The full title of this book is Chasing the Same Signals: How Black-Box Trading Influences Stock Markets from Wall Street to Shanghai by Brian R. Brown (2010).
Brian served as Director of Pan-Asia Systematic Trading at Morgan Stanley, and also did statistical arbitrage strategies at Monroe Trout’s (a Schwager Market Wizard) Trout Trading Management.
This book provides a high-level overview of what black-box trading is, and gives a brief history of the development of the industry (the markets, the investment banks, the black-box trading firms, etc). Brian also highlighted that going forward, trading firms have started to look at weather forecasting, harvesting location-based consumer spending data, and making use of information on the internet.
The content of this book I feel is more suited for someone relatively new to the financial markets who is interested to learn more, rather than long-time investors or traders. From Brian’s bio, I was hoping that he would share some deeper insights that he gained from the practical implementation of black-box strategies, however book did not go down into details of trading strategies, the process of development, implementation pitfalls and difficulties, etc. The current book can be written by someone without Brian’s unique experience, so I think in a way, it is an opportunity lost here.
Why All Firms Are Chasing the “Same Signals”
- The reference to “same signals” is not an implication that all indicators are alike, but rather it’s an affirmation of the old expression “there are only so many ways to skin a cat.”
- It must be expected that there will be a high correlation among signals with the same intention…. One firm may have a higher predictive model for momentum but it will have a common relationship with other trend followers — they will be looking at the same stocks, just entering at different times, in different ways, with unique holding periods. However, the byproduct of chasing the same signals is that these strategies will all influence one another.
- Capitalize on empirical price discrepancies (e.g. serial correlation)
- Statistical arbitrage
- Market-neutral strategies
- Automated market-making
NYSE Stocks Demonstrate Intraday Inverse Autocorrelation
- Research by microstructure professors at the UCLA validated that overnight NYSE stock returns are serial independent while the intraday movements are less efficient.
- On a five-minute interval, NYSE stocks demonstrate an inverse serial correlation: stocks that move up in a five-minute window more often than not will revert in the next five minutes.
- However the “serial correlation” of NYSE stocks has been on a steady decline for most of the past decade. The decline accelerated in the late 1990s when electronic traders began to flourish and then further accelerated when decimals were introduced in 2001. Those five-minute windows of serial correlation have decayed to a fraction of their statistical significance.
Market-Neutral Strategies Depend on Large Dispersion and Leverage
- Market-neutral strategies depend on the overall market volatility and the “dispersion” of returns within the index and sector. Dispersion, defined as the difference between the best and worst stocks within a group, is an important determinant for the profits of market-neutral strategies. If the dispersion is large, there is a greater potential to outperform the market by picking the winners (and losers) within the sector.
- Market-neutral firms employ leverage to magnify the returns of their portfolios, where even the most proficient stock selectors may require 2x or 4x leverage to achieve double-digit returns.
HKEx’s Unique Market Structure
- Brokers’ names are disseminated to the other brokers alongside their orders in the queue.
- Exchange’s order book throttles brokers at 3 orders per second, to constrain the rate of trading.
- HKMA imposes stamp taxes of 12.5 basis points per transaction. Any speculator wishing to provide short-term liquidity will pay 0.25% in round-trip taxes, regardless of whether he or she earned a profit or a loss.
Larger Tick Size Leads to Greater Volatility
- Higher transaction costs lead to greater market volatility. Higher costs discourage short-term speculation, which correspondingly reduces the supply of liquidity.
- A variety of empirical evidence validates that market liquidity is inversely proportional to the costs of trading. Markets with the lowest frictional effects, such as the U.S. markets, attract foreign investors and cultivate a diverse variety of investment strategies. The interaction of these different investment strategies has a dampening effect on market volatility.
Investment Banks Offer Index Funds Guaranteed Close Prices At Russell Rebalancing
- Russell rebalances annually on the last Friday of June. As the Russell Investment Group applies the closing prices to derive the value of its indexes, index funds all want to trade at the market closing price.
- On an average day in U.S. markets, 5-10% of the stock’s daily volume might transact in the closing 5 minutes of trading; on the Russell, the stock’s volume is in the range of 30-50% in the closing moments.
- Investment banks offer index fund managers a “guaranteed close” price on their portfolios in exchange for a commission. The investment bank’s black-box strategies will manage the competition for liquidity.
- A bank stands a better chance of minimizing slippage if it has a greater share of the market. The advantages of size are twofold: more likelihood of offsetting client orders so that they can cross off market at the same benchmark price; and lower slippage if they are a larger share of the market turnover.
- In a study by Russell, the additions to the Russell 2000 index were shown to gain on average 1.46% of excess return between the announcement date to the rebalance day, and then reverse on average 0.83%.