The Office of the Chief Economist produces original research papers on a broad range of topics relevant to the CFTC’s mandate to foster open, transparent, competitive, and financially sound markets in U.S. futures, option on futures, and U.S. swaps markets. In this role, the papers are written, in part, to inform the public on derivatives market issues and can be freely accessed below. They are commonly presented at academic conferences, universities, government agencies, and other research settings. The papers help inform the agency’s policy and regulatory work, and many are published in peer-review journals and other scholarly outlets.
The analyses and conclusions expressed in the papers are those of the authors and do not reflect the views of other members of the Office of Chief Economist, other Commission staff or the Commission itself.
Both the fundamental surprises and the market structure related variables are found to have statistically significant effects on price and price volatility of corn and soybean futures.
Fundamental changes are captured by the deviations of the supply and demand condition estimates released by USDA from the pre-announcement analysts’ forecasts published by Bloomberg.
We employ the transaction databases of CFTC (Commodity Futures Trading Commission) to construct the percentage shares of detailed participation group trading in the market.
The paper analyzes the prevalence of automation across futures markets, tracking changes over the period from 2012 through 2018.
Automation use is highest for financially based instruments like FX futures, the S&P E-mini and U.S. Treasury contracts. Automation levels are commonly lower, though increasing, for physical commodities like grains, softs and livestock.
Though most markets have gotten faster over time, with order resting times and execution times decreasing across the six year period, the rate of change appears to have flattened in recent years.
Dealers use Treasury futures to risk manage their inventory of Treasury cash positions.
We conclude that there is a “price pressure” effect in Treasury yields: market yields adjust to compensate dealers for holding net inventory.
Order flow and price discovery: the back end of the curve is most impacted by 10-year futures, and the front end is most impacted by the 5-year cash market.
For a couple of days in May of 2015, the matching algorithm of the 2-year Treasury Futures contract unexpectedly switched from pro-rata to price-time priority.
This unexpected change caused average trade sizes to increase, number of transactions to decrease, and fill ratios of passive orders to increase in the 2-year Treasury Futures market for those two days.
In addition to the changes to the market statistics, we also find that one measure of price efficiency dropped and revenue distribution became more concentrated as a result of the unexpected change in the matching algorithm.
The paper analyzes regulatory data collected on open uncleared swap positions to identify entities which may be caught under uncleared swap margin requirements.
This analysis finds that the final phase of the uncleared swap rules may catch a far higher number of entities than the other four phases combined: over 700 entities, representing nearly 7,000 counterparty relationships. A majority of these entities have swap exposures quite close to the Phase 5 lower threshold.
Entities potentially caught in Phase 5 span a variety of business sectors; excluding one swap type commonly used for hedging (physically settled FX swaps), could reduce the number of entities by almost 30%.
We propose a theoretical model exploring the incentives to manipulate reference prices under two alternative closing price regimes.
We test the predictions of the model in the CBT corn futures market around the change in settlement price calculation methodology that took place in June of 2012.
We find that the new settlement price calculation methodology, namely basing the settlement price on all trades, was more efficient and robust.
The paper compares cleared margin to hypothetical uncleared margin generated by ISDA SIMM on interest rate swap portfolios currently cleared at two DCOs. First the market risk measure is examined, and then the overall initial margin figure with add-on charges included.
The ten-day value-at-risk as calculated by SIMM is not necessarily higher than the five-day DCO measure. The relative measures are dependent on portfolio composition, which in turn points to key model assumptions.
Once non-market charges are included, the cleared initial margin requirements are much closer to the equivalent uncleared figures. This may be explained by a difference in the treatment of liquidity and concentration risk across the two models. The SIMM framework extends the holding period to account for large-position liquidation risk, whereas the DCO models calculate simultaneous market and liquidity costs throughout the five-day period.
Examines the liquidity of the December 2016 NYMEX contracts for crude oil, natural gas, diesel, and gasoline.
Finds that there is excellent liquidity near expiration as well as good liquidity when there are multiple years until expiration that is improved by the trading of calendar spreads.
Recommends a new liquidity assessment tool that may be used to calculate initial margin for large positions or by traders wanting to establish or remove a large position.
The paper analyzes the effect of transaction networks on the liquidity of credit index swaps.
It finds that transaction costs fall in cases when customers trade with a larger number of dealers and when they trade with the most active dealers.
The paper also summarizes a few other recent credit index trends, including possible liquidity improvement like daily volume increases and reduced price impacts. In possible contrast we do see slight trade size decreases for some contracts.
Agostino Capponi, W. Allen Cheng, Stefano Giglio, Richard Haynes
The paper tests whether initial margin held at a clearinghouse against credit swap positions can be estimated using a traditional VaR measure.
This analysis finds that VaR is often not a good proxy for actual initial margin levels, with collected margin often far higher than would be implied by the VaR calculation. Other proxies which more highly weight extreme events are found to better align with empirical margin.
The paper also tests how certain financial frictions, like funding costs and market-level volatility, translate into changes in margin requirements.
