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Proprietary Derivatives Trading in the Last Decades

It's a no-brainer; the financial industry has changed a lot over the last decades. There are multiple causes. Among the structural factors, one can mention the rise of technology, the decimalization and electronification of exchanges, the introduction of ECNs for equity, the increases in volume and speed of those exchanges. There were also significant regulatory changes (MiFID, Basel, Dodd-Frank...). Derivatives trading has changed a lot too. But what happened to the VIX on February 5th, could be a wake-up call to the industry and generate another wave of deep changes.

A few decades ago, derivatives trading was the monopoly of broker/dealers. Those institutions enjoyed virtually unlimited capital, first-class technology and IT resources, good relations with exchanges/regulators. Derivatives trading was an essential part of their income. For those market-maker and proprietary traders, new trading ideas, supported by innovation in products and in techniques, implemented with know-how and skills, were elating. These activities generated regular and significant profits, fueling a virtuous cycle of talent, imagination, efficiency and products.

Internal supervision was not always able to understand the complexity of these businesses. Compliance & risk officers increasingly relied on trading management for proper decision-making. But as complexities increased, pressure for results also increased well, and management grew more tolerant to complexity, as well as operational and headline risks. As long as profits were there to support the growth and feed the bonus pools, as long as mistakes and losses were minimal or could find a simple explanation, the game was worth it and few people asked too many questions.

The derivatives world took a major turn in 2008. Fueled by zealous mortgage brokers, result-oriented rating agencies and a general appetite for leverage, many banks and buy-side investors had filled up their balance sheets and activities with dubious financial products. The king lost his clothes when Bear Stearns and Lehman disappeared from the world. AIG had a near-death experience. Nobody knew who had those risky assets and who could go bust, initiating a self-feeding market downturn. The Fed saved the day by injecting enormous amounts of liquidities and by bailing major actors out more or less discreetly. Although it could have been much worse, the stupidity of those products had led to a serious financial and economic crisis.

The regulatory blowback was severe. Among many restrictions, Dodd-Frank effectively eliminated prop trading in banks and strongly increased monitoring and compliance. International capital requirements crippled bank risk limits and eliminated huge swath of market-making activities, especially in the fixed income world.

Hedge funds and trading houses filled the void. Luring the most profitable traders with technical resources and budgets, higher payouts and investors' hunger for returns, those nimble structures became and are to this day the core centers of trading activity.

The Short Vol. Trade

During the 2008 debacle, hidden losses and counter-party risks exploded. Lower and less accurate forward company earnings became the norm. Nobody really knew what would happen, 'exuberance' and choppiness reigned. The market eventually went back to normal. Confidence and earnings forecasts came back. Central bank support and the low-rate environment fueled a corrective rally.

Equity volatilities subsided. They actually returned to surprisingly low levels. Although the causes of that low-volatility environment are still debated, fingers point to ETFs and indexing. Huge retail investments moving from discretionary funds to passive index-replication structures reduced local stock mispricing, dispersion and the general volatility. The 'short gamma' players, those who make money when volatility is lower than expected, were the big winners. Most volatility traders would have difficulty shorting on such low levels, but that's the trade that paid. Historical S&P vols around 6-9% were constantly lower than short-term implicits on a contango-type term structure, and way below long-term historical averages (13-15%).

During that rally, quantitative investment strategies gained further attention in the retail, semi-retail and institutional spaces. Let's face it, quantitative strategies bring returns of much better quality than discretionary investments. Macro traders, allocators, discretionary traders in most asset classes struggle to reach a 1 Sharpe. In the statistical arbitrage space, if you do not have at least 2 you are nobody. Good portfolio managers can reach 2.5 or 3. I am not even talking of intraday and HFT players, who reach much higher levels, albeit in much smaller capacities. You can argue that quant strategies have their 'good' and their 'bad' periods, but if you eliminate the mean-reverters, momentum players and factor rotators, there is a solid core of quality returns based on experience and well-researched models.

The technicalities, complexities and diversity of this segment escape most retail and HNW individuals. Banks took advantage of that void with appealing 'quantitative investment strategy' products. This article will not disparage that segment altogether, far from it. Having interviewed hundreds of accomplished portfolio managers and run detailed due diligences on their strategies, I have seen solid ideas and approaches. I am actually a solid believer in quantitative approaches. Bank strategy desks can provide very good ideas, packaged in very efficient structures. It's just that not all quant strategies make the grade. You need years of research with competent and expensive staff to build proper, original, adaptive quant strategies, which should surmount the test of time while diversifying your portfolio. It is tempting to jump into something that looks good, according to a back-test over the recent years. Over-fitting is not rare, like probably the latest machine-learning fad (at this time). There is an entire gradation of quality.

But somehow, the short-vol trades were recommended for public investments. Yes, they had provided good returns in the always-lower vol environment, but past results are not an indication of future returns and volatility trading is not for beginners. The VIX is a fear gauge, which the general media now loves, but you are committing a solid mistake if you assume that volatility behave like physical assets.

Equity indices are structurally different from volatility indices. Dow and S&P have long-term positive trends. Good year, bad year, they will grow at ~10% per year on average plus dividends. Investors get a return premium over fixed-income instruments for carrying some volatility risk. Nothing new here, this is well-documented. Also, econometrics models and analysis are far from easy, but you still can enjoy some forecasting capacity between asset classes.

Equity index volatilities, on the other hand, are much harder to forecast. They have no trend, forcing them to mean-revert. Their trajectories are far from oscillating around their average: they tend to gap up and smooth down exponentially. Vol traders know this drill well - buy it cheap ahead of possible events, try to sooth the theta-negative cost with calendar spreads, skew or out-of-the-money positions, and enjoy the fruits of a vol gap up. You then sell short when everybody is scared and wait until it goes back down. Repeat.

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Gontran de Quillacq has over 20 years of Securities experience specializing in Portfolio Management, Equity Derivatives Trading, Proprietary Trading and Investment Research. He has worked with top-tier banks and hedge funds in both London and New York. Mr. de Quillacq's investment experience and cross-sectional review of other professionals give him unique experience on what can be done, what should be done, what should not be done, and the grey areas in-between. Mr. de Quillacq's services are available to attorneys representing plaintiff and defendant and include written reports, deposition, arbitration, mediation, and trial testimony as needed.

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