1. It's always fascinating to see different types of exotic derivatives in the crypto space. I was pretty interested to come across @RealHxro's TIX contracts which are crypto binary options. These are similar to vanilla options but the payouts and pricing are slightly different.
2. In this analysis I viewed TIX options as "cash-or-nothing binary options". For a call, this means that at expiry if spot > strike, then you get paid out a certain amount (the odds x the amount you bet). At maturity if spot ≤ strike, the payout is 0. Vice-versa for puts.
3. Here we can see the active TIX contracts. The odds represent the amount you get paid if the contract ends in the money (spot > strike). As an example, for the $20k call, if BTC > $20k on Dec. 25th/2020, then a $1 bet would turn into $5.741. Image
4. In other words, this contract is pricing in a ~17% (1/5.741) probability that BTC will be > $20k on Dec. 25th. Given cash-or-nothing options have a theoretical closed-form solution, we can approximate the market implied volatilities used to price these products.
5. Here we can see the estimated TIX IV plotted against the Deribit mark IV for strikes between $9k to $20k. It's cool to see the TIX IVs are somewhat in line with @DeribitExchange's vanilla option IVs - I expect this difference to narrow as we see more volume on the platform. Image
6. What do you folks think of this comparison? Should a binary option IV plot like this have a similar shape compared to a vanilla options IV curve? @MMKustermann @fb_gravitysucks @robbylevy

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More from @samchepal

26 Dec
1. Huge thanks to the devs at @RealHxro for helping me pull data for TIX contracts - really grateful for the responsive team! This is one of the first times I've been able to build out relatively liquid vol curves not only for BTC/ETH but also for alts such as LINK, UNI, and YFI.
2. As a refresher, TIX contracts can be thought of as "cash-or-nothing" options. Here's a thread explaining the details of how these products work.
3. Pricing these options is fairly straightforward as it requires us to only look at the second term of the BSM model. In this case, N(d) represents the prob of option expiring ITM and multiplying by the payoff (K) gives us the EV of this bet. Math from @EGHaug's great book. Image
Read 17 tweets
19 Dec
1. The recent rise in BTC spot and implied volatility has led me to re-read @SinclairEuan's book, “Positional Options Trading”. I found the chapter on volatility positions quite interesting with some useful parallels for crypto vol markets.
2. If we're shorting IV, ideally we want a strike with the largest vol premium. Although deep OTM puts tend to have the highest IV, we need to sell a lot of these options b/c their vega is low. As a result, selling these teeny options in size based only on high IV is dangerous.
3. Another method is to “sell options with the greatest dollar premium over what the option would be worth if it were priced with ATM IV". This allows us to quantify how much of the premium in dollars we are collecting in terms of skew.
Read 10 tweets
12 Dec
1. To stay in the game all option market-makers must actively manage their greeks. One of the challenging tasks is aggregating the portfolio vega across different maturities. While we can aggregate the delta/gamma/theta fairly easily, vega is trickier to manage. Let’s see why…
2. Suppose we’re a market-maker trading on @tradeparadigm with a book of three options:

Option A: Maturity = 30 days
- Short 100 contracts
- Vega = 3

Option B: Maturity = 60 days
- Long 50 contracts
- Vega = 6

Option C: Maturity = 90 days
- Long 50 contracts
- Vega = 10
3. An initial (but likely incorrect) approach to aggregate the portfolio vega exposure would be:

- Option A: -100 x 3 = -300
- Option B: 50 x 6 = + 300
- Option C: 50 x 10 = + 500

Portfolio Vega = A + B + C = +500
Read 14 tweets
14 Oct
1. Huge thanks to @digitalbrock and his team at @Round_Block for supporting me with some very useful #BTC @CMEGroup options data for research! I've been focused mostly on @DeribitExchange in the past but CME seems to target institutional folks which should lead to new insights.
2. Given I had access to historical time-series options data, one of my first thoughts was to implement @SqueezeMetrics's paper on Gamma Exposure (GEX) and see whether this metric is relevant to crypto markets. This will be a longer and more involved post!
squeezemetrics.com/download/white…
3. Market-makers generally do not like to have exposure to the price of the underlying as their business is focused on collecting the bid-ask spread. To stay in business, option market-makers hedge their delta exposures when buying or selling options.
Read 24 tweets
5 Oct
1. This is one of the best resources I've come across for implementing emergency hedges using options in a cost effective manner. Now more than ever I think Hari's wisdom can be applied to manage risk within the crypto options space especially before things get interesting...
2. As @zackvoell mentioned in this note, #BTC 180 day rolling realized vol is at nearly a 2 year low. Vol has several characteristic features across every market - one of them is the concept of mean-reversion.
3. We may not know when, but vol tends to go back to its average long-term value. Since realized vol is so low right now, I'd be risk-averse to place large short vol trades. It feels as though things have quieted down a little too much - seems a bit off.
Read 16 tweets
2 Oct
1/ Learned a lot about variance swaps by reading through @EmanuelDerman's awesome paper. This inspired me to replicate a variance swap term structure for #BTC by using options data from @DeribitExchange. Image
2/ During my research I read about the first #BTC variance swap between @GSR_io and @BlockTower which occurred in the summer of 2019. Given the lack of public data for these swaps, the only real way to get a decent price estimate is to use a replicating portfolio of options.
3/ These variance swaps allow for traders to make outright bets on volatility^2. Instead of using options (ie: straddles), with these products there is no need to delta-hedge. The payoff is as follows:

(Realized Variance - Strike Variance) x Notional
Read 6 tweets

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