Category Archives: White Papers / Thought Pieces

Volatility, VIX & The Weeklys


(previously published on LinkedIn)

by Jack Fonss

The range of volatility products has continued to grow since the launch of VIX futures, but greater product choice has not necessarily simplified volatility trading. Most active traders continue to find the volatility market more idiosyncratic than other markets. Quick jumps, reversals, and VIX’s range-bound properties all mean that volatility analysis and trading differ from more conventional markets.

The presence of conventional-looking features in the volatility market such as spot levels and futures markets make it tempting to analogize to other asset classes – however, unlike other asset classes, S&P500 volatility may be more like a collection of separately and loosely related sub-markets rather than a single market.

Historically, volatility trading tools have been aligned with their direct application to options trading and options hedging (with a focus on 30 day and longer expirations). The CBOE Weeklys initiative will change the users and the applications of volatility tools. While the most often cited benefits of the CBOE Weeklys are higher-delta and more responsive contracts, I believe that the Weeklys are also a new direct market for near term volatility – because we now have a good tradable surrogate for the elusive cash volatility, we can now have the widest range of traders participating in price discovery.

What Makes Volatility Unique?

Most commodities and financial instruments have spot and forward levels which look similar to VIX curves (albeit the VIX curves are usually more pronounced).

Further, most commodities and financial instruments share the property that a barrel of oil (or share of stock) is fungible across time – once one accounts for factors such as storage costs, interest rates, and dividends, the barrel (or share) bought or sold today is translatable and convertible into the same barrel (or share) transacted in a forward market.

In contrast, volatility in different timeframes (e.g. 1-week spot, or 1-week 3 weeks forward) have no simple linkage – volatility underlying an index or contract is temporal and generally linked to a specific 30-day period now or in the future. The “temporal specificity” of a particular volatility is more like rainfall or temperatures within a specific month, and less like XYZ Co. stock which can be bought or sold spot or 30 days forward.

What Might the Addition of the Weeklys Deliver?

Even though the settlement values of the Weeklys are entirely based on the specified options chains, Weeklys trade independently from the options underlying the VIX values. I expect much of the Weeklys’ volumes will be transacted by portfolio hedgers and traders positioning to enter and exit equity index positions.

There are lots of estimations regarding the expected correlation (of daily returns) and term structure (of price levels) between the Weeklys and the cash VIX. By my rough estimation, the return correlations since last October (the launch of options on the Weeklys), exceeds 0.90. Early and rough estimates of the 1 week term structure (i.e. percentage term structure curvature over 1 week) are approximately 3%; when one factors in that futures-to-spot measured at and around futures expiry is ~ 1.5% (that is, even when time-to-expiry is practically zero, futures prices tend to fall ~ 1.5% over cash values), a “real” average 1-week term structure can be estimated to be between 1 and 2 percent. Even with light volumes, I believe that the Weeklys have already delivered on their goals.

An underappreciated benefit from the introduction of the Weeklys may be increased choice for volatility product users. Even though most of the volatility product landscape is dominated by 30-day forward/30-day volatility underlyings (seemingly simple), operations of these products usually force a rules-based daily trading regime which complicates timing and positioning for the uninitiated. The addition of Weeklys may present opportunities to deliver simpler exposures.

Of course none of this is a recommendation to buy or sell Weeklys or anything related to the Weeklys. But, I do recommend that those interested in volatility market structure closely follow developments in this space.

The ETF Paradox and Defying Physics

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(previously published on LinkedIn)

by Jack Fonss

While ETFs are generally designed for passive indexing, their continued growth means that they may influence and alter the underlying markets they seek to passively track.

ETFs pursue a number of ideals including simplicity, intuitive use, and low cost, but all ETFs are constrained by market realities. Similarly, new ETFs need to promise something novel (and currently unavailable), but where an ETF is constrained by the underlying market that came before it, the measurement of novel and useful becomes subjective. While the “physics” of more and larger ETFs would seem to lead to unavoidable concerns, some clever pivoting in product design may cure these concerns altogether.

