Tag Archives: time

Invaluable Information For Portfolio Rebalancing

Introduction If you’re a financial advisor (or a sophisticated investor), you know that the pains of portfolio management persist long after a portfolio has gone through its initial allocation. Take the example where you’ve put to work client’s (or your own) funds based on a pristine allocation that incorporated a well-devised Investment Policy Statement (“IPS”), current market dynamics, and client goals and objectives (e.g. future need). The funds have been fully allocated now for about 6 months, and you’re faced with the challenging task of “is it time to rebalance?” You might simply employ an interval-based rebalancing framework, (such as annual rebalancing) to ensure allocation weights don’t drift too far afield, but if you’re a student of capital markets, you know there’s more information that you might want to incorporate in your decision-making process. In this post, I go over some high level considerations and even summarize a back-of-the envelop calculation you can use if you don’t have access to tools like Viziphi. Drifting Weights & Risk Contributions At the time of portfolio implementation (or throughout the Dollar Cost Averaging process), dollars allocated to a specific asset or asset class are neatly apportioned based on some pre-defined weighting schema. If you’re implementing asset allocations that take tactical tilts based on your “view” of capital markets, then you’re likely quite interested in a deeper layer: how each asset/asset class is contributing to the risk of the entire portfolio over time. Moreover, as asset price fluctuations and underlying market dynamics change, there’s the possibility that drift and market dynamic have coalesced to expose the portfolio to far greater risk from a given asset/asset class than was originally intended. One terrific, easy to understand concept (and visualization corollary) is “Contribution to Risk.” There are different ways to do this calculation, however at Viziphi, we adhere to best practices of looking at assets’ contribution to tail loss, showing how risks within the portfolio have changed irrespective to, and including asset drift. With this information, advisors and investors can make fully informed decisions about whether it makes sense to rebalance to IPS risk allocations or stay put until the next rebalancing period arises. An Example Scenario I’ve created a 60-40 portfolio that incorporates alternative asset classes such as Commodities and REITs, using the following broadly diversified and deeply liquid ETFs: Asset Class Ticker Weight US Fixed Income BND 40% US Equity IWV 25% Foreign Developed Equity EFA 15% Foreign Emerging Equity EEM 10% Global REITs RWO 5% Commodities GSG 5% Assuming this is an annually rebalanced portfolio, here are the asset allocation weights on 1-4-2016 – the last date of rebalancing – and as of March 22nd, 2016, the close of the last trading day, assuming no trading activity during this time interval occurred. Click to enlarge From the image above, it’s clear that not much asset drift has occurred since the start of the year. The greatest drift has taken place in Foreign Developed Equities (NYSEARCA: EFA ) by falling nearly 0.5% and Foreign Emerging Equities by increasing nearly 0.5%. With a clear view on asset drift since the time of rebalancing, we can add a further layer of information by examining how risk contributions have changed. When looking at how asset contributions to risk have changed, it’s valuable to look at two different pieces of information: irrespective of weighting allocation and current (or past) weighting allocation. Equal-weighting allocation provides an understanding of how assets and their risk attributes have evolved in aggregate, whereas risk contribution using current/past allocation weights provides actual information about sources of risk and their magnitudes in the specific portfolio being analyzed. Click to enlarge From the above chart, it’s clear that there haven’t been dramatic shifts in how each asset is contributing to the risk of the entire portfolio. US equities and commodities ( IWV and GSG respectively) represent the biggest changes with about a -3% and 3% change, respectively. Examining each asset’s contribution incorporating the weights, e.g. the asset’s drift is illustrated below. Click to enlarge Note that the decrease in contribution to risk for US equity (ticker IWV) has been reduced even further by asset drift. If the advisor/investor believes that US equities are likely to outperform, this combination of asset drift and change in capital market dynamic could serve as a missed opportunity to gain the desired level of exposure. Even if the result is to maintain the current allocation, the advisor/investor has done one of the most important parts in the investment management process, which is to extensively test and understand how portfolio dynamics have changed and the potential impact of rebalancing or non-action. When an advisor validates investment decisions using a consistent and measurable investment process, the value they provide through their investment decisions is not only defensible, it’s irreplicable. Back-of-the-Envelope Estimate For users looking to do a quick estimate of this same calculation, here’s something that will get you fairly close (however, unfortunately, this does not take into account tail risk, but rather assumes returns are normally distributed): Take the log returns of the portfolio and each asset since the portfolio was last rebalanced Calculate the correlation of the log returns of each asset and the log returns of the portfolio Calculate the volatilities of each asset Multiply the correlation value of an asset with the volatility of the asset Sum all of the values from step (3) and then calculate the proportion that each asset represents of the total (that’s your marginal contribution to risk) Multiply the marginal contribution to risk in (5) against: a. Equal weights, that gives you your “contribution to risk” irrespective of weight b. Actual weights, that provides the “contribution to risk” based on actual holdings

