Fundamentals of Short-Term Trading
Welcome to the first article in our series on short-term trading. This guide delves into the core concepts crucial for effective short-term trading, focusing on risk management, position sizing, and the dynamics of intraday trading. By understanding these fundamentals, you will be better equipped to navigate the complexities of short-term trading and enhance your trading strategies.
Understanding Market Behavior
As you may remember, we've explored intraday volume patterns and their implications for trading. One critical takeaway was the non-stationary nature of price changes throughout the day. This means that applying the same buying and selling parameters throughout the trading day can be risky.
To determine whether a market movement is significant, analyze market behavior from both horizontal and vertical perspectives. This approach involves comparing current actions at a specific time of day to similar actions from previous days. By doing so, you can better assess if a movement is noteworthy or just noise.
Risk, Size, and Holding Period
Consider a scenario where you are willing to risk 2% of your trading capital on a trade. If you are trading on a tick-by-tick basis, you might trade multiple contracts while adhering to your risk parameters. Conversely, holding positions overnight increases the risk of significant moves, meaning the same 2% risk would translate to fewer contracts.
For example, a scalping trade early in the morning might carry a higher risk of a multi-tick adverse move compared to a trade placed closer to midday. Maintaining a constant position size during non-stationary periods—or increasing it during high volatility—can lead to substantial losses from a single trade.
Michael Bryant’s article “Position Sizing With Monte Carlo Simulation” in Technical Analysis of Stocks and Commodities (Feb. 2001) illustrates how simulations can define the fraction of trade capital to risk while maintaining a low probability of severe drawdowns. For instance, his MiniMax swing trading system shows that risking 2% of capital results in a 24% maximum drawdown with 95% confidence. Reducing the risk to 1% of capital lowers the drawdown to 12% with the same confidence level.
The fixed-fractional strategy for position sizing is calculated using the following formula:
N = ff * E / RWhere:
- N = Number of contracts traded
- ff = Percentage of trading capital allocated to the trade
- E = Total trading equity before placing the trade
- R = Risk of the next trade in dollars (i.e., stop loss)
For instance, if you are risking 2% of a $100,000 trading account with a 4-point stop ($200 per contract), you could trade 10 contracts while remaining risk-prudent. Adjusting position size based on the stop level and trading strategy is essential for effective risk management.
Adjusting Risk and Reward
The concept of stationarity is critical in trading. For example, if you set a 4-point stop, the risk of a setback can vary depending on the time of day. An intraday trader using a fixed-point stop may be taking too much risk at some times and too little at others.
Monte Carlo simulations can determine the 95% probability of a market drawdown at different times of the day. Just as position size should vary between intraday and swing trading, it should also adjust according to the time of day.
Successful traders often increase their position size in proportion to their confidence in a trade. This method can lead to significant gains if executed correctly. However, increasing position size adds risk, particularly if a trade is nearing its peak. The risk of a reversal when the position size is largest can negate previous gains.
Scaling into positions over time can mitigate this risk. Michael Covel’s forthcoming book on Trend Following cites Ed Seykota’s approach to pyramiding, which involves adding smaller units progressively while monitoring the trade’s performance. This method keeps initial risk lower and allows for profit maximization as the trade progresses.
Final Remarks
Short-term trading, like all forms of trading, is fundamentally a mathematical exercise. To achieve profitability, the average size of winning trades must significantly exceed the average size of losing trades. Failure to adjust trading size and holding periods can result in a good methodology but poor profitability due to larger losses overshadowing smaller gains.
Effective self-assessment involves evaluating the time and effort spent on defining market entries, gauging exits, and managing trades. Many traders focus excessively on entries, are impulsive with exits, and overlook the critical aspects of trade size and risk management. Money management, rather than just entry signals, differentiates successful traders from less profitable ones. Emotional responses during trading often hinder good management practices. More on this topic will be covered in the next article.
