Imbalance Trading Strategy – Backtest, Live Trading, Statistics, Facts

Imbalance trading strategy, also known as order imbalance trading, is a “technical analysis” approach that utilizes the imbalance between buy and sell orders to identify potential trading opportunities.

This strategy is based on the premise that large imbalances, especially when sustained over time, can indicate the underlying momentum of the market and provide insights into the sentiment of large institutional traders. As such you are working as a small market maker because you are providing liquidity.

Imbalance trading strategy involves observing order flow data, which captures the volume and price levels of buy and sell orders in a financial instrument. By analyzing the distribution of these orders, traders can assess the imbalance and determine whether it suggests a trend reversal or continuation.

The significance of imbalance trading lies in its ability to provide early signals of market direction, potentially offering traders a competitive edge. By identifying large imbalances early, traders can position themselves for potential price movements before the broader market catches on.

In the dynamic world of financial markets, market imbalances arise when the number of buy or sell orders for a particular security deviates significantly from the other. This imbalance disrupts the natural equilibrium of supply and demand, potentially influencing the security’s price.

Imbalance Trading Strategy – backtest and statistics

We have first hand experience in order imbalance trading. We used this technique for trading stocks at the open for about two decades.

Before we explain the order imbalance trading strategy at the open (and close), you might want to read the takeaways, statistics, and facts from 2002 to 2012: 12 years of real empirical analysis from live trading.

For example, the best month was October 2008, in the midst of the financial crisis, where we made a significant amount of money by only day trading (and mostly from the long side even though the markets were free-falling). We have covered our day trading in a separate article called it possible to make money day trading – a real historical strategy simulation. We consider the article a live backtest of the imbalance trading strategy.

Now, before you get eager to try this out, we have to disappoint you:

First, the strategy is not performing so well anymore. Markets have changed and the big imbalances are not there anymore. Second, it’s not as straightforward as we explained because we had a couple of other variables/twists we put in and which we don’t want to reveal. Sorry.

And, in case you are wondering, we are not trading this strategy anymore and we assume it has been mostly “arbed” away for good (?). But the main principles and takeaways are still valid and can probably be used as inputs for other strategies, or it might give you some ideas.

This is how we played the order imbalance strategy at the open:

1. We adjusted the closing price of each stock based on the indications of the S&P 500 futures. This is the fair value of the stocks. If the futures indicates an opening 0.5%, the fair value of the stock is also 0.5% up.
2. Then we placed both a buy and sell order x % below and above the fair value. For example, we placed a buy order 0.5% below the fair value, and a short order 0.5% above the fair value. Pretty simple.
3. We sent thousands or orders.
4. When the market opened we got many fills, but most stocks opened without any fills. At busiest days we could end up with as much as 200 different tickers.
5. We exited partly via profit target and time exit.

In essence, the above sequence is what we did for about two decades, however, as indicated, we had a few twists that we don’t want to reveal. Some stock exchanges are still distributing order imbalances both for the open and the close.

We made about 2 cents on average per trade. That is not much, but it’s all about volume and getting many fills. This is a perfect example of quantitative and automated trading. Sending orders was done by pushing buttons.

You might also find our pretty personal article about confessions of a day trader and how day traders can make it pretty interesting.

Imbalance Trading Statistics

Let’s look at some statics we have gathered from the web (in addition to our own data and statistics above):

• Real-time Imbalance Data: Nearly three of every four traders are watching real-time trading imbalance data, and 70% of traders said real-time imbalance data can influence how their firm trades in the auction or continuous market.
• The trading imbalance data are derived from the changes in the number of shares held in margin accounts, which are collected and published by the exchange
• For larger imbalance trade sizes, the market moves more than for smaller imbalance trade sizes, indicating a correlation between imbalance trade size and market movement[2].
• Auction Trading Dominates: Approximately 7% of a stock’s average daily volume now occurs during the auction phase, a surge of 44% from just six years ago.
• Guaranteed Strategies Ascend: Market-on-open (MOO) and market-on-close (MOC) strategies, which rely on imbalance data, have risen in popularity, accounting for 14% of portfolio trading compared to 5% in 2015 (source is Ibid).
• Global Adoption: Imbalance trading is increasingly prevalent across global markets, with adoption rates reaching 40% in Asia Pacific and 25% in Europe (source Ibid).

Understanding Market Imbalances

Why are there market imbalances? Market imbalances can stem from various factors, including:

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  News events: Significant news releases, such as earnings reports or company announcements, can trigger sudden surges in buying or selling pressure, creating imbalances. Funds with huge orders might want to buy or sell.

