Preparing for Volatility Expansion in Investor Portfolios

From 361Capital.com

Preparing for Volatility Expansion in Investor Portfolios

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As advisors work to position client portfolios for market conditions which may lay ahead, a common question is how certain investments may perform in an expanding volatility environment—an important consideration given recent low levels of volatility—and historical patterns of reversion.

When looking at the long-term average of volatility, it’s widely accepted that volatility tends to exhibit mean reversion traits. Using the VIX, a volatility index that represents the market’s expectation of 30-day volatility, one can see these reversion tendencies.

Daily VIX Price
Daily VIX Price

At the time this article was written, only 3 days—out of 6,889 observed days of VIX prices—closed below the May 8, 2017 price of 9.77. Those days came during Christmas week in 1993. Following that time period, implied volatility expanded roughly over the next two and half years, taking the VIX above the long-term average where it would continue its upward climb before bouncing between 20 and 40 until 2004. After a period of compression, a similar pattern of expansion can be seen again from late 2006-2007 before the Financial Crisis pushed the VIX to all-time highs.

Since 2008, the trend has been primarily one of continued compression—minus a few pockets of volatility in 2010, 2011 and again in 2015. This trend has pushed the one-year average VIX to a level below that observed in 84% of all other rolling one-year periods.

It’s true that the very calculation of the VIX implies that volatility levels are likely to stay low for at least the near term, and predicting exactly when the expansion will start is futile. With that said, only in the financial markets do people equate variance with risk. According to Merriam-Webster, investment-related “risk” is defined as the chance that an investment (such as a stock or commodity) will lose value. And, often times it is after market risks manifest themselves through loss that volatility spikes. Luckily, the purpose of proper portfolio construction is not dependent on the exact timing of these events, but rather an intuitive mission statement that may go something like this: “To position portfolios in such a manner to give the investor the greatest chance of prudently growing capital in accordance with the investor’s goals and risk tolerances given a likely forward looking environment.” In this case, the likely forward looking environment is one of expanding volatility, thus the question that
started this piece is appropriate to examine.

How should low volatility strategies such as, 361 Long/Short Equity Strategy, perform in an expanding volatility environment?

361’s Long/Short Equity strategies, sub-advised by Analytic investors, pioneers of the research surrounding the low volatility anomaly, combine two return-generating ideas where they look at the investable universe through two separate lenses. One lens is solely focused on returns, while the other is solely focused on the stocks’ risk profiles by using predicted betas. After risk controls for individual holdings and constraints are applied, the portfolio is optimized on predicted risk and return characteristics. The portfolios can be expected to have a net exposure of 70% over time, but with a beta much below what might be assumed, given that exposure level. In fact, the strategies have both targeted and realized betas of between 0.4-0.6, while attempting to match the return of the market over time.

When examining equity markets across quintiles of volatility, assuming CAPM holds, one would expect the lowest volatility stocks to underperform the highest volatility stocks. However, that is not what has been observed over time. Indeed, there is actually a relatively flat payoff to risk quintiles using simple averages, and that payoff falls off as you move across the curve to higher volatility stocks once you take into account that impact that volatility has on compounding.

The reason this is important background is twofold. First, generally these portfolios look to be 100% long the lower volatility stocks of a given market and 30% short the highest volatility stocks (Net 70% with a targeted beta of 0.4-0.6). Second, there are specific timeframes when high volatility stocks do outperform low volatility stocks. Those timeframes are generally during periods of volatility compression, or more appropriately, compression of implied volatility (VIX) associated with “risk on” environments like that observed in the U.S. for most of 2016. Conversely, during periods of a market’s implied volatility expansion, high volatility stocks underperform, and at times significantly. The chart below examines domestic stocks and volatility using the VIX, and different quintiles of returns of the Russell 1000 grouped by volatility.

Periods of VIX Compression: Low Vol – High Vol*

The red arrows and corresponding numbers represent the low volatility minus high volatility spread during time periods of overall VIX compression, while the green arrows and corresponding numbers represent the same spread during time periods of VIX expansion. It’s clear that low volatility stocks have historically performed better than high volatility stocks during periods of volatility expansion. To represent this further, the graph below compares cumulative returns for both low and high volatility stocks during “extreme” time periods. Here the graph examines the run up of tech stocks and subsequent collapse, as well as the financial crisis.