New SEC proposed rules are formally raising questions about how ETFs operate within their larger markets in theory and in reality. While further and continued ETF growth might appear to exacerbate market structure concerns, continued ETF growth actually presents opportunities for accurate and less market-impacting ETFs which do not alter or overrun their underlying markets.

Ideals vs. Realities

An ideal ETF should be perfectly linked to its underlying, have unconstrained creation and redemption activities, and be more intuitive to use than its underlying constituents or market. Done to perfection, the ETF becomes a more perfect version of its underlying market than the actual underlyings. As a credit to the ETF industry and many of the industry’s pioneers, a number of ETFs (including many large cap equity ETFs) appear to actually achieve this seemingly impossible goal, and the majority of ETFs do a very good job.

ETFs and Quantum Mechanics

Common wisdom suggests that the physical mass of the ETF space cannot be overcome – that is, as ETFs become larger relative to their underlying markets, the creation/redemption/trading activities of the ETF will influence and alter daily and intraday movements of the underlyings. However, I believe that physics can be overcome with some product design. The measurement linkage an ideal ETF has with its underlying assets has some interesting parallels in pop-science including the Heisenberg Uncertainty Principle, Schrodinger’s Cat, and the Observer Effect.

In brief, Heisenberg states that precision of measurement in one dimension constrains measurement precision in another – “we cannot independently measure the level of the S&P500 and SPY’s price”.

Similarly, Schrodinger suggests that two or more mutually exclusive states can coexist – “volatility ETPs both track and lead VIX futures”

And lastly, the Observer Effect states that the act of measuring a phenomenon (or state) affects the phenomenon (or state) we’re trying to measure – “do commodity ETPs change commodities prices?”.

…collectively the ETF Paradox – ETFs seek to do what may sometimes be physically impossible, and to date they have done it surprisingly well.

Avoiding the Physics – How a Larger and More Complete ETF Market Helps

The ETF industry has continued to deliver more investing tools for different directional views, different time horizons, and a wide ranges of markets and indices. In our current world, each ETF trades independently in its underlying market leaving footprints of order flow, price impact, and transaction costs behind. For a variety of regulatory, administrative, operational, and tax reasons individual ETFs and ETP fund families are largely precluding from netting down (or not trading) underlyings across funds.

With the merging of some new and some old technologies, I believe that ETP fund families will be able to consolidate their share issuance into multi-share arrangements. Consider that many fund families have long (e.g. “+1x”) funds, inverse funds, and leveraged funds in differing direction, where the actual net market delta is low or zero. Similarly, many liquid and widely held ETPs are used as two-way trading tools – reported short interest can be in the billions of dollars. By re-configuring some of the more challenging funds, a largely self-contained ETF ecosystem can be created with less impact on underlying markets. In equities, credit, commodities and other markets, much of the natural demand for longs, inverses and geared funds can be sourced from within the ETF market itself. A well-structured system can deliver the benefits of a self-contained ecosystem and accommodate differing ETF supply and demand conditions.

An industry goal should be an advancing ETF world in which a bigger and more complete ETF marketplace delivers better price discovery and liquidity without the risks of over-running underlying markets.

Are You Paying The Other Guys ETF Taxes and Does It Matter? …or how I lost money trading “XYZ” and then got a tax bill

(previously published on LinkedIn)

The answers are Probably, and Maybe.

Of course, none of this is tax advice – even for the fictional ticker “XYZ”.

I’ve heard the story many times of investors losing money in a quick ETF commodities trade, only to be surprised months later with a K-1 tax allocation.  Like many puzzling phenomenon in ETF investing, investors will choose one fund over another over 0.01% in annual fees, but somehow the mystery of $2,000 of taxable income is quickly forgotten – and then repeated.

