by
Nupur Pavan Bang[1] and Vikram Kuriyan[2]
http://www.moneylife.in/article/underestimating-liquidity-risks-how-investors-can-suffer/36141.html
Risk management models used by professional investors often assume that securities can be traded infinitely. When liquidity dries up, especially in a systemic way during periods of crisis, it becomes very expensive to trade.
“When there is rain, umbrellas become expensive. But when there is no rain, nobody cares about the umbrella and the prices are low. The case of Liquidity is similar”, says Professor Yakov Amihud, Ira Rennert Professor of Entrepreneurial Finance at the Stern School of Business, New York University. Prof Amihud has been actively researching the effects of liquidity of assets on their returns and values, and the design and evaluation of securities markets’ trading methods for over three decades.
In conversation with Dr Nupur Pavan Bang of the Insurance Information Bureau of India and Prof Vikram Kuriyan of the Indian School of Business, Prof Amihud explains that liquidity risk is often ignored by investors. Risk management models used by professional investors often assume that securities can be traded infinitely. When liquidity dries up, especially in a systemic way during periods of crisis, it becomes very expensive to trade. Firms like Morgan Stanley and Long Term Capital Management have suffered huge losses due to underestimating the cost of liquidity.
So when does liquidity dry up? “It is a chicken and egg story”, says Prof Amihud. When prices fall, traders with leveraged positions need to come up with additional funds. If funding is too costly, traders must liquidate part of their positions and this makes stocks less liquid. When stocks become illiquid, their prices fall further; this exacerbates the problem of illiquidity. In addition, information asymmetry is an important determinant of illiquidity. When there is overall panic and information gaps between traders widen, transaction costs go up and liquidity dries up.
The introduction of high frequency trading (HFT), algorithmic trading and technology improvements in terms of direct market access and co-location has not hurt the markets in terms of overall liquidity. Every generation, there are some people who are more technologically advanced than the others and consequently they have an advantage over the others. In earlier times, people who had telephones had an advantage over those who did not have telephones. Then came computers. Initially, only a few had computers. Now, everyone has it.
It’s not an arms race, which imposes a dead-weight cost with no benefit. For example, when both India and Pakistan did not have nuclear weapons, they were equal. Now both have it, and they are still equal, but after burning billions of dollars. Similarly, people argue that when there was no HFT every one was equal in terms of technology. And now with HFT, everyone might eventually reach there and then again everyone will be equal. So why have it? Well, by improving the speed of transactions, HFT helps improve stock liquidity. Limit orders are tighter (have narrower gap between the buying and selling price), which benefits all traders who can trade at lower cost. This applies particularly, to large and more liquid stocks, in which HFTs are more actively involved. The level of illiquidity and its price have declined over time. This is not an anomaly which will disappear once the market finds out about it. It will stay there and benefit all traders and the economy at large.
On being asked about liquidity in the Indian markets, Prof Amihud says that India is among the least liquid markets in the world. Ironically the corporate world would get upset if the Reserve Bank of India (RBI) would raise bank interest rates. Yet, they are not worried about the illiquidity in the securities markets, which raises their cost of capital. If the Securities Exchange Board of India (SEBI) comes out with a regulatory scheme that would make the market more liquid, it will reduce the corporate cost of capital, akin to the RBI lowering interest rates.