Cumulative Return Low Volatility – High Volatility with VIX

This graph also demonstrates that when high volatility stocks vastly outperform low volatility stocks, it is during times of “risk on” environments that have historically been associated with a compressing VIX. Conversely, low volatility stocks outperform as investors seek relative safety during periods of fear and thus an environment with expanding VIX.

Conclusion

It is not likely that volatility will remain at these low levels and investors need to prepare for a return to something resembling normality at some point in the not too distant future (and when that occurs, it will likely blow through “average” if history is any guide). Given investing is a forward-looking exercise, this means investors need to be thinking about how portfolios will perform when volatility does normalize (i.e., how best to include investments that benefit from an expanding volatility environment). While past performance is not indicative of future results, 361’s Long/Short Equity strategies may perform well given the structure of the stock compilation generally being long low volatility stocks while maintaining a short position in the higher volatility stocks. If expanding VIX levels do in fact occur and the historical pattern holds, which seems likely given the desire for investors to move to “safer” investment in the face of uncertainty, this positioning should be favorable

Someone Says Volatility Doesn’t Measure Risk

Notes from:

Volatility: A Misleading Measure of Risk

Pertinent when the VIX just hit low 10’s.

Michael Lebowitz says that there is a huge chasm between perceived risk (which if you go by VIX is 0) and reality. He like many others blames the Fed. It should be noted that hes selling “Financial Survival Guides” here. That should clue us in on what is to come in this note…

First, he includes a great quote from Chris Cole of Artemis:

“(volatility) is the difference in the world as we imagine it to be and the world that actually exists.”

The author then goes on to say that implied volatility “has been abnormally low more often than not” since 2008. “Currently implied volatility is at a level that has only been experienced 0.22% of the time since 1990 and is almost half of its longer term average.”

My issue with this is that implied volatility is the estimated volatility of the underlying price. You cannot just say “low” implied volatility. It has to be in relation to something – in this case implied (estimated) volatility has to be compared to realized (actual) volatility.

Here is their VIX chart:

Lets use the last 12 months as an example. Realized volatility is ~9%. Thats under the red line that he draws on the chart above.

This chart shows more:

My point is you can’t just say “implied vol is abnormally low” you have to compare it to realized.

Second, you could also easily make the case the markets in 1990 were totally different than they are now, for better or worse. For one, VIX options didn’t start trading until 2006. Markets are now all electronic and connected globally. Information spreads like never before. Dodd Frank, CCAR and the like have changed the risks banks can take, this is particularly an issue for hedging as they are required to have risk hedged in the event of a 20-30% equity market moved.

The reasons the author sites for this “low implied”:

  • The Fed & its easy money
  • Corporate buybacks
  • Volatility Trading
  • “Passive Mentality”

Strangely he mentions the falling dominoes the same day Martin Armstrong did. Coincidence? Someone copied someone…. I suppose his conclusion is to expect a major volatility event but he just says:

“When the entirety of the current situation begins to more fully reveal itself, investors are likely to find that the difference between esoteric measures of implied volatility and their very tangible perception of reality could not be more different.”

I think to find out how to hedge this coming cataclysm you have to sign up for their newsletter.

 

Remembering the “TVIX Fiasco”

History often rhymes – TVIX, VVX doesnt really rhyme but its close. Below is a very good review of what happened when TVIX broker and almost caused major problems for Credit Suisse.

As Volatility Turns: Understanding the TVIX Saga

Henry Chien, Formerly TG
02 March 2012

For many investors, all was well the week of Feb. 13 but anyone who peeked behind the scenes caught a glimpse of an episode worthy of its own award show in the financial world.

For many investors, all was well the week of Feb. 13 as the S&P 500 finally reached highs not seen since June 2008. The VIX dropped over the week by nearly 7 percent to finish at 17.78 that Friday as short-term volatility also receded. Yet anyone who peeked behind the scenes caught a firsthand look at an episode worthy of its own award show in the financial world.

Out of nowhere, the following week, on Feb. 22, Credit Suisse, the sponsor behind VelocityShares’ line of VIX exchange-traded products, temporarily suspended creation of shares in TVIX, a two-times levered short-term VIX ETP. According to a terse news release, the product’s assets had gone beyond the firm’s own internal trading limits. That was it. Except that the suspension electrified attention from market commentators.

So what happened? Well, the first forebodings occurred on Feb. 10 when notional vega volumes for TVIX over the day reached 52 million, an astounding increase of 128 percent from the previous day’s TVIX notional vega volume. Vega traded is the dollar exposure to the change in volatility. It disregards the notional price of the derivative contract. While somewhat odd, the VIX did spike 12 percent that day, which would indicate more the extreme skittishness on part of SPX option traders as the S&P 500 declined by 0.9 percent. High volumes in TVIX would be expected given the majority of its users are short-term speculators playing the index.

