Lately, we had come across comments on the quality of data (or, rather the lack of it) that our policymakers work with. The governor of the Reserve Bank of India (RBI) spoke about the limitations of data on industrial production and inflation. Swaminathan Aiyar wrote a column on the Indian labour force and employment data. Problems with data quality and reliability are well known.
This problem with data quality not only hampers policymaking, but also research. Andrew Haldane, executive director (financial stability) in Bank of England has been delivering high-quality speeches on various topics related to the financial sector in the UK and globally too. His speeches are backed up by solid empirical analysis provided by the research department of the Bank of England.
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One of his latest speeches, “The race to zero”, concerns the impact that high-frequency trading (HFT) and trading driven by algorithms have on market liquidity, on volatility and correlations. It is a topic of huge importance considering the big role it played in the market meltdown in the US last year in May.
There is pressure on many countries to allow HFT. HFT forums hold conferences in different countries to garner support for the introduction of this “innovation”. See, for example, http://highfrequencytrading911.com/2011/05/17/high-frequency-trading-in-india-set-to-double-as-goldman-nomura-fight-for-pennies/. Both investors and regulators need to understand the changes that HFT causes to the distribution of risk and return in the financial system.
According to Haldane, on 6 May 2010, the price of Accenture shares dropped by over 99% from $40 to $0.01 and the price of Sotheby’s rose 3,000-fold from $34 to $99,999.99. Not only are trading times now racing towards zero, even prices raced towards zero on that day.
In the race towards reducing the trading time from seconds to milli seconds, to micro seconds to nano to pico seconds, investors and traders relying on algorithmic traders have resurrected the importance of physical distance. “The shorter the cable to the matching engine of the trading exchange, the faster the trade”.
Haldane admits that there is empirical evidence to support the claim that algorithmic trading and HFT have narrowed bid-ask spreads. But it comes with costs attached. Arguably, those costs, from a system stability perspective, could be greater. Coinciding with the emergence of trading platform fragmentation and HFT, not only have volatility and cross-correlation (correlation of movements between stocks in an index) increased but correlation per unit of volatility has gone up, too. Put differently, “any rise in volatility has a more pronounced cross-market effect than in the past”.
While coincidence of the rise in volatility, cross-correlation and correlation per unit of volatility with the emergence of HFT and algorithmic trading does not imply causality, event studies help to answer that question. The official report on the flash crash of May 2010 assigns a key role to HFT in exacerbating the liquidity problem even if HFT might not have set off the crash. “HFT algorithms were automatically offloading contracts in a frenetic, and in net terms fruitless, game of pass-the-parcel. The result was a magnification of the fat tail in stock prices due to fire-sale forced machine selling… Bid-ask spreads did not just widen, they ballooned... Prices were not just information inefficient; they were dislocated to the point where they had no information content whatsoever”.
In this highly insightful talk, Kevin Slavin warns that Wall Street code-writers are writing codes that they do not know how to read themselves (Listen to him at http://www.ted.com/talks/lang/eng/kevin_slavin_how_algorithms_shape_our_world.html).
There are other consequences, too. HFT robs the low-frequency traders of information content because they have no idea of the prices at which they could execute their transactions. They stop trading. There is a double-whammy impact on liquidity, thus. Further, HFT impacts prices of derivatives linked to stocks and since stocks are traded in multiple exchanges across continents, the contagion spreads. Citing Charles Perrow, Haldane points out that two aspects of the trading system, as they have evolved in recent years—increasing complexity and their tightly knit character— are recipe for systemic failure.
While the rest of the paper deals with potential policy responses, Haldane’s conclusion is that HFT “fattens tail risk” and that mitigating the systemic impact of tail risks is the responsibility of policymakers. “Some grit in the wheels of stock trading could help to forestall the next crash.”
Overspeeding drivers are dangerous to other users on the highway and ultimately to the driver herself. But the cultural propensity of the West is to seek out excitement and speed, sometimes for their own sake. The East can and should bring about a bit of balance to the situation instead of feeling insecure and aping the “innovations” that the West sells hard to them. India has resisted many of the bogus innovations in financial markets so far and has introduced them into Indian capital markets only gradually. It should continue to stick to that path.
V. Anantha Nageswaran is an independent macroeconomic and investment strategy consultant, based in Singapore. Your comments are welcome at email@example.com