【Application】Block Trade Strategy Achieves Performance Beyond The Market Index
Preface
In recent times, there has been a global surge in AI, with Taiwan’s electronics industry attracting a lot of interest from institutional investors due to its comprehensive supply chain. In addition to trading stocks through conventional methods on stock exchange markets, investors can also utilize block trading offered by exchanges for transactions exceeding a fixed amount. This approach not only helps prevent price fluctuations on ordinary exchange markets due to large positions transfers but also ensures execution with pre-agreed counterparties, thereby promoting market stability and enhancing trading efficiency.
Since its introduction in 2005, the block trading system by the Taiwan Stock Exchange has undergone revisions and adjustments to related regulations. Over the past three years(2021–2023), the annual trading volume under this system has consistently exceeded 600 billion NT dollars. Although block trades represented only about 1% of the overall market, the increasing trend in transaction amounts and the growing interest in Taiwanese stocks among domestic and international institutional investors suggest that further research into the relationship between block trading information and stock’s expected return is warranted.
Past studies have indicated that block trades cause certain inefficiencies into the market. For instance, in some countries, stocks that receive less attention tend to have lower pricing efficiency. Therefore, executing block trades can signal important information to investors. Additionally, block trades have an asymmetric impact on prices depending on whether the trade is initiated by the buyer or the seller.This paper categorizes block trades based on whether they are initiated by the seller or the buyer, utilizing quantitative methods to examine their predictive ability on stock prices. Then, the results are used to develop investment strategies, which are backtested to evaluate their practical feasibility.
What is a block trade?
Based on the transaction volume and amount, securities transactions that meet the following criteria must be reported as block trades:
- Single security: A quantity of 500 trading units or more, or an amount more than NT$15 million.
- Basket of stocks: Five or more stocks with a total amount more than NT$15 million.
Block trading is divided into two types: non-paired trade and paired trade. The reporting price range is subject to the same price limits as regular trades.
- Non-paired trade: The transaction price is matched based on the buy and sell prices and the order of submission.
- Paired trade: The client negotiates with a specific party at a designated price and quantity. The latest time for placing and matching orders for block trading is 17:00.
To prevent significant fluctuations in intraday prices, block trade is usually executed after the market closes.
Taiwan Stock Exchange introduced the block trading facility in 2005 and made related revisions and adjustments in 2007. These included adding paired trading methods, extending trading hours, and adjusting the price increment units and ranges. These adjustments not only met market demand but also significantly increased the willingness of market participants to engage.
Data
Data Source: TEJ Market databank
Stock Price Data: Adjusted stock price, return on investment
Blocking Trading Data: Block trading categories, transaction price, transaction volume, transaction amount
Sample: Taiwan listed and OTC stocks
Since the annual transaction amount for single securities from 2018 to 2024 has been significantly greater than that for basket of stocks, this paper considers using single securities as the sample for block trading tobetter reflect the public’s views on the future of stocks in block trading.
Variables
The original block trading information does not indicate whether the transaction was initiated by the buyer or the seller. Therefore, this paper infers the initiator using the following method: if the closing price on the trading day is higher than the block trading transaction price, the transaction is considered initiated by the buyer, serving as a buy signal. Conversely, if the closing price is lower than the block trading transaction price, the transaction is considered initiated by the seller, serving as a sell signal.
Large-cap companies usually receive more market attention compared to small-cap companies. Therefore, this paper proposes using market capitalization as a proxy for the level of attention. The median market capitalization of listed and OTC companies on a daily basis will be used to distinguish between large-cap and small-cap stocks, with large-cap stocks representing high attention and small-cap stocks representing low attention.
Factor Analysis
Three equal-weighted investment portfolios will be established based on signals each day: buy, sell, and neutral. The level of attention is divided into high attention and low attention. By pairing these categories, six investment portfolios are formed.
From the analysis results shown in the figure below, it can be concluded that the buy and sell signals derived from block trading information have a positive relationship with future stock returns. The portfolio returns of buy signals are superior to those of the other two groups. Furthermore, when considering stock attention levels, it is found that the lower the attention, the more significantly the predictive ability of the signals on future stock returns is enhanced.
Backtesting and Performance Analysis
Our investment strategy primarily utilizes block trading buying signals and stock attention levels as stock selection indicators. Additionally, practical trading costs and risks need to be considered, such as commission fees, securities transaction taxes, liquidity constraints, and trading risk limits.
Analysis results indicate that the strategy’s performance outperforms the weighted index. Even under the impact of two interest rate hikes, the strategy’s cumulative returns can still reach new highs. However, it should be noted that the strategy may experience a drawdown period of up to one and a half years during interest rate hike periods, with a drawdown magnitude of approximately 24%. Additionally, the strategy’s long exposure ratio is about 0.85, while the short exposure ratio is 0, indicating that the strategy is susceptible to negative impacts during market pullbacks. Therefore, this paper suggests that this investment strategy can be applied in actual investments and can serve as one of the options for asset allocation.
Conclusion
Based on the above analysis, three conclusions can be summarized:
(1) Block trading buying and selling signals have a positive relationship with future stock returns. Block trading information has the ability to predict future stock returns.
(2) Further grouping by stock attention levels reveals that the predictive ability of stock prices is enhanced under low attention. This also indicates that in situations of low pricing efficiency, block trading conveys more significant information to investors.
(3) An investment strategy based on low attention levels, considering related trading costs, liquidity, and trading risk constraints, the strategy outperforms the weighted index in both performance and risk metrics. Additionally, the strategy continues to reach new highs during the backtest period. However, it should be noted that during interest rate hike periods, the strategy may experience a maximum drawdown period of up to one and a half years, with a drawdown magnitude of 24%.
Overall, using block trading information and attention levels as stock selection indicators to establish an investment strategy can outperform the market. It is recommended that readers also combine block trading information with other indicators and use similar research methods for analysis, as they may discover more effective investment strategies.
This article utilizes TEJ Market Databank to construct various indicators and backtest their performance. Readers interested in various trading backtesting scenarios are welcome to visit our Databank or contact us for free trial!
Reminder: This strategy is only for reference and does not constitute any product or investment advice.
Further Reading:
Price Momentum Factor Strategy: The Market Favors the Strong