While the 2016 presidential campaign term “schlonged” might seem the appropriate characterization for getting taxed on someone’s else’s gain, the reality is more complex and less awful.

General ETF Tax Principles.

Many ETFs create and redeem their shares through “in-kind” transactions, where dealers who transact directly with the fund essentially deposit or withdraw actual securities from the fund in exchange for the fund’s ETF shares. In brief, because a fund doesn’t generally sell securities (but rather ships them out in exchange for its own shares in a redemption), and because these “in-kind” transactions are generally non-taxable, gains which would otherwise be taxed are avoided. Any remaining taxable gains must be allocated to investors, but those remaining gains are usually minimal.

In contrast, those ETFs which transact directly in futures or derivatives cannot avail themselves to in-kind exchanges – generally these funds regularly trade their positions and they regularly create taxable gains and losses. Because the tax needs to be paid, and because these funds seek to minimize multiple layers of taxation, taxable items which would otherwise be borne at the fund level are allocated to the fund’s investors (based on proportional holdings). Holders of these funds usually receive a K-1 allocation of the fund’s taxable items.

So how does an investor that took a loss in a fund’s shares get tagged with a fund’s taxable gains?

What’s Going On In These Funds?

Similar to scheduled roll/trading dates, these funds also  identify a schedule of taxable income allocation; this schedule is usually detailed in the fund’s prospectus  - look for the “tax consequences” section or search for phrases such as “monthly allocation” and “in proportion to”.

Many funds have adopted a monthly schedule which is based on “the last trading day of the immediately preceding month” –  this means that if you hold shares on November 30th, even if you sell your shares on December 1st, you are allocated the fund’s taxable items for the entire month of December. Similarly, if you acquire shares in early December, but sell them prior to the end of December, you will be allocated none of January or December’s taxable items. When a fund’s taxable items are allocated based on a single day’s holding from the prior month, taxable items and ETF-share market results may have little relationship. Revisiting the earlier example, where an investor holds shares in November (including the last day) and sells early in December, and where November stinks and December is great, a share loss accompanied by a tax allocation is likely.

How Is This Reasonable?

In the example where an investor pays $10,000 for ETF shares, sells them for $8,000, and then gets a $2,000 K-1 allocation, the K-1 allocation presents both a tax bill (bad) and an increase to the investor’s tax basis (good). So while our investor’s taxable income has increased by $2,000, our investor’s tax loss has also increased by $2,000 (i.e. 2,000 is added to the cost basis of $10,000 for a tax loss of $4,000; 12,000 – 8,000) – our investor has “traded” $2,000 in additional income for an additional $2,000 in tax losses.

Two related and general principles of partnership (K-1) taxation include: (i) taxable income allocations are generally added to one’s tax (cost) basis, and (ii) distributions of cash or property are generally deducted from one’s tax (cost) basis.

Because different funds have different underlying assets, and different underlying assets generate different kinds of income (e.g. precious metals funds have different taxation than crude oil funds), it’s hard to generalize about the K-1 impact. Similarly, because different investors and different holding periods will cause different types of gains and losses on ETF sales, it’s hard to generalize about the impact of ETF taxable trading gains or losses. Cautioning again, that this is not tax advice, an investor may find himself with a mismatch of non-offsetting gains and losses, and possibly a tax loss carryover for next year.  Uncle Sam is generally more excited to share your gains, and less excited to participate in your losses – tax character asymmetries (e.g. ordinary vs. capital) and limitations on certain tax items usually tip in favor of Uncle Sam.

What to Do.

Again, cautioning that none of this is tax advice, investors in all ETFs are encouraged to keep accurate records of cost bases (the plural of basis!), allocated tax items, and the character of the gains and losses their portfolio is generating. Additionally, investors should be sure to record and track carry-over items. In other words, don’t blindly download brokerage statements or blindly enter K-1 items into your return.

