High frequency algorithmic trading- the new buzzword or next disaster?

I see a lot of posts today morning on the new financial assets trading jazz- High Frequency Trading or High Frequency Algorithmic Trading (HFT).

Wilmott explains what it is:

The idea is straightforward: Computers take information — primarily “real-time” share prices — and try to predict the next twitch in the stock market. Using an algorithmic formula, the computers can buy and sell stocks within fractions of seconds, with the bank or fund making a tiny profit on the blip of price change of each share.

I don’t know what the excitement is about (as Wilmott rightly points ) . This has been happening for a long time. I have read many articles/interviews (before the crisis that is) where people sang praises about their new algorithmic/quantitative model and how they are making so much money. The only difference this time (and each time) is a new name and new buzzword- it is  HFT this time. Supposedly Goldman has made quite a lot of money using HFT. This has led others to be excited and would most likely join in.

I have never been a part of designing any such algorithms and am not even capable of doing it. So cannot pass much comments on what it is and what it is not.

However, one thing I have noted and can say it with much confidence – When financial market players get excited about any new trading strategy/buzzword, it is most likely to fail. Most of it is done to make quick money and the long/mid-term repercussions are never discussed/ understood. As Wilmott says:

It’s a nice idea, and to do it properly requires some knowledge of option theory as developed by the economists Fischer Black of Goldman Sachs, Myron S. Scholes of Stanford and Robert C. Merton of Harvard. You type into some formula the current stock price, and this tells you how many shares to hold. The market falls and you type the new price into the formula, which tells you how many to sell.

By 1987, however, the problem was the sheer number of people following the strategy and the market share that they collectively controlled. If a fall in the market leads to people selling according to some formula, and if there are enough of these people following the same algorithm, then it will lead to a further fall in the market, and a further wave of selling, and so on — until the Standard & Poor’s 500 index loses over 20 percent of its value in single day: Oct. 19, Black Monday. Dynamic portfolio insurance caused the very thing it was designed to protect against.

This is the sort of feedback that occurs between a popular strategy and the underlying market, with a long-lasting effect on the broader economy. A rise in price begets a rise. (Think bubbles.) And a fall begets a fall. (Think crashes.) Volatility rises and the market is destabilized. All that’s needed is for a large number of people to be following the same type of strategy. And if we’ve learned only one lesson from the recent financial crisis it is that people do like to copy each other when they see a profitable idea.

Most strategies are like picking nickels in front of a steamroller. You may fool the steamroller most of the time but even once the steamrollers gets ahead, it is enough to create a much bigger damage  and erode all the nickels made so far.

It is not that people who design these strategies are not aware of the problems. They are just too smart to know the limitations. However, they also know at the back of the mind that the losses would be socialised and some kind of bailout/support would come from Govt/ Central banks. Each crisis leads to a much bigger moral hazard and the machine keeps running. How else do you explain the recurrence of some fancy strategy when its near-twin has just failed?


One Response to “High frequency algorithmic trading- the new buzzword or next disaster?”

  1. Do I Eat More Or Eat Less To Lose Weight And Fat? | WHEN LOSS MAKES YOU THE BEST Says:

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