Will There Be Another Market Crash?
No doubt. With each passing month, order, transaction, and data speeds increase. Trading is done on increasing numbers of exchanges, linked together by HFT pricing and rebate-induced arbitrage. The markets have become even more fragmented.
The leverage employed by HFT firms remains at extremely high levels, similar to the 40-1 debt to equity ratio used by MF Global, which amplified the disastrous effects of its poorly chosen bets. Because HFT firms’ strategy is to start and end each day owning nothing, they have little tolerance for adverse “bets.” When they are “wrong,” their technology and speed enables them to dump their inventory in such a ferocious manner that limit order books quickly thin out in terms of price and depth. Because their algorithmic models price securities with such an emphasis on nearby prices and robust uninterrupted pricing data flow, when that data displays discrepancies, they withdraw their “liquidity provision” and shut down.
The Joint CFTC-SEC Advisory Committee, set up to study and report findings on the events of May 6, 2010, summed it nicely: “In the present environment, where high frequency and algorithmic trading predominate and where exchange competition has essentially eliminated rule-based market maker obligations...even in the absence of extraordinary market events, limit order books can quickly empty and prices can crash.”1
Another concern is the market’s instrument makeup. In 2010, Exchange Traded Products (ETP), including its biggest category, exchange traded funds, or ETFs, reached an asset under management (AUM) level of $1.3 trillion. 2 Only ten years prior, ETP AUM totaled a mere $66 billion.3 This represents nearly a 19-fold increase. Each year stock exchanges, which are struggling to list shares of promising companies in the form of IPOs, manage to set new records in the number of ETPs and ETFs they list for trading. NYSE-Arca listed a record 300 new ETPs in 2011 versus 220 in 2010.4 The result: More and more volume on exchanges is in the form of derivative products, of which an increasing number are leveraged and a large percentage of the trading is done by HFTs.
On calmer, benign days in the market, you can argue that HFT firms may do a good job of arriving at a fair price for large capitalization, highly liquid stocks such as Bank of America. However, in thinner issues that trade less often, HFT may not do such a good job. Although HFT is agnostic to the merits, fundamentals, and prices of the stocks it is flipping, it prefers liquid, lower-priced stocks because it can trade more shares of those for the same amount of capital deployed.
On volatile days, however, HFT exacerbates and amplifies price moves in short amounts of time. It’s like lemmings. Lemmings behave normally when their population is in check, but their population is wildly erratic. They migrate in a massive group when population density swells. The group moves together in lockstep and walks off cliffs or jumps into large bodies of water in mass with horrific results. HFT has been around for nearly 15 years, its “population” swelling only fairly recently, corresponding with the implementation of Reg NMS. Their strategies are similar, frequently depending on speed to differentiate their success. HFT decides how, where, and when to buy and sell stock by examining relationships of data points immediately near each other. This modus operandi can cause them to chase stock prices up and down a ladder wildly. On May 6, 2010, HFT algorithms sold Accenture Corp. (ACN) down to pennies and Phillip Morris (MO) from $48 down to $17 and right back up to $46.