 

The following week – the week of Feb. 13 – another round of huge notional vega volumes in TVIX traded. Daily volume averaged 52 million each day, with a one-day peak of 72 million on Feb. 15. That compared with a five-day average daily 23 million in the prior week.

Authorized participants, who include market makers and HFT firms, have the ability to create new shares of TVIX to meet demand and ensure liquidity in the product. In the week of Feb. 13, total notional vega outstanding for TVIX notes jumped by 40 percent, or 17 million, to reach 60 million in just five days. As exchange-traded notes are unsecured debt securities, this number also indicates exposure from the point of view of the note issuer and the associated broker-dealer.

Keep in mind that under the ETN model, dealers are not limited to the VIX futures market and can hedge exposure via a variety of products. This feature is a plus given that liquidity flows across various products within the ecosystem of the S&P 500 volatility market. The caveat is end-user counter-party exposure.

Perfectly hedging that change in TVIX exposure over the week would require an equivalent 17 million in additional notional vega exposure, for the issuer, to rebalance the notes’ underlying holdings. That’s 3.4 million each day. The front-month VIX future traded a five-day average of 82 million per day in notional vega volume that week. Using these back-of-the-envelope calculations, a rebalancing of TVIX hedges would account for an estimated 4 percent of the front-month futures volume. This does not include the additional volume that would account for the daily rolling of the note.

While these numbers don’t seem like much, remember this is per point change in volatility – and in this case the corresponding VIX futures. This also does not take into account the market impact of this trading – an influence on the VIX futures price – that would make it tougher to cost effectively hedge.

During that Feb. 13 week, the front-month VIX future’s price rose, particularly on Feb. 15 when it jumped to 24.25, a 15 percent spike from the previous day. At the end of the week there was a 3.58 premium over the spot VIX, or 19 percent, and that premium remained elevated over the following week.

 

I’m not necessarily arguing a connection between the huge increase in TVIX vega volumes, the rebalancing to hedge the change in vega outstanding, or the spike in the underlying front-month VIX future. Rather, the confluence of the events all contributed to a perfect storm that made it difficult to manage exposure, which undoubtedly played a hand in Credit Suisse’s decision to suspend creation of TVIX notes.

In other words, I imagine a prudent trading manager took a look at TVIX liquidity, compared it with liquidity in the VIX futures market, assessed the desk’s position, and decided, ‘Whoah. Let’s back away from this. Better safe than sorry.” Further issuance of TVIX notes was then suspended.

One consequence was TVIX then effectively became a closed-end fund. With a cap on supply, TVIX began trading at a premium to its net asset value, the level of which has fluctuated since and remains in place today. The price of this premium is an additional market-determined element for TVIX that should be interesting to observe as it changes with differing levels of volatility.

While this episode has been great fodder for market commentators all around, there is a broader implication for industry participants. It demonstrates the limited direct arbitrage of VIX futures to the underlying spot VIX – and thus movements in the VIX futures market can be subject entirely to forces of supply and demand. While front-month VIX futures tend to trade at a slight premium to spot, the movements of the past few weeks highlights the potential for the contract to occasionally and temporarily move in a different direction than the underlying spot VIX. As more participants trade volatility directly, thereby broadening the variety of views on the direction of the VIX, it is likely this kind of action will happen again.

Surging liquidity in the VIX ETPs – which in turn has broadened access to volatility – is a key driver behind trading volumes in the VIX futures. Welcome to the new world of volatility as an asset class.

Trouble Comes When VIX Term Structure Inverts

There is a very good presentation from JPM here on VIX and VIX related products. One section that caught my eye was on VIX futures term structure inversion. The presentation is from 2012 – but the data from 1990 says that you don’t see major VIX spikes (over 40) unless the term structure in futures is inverted first. Also, the VIX was around ~20 before going to 40+. IE there aren’t many incidences (or any?) where the VIX is 12 today and 40+ tomorrow. Incidentally I checked August 2015, and the VIX hit ~21 on the Friday before the major spike to +40 (Monday).

Summary: When the VIX term structure inverts you need to be on watch.

JPM VIX futures term structure

 

You’re Probably Short Volatility and Don’t Realize It

I like this presentation from Nomura:

Vol Risk Premia in Equities

“Selling Vol” or Earning a Risk Premium?

