VegaLABS research review 1

Our core philosophy at Vega Capital is to consistently search for new ways to invest and improve our performance. Today, I wanted to review a little research I've been working on around Vega's hedging algorithm. 

Memo to: Vega Capital clients
From: Scott Shuttleworth

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An idea I’ve been experimenting with over the past few months is using optimisation algorithms to reduce our hedging costs whilst improving our returns. I’ve dubbed this assignment “Project Tardis” (a Doctor Who reference, since back testing is a process of moving back and forth over time!).

The essence of Project Tardis is to allow the algorithm on each day to assess how to hedge our downside risk when we’re holding long market exposure.

For example, let’s say we have a portfolio of short puts on the S&P500 index, should we:

  • Buy short dated long VIX futures?
  • Buy short dated out-of-the-money long S&P500 puts?
  • Use some other form of protection?

If the market has a sudden 5-10% capitulation then our long market exposure will incur us a loss. Each of these techniques could act as a hedge for this event. E.g. in such a capitulation, the VIX will spike meaning that the VIX future positions will move into profit…the same occurs with the cheap puts, e.g. a $1 put may jump to $5.

So what are the cost of each alternative? As we’ve previously discussed, the cost of buying a VIX future is it’s level of contango – i.e. the difference between where the VIX currently stands and where it’s futures are priced at. This cost can be high as it is currently in October ($1,760 per future contract).

The cost of buying the short dated out-the-money puts is straight forward – the cost of the premium paid. These options are quite cheap since the chance of them becoming in-the-money over a short timeframe is quite small, but they may jump a lot if a capitulation occurs.

We could hedge some of our downside risk in the portfolio by choosing either method. But which? Clearly we should evaluate each alternative via:

  1. Hedge effectiveness
  2. Hedge cost

So with some code, we can build a simple algorithm to evaluate the cost of each hedging method and then decide accordingly. The algorithm calculates the cost of buying a portfolio of far OTM puts. If that cost is less than a maximum of 10 per cent p.a. it will buy the puts but if it’s higher it will instead employ VIX futures.

The Vega Fund is only using VIX futures to hedge our downside risk so in a sense, the current hedging method is our null hypothesis and we’d need sufficient evidence that an alternative method is better.

With this in mind, let’s have a look at some summarised results.

What’s immediately apparent is the lower returns which Tardis offers relative to Vega. In fact we could even half our weightings in Vega, put the excess cash into a term deposit earning some rate of interest and it would outperform Tardis.

Tardis’ volatility is lower but this isn’t exceptional given the lower returns as reflected by the Sharpe ratio. The drawdown is roughly the same.

Whilst it’s not possible to see from this table, the periods in which Tardis outperforms Vega is during bull market capitulations of 5-10% and also periods where VIX contango costs are abnormally high. Hence there’s clearly some appeal to Tardis in limited circumstances.

When time allows we’ll redo these simulations after amending the algorithm to transition into Tardis when VIX contango costs are too high and then revert to the traditional Vega strategy when this condition no longer holds.



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