Better understanding complex and opaque products through more dynamic analytical models.
It’s been a wild rollercoaster ride these days for Bitcoin investors. The cryptocurrency hit an all-time high of $64k in April only to plummet nearly 50% a month later. Last year, as the entire world shut down access to mountain peaks and surfing spots, people started to look for stay-at-home ways to supply their adrenaline fix – and speculative trading fit the bill.
Following up on our most recent article, “Infinity Q: Too Much Alpha,” Infinity Q also managed a hedge fund product, Infinity Q Volatility Alpha, which exclusively employed volatility strategies. Using known sub-strategies as regression factors for a multi-strategy product can prove very useful in identifying the source of both skill and risk in a more complex product.
The suspension of redemptions and planned liquidation of the Infinity Q Diversified Alpha fund (IQDNX, IQDAX) – a $1.8 billion hedge fund-like multi-strategy liquid alternatives mutual fund that was started by investment staff from the family office of a private equity titan – has sent shockwaves through the fund management industry. Using MPI’s quantitative surveillance framework we discover a slew of red flags that could have alerted the fund’s investors.
We use our tools and proprietary dynamic factor model to analyze Renaissance RIEF to gain insight into the results in the first quarter of 2020.
Bitcoin has had a spectacular year, with its price growing by 2,000 percent, topping out at nearly $20,000 before falling to a little over a third of that value. So, we posed the question to ourselves: how might investors have achieved Bitcoin-like returns over the last two years without needing Ambien to stomach the whipsaw swings in price?
We use Bridgewater All Weather, one of the largest hedge funds, to illustrate how to quantitative techniques could provide investors with a more dynamic understanding of the potential fund behavior intra-month using only monthly fund data.
A July 20th WSJ article featured Quantedge Capital, a quantitative global macro hedge fund manager that gained 40% after fees year-to-date through June. We provide a quantitative insight into potential sources of such performance.
As the trickle of announcements about institutional investors exiting hedge funds became a steady stream, MPI decided to explore whether performance really justified an apparent growing disillusionment. Whereas much analysis and commentary to date had focused on the recent failure of hedge funds to beat the S&P 500 and other equity benchmarks, in our research we wanted to find out whether hedge funds had failed on their own terms.