ETFs, Their Alter Ego, and the Future

(previously published on LinkedIn)

Far from the original “spider” ETF, many of today’s ETFs look to deliver new kinds of returns in a wide range of markets. The recent Icahn-Fink debate over fixed income ETFs, the recent SEC release on leveraged ETFs, and the perennial debate around futures-based ETFs all look like separate issues, but they all go to the same basic questions – what are ETFs supposed to be, and how are ETFs supposed to interact with (or be isolated from) the larger market. Further, ETFs almost always face an identity crisis prior to launch – in order for a new ETF to be useful it must deliver something currently unavailable, but at the same time, it must be the same as everything that’s come before it so that it can be easily regulated, valued, and arbitraged.

In an ideal world, ETFs would deliver perfectly intuitive returns and continuous liquidity, while neither impacting nor relying on underlying market limitations. As a testament to the ETF industry, it actually has done a remarkable job of launching useful and effective tools which fit neatly into available liquidity and real-world constraints.

Where Are We Going In the Near Term?

New ETFs will continue to present two faces to the market:  the new-new thing on one hand (to the media and investors), and “nothing to see here” on the other (to regulators and market makers). This approach may become impractical as the industry tries to deliver new tools and to fix old ones. Nobody likes the idea of flashing 15-second indicative values over a pool of trade-by-appointment high yield loans for the “benefit of” fixed income ETF investors; but where there’s a demand for access to otherwise challenging market exposures, the industry should evaluate how to best deliver it – even where the delivery solution is not based on the original “spider”.

ETF Myopia.

A good consequence of our vast ETF market is that investors and traders don’t need to leave ETFs to trade an almost unlimited range of long, short and hybrid positions. A bad consequence of our vast ETF market is ETF myopia – that is, ETF investors and traders usually forget that there’s a trader or counterparty on the other side of every ETF share; somebody bought, sold or swapped something for the ETF to create its shares. For example, an explosion of AUM in a commodities ETF doesn’t mean everyone’s a buyer or a bull, but rather it means that (at that commodity price) there’s a whole lot of futures-market sellers willing to go short to ETF investors. Using the ETF market as one’s sole lens into market trends is almost certain to miss half the story.

Where Are We Going In the Long Term?

The original spider has taken the industry through over two decades with thousands of launches across hundreds of markets. As the ETF industry continues to explore new markets and improve on old ones, it’s likely that variations on the spider formulation, if not wholly new solutions are likely to be advanced.

In particular, if we can read the range of analysis and questions in the SEC’s recent proposal (on derivatives in leveraged funds) as constructive, the industry may have an opening to both keep some old solutions and to advance new solutions in response to long-standing market demand.

Lessons for a Startup from a Startup

(previously published on LinkedIn)

Anticipating and Navigating the Post-Launch Pivot

Launching a start-up is all about meticulous plans for products, patents, market share, and capital. In practice, those carefully orchestrated plans are quickly overwhelmed with the realities of budgets, staffing, leases, taxes, IT systems and everything else that didn’t make it into the spreadsheet plans. And, if the start-up has a regulatory approval component, challenges can compound exponentially.

Having survived the early phases of a start-up which has been required to navigate the rules and regulations of at least four federal agencies and a countless number of industry bodies, I share the following observations in the spirit of everyone who has helped me.

While a launch requires a brave and unwavering devotion to a narrow ideal, the (post-launch) running of a start-up requires broad flexibility, and an unwavering devotion to listen to everything and everyone.

Develop a Deep Bench

The launch of a start-up will demand considerably more time and money than originally planned – the rule-of-thumb “twice as long and twice as much” is probably a good guide. No matter how committed your founder or initial management team appears, the stress of running the start-up compounded with life outside the start-up (a.k.a. family, friends, mortgages, tuition, etc.) is likely to leave casualties in the management ranks.