  
  
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  Investor sentiment: Market sentiment, shaped by factors like economic outlook or geopolitical tensions, can sway investor decisions, leading to imbalances. A fund or big player might decide they want to sell to free up cash for other investments, for example.

  
  
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  Algorithmic trading: High-frequency algorithmic trading strategies can amplify imbalances by rapidly placing large orders in a short period, just like we explained above for our the day trading we did ourselves.

  
  
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  Liquidity conditions: In illiquid markets, where fewer traders are active, imbalances can arise more easily, as it becomes harder to find counterparties to match orders. Even a couple of thousand shares can create an imbalance and make the stock move.

  
  

Market imbalances are often short-lived, as prices adjust to reflect the prevailing supply-demand dynamics. However, in volatile or illiquid markets, imbalances can persist and have a more pronounced impact on price movements.

Historical Context of Imbalance Trading

Imbalance trading refers to the situation where the supply and demand for assets in a market are not balanced, leading to significant fluctuations in asset prices. We have mentioned short term imbalances, but they can also exist for longer periods of time and in the economy. 

The historical context of imbalance trading can be traced back to the 2000s, when global imbalances emerged as a result of economic policies followed in various countries and through global financial markets. Some key factors contributing to the evolution of imbalance trading include:

1. Economic policies: The global imbalances of the 2000s were influenced by economic policies followed in different countries, which ultimately affected global financial markets.
2. Financial market deregulation: Since the 1970s, financial markets have been progressively deregulated, leading to a fragmented and ineffective system of government prudential oversight. As an example, the start of S&P 500 futures trading in 1982 most likely changed the markets a lot: mean reversion trading strategies saw the day of light. 
3. Asymmetries in the supply and demand for assets: Asymmetries in the supply and demand for assets have been identified as a significant factor contributing to global imbalances.
4. Wage-bargaining institutions: Differences in wage-bargaining institutions have been proposed as an explanation for persistent current account imbalances.
5. Globalization and trade imbalances: Globalization has led to the evolution of trade imbalances across countries, which in turn affects the behavior of asset prices.

The interaction among these factors has contributed to the emergence of imbalance trading, which has been a significant concern in the global economy. The recent global financial crisis in 2008/09 is a clear example of the potential risks associated with imbalance trading, as it was triggered by a rapid change in the underlying equilibrium.

How do global imbalances affect the economy

The origins of global imbalances can be attributed to asymmetries in the supply and demand for assets, economic policies, and the rapid evolution of financial markets, which have led to a fragmented and ineffective system of government prudential oversight, often because of derivatives. Warren Buffett has called derivatives “financial weapons of mass destruction”.

These imbalances, particularly the persistence of external deficits and surpluses, have been linked to the recent global financial crisis, highlighting the intimate connection between global imbalances and economic instability.

Global imbalances affect the economy by creating inherent instability, systemic risks, and long-lasting phenomena, which can lead to tensions in the world economy and have significant implications for employment and global governance.

Theoretical Foundations of Imbalance Trading

Imbalance trading is rooted in various theoretical frameworks:

1. Market Efficiency: Arbitrage theory underpins imbalance trading, as it assumes markets to be efficient, leading to price convergence. By identifying and exploiting price imbalances, traders can capitalize on mispricings before markets adjust. The markets are mostly efficient, but you can explore market inefficiencies.

2. Order Flow Analysis: Imbalance trading relies on order flow analysis, studying the patterns of buy and sell orders to infer market sentiment and identify potential imbalances. This analysis helps traders identify orders that are likely to execute and profit from the resulting price movements. Please see our section above about backtest and statistics.

3. Limit Order Books: Imbalance trading heavily utilizes limit order books, the records of outstanding buy and sell orders at different prices. By studying order book depth and order placement dynamics, traders can identify potential imbalance opportunities and execute trades strategically.

Imbalance trading involves identifying and capitalizing on discrepancies between buying and selling pressure. This technical trading strategy utilizes order book data, price action, and other market indicators to assess the strength of buying and selling sentiment.

Types of Imbalance Trading

Imbalance trading, a technical trading strategy, identifies and capitalizes on discrepancies between buying and selling pressure.

It involves analyzing order book data, price action, and other market indicators to gauge the strength of buying and selling sentiment. The strategy encompasses various approaches, including:

• Order imbalance analysis: This method focuses on the relative size of buy and sell orders in the order book. Accumulation of orders on one side of the order book indicates a potential price movement in that direction. For example, one stock might have a buy order of 100k shares and a sell orders totaling 200k shares.