The author brings up the fantastic point that if you are making a return via long stocks, long bonds etc then you are short volatility.

One of the great things he mentions is Warren Buffet when he calls derivatives “weapons of mass destruction” – but he loves selling puts. Hes cunning.

Click here to see the presentation.

What is “Volatility Risk Premium”

Russell Investments relates volatility to prospect theory.  That explanation takes a different tact than many I’ve read. They equate shorting volatility to selling insurance, saying that even in large market drawdowns volatility can recover (i.e. mean revert) more quickly than underlying markets.

While I’ve read that put/call skew didn’t exist before the October 1987 crash, equating all put options trading to prospect theory is quite an oversimplification. Due to regulatory issues like CCAR and Fed Stress Tests, banks and other regulated entities are required to hedge their books and often due so with put options.

The edge as shown in their chart from selling 50 delta options in the S&P is interesting – but 50 delta is quite close to at the money. Anecdotally I think many of these studies look at options more in the 20 delta range -obviously less risk but less return in selling  options with a lower delta.

From RI:

Volatility is defined as a measure or the variation in the price of an asset over time. Individuals are risk averse; they prefer a certain gain to a potentially larger uncertain gain where there is also a risk of loss. Higher risk or volatility has a greater potential for larger losses. It is this desire to avoid loses that leads individuals to pay for insurance. Identifying this behaviour – where losses and gains are evaluated in an asymmetric fashion – is what behavioural economics calls ‘prospect theory’. The world famous behavioural economists Kahneman and Tversky received a Nobel Prize for this.

This precise human behaviour is what financial and insurance companies try to exploit by providing products and services that protect ‘tail events’ (or events which, if they occur, can lead to a high cost). Examples are damage to your car (car insurance), fire damage to your property (property insurance), and risk of damage to property from earthquake (catastrophe insurance). Individuals are so keen to avoid risk that they often overpay for insurance. It is this behaviour that we are seeking to ‘profit’ from. It is possible to capture a return premium from selling insurance to those wishing to protect themselves against market uncertainty. This is what is known as the ‘volatility risk premium’.

Financial markets have similarly created securitised investment products that can price these risks in the markets using forward looking estimates of volatility (aka implied volatility). An imbalance of demand for hedging (or insurance) over supply pushes up the price of implied volatility over and above what is considered ‘fair value’. This systematic overpricing of implied versus actual (or realised) volatility can be captured by sellers of insurance and can be considered to be a form of insurance premium – or more formally the Volatility Risk Premium (VRP).

So let’s return to the question, why is volatility not necessarily a bad thing for investors? If volatility is treated like any asset that has a long term expected return and a risk profile, it can be considered as a viable part of an investment portfolio. The expected return that investors can aim to capture is the VRP i.e. the difference between implied and realised volatility. History has shown that this difference or spread on average is positive 4 out of every 5 years (see Exhibit 1 which shows how implied volatility has been generally higher than realised volatility).

Simplistically this can be thought of as selling hedging or insurance in the derivative markets, and systematically continuing with this strategy to profit from the asymmetry of returns over time. However as in insurance markets, sellers of insurance products should always be wary of the risk of large losses and hedge their exposures accordingly.

In this case, as we are selling volatility or are short volatility, any spike in volatility should result in a negative outcome for this systematic strategy. For investors that own other risky assets such as equities, a spike in volatility is also associated with a drawdown in equities. The two risks are not equivalent, as the drawdown in a short volatility strategy is typically smaller and the recovery is quicker versus equities. Nonetheless the co-movement between the two assets cannot be ignored.

Profiting from the Volatility Risk Premium 2 Exhibit 1: Volatility risk premium on a rolling basis

Russell Investments Volatility Risk Premium Returns

At Russell we believe that the VRP generates a worthwhile return source that provides diversification to traditional asset classes. The VRP has proven to be persistent over the long-term, as investors in options markets are inefficient at pricing risk and thus provide the opportunity to extract this premium on a sustained basis. By employing a systematic investment approach and diversifying across a number of underlying volatility strategies, investors are able to add value to their portfolios.

Within the context of total portfolio management, a multi-asset portfolio, should aim to combine a number of different risk premia in the appropriate way to achieve the desired risk/return outcome for the investor’s particular investment objectives.

Furthermore strategies that can outright benefit from markets sell-offs may be employed. These include for instance options-based downside protection strategies. When combined with VRP the result is a ‘better’ risk-adjusted portfolio return. The whole portfolio must be managed dynamically, including the interactions between components and between the portfolio and the goals that it is aiming to achieve.

