Category Archives: Applied Investment and Trading

24/3/18: A Traders’ Nightmare: When all Risks Coincide



Really great analysis of recent volatility spike (early February correction) from the BIS Quarterly:

“The VIX is an index of one-month implied volatility constructed from S&P 500 option prices across a range of strike prices. …Because it is derived from option prices, theoretically the VIX is the sum of expected future volatility and the volatility risk premium. Model estimates indicate that the rise in the VIX on 5 February far exceeded the change in expectations about future volatility (Graph A1, centre panel). The magnitude of the risk premium (ie the model residual) suggests that the VIX spike was largely due to internal dynamics in equity options or VIX futures markets.”


“Indeed, the considerable expansion in the VIX futures market – market size (ie total open interest) rose from a daily average of about 180,000 contracts in 2011 to 590,000 in 2017 – means such dynamics are likely to have had a growing impact on the level of the VIX.”

And the dynamics were spectacular. Per BIS:
“Among the growing users of VIX futures are issuers of volatility exchange-traded products (ETPs). These products allow investors to trade volatility for hedging or speculative purposes. Issuers of leveraged volatility ETPs take long positions in VIX futures to magnify returns relative to the VIX – for example, a 2X VIX ETP with $200 million in assets would double the daily gains or losses for its investors by using leverage to build a $400 million notional position in VIX futures. Inverse volatility ETPs take short positions in VIX futures so as to allow investors to bet on lower volatility.” One that comes to mind immediately is XIV. 

And things went spectacularly South for these, once VIX started heading North.
“The assets of select leveraged and inverse volatility ETPs have expanded sharply over recent years, reaching about $15 billion at end-2017 (Graph A1, right-hand panel). …many market participants use these products to make long-term bets on volatility remaining low or becoming lower. Given the historical tendency of volatility increases to be rather sharp, such strategies can amount to “collecting pennies in front of a steamroller”.

“Even though the aggregate positions in these instruments are relatively small, systematic trading strategies of the issuers of leveraged and inverse volatility ETPs appear to have been a key factor behind the volatility spike that occurred on the afternoon of 5 February. Given the rise in the VIX earlier in the day, market participants could expect leveraged long volatility ETPs to rebalance their holdings by buying more VIX futures at the end of the day to maintain their target daily exposure (eg twice or three times their assets). They also knew that inverse volatility ETPs would have to buy VIX futures to cover the losses on their short position in VIX futures. So, both long and short volatility ETPs had to buy VIX futures. The rebalancing by both types of funds takes place right before 16:15, when they publish their daily net asset value. Hence, because the VIX had already been rising since the previous trading day, market participants knew that both types of ETP would be positioned on the same side of the VIX futures market right after New York equity market close.”

“The scene was set.” Or put differently, once information about leveraged funds having to go long at the end of the day became market information, arbitrage went to work like a sledgehammer over trading books. The impact risk, compounded by adverse price movements, went through the roof. The two key changes in trading environment were made even more egregious by the fact that intraday spreads are usually higher toward the day close, and risk of non-execution had become completely intolerable for the leveraged funds. Which means spreads ballooned. This was a classic trading nightmare:

“There were signs that other market participants began bidding up VIX futures prices at around 15:30 in anticipation of the end-of-day rebalancing by volatility ETPs (Graph A2, left-hand panel). Due to the mechanical nature of the rebalancing, a higher VIX futures price necessitated even greater VIX futures purchases by the ETPs, creating a feedback loop. Transaction data show a spike in trading volume to 115,862 VIX futures contracts, or roughly one quarter of the entire market, and at highly inflated prices, within one minute at 16:08. The value of one of the inverse volatility ETPs, XIV, fell 84% and the product was subsequently terminated.”



15/1/18: Of Fraud and Whales: Bitcoin Price Manipulation


Recently, I wrote about the potential risks that concentration of Bitcoin in the hands of few holders ('whales') presents and the promising avenue for trading and investment fraud that this phenomena holds (see post here: http://trueeconomics.blogspot.com/2017/12/211217-of-taxes-and-whales-bitcoins-new.html).

Now, some serious evidence that these risks have played out in the past to superficially inflate the price of bitcoins: a popular version here https://techcrunch.com/2018/01/15/researchers-finds-that-one-person-likely-drove-bitcoin-from-150-to-1000/, and technical paper on which this is based here (ungated version) http://weis2017.econinfosec.org/wp-content/uploads/sites/3/2017/05/WEIS_2017_paper_21.pdf.

Key conclusion: "The suspicious trading activity of a single actor caused the massive spike in the USD-BTC exchange rate to rise from around $150 to over $1 000 in late 2013. The fall was even more dramatic and rapid, and it has taken more than three years for Bitcoin to match the rise prompted by fraudulent transactions."