  • make some of your earliest hires individuals you would like to see replace you
  • engage one or more industry veterans as advisors early in the process – they can both take a leading role at disruptive times, and help to recruit as and when needed

Don’t Rely on Thought Leaders for Validation

If your start-up is staffed with industry veterans, you’re likely to have good access to C-suite executives and industry thought leaders. While positive feedback from this expert group is important validation, it can lead to “false positives” because the industry leaders are likely to applaud innovation and more likely to think like you. Make sure you balance your pitches to leaders and innovators with pitches to actual practitioners – particularly those in the camp of “don’t fix it if it ain’t broke”.

  • ask the C-suite/thought leader for access to their managers and transactors, to hear a range of voices
  • make sure you have a good sampling of “bad meetings” – particularly where the audience is under-informed and not thrilled to be there, because that’s probably more indicative of a real-world conditions

Maintain a Continuous Long-Term Approach to Your Regulatory Regime

Regulatory relief and regulatory rule-making are at the heart of all new things in financial technology and the fund industry; in particular, the ETF industry’s push into (non-transparent) actively managed funds has made non-lawyers and industry observers active followers and participants in the regulatory process. Navigating one or more regulatory regimes requires unique focus and preparation, and it is tempting to regard a successful filing as an item on a checklist. In reality, because market structures change, and opportunity sets shift, one must view the regulatory process as a core ongoing requirement.

  • appreciate that every step you make in the regulatory process will either expand or narrow your degrees of freedom going forward – assess each correspondence, meeting or exchange in the long term
  • realize that regulators are assessing your filing with their own information set and on their timetable – try to help them by understanding their perspective and their challenges – it’s a forward-looking ongoing process

What BlockChain and Ledger Technology Can Do For Exchange Traded Products

(previously published on LinkedIn)

New Technologies Will Blur the Lines Between ETFs, Mutual Funds, and Separate Accounts

Blockchain and Ledger Technologies have the potential to deliver the seemingly impossible – the scale and liquidity of large funds combined with the individualized returns of separate accounts.

The exchange traded product space continues to develop and launch novel and useful tools despite the limitations inherent in a U.S. settlement system which predates the modern ETF by decades. “T+3” settlement combined with the limitations of “street name” ownership have precluded many types of fund innovation, and in particular structuring over the liability side of the fund’s balance sheet. Because of this asset-only orthodoxy, few have ever asked the question, “what can be achieved if we apply fund management techniques to both the assets and the liabilities of a fund?” The answer is quite a lot.

Leveraged Returns and Where Does the Multiplier Go?

One of the most pronounced limitations in today’s exchange traded market can be found in leveraged and inverse products. Consider that without the need to clear daily P&L results and re-strike leverage for tomorrow’s investor, there’s no school of investing which favors daily rebalancing – investors who go long AAPL or short MSFT look to execute their trades over a specific number of shares or specific dollar value as opposed to a floating/compounding/de-leveraging arrangement.

Daily rebalancing of fund assets disrupts investor returns, increases transaction expenses, and may unnecessarily contributes to market volatility; in fairness, leveraged and inverse ETFs and ETNs thoroughly disclose their day-by-day return limitations, and over most short periods, the undesirable effects of daily rebalancing are small.

For investors putting on leveraged trades, the effect of how the leverage is achieved means everything. The difference in the two equations below, RETURN(PRIME) and RETURN(ETP), can mean materially different results for the tactical investor.

The leverage an institutional investor achieves through a traditional prime brokerage arrangement or a non-rebalancing fund is consistent with RETURN(PRIME), where R(n) is the return for day “n”:

RETURN(PRIME) = LEVERAGE x [ -1 + (1 + R1) x (1 + R2) x (1 + R3) x …..]

In contrast, the leverage an exchange traded product buyer achieves through a conventional ETN or ETF is calculated as follows:

RETURN(ETP) = -1 + (1 + LEVERAGE x R1) x (1 + LEVERAGE x R2) x (1 + LEVERAGE x R3) x …..)