<end RI>

Harvesting Volatility Risk Premium

Harvesting Volatility Risk Premium (VRP) – aka Selling Vol

This paper from Parametric covers three ways to sell equity vol:

  • Index options
  • Variance swaps
  • VIX futures

My Summary and notes from Parametric Portfolio:

Selling Index Options [ex: SPX, RUT, VIX]

He looks at selling straddles and strangles using 20 delta options. 20 delta options are generally far enough away from where the underlying asset is trading that they shouldn’t (but they definitely can) go in the money – while still having enough risk that they hold some value. I.E. 20 delta options are seen as a good risk/reward balance.

Selling straddles and strangles is essentially a bet that implied volatility (at the level you sell) is higher than the realized volatility of the asset. Essentially if you sell the option and the option moves in a major way you could lose. If the stock flat-lines, you should come out ahead.

According to the author selling index options has less volatility than selling variance swaps and/or futures. And if the options are fully collateralize you reduce the chance of margin issues. (You can definitely have a “cash secured”  short put, but I don’t think there is such a think as a cash covered short call, because you have essentially unlimited risk).

He calls options “an impure form of trading volatility” because the options are only “indirectly linked to volatility.” The options price is ultimately determined by price of the underlying. I would agree with this in regards to stock options, and some index options however I would say that might not be as true with VIX Index options. (VIX is linked to the value of rolling 30 day options on the S&P500).

Finally he says that “it can be daunting for inexperienced investors to manage an option strategy”. But variance swaps aren’t?

Variance Swaps

The “swap” in “variance swap” is a misnomer as there are no cash exchanges for the duration of the trade. The variance swap has a fixed strike and expiration. The value of the contract is based on the difference between the “realized variance (volatility squared)” of a given asset (usually an index like the S&P500) and the strike level. The value of the variance swap is related to the vega notional which is a metric used to determine the sensitivity of a derivatives value to the changes in volatility.

Essentially its a more “pure” bet strictly on the volatility of an asset. The seller of the variance swap bets the buyer that volatility will stay under x level. These are called OTC (over the counter) trades and are generally left to banks, hedge funds and the like. The author says these are “the purest” form of trading volatility. They are also easy to leverage and can be tailored to meeting investors specifications.

The downside of these contracts are the “quadratic form of the payoff function”. Which essentially means that the returns are “convex” or upward sloping. A stock for instance has a linear payoff – you make $1 per share if they stock goes up 1 point. When volatility really spikes the variance swap (and all options for that matter) can start with a return of $1/pt then quickly rise to return 4,5,6 and up per point. Put another way its a curved upward sloping (convex) payoff, not a straight line.

VIX Futures

Derivatives linked to VIX offer investors a “direct approach to monetize the premium embedded in equity volatility” as the VIX is linked to the S&P500 index options. He alleges that VIX futures are more popular than variance swaps. The VIX futures are a popular form of “tail risk” insurance, but its expensive as they contango of the VIX futures curve makes it expensive to own. I.E. owners of VIX futures lose every month rolling the futures in a “normal” environment. So if you were to sell you might make profit on this roll.

VIX Futures Curve

VIX futures are very liquid and are a pretty pure play on volatility. The futures can be very volatile in the short term, distorting  pricing. There is a strong equity beta towards VIX futures (linked to the movement of the S&P500). Notional exposure of VIX futures is expressed in vega (as in variance swaps).

The Returns:

I heard someone once say “no one ever lost money backtesting”. I agree, so take the returns below with a grain of salt. In reality you have issues to deal with when actually trading this stuff – margin calls, transaction fees and the like. That being said you can see the significant drawdown on the variance swap. Linking back to the authors note about the “convexity” of the variance swap gain/loss …I would not want to be on the wrong side of that trade.

short volatility returns

The Benefits of Systematically Selling Volatility

Now seems like a good time to reexamine shorting volatility. An interesting paper from RiverPark Funds ($4bn AUM): “The Benefits of Systematically Selling Volatility”

A good overview of some short vol strategies – mainly selling straddles when the spread between realized and implied volatility is high.

They conclude (unsurprisingly) that its a good way to generate alpha if you’re disciplined.On its face the results as seen below are compelling.

