Gold, Gold, Gold, Ale Ale Ale!!!

In May this year, I posted a note on a dynamic commodity long/short strategy which tries to establish a bull/bear signal for a specific component commodity market. Currently the model is signalling a bullish outlook for the precious metals sector, including gold and silver, for the coming month. Indeed, the signal is really strong as the underlying composite factors including fundamental factor, momentum factor, and market sentiment factor all point to the potential upside.

Interestingly, an article on Bloomberg today also confirmed the bullish outlook for gold.

"Gold will rise to more than $1,000 an ounce next month based on moving-average “deja vu” patterns since the start of 2005, according to Barclays Capital.

JPMorgan Chase & Co., Standard Chartered Bank and three other financial companies predicted bullion would top $1,000 in the fourth quarter, the survey by Bloomberg showed."


The party for gold has yet started....

An Innovative Asset Allocation Framework for Alternative Investment Strategies

I have recently developed a dynamic asset allocation model that could be used to address the need of investors focusing on absolute return performance, as compared to those investors with relative return performance mandate. Basically, the model is developed to try to address the following issues associated with traditional asset allocation models.

Firstly, portfolio optimization tools based on normally distributed asset returns (Markowitz) no longer give valid outcomes, as the inclusion of alternative investments introduces skewness and kurtosis (fat tails) to the probability distribution of the returns of a combined portfolio. Risk measurement tools may underestimate the true risk-characteristics of a portfolio. One needs a distribution with adjustable skewness and kurtosis, which gives a higher probability to outliers than the normal distribution.

Secondly, given the non-normality of the return distribution, the traditional risk measure - standard deviation - is unable to address the higher probability of extreme losses (fat tails) faced by most investors. An intuitive measure of risk (short fall risk) is used to only penalize downside risk in the portfolio risk budgeting.

Thirdly, traditional portfolio optimization with asset weights constraints might not generate truly risk-diversified portfolio. The resulting optimal portfolios tend to be overly concentrated in a very limited subset of the full assets or securities spectrum. Traditional 60/40 (i.e., S&P 500 and Lehman Aggregate) or so-called balanced portfolios do not offer investors true diversification because the 60% stock allocation (S&P 500) actually accounts for almost 95% of the portfolio risk. In a sense, 60/40 portfolios put almost all the “eggs” in one basket. When (not if) the stock market has a severe downturn (as witnessed recently), 60/40 portfolios would also suffer tremendous losses.

The following example shows the risk profile of an optimal portfolio, compared to its three underlying component strategies. The component strategies are long/short (market neutral) strategies in the equities and commodities space.