• Imbalance continuation: This strategy exploits the tendency of price movements to retrace to areas of imbalance, offering entry points for traders.

• Imbalance reversal: This approach identifies price breaks from areas of imbalance, signaling potential trend reversals.

Real-world Applications of Imbalance Trading

We have already given you examples of real world trading example of how to trade market imbalances (the day trading statistics we mentioned further up in the article).

One other real-world application of imbalance trading is identifying breakouts – breakout strategies. When a security breaks out of a well-established range, traders can examine the order imbalance to assess whether the breakout is likely to be sustained. A significant positive imbalance during the breakout suggests that buyers are in control, indicating a continued upward movement.

Another application is anticipating reversals – reversal strategies. Imbalances can foreshadow price reversals when the order imbalance reverses direction. A sudden surge in buy orders amidst a declining market suggests that sellers are capitulating, potentially leading to a price rebound.

Imbalance Trading Tools and Indicators

Several tools and indicators are employed to assess order flow and assess the strength of buying and selling pressure.

Order books, depth of market (DOM) charts, and imbalance indicators provide real-time insights into order flow dynamics, allowing traders to make informed trading decisions.

These tools help identify areas of potential buying and selling exhaustion, potential support and resistance levels, and potential price breakouts.

Pros and cons of Imbalance Trading

Imbalance trading is a strategy in which traders take advantage of price discrepancies between different exchanges. It can be a profitable strategy, but it also carries significant risks.

Pros:

• Potential for high profits: Imbalance trading can generate significant returns if traders can identify and exploit price discrepancies quickly.
• Scalability: Imbalance trading strategies can be applied to a wide variety of assets and markets, making them scalable for traders of all sizes. In our opinion, this is the biggest advantage of an imbalance trading strategy.
• Relatively low capital requirements: Imbalance trading strategies often require less capital than other trading strategies, making them accessible to a wider range of traders.
• Automated trading: Because of scalability, you can use automated trading systems.

Cons:

• High volatility: Imbalance trading strategies can be highly volatile due to the nature of the strategy. However, this can be offset by trading plenty of orders – scale.
• Risk of losses: There is a high risk of losses in imbalance trading, as traders must be able to accurately identify and exploit price discrepancies. Trading is risky!
• Regulatory scrutiny: Imbalance trading strategies may be subject to increased regulatory scrutiny, as they can be perceived as manipulative.
• Fat finger errors: It relies on automation and scaleability, and this is prone to fat finger mistakes. If you are sending many orders, losses can multiply. Be careful!

Risk Management in Imbalance Trading

These risks can be mitigated through effective risk management strategies.

Key risk factors include counterparty risk, settlement risk, and potential losses from adverse price movements.

We mentioned fat finger errors, and you must have systems in place to avoid them.

Price risk can partially be mitigated by trading strategy diversification and trading complementary trading strategies.

Challenges and Pitfalls of Imbalance Trading

While imbalance trading offers the potential for high returns, you must recognize the inherent challenges and pitfalls that lie ahead. Improper risk management, inadequate market knowledge, and the volatility of imbalanced positions are common stumbling blocks traders face.

And the most important thing of all: you must backtest or gather as much data and statistics as you can before you start live trading!

One prevalent mistake is overleverage, where traders take on excessive debt to amplify their gains. This strategy can backfire swiftly, as even small market fluctuations can lead to margin calls and severe losses. Always remember that the worst drawdown are yet to come!

Another common error is underestimating the volatility of imbalanced positions. Imbalances magnify price swings, increasing both the upside and downside potential. A sudden market reversal can quickly wipe out gains or even lead to account liquidation.

Traders also need to be mindful of liquidity constraints in imbalanced markets. Bid-ask spreads can widen significantly, making it difficult to exit positions at desired prices. This can lead to slippage, where trades execute at unfavorable prices.

Future Trends and the Evolving Landscape

As market participants become increasingly sophisticated and technology advances, imbalances are likely to become more nuanced and fleeting. Since we started trading in 2001, the window of opportunity for smaller independent traders have diminished. The opportunities to catch imbalances are reduced, and bigger and more capitalized players take more of the prey.

Strategies will need to become more adaptive, leveraging machine learning and AI to identify and exploit emerging imbalances with greater precision.

Additionally, the emergence of decentralized exchanges (DEXs) and other innovative trading platforms will necessitate strategies that seamlessly navigate these new ecosystems. The future of imbalance trading lies in its ability to adapt to these shifting market conditions, harnessing technology to enhance efficiency and exploit temporary market inefficiencies.