

• New portfolio balancing

• Econometric modelling

Short-term models

In September 2004, we introduced short-term trading models as a component into the program in which the dynamics are geared towards increasing exposure to the short-term models when daily volatility rises in particular markets. This was the scenario in March and April 2005. April was a very good month for the short-term models. Many key markets have been in relatively broad ranges, which has hurt traditional mid-and long-term trend-following programs.

Portfolio Balancing

New portfolio balancing based on trends and cycles in the volatility of the global market place, market sectors and individual instruments was also introduced.

The new balancing allows for efficient risk management and risk allocation to ensure a balanced and well-exposed portfolio. The negative impact of many classical drawdown periods for managed futures strategies can be substantially reduced.

Econometric Modelling

In 2004, we introduced econometric modelling as an overlay for exposure allocation to trades with a higher probability of success. Foreign exchange rates markets were included in September 2004 and models on interest rates at that year's end.

In February 2005, we added the methodology as an independent model to interest rates, and in March 2005, it was added to foreign exchange rates. Econometric modelling on commodities was added in April 2005.

How large is the firm's research and development team and what is their background?

The research and development team at the firm currently consists of 11 people, several possess PhDs in finance, physics or mathematics. The research and development efforts are of vital importance to our systematic approach when modelling and fine-tuning our programmes at Estlander & Ronnlund.

What happened between February and August 2004 as the fund fell during this time period?

We saw a strong start in early January and February 2004, driven in particular by upward trends in bonds.

In March and April of 2004, all major financial markets reversed, resulting in a step back from heavy yen selling. The equity and interest rate markets were also affected by news of changes in the Federal Reserve's monetary policy.

Equity markets remained choppy and faced strong resistance due to fears of higher interest rates in the United States. So Spring was distinguished by shrinking long volatility with high short volatility, which is an unfavourable environment for the fund strategy. Market conditions remained choppy during the summer, with several markets still looking for direction.

In the late summer, the situation improved and we saw increasing long volatility in most financial markets. So, overall we saw a bad first half of the year with underperformance.

Enhancements we then made to the strategy proved their efficiency during the second half, with strong performance. In general, the second half of the year was a good environment with a low daily volatility, and thus provided a low cost for gaining a long volatility exposure, then a strongly increasing longer volatility.

What percentage of capital do you allocate to the strategy?

The leverage or exposure is measured as margin to equity, minimum of 8%, maximum of 20% and average of 15%.

What were the main drivers of returns in 1995?

The main drivers were rising bond prices on both the European and United States sides.

What volatility should investors expect to experience in your fund?

The volatility target of the fund, calculated on daily observations, is 10%.

What other funds do you run?

On top of the Global Markets fund at the firm we also run the er Global Volatility fund and er Global Equity Arbitrage fund.

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