Looking at a recent market example, using the daily returns of a 3-times leveraged WTI crude oil futures index over August 2015, RETURN(PRIME) indicates a gain of over 8%, while RETURN(ETP) indicates a loss of approximately 1%.

Because most investors and traders plan on holding positions over more than a single trading day, and because investors and traders continue to prefer fund products over alternative instruments, this area remains fertile ground for commercialization.

Why Must the Conventional Inverse and Leveraged ETF/ETN Rebalance its Positions Daily?

The following is a simplified 2-day example which illustrates why a conventional leveraged exchange traded product rebalances its positions daily.

Assume at the close of 1/5/15, a single investor enters an order for $100 of a 3X-leveraged ETF, where the share price is $10 and the order is for 10 shares (“Day1 Investor”); our $100 order will cause the ETF to execute an asset position equivalent to $300 (i.e. “3X”). Rolling forward to the close of business on 1/6/15, assume that the return on the assets is 8.33% – our ETF trading price should be approximately $12.50 (3 x 8.33% applied to a $10 opening price), and our assets position is $325, and our shareholder’s value is $125.

For the second and last step in our example, assume that a second investor (“Day2 Investor”) submits a $100 order on the close of 1/6/15 when the share price is $12.50 for 8 shares. To summarize, we now have Day1 Investor in for $100 with a 25% gain (3 x 8.33%), and Day2 Investor just having acquired 8 shares for $100.

Examining the ETF’s leverage going into the next trading day (1/7/15), the ETF has an asset position of $625 (our first day’s position of 300 with a 8.33% gain, plus another 300), and the ETF has an aggregate shareholder’s equity position of $225 (Day1 Investor’s position of 100 with a 25% gain, plus the Day2 Investor’s position of 100). The leverage measure is then simply 625 (assets) divided by 225 (shareholder’s equity) or 2.77x – materially below the ETF’s stated leverage of 3x.

To restrike the leverage to 3x, our ETF leverages up the day1 $25 asset gain such that it is also leveraged 3x, so assets go to $675 ($300 plus 3 times $25, plus the $300 relating to Day2 Investor), and the ETF’s final leverage position is $675 over $225 or “3x”. Note that shareholders’s equity remains unchanged from $225, because the additional market exposure is achieved entirely through leverage.

Part of the “cost” of the daily rebalancing process comes from causing the fund to increase assets in an already up-market (i.e. a “buy high” move). If the market goes down 8.33% from here, our share price will drop to $9.375 (assets of $675 adjusted downward by 8.33%, further adjusted for $450 of leverage). So while our Day1 Investor might have expected a net 2% loss (e.g. RETURN(PRIME)), the Day1 Investor actually realizes an ETF loss of 6.25%.

What Happens if We Rebalance the ETF’s Shares Rather Than Its Assets in This Sample Example?

It’s illustrative to begin with the constraints of ETF design:

  1. The net asset value (NAV) of the fund has to equal the aggregate value of the assets minus the liabilities,
  2. The aggregate sum of shareholder claims must equal the NAV, and
  3. The shareholder claims (a.k.a. the “shares”) should be universal and indistinguishable with one published price and readily tradable on any exchange

While we typically think of ETFs in terms of share price, shares outstanding, and NAV, there are no real constraints relating to share counts – and share price is simply an artifact of share count. So the question remains - what can we do if we manage or rebalance share counts rather than assets?

Below we recreate the two-day example, but instead of rebalancing assets, we rebalance share counts similar to how a mutual fund adjusts share counts.

The Share Count Alternative

Recall in the example above, after the Day2 Investor entered our ETF for 8 shares at $12.50 each ($100), we found that the fund was under-leveraged with an aggregate leverage of 2.77x rather than the target of 3x so we added another $50 (an additional 8%) to the assets to increase the leverage. What if, instead of increasing assets (i.e. “buying high”), we rebalanced share counts in response to market moves? As is demonstrated below, RETURN(PRIME) results can be generated by aligning our fund’s share counts with NAV percentages.

