Should a brokerage allow scalping?
A technology provider discusses the key questions a broker should ask before making a decision on short-term trading strategies.
A technology provider discusses the key questions a broker should ask before making a decision on short-term trading strategies.
How does scalping work?
Short-term trading, like scalping, remains among the most profitable trading strategies, especially in highly volatile markets. Despite their attractiveness, many brokerages do not welcome these strategies because their performance may significantly affect and, in some cases, even overload the brokerage’s entire infrastructure.
Making a profit by opening a large number of micro trades rapidly, scalpers benefit multiply by the number of closed trades and the frequency of their closing even if the profit per one trade is insignificant. This feature of short-term trading ensures that it is often performed with automated methods, for example, bots that open and close traders’ positions.
How does short-term trading affect the trading process?
As mentioned before, even though scalping is considered a profitable strategy for traders, most brokers restrict its use on their servers or offer stringent conditions for “scalping” clients. To decide whether to allow short-term trading to clients, the broker should analyze how this trading practice may affect the brokerage’s internal business processes.
- The key process that will be influenced by short-term trading is order execution. For brokers who allow scalping on their servers crucially important to ensure receiving high-quality market data for the trading platform. This condition may be achieved with reliable liquidity providers who aggregate data from multiple sources. Alternatively, random quote spikes may occur if the broker uses raw data.
The spikes will not significantly affect trading strategies and funds of long-term investors, but for traders using short timeframes, such artificial volatility is both a risk and a desirable chance of making an easy profit. Fortunately, modern data feed technology usually comes with a spike filtering feature and may be set up easily and correctly for particular cases.
- Besides receiving and processing market data, the key stage for the trading process performance is the order execution. How exactly this process is performed is determined by the broker’s business model or risk management model. The most common models are market-maker or b-book, STP or a-book, and hybrid — a combination of both. Each of these will have its own difficulties while using high-frequency trading.
For brokers who process risks in-house, such a rapid and abrupt introduction to the market with many trades may appear to be a blow to risk management. Companies using such models usually mitigate risks by hedging a part of clients’ open positions to balance funds and manage possible losses. The hedging processes that are configured to operate not in real-time, but periodically, i.e. every 1 minute, may miss such short-term positions and lead to increased risks.
- Finally, one of the most neglected concerns is the trading platform performance. Receiving market data and trades execution is key, but not the only processes performed on the trading platform. For example, if a broker offers clients bonuses for each closed position, the bonus distribution process will result in the extra load due to the frequency of trades. Similarly, if a broker provides a copy trading service, automatic copying of short-term trades will increase the load in scale. Thus, the broker’s risks increase significantly, and other clients may experience technical problems, i.e., trade execution delays and lagging charts.
Why do many brokers prohibit their clients from using scalping?
To sum up, even if a broker can accurately calculate all potential risks, preparing the infrastructure to provide needed trading conditions may require too much time and resources. Moreover, when introducing any innovations into the business model, the broker will have to assess the short-term trading as an additional risk factor in areas of:
- Pre-execution: Market data and liquidity aggregation;
- Order execution: Hedging and risk management;
- Post-execution: Additional services and trading platform performance.
