Posted on

Trading – When trades go wrong

Many a times common traders find that the trading assumption or trades they make do not work out. For instance, they could be buying a stock which reverse gear and went into a steep decline. Or they were shorting the market which made a quick turnaround and sprint upwards.

What would a real elite trader do in these types of situations?

To put in perspective first, you should not confuse the concept of winning and losing traders with good and bad trades.

This means that a good trade can lose money, and a bad trade can make money. Even the best trading system and process will lose a certain percentage of the time. Of course, a good system will always keep the win ratio and win % gains high and the loss ratio and the loss % low.

While there are certain ways we can project in advance which trades will make substantial profits, there is no guarantee that 100% of the trades will turn up as projected.

However, as long as a trade adhered to a process with a positive edge, elite traders know that it is a good trade, regardless of whether it wins or loses, because if similar trades are repeated multiple times, they will come out ahead.

Conversely, a trade that is taken as a gamble is a bad trade regardless of whether it wins or loses because over time such trades will lose money.

Hence, while trades do go wrong, the elite trader will know how to adapt and be still confident in his skill and the system he uses. Knowing one’s trading edge is like almost winning the whole battle in trading.

Traders must find a methodology that fits their own beliefs and talents. It would be nice to believe that if you can find a trading methodology that works and also have the discipline to apply it consistently, then trading success is assured.

Unfortunately, the real world is a bit more difficult. Markets change, and strategies that work may eventually deteriorate and traders find it hard to monitor and keep track of the market daily.

As such, traders need to be vigilant to the possibility that a once reliable approach may lose its efficacy or even become a losing strategy due to changing market conditions. Or the trader may need to modify the strategies to adapt to the changing market conditions.

A good trading system and strategy is one that will allow a trader to thrive in all market conditions such as in a bullish, bearish or sideways market.

Even as such, not all trades will work and thus elite traders always adopt a risk safeguard in position sizing in every trade entered.

For example, if a position is too large, the trader will be prone to exit good trades on inconsequential corrections because fear will dominate the decision process.

Limit the size in any position so that fear does not become the prevailing instinct in guiding your judgment.

In this sense, a smaller net exposure may actually yield better returns, even if the market ultimately moves in the favourable direction.

For example, a large net long exposure in high beta stocks in an increasingly risky market will bring fear and risk to the portfolio and lost opportunity in the sense that when the subsequently plunged, the trader would not be well positioned to increase his long exposure.

Had the trader remained heavily net long, he might instead have been forced to sell into the market weakness to reduce risk, thereby missing out in fully participating in the subsequent rebound.

An elite trader thus is never worried about losing trades or when trades go wrong as these would have been factored in his trading system and plan before entry.

Our own mPower Algorithm program at Malacca Securities uses sophisticated, complex and specialised mathematical and statistical algorithm and large-scale data analytics of price, volume and volatility movements in the whole market and individual stocks to not only identify trading opportunities but to also limit risks when trades do go wrong.

The algorithm presents a comprehensive and Integrated strategy for elite traders where all trading strategies in multi-time frames are covered such as sideways, breakout, trend, counter-trend, etc.

All trading picks of the algorithm are formulated to meet a very stringent risk-assessment analysis designed to identify low-risk high-probability reward situations only.

Because it is primarily focused on risk first and reward second, there will be times and days when no trading picks will be highlighted by the algorithm despite scanning the entire breadth and depth of the market.

This could occur when the algorithm detects elevated risks as being present in the individual stock, sector or market, such as when there is a possible change in the overall market trend or when extreme volatility is present in the individual sector of the stock or the stock itself.

The final selection of trades undergoes a further complex filtering of risk-reward assessment criteria by the human element (master traders) in our elite Algorithm Team and hence only select risk-adjusted instruments can pass through the final process.

We are not only interested in high probabilities trades but only in low-risk high probabilities trades. Hence, bad trades are minimised while the good trades are maximised.

Whichever trading system or processes you are using yourself personally, always ensure that you are able to adapt when faced with bad trades under the system.

Unlike elite traders who are in control of their trading, common traders tend to end up angry, confused, frustrated and dejected at their trades and often quietly exit the market after losing all their capital.

The key is to be confident in your own trading system and edge and be adaptable when trades go wrong.

One thought on “Trading – When trades go wrong

  1. […] Markets love to surprise and markets love to trap too. The immense skill of an elite trader is to determine which is the likely scenario on the balance of probabilities using the widest array of information available. Common traders will tend to get carried away in media headline news explaining the move AFTER it happened (see this report on “when trades go wrong”) […]

Comments are closed.