Restating the Day1 Investor position, the Day1 Investor owns 10 shares at an original cost of $10 per share, and once assets have increased by 8.33%, the Day1 Investor’s position is 10 shares at $12.5. Restating the Day2 Investor position, the Day2 Investor owns 8 shares at an original cost of $12.5.

Assets Have Moved Up 8.33% & Fund Price per Share is $12.50          3x Leverage

Continuing with the earlier example, day 2 is a down 8.33% day, and as noted in the immediately following table, the % of shares and % of NAV have deviated which triggers a share count rebalancing under this approach (i.e. each shareholder or shareholder group’s % NAV is not equal to their % Shares…56.63% vs 55.56%).

Assets Have Moved Up 8.33%, Then Down 8.33% – 3x Leverage

Share Count Rebalancing is Executed in 2 Basic Steps:

One: take the lowest % NAV (group or investor) and divide it into the related number of shares in order to determine the revised share count for the entire fund:  8 / 0.4337 = 18.44 – the fund requires a shares rebalancing of 0.44 shares from 18 to 18.44 (this simplified example retains fractional shares)

Two: Distribute shares as required to cause the share percentage ownership to equal the % NAV  ownership for each investor or investor group (e.g. investors with the same acquisition date, record date, tax lot date, etc.), subject to the condition that an investor or investor group’s share count will never decline – simply multiply 18.44 and the % NAV for each investor or group of investors. The final result is in the following table where rebalanced-changed cells are shaded. The new fund share price is $9.38 [(297.92 + 275.00) – (200 + 200)]/18.44:

Assets Have Moved Up 8.33%, Then Down 8.33% and Price per Share of $9.38 –  3x Leverage

Now check the system for RETURN(PRIME) results:

Day1 Investor:  (10.44 x $9.38) / $100 – 1 = -2%  Ok

Day2 Investor: (8 x $9.38) / $100 – 1 = -25% Ok

What Happens When Either the Day1 or Day2 Investor Sells?

The sold shares simply get tagged to the new acquisition dates which determines the targeted return (i.e. RETURN(PRIME)) and the share distribution entitlement for that return.

What Happens If the Index Has a Large Move Which Wipes Out a Shareholder’s Equity?

If the net value of the equity position relating to a Day”X” investor or investor group falls through a threshold (e.g. <50%), that group’s  asset position will be rebalanced to the current market – the same process which occurs daily in conventional leveraged funds.

Arrangements such as the share-based rebalancing described above can be implemented in a mutual fund format, and as settlement systems become more accommodating, the arrangement should be exportable to the ETF and ETN marketplaces. For readers looking for more detail in the system and the particulars of its implementation, see United States Patent No. 8,630,935.


In this brief example, a wholly different kind of fund can be launched where the only new data requirement is the acquisition dates of outstanding shares – importantly we do not need to identify or track any beneficial owner information.  Basic corporate action techniques, such as the shares rebalancing described above, will enable fund sponsors to offer the liquidity and benefits of large scale funds all while delivering customized returns. While this technique, and similar ETF enhancements can be implemented today in a mutual fund format, we expect new settlement and operation technologies to blur product boundaries and expand product options.

AccuShares Investment Management White Papers

Below is a list of AccuShares Investment Management authored white papers on volatility:

“A New Look at Exchange Traded Volatility Products – July 2015″
Download Here


Below is a list of AccuShares Investment Management authored white papers on commodities:

“Everything We Wanted to Know About Spot Prices and Were Dumb Enough To Ask – July 2015″
Download Here


Below is a list of AccuShares Investment Management authored white papers on the structure of ETPs:

“Understanding Inverse ETPs – July 2015″
Download Here
“What Blockchain and Ledger Technology Can Do For ETPs – Sept. 2015″
Download Here