Oops... so much for 'security' of Bitcoin...


15/10/17: Concentration Risk & Beyond: Markets & Winners


An excellent summary of several key concepts in investment worth reading: "So Few Market Winners, So Much Dead Weight" by Barry Ritholtz of Bloomberg View.  Based on an earlier NY Times article that itself profiles new research by Hendrik Bessembinder from Arizona State University, Ritholtz notes that:

  • "Only 4 percent of all publicly traded stocks account for all of the net wealth earned by investors in the stock market since 1926, he has found. A mere 30 stocks account for 30 percent of the net wealth generated by stocks in that long period, and 50 stocks account for 40 percent of the net wealth. Let that sink in a moment: Only one in 25 companies are responsible for all stock market gains. The other 24 of 25 stocks -- that’s 96 percent -- are essentially worthless ballast."
Which brings us to the key concepts related to this observation:
  1. Concentration risk: This an obvious one. In today's markets, returns are exceptionally concentrated within just a handful of stocks. Which puts the argument in favour of diversification through a test. Traditionally, we think of diversification as a long-term protection against risks of markets decline. But it can also be seen as coming at a cost of foregone returns. Think of holding 96 stocks that have zero returns against four stocks that yield high returns, and at the same time weighing these holdings in return-neutral fashion, e.g. by their market capitalization.  
  2. Strategic approaches to capturing growth drivers in your portfolio: There are, as Ritholtz notes, two: exclusivity (active winners picking) and exclusivity (passive market indexing). Which also rounds off to diversification. 
  3. Behavioral drivers matter: Behavioral biases can wreck havoc with both selecting and holding 'winners-geared' portfolios (as noted by Rithholtz's discussion of exclusivity approach). But inclusivity  or indexing is also biases -prone, although Ritholtz does not dig deeper into that. In reality, the two approaches are almost symmetric in behavioral biases impacts. Worse, as proliferation of index-based ETFs marches on, the two approaches to investment are becoming practically indistinguishable. In pursuit of alpha, investors are increasingly being caught in chasing more specialist ETFs (index-based funds), just as they were before caught in a pursuit of more concentrated holdings of individual 'winners' shares.
  4. Statistically, markets are neither homoscedastic nor Gaussian: In most cases, there are deeper layers of statistical meaning to returns than simple "Book Profit" or "Stop-loss" heuristics can support. Which is not just a behavioral constraint, but a more fundamental point about visibility of investment returns. As Ritholtz correctly notes, long-term absolute winners do change. But that change is not gradual, even if time horizons for it can be glacial. 
All of these points is something we cover in our Investment Theory class and Applied Investment and Trading course, and some parts we also touch upon in the Risk and Resilience course. Point 4 relates to what we do, briefly, discuss in Business Statistics class. So it is quite nice to have all of these important issues touched upon in a single article.




16/5/17: Insiders Trading: Concentration and Liquidity Risk Alpha, Anyone?


Disclosed insiders trading has long been used by both passive and active managers as a common screen for value. With varying efficacy and time-unstable returns, the strategy is hardly a convincing factor in terms of identifying specific investment targets, but can be seen as a signal for validation or negation of a previously established and tested strategy.

Much of this corresponds to my personal experience over the years, and is hardly that controversial. However, despite sufficient evidence to the contrary, insiders’ disclosures are still being routinely used for simultaneous asset selection and strategy validation. Which, of course, sets an investor for absorbing the risks inherent in any and all biases present in the insiders’ activities.

In their March 2016 paper, titled “Trading Skill: Evidence from Trades of Corporate Insiders in Their Personal Portfolios”, Ben-David, Itzhak and Birru, Justin and Rossi, Andrea, (NBER Working Paper No. w22115: http://ssrn.com/abstract=2755387) looked at “trading patterns of corporate insiders in their own personal portfolios” across a large dataset from a retail discount broker. The authors “…show that insiders overweight firms from their own industry. Furthermore, insiders earn substantial abnormal returns only on stocks from their industry, especially obscure stocks (small, low analyst coverage, high volatility).” In other words, insiders returns are not distinguishable from liquidity risk premium, which makes insiders-strategy alpha potentially as dumb as blind ‘long lowest percentile returns’ strategy (which induces extreme bias toward bankruptcy-prone names).

The authors also “… find no evidence that corporate insiders use private information and conclude that insiders have an informational advantage in trading stocks from their own industry over outsiders to the industry.”

Which means that using insiders’ disclosures requires (1) correcting for proximity of insider’s own firm to the specific sub-sector and firm the insider is trading in; (2) using a diversified base of insiders to be tracked; and (3) systemically rebalance the portfolio to avoid concentration bias in the stocks with low liquidity and smaller cap (keep in mind that this applies to both portfolio strategy, and portfolio trading risks).