I am still in a quant-mood at the moment, so today I will go through some work I’ve done on portfolio optimization with US large cap equity sectors. I am doing this to augment my current MinVar framwork, which I use for my own investments. A quick re-cap on the basics of portfolio optimization, with advance apologies to PMs reading this and lamenting that I’ve missed something. Finance has two workhorse models; the tangent portfolio, which places the investor on the efficient frontier, where risk-adjusted return—or the Sharpe ratio—is maximised. Or the minimum variance portfolio, which offers exposure to the combination of assets with the lowest variance, or standard deviation, regardless of return. These portfolios often are estimated given a set of constraints, as I explain below. Assuming most portfolio allocation decisions start with one of these ideal models in mind—you either want to achieve the best risk adjusted return or the lowest volatility—the difference between the textbook models and real-time allocations is governed by the following layers of complexity.
Read MoreI’ve recently added a new chapter to my long-running demographics journal, which I will present in more detail later this month. Before I get to that, I thought that I would have a look at my own financial performance in 2021. In preview, I did ok, but not as well as the market. My portfolio, split across two accounts at AJ Bell and Nordea, returned 6.6% in 2021, when adjusted for a significant zero-return cash position, and around 10% on its own. I am embarrassed to say that I dropped the ball on the month-to-date PnL calculations throughout the year to a larger extent than usual, so these numbers are a bit a uncertain. They are, in any case, far from the show-stopping returns of the MSCI World equity, index at just over 21%, let alone the performance of the mighty S&P 500, at 27%. My first two charts plot the top and bottom 10 performers, which is as good a basis as any to talk about markets.
Read MoreIt’s been a while since I updated these pages, mainly because I have recently moved across the country, back to the Big Smoke, where I am now nestling in the hopefully up-and-coming part of southern London. I will be up and running with my market updates and videos soon enough, but first things first. I have been sitting on this piece, mentally more than anything, for a while, and I thought it would be a nice way to re-start my posting. I have long been thinking about whether it is possible to provide a good quantitative argument in favor of the defunct value equities, or more specifically the value “factor”. I think it is, but as always, I leave to you to judge. In my last post before my temporary hiatus, I made the argument that the vast majority of investors are structurally short volatility. Accepting this premise raises the obvious question; how does one achieve a cheap and effective long vol position? In this post I will try to offer a concrete and quantitative perspective on this question using the simplest tools available to us from finance theory. Before I get to that, though, I want to state the problem more precisely. In a nutshell, the traditional 60/40 portfolio is doing too well. The increasingly concentrated leadership in equity beta centered around the ubiquitous growth factor—essentially U.S. technology firms—and the correlation of this position to the performance of government bonds—driven by structurally falling interest rates—has been a boon for investors. A 60/40 portfolio with a concentration in growth stocks has increased by a factor of almost 4 since 2010, beating the MSCI World by almost 25%, not to mention breezing past the main regional indices—MSCI EM and MSCI Europe—by a factor of 2-to-2.5. That’s great news, but it also puts investors in a bind. If a balanced portfolio is winning on both legs what happens when the tide turns?
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