I’d note that when back-testing every strategy looks good – you don’t have to content with margin calls and the like. Certainly when your short volatility and the markets get chippy you can expect your broker to increase their capital requirements, which cause hedging (or liquidation) and that eats into returns.

riverpark short strangle returns

“Forecasting a Volatility Tsunami”

Andrew Thrasher CMT won an award for this paper “Forecasting a Volatility Tsunami” which is about preemptively detecting major moves in volatility. The paper is here. My review/notes are below.

He calls it the “volatility dispersion method”. Essentially he looks at the “20 day standard deviation” (he arrived at 20 days through Bollinger Bands, and notes the time period could be optimized) of the VIX and VVIX and notes that the largest spikes in VIX occur “when price dispersion is extremely low”. He then runs the same excercise with VVIX, creating two “signals” to use marking low “price dispersion”. His theory is that this is a great predictor of an impending volatility spike.

Here is my problem. His data set was May 22, 2006 to June 29, 2016. Why? I don’t know much about the market around May 2006 but I know a lot about June. That was BRExit. His data would catch that volatility event, but ignore the rest of the year.  Also many of the papers and data he cites are very old – he quotes a VIX options volume stat from 2011 (its a 2017 paper). He did use 10 years of data which is quite a lot, so its possible that the rest of 2016 didn’t diminish his signal.

The notable thing about the rest of 2016 was:

  1. Historic levels of calm – “low price dispersion” as Thrasher would call it.
  2. Volatility mean reversion at record speed indicating large demand to sell vol and keep it lower.

So, I’d be very curious to see why he chose those dates. The other stat which he doesn’t mention is realized volatility. I would be curious to see if the “dispersion” measurement would work on the S&P 500 as a whole as well? Several times he notes that there is an “anecdotal belief…that a “low” reading in the [VIX] or a large decline alone are ample reason to believe that volatility will spike in the near future.” Well, whats “low”? To answer that you have to examine realized vs implied volatility levels.

My point is that while this signal could prove useful I wouldn’t take it for anything more than face value. I would also hesitate to base much off of it going forward if the Fed substantially changes its methodology (removal of Fed put) as that type of structural market shift could ruin this signal.

For example, using this signal to buy UVXY or VXX still probably gets you nowhere.

finviz dynamic chart for  VXX

 

 

“Vol of Vol” Research from Pioneer Investments

“A Sting In the Tail” is an interesting 2015 paper from Pioneer Investments (AUM $240BN USD) that seems prescient today. Much of it is covering different indicators and signals of impending doom aka “tail risk”.

Two things I found particularly interesting:

  1. Their mention that the flood of liquidity [from central banks] has kept volatility artificially low. Just last week the Fed hinted at reducing their role, saying markets were “overvalued” and the market spooked.
  2. Crowded trade: the world is short volatility as a way to generate alpha (returns). Remember the State of Hawaii selling cash secured puts (they are required to have 105% collateral per put). Also the popularity of short volatility ETF/ETN’s and you can start to get the picture. When the short vol positions have to be unwound there could be a really nasty move up in volatility.

Jump to their full conclusions:

→ Standard volatility measures do not provide investors with sufficient information about the actual level of risk they are assuming in their portfolios.

→ The potential for a sustained rise in volatility remains:

– The low interest rate environment means investors have to embrace more risk to meet their investment goals

– There is no longer synchronicity in the policies of the global central banks. The European Central Bank and the Bank of Japan continue to pursue ultra-loose monetary policies, while the Federal Reserve appears primed to raise rates for the first time in almost nine years

– Abundant Liquidity, but not where needed

– There is evidence of investors herding into consensus trades.

→ As long as this situation continues we think that the actual frequency of extreme events will be higher than the implied frequency of such events.

→ We believe that “fatter tails” could be a feature of investment markets for the foreseeable future and investors need to reappraise the traditional methods of measuring risk and portfolio construction.

→ In the prevailing environment, prudent investors may wish to consider hedging against extreme events.

→ In managing extreme events, it is important to analyse multiple scenarios that may drive significant portfolio losses and estimate their probability of occurrence.

→ It is vital to stress test portfolios to estimate the extent of potential losses under extreme circumstances. This enables an assessment of the most efficient way to protect a portfolio from significant loss.

→ We strongly believe in the renewed role of hedging techniques to help protect against tail risks.

→ Thanks to the development of the derivatives markets, there are multiple hedging techniques available to help protect against tail risks. In our experience, it is prudent to hedge low probability events that may have a material effect on portfolio performance, as long as the cost of providing portfolio protection is not excessive.

<end of Pioneers conclusions>