Stock Spinoff Performance By Market Cap

I wanted to share a quick stock spinoff analysis. I downloaded all the stock spinoff data that was available on Bloomberg and then analyzed total 1-year returns, 3-year returns and 5-year returns by market capitalization. Here is what I found: micro-cap spinoffs outperform in year 1. Specifically, “Less than $500M Market Cap Spinoffs,” “Less than $100M Market Cap Spinoffs,” and “Less than $50M Market Cap Spinoffs” generated total 1-year returns of 29%, 37%, and 55%, respectively. However, over longer time periods, the outperformance of micro-cap performance fades. Over longer time periods, the best-performing spinoff market cap cohort is “Less than $1B” which generated 3-year and 5-year total returns of +69% and 170%, respectively. Here are the charts: Click to enlarge Click to enlarge Click to enlarge Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it. I have no business relationship with any company whose stock is mentioned in this article.

Don’t Be Fooled By The Short Squeeze

By Alan Gula, CFA On November 18, 2015, KaloBios Pharmaceuticals Inc. ( OTCPK:KBIOQ ) announced that Martin Shkreli and a consortium of investors had acquired more than 50% of its outstanding shares. The stock, which had closed at $2.07 that day, traded above $10 the day after the announcement. The next day, shares rose above $23 and closed at $18.45. The following Monday, the stock miraculously traded for over $45 per share. In just six trading days, the market cap of KaloBios had risen from under $4 million to over $160 million. It was a blatant example of market inefficiency. But what could cause such an irrational spike? The answer is an acute “short squeeze.” A sharp rally in the price of a stock puts pressure on short sellers, who are betting the stock will fall. They may feel the need (or be forced) to close out their short sales by buying the stock. The buying pressure from this short covering causes the stock to move higher, compelling even more traders to cover their shorts. Over the past month, we’ve seen a bevy of short squeezes as the U.S. stock market has bounced along with the price of crude oil. These squeezes haven’t been as spectacular as the above example, but judging by how heavily shorted some of these stocks are, they’ve been very painful for the short sellers, nonetheless. The following table shows a few of the largest squeezes: The short interest ratio (SIR) is the number of shares sold short divided by the average daily trading volume. The average SIR for S&P 500 constituents is 3.3 times. At 9.5 times, the average SIR for these stocks is much higher – and for good reason. The risk of bankruptcy is very high for the companies on this list. Thus, they all have Standard & Poor’s credit ratings of CCC+ or lower. Two of the companies are already in selective default (SD). Others will eventually join them. Many of the stocks on this list will end up worthless. Risks notwithstanding, the short squeezes have been eye watering. Chesapeake Energy Corp. (NYSE: CHK ) shot up 208%. Linn Energy LLC (NASDAQ: LINE ) annihilated the shorts with a 398% maximum gain over the past month. In spite of these equity gains, though, many of these companies won’t have fairy tale endings. For example, the 6% bonds due 11/15/2018 for Peabody Energy Corp. (NYSE: BTU ) have rallied, but they’re still trading around $7 ($100 par). The bond market is saying that there won’t be much recovery for senior unsecured creditors, which means that equity shareholders will be left with approximately zero. The equity shareholders of the companies listed above are deluding themselves if they think the market cap reflects underlying fundamentals. It’s important to recognize that a sharp rally in a stock doesn’t necessarily signal all is well. In most cases, these stocks aren’t rising from the ashes. In fact, many of the companies with the most violent short squeezes will end up filing for bankruptcy, just as KaloBios had to do on December 30, 2015. Safe (and high-yield) investing. Original Post Editor’s Note: This article covers one or more stocks trading at less than $1 per share and/or with less than a $100 million market cap. Please be aware of the risks associated with these stocks.