It is tempting to say that the last decade has been an interesting time to live in on Wall Street. But that would belie the observation that the 80s, and the 90s also came with dramatic changes to the markets and for practitioners.
I was not on the street during the 80s, but the 80s were really the start of the acceleration point towards model and technology driven trading. The 70s brought us the famous Black-Scholes model, the 80s a variety of synthetic instruments such as swaps, swaptions, CMOs, etc. The 80s really had not fully ushered in the leveraging of technology as it would do in the 90s and the ultimate step-up in the 2000’s.
Arguably without technology we would not have gotten much farther than basic option modeling. The 90s saw the rise of quantitative modeling and financial application of technology unlike any time previous. To be a quant or quantitative developer in those days was exciting and rewarding.
I remember joining Lehman Brothers in the early 90s. Swaps and swaptions though about 10 years old at that point still were traded on the back of HP calculators or maybe lotus 1-2-3 spreadsheets. The spreads were wide, in the 10s of basis points, today in fractional basis points.
With the full embrace of technology in investment banks it was a matter of time before we saw an explosion in complexity in exotic derivatives. Over time many of these exotics would become mainstream “vanilla” products. The interest rate markets moved in the direction of more volume in vanillas and more complexity in exotics.
Of course the equity markets also developed out derivative products, but more interestingly were “quietly” building out increasing sophistication on the “program trading” front (as it was called in those days). This was mostly unique to the equities markets, whereas the interest rate and FX markets continued to be largely OTC.
Program trading is the grandfather of all we know as “Algo Trading” today. The NYSE introduced DOT in the 80s as a means to provide automated clearing and semi-automated execution (order routing) to the manned floor.
Program trading facilitated basic execution algo, index arbitrage, and proprietary strategies. Index arbitrage involved buying or selling index futures against executing a basket of the same or similar components. The game then as it is now was speed.
In some of the foreign equity markets electronic execution was prohibited, throttled, or limited in various ways. For instance I remember that the Japanese MOF would not allow electronic execution to the exchange or at least required keying of orders by humans placed in Osaka, perhaps partially to protect such jobs, but maybe also to protect companies with less sophistication.
Morgan Stanley, Goldman, and Lehman had each, individually, hacked the serial lines from such terminals so as to simulate typing orders. Technically they employed people at the exchange to lend some credibility to the idea that they were following the rules, but was pretty much common knowledge that this was going on. They just happened to have very fast typists 😉
The “equity guys” pioneered many of the execution strategies that we use today in the 90s on the back of the growing program trading business.
The 90s (and perhaps late 80s) saw a number of (now) well known hedge funds spawn from this environment such as D.E. Shaw, Citadel, Renaissance Technologies, etc.
Thinking about it the 2000s encompass a period with a number of large failures in the market:
- the end of the internet bubble
- the explosion and implosion of credit markets
- the failure of major wall street firms and life-support for the designated survivors
Much has been written on the above, so I would like to focus on innovation and future direction. Here are some thoughts on what has characterized the last 10 years:
- commoditization of derivatives
- program trading (now “algo trading”) crossover into other asset classes
- automated market making
- automated trading via statistical or rule driven strategies
- faster, faster, faster;)
What I really read from the above is that the days of the instinct driven prop-trader or market maker are numbered. A raft of traders are being replaced by teams of quant / traders, usually more on the quant / CS side than time spent in trading.
The new setup is often a group of quant / dev / traders that develop trading strategies and a much smaller number of “execution traders” that manage the strategies day to day. Now *that* is really exciting, but perhaps shows my bias being in the former group.
I think the big days of derivatives are over (mostly). Regulations and standardization will push for more commoditization, automated clearing, and eventual exchanges. The new areas of innovation in the medium term for derivatives need to be in risk management IMO.
The Next Decade
It would be hard to predict the next decade in the markets given the rapid pace and surprises of the last 3 decades. The markets are a function not only of the practitioners but of global events, regulation, governments, and seen or unforseen technological advancements.
Here are some predictions:
- quantum computing goes mainstream in automated trading
- fewer traders more quants
- algo dominates all asset classes
- hard to find job as derivatives quant
My strategies are market ambivalent, however there are some changes in progress:
- US$ devaluation, possible move to another cross currency (maybe in 20 yrs)
- Dominance of china in market and world politics
- Dramatic changes on Wall Street in terms of Risk Practices
- Wall Street takes long term investment focus
- Transportation economy largely moves to electric by end of decade (more like 20yrs). End of oil domination.
- Reset of compensation and fees on Wall Street; Incentivize more CS / Physics / Mathematicians to do one and the same 😉
We note that the street is moving increasingly into, say, automated market making. Now firms engage in this for their own benefit, but it serves an important function in providing liquidity to the market, a useful function beyond speculation.
A real AI will be achieved, but doubtful in the next couple of decades. It may take another 50 years or more to achieve. I suspect the first AI will be achieved as a neural mapping of a human brain to a machine. Whether it is achieved this way or through an evolution of our machine learning and knowledge algorithms, accelerated with quantum computing, is immaterial.
Such a development will have dramatic consequences not only for mankind but also for the markets.
The financial services as they stand eventually will be coordinated by an AI. An AI will be developed by a research organization and be deployed at some point in the market. More than one may be deployed, at which point the game will become so tight that in the end the AIs will effectively be running the market.
Beyond market making, broader responsibilities could be given to manage money supplies, handle capital allocation / investment (now via loans, public stock offerings, etc). Anything a human can do could eventually be done more efficiently and at magnitudes lower cost by an AI.
This would effectively put a whole industry out of business. Would it not be better for great minds to be deployed in the pursuit of knowledge, sciences, etc? Today it is hard to make a living that way. I can only hope that there would be more balance in the direction of the sciences and progressive commerce.