Founded in 2006, Quantedge is a quantitative global macro hedge fund with offices in Singapore and New York.
Eurekahedge: As one of Asia’s premier home-grown billion dollar macro hedge funds, please share with our readers the key highlights of your journey so far
The Fund was launched in October 2006 with AUM of US$3 million, and breached the US$1 billion mark in June 2014. The strategy has achieved annualised returns of 33% over the past 8 years, with NAV per share increasing from US$100 to US$917 as of July 2014. The team has similarly expanded over the years, and currently consists of 9 professionals in New York and 19 professionals in Singapore.
EH: You are one of the very few funds that have successfully grown assets without institutional or fund of hedge fund money. Growing from under US$5 million into a billion dollar hedge fund, how have you managed this feat?
We actually have about 15% of assets from institutions, with the remaining 85% of assets from ultra-high net worth individuals, family offices and employees. Approximately 60% of the growth in AUM of the fund comes from investment returns while the remaining 40% are from cumulative subscriptions over the years. Institutions typically learn about us from databases and ranking tables, while ultra-high net worth individuals are generally referred via word-of-mouth.
EH: The average global macro hedge fund has posted disappointing returns over the last three years, but Quantedge has posted handsome double digit returns consistently over the last six years. How has Quantedge ensured its ‘edge’ so consistently?
Quantedge has a systematic strategy that employs ultra-diversification across multiple asset classes, and a dynamic asset allocation strategy that enables us to overweight (underweight) more (less) attractive instruments. We also target constant volatility to ensure that exposures are tuned downwards during turbulent times and increased to take full advantage of calm periods.
EH: We notice that your fund has delivered spectacular annualised returns of 34% since its inception in 2006, with 2010 being a banner year for the fund (82% returns). How does your fund fare under different market conditions and what macroeconomic developments have been most favourable to your trading strategy over the years? What worries you most about the next potential downturn?
The strategy will perform best in a long trending market, with low volatility, and low correlations. In a directionless market with low to medium volatility, the strategy will generate moderately positive returns. The strategy will perform worst during a sudden, severe and correlated correction. We fully expect drawdowns to happen once in a while and recognise that it is an unavoidable aspect of the strategy. We take pains to actively dissuade unsuitable prospective investors who are unable to handle volatility by pointing out that a double-digit monthly loss is expected to occur once a year on average and a drawdown of more than 40% will happen in a severe crisis.
EH: Quantedge Global Fund targets annualised returns and volatility of 30% in its investment goals. Does return or volatility take precedence over the other in your investment decisions? For example, would you increase your exposure to reach targeted volatility even if the targeted returns have been achieved or exceed the volatility target in order to realise desired returns?
The volatility target of 30% is paramount. We run the strategy at this constant level of volatility at all times, and expect it to generate 30% annualised returns in the long run.
EH: Volatility seems to be an important component of your strategy. Could you provide us with some insight on how your proprietary statistical models estimate and achieve the targeted volatility in your portfolio? Do you use forward or backward looking models in predicting volatility and what role does manager discretion take in your strategy? Other than varying exposure to different asset classes based on expected volatility, do your models perform any specific ‘stock picking’ in individual securities as well?
The model is fully systematic, and is a reactive model – not a predictive one. We use historical data (including prices and liquidity) to statistically estimate expected returns, volatilities and correlations. For competitive reasons, we are unable to go into the details of our models, but we can reveal that we generally do not engage in ‘stock picking’ individual securities, and instead have some exposure to equity styles (e.g. value vs. growth stocks).
EH: Quantedge Global Fund takes up positions in a wide variety of markets, creating efficient portfolios in a manner similar to mean-variance optimisation. Could you describe how your portfolio looks like at any one point of time? How does ultra diversification improve the risk-return profile of your fund as compared to simple diversification?
We currently have more than 170 instruments in our investment universe, and will typically have positions in about 90% of these instruments. A single instrument will generally not account for more than 5% of the portfolio’s total risk, so the portfolio is always extremely diversified. Ultra diversification further enhances the risk-adjusted returns, relative to simple diversification.
EH: Could you share with us your major tenets for risk management? How do you deal with the threat of systemic risk that could affect the correlation matrix of multiple asset classes simultaneously? Especially during periods of stress marked by low liquidity in financial markets and increased correlations across the various asset classes.
Given that we target a constant volatility in our portfolio, we would, by design, have a good overview and quantification of the market risks at any point in time for each instrument and at portfolio levels. Liquidity risk is also of utmost importance to us and will have direct implications on the allocation of risks. We also estimate and monitor stressed scenario losses where different assets are expected to be most correlated. For competitive reasons, we are unable to go into the details of our risk models.
EH: Now coming full circle, what advice do you have for other new managers launching with just a few million, these days?
Be patient, and concentrate on building up a strong track record. A robust and long record of investment profitability is key. Capital raising is secondary.