Most traders can quickly recite the requisite win rate, average expected return, risk levels, and position sizes that are necessary to their success. These metrics often vary from trader to trader but need to be as fine-tuned as possible in the long run to ensure success. Slight deviations in these figures can mean the difference between success and failure, performance truly sits on fine-tuned balance.
Trading might be referred to by some as an art, but once you realize the factors that are necessary to take into consideration, it is obvious that it is more of a science than anything else.
If a trader is executing poorly and keeping proper records, they can easily look to what is the source of their shortcomings, and mitigate these performance issues by some change in approach, strategy, frequency, etc.
One unavoidable issue has always been built-in transaction costs such as fees and the cost to jump the spread. Of these two frequently encountered issues, one has been a bit more difficult to alleviate: fees.
An example of such an unavoidable situation is when a person trades CFDs or contracts for difference. The exchange might not advertise a fee, but that is only because it is already baked into the spread. This trader might be paying upwards of 1.5% to take a round trip in a position. This means that before considering the possibility of the trade moving favorably or poorly, they are already taking a loss to get in and out.
Another example involves a crypto trader using an exchange that charges for being both a taker and a maker. This means that even if the trader is being a provider of resting liquidity, they are still paying a fee to do so. Some exchanges charge upwards of 50 basis points or a half a percent to enter or exit a position.
This might seem like a small value, but now consider the compounding effect this can have, especially on an active trader. Everyone who is not an investor is already transaction costs sensitive, but traders who are more active experience the worst of this.
Let us consider a trader who scalps momentum on low time-frames. In this example, we will give them the benefit of the doubt of having a trading approach with a positive expectancy. Without even getting into the returns or losses of their strategy, let’s imagine they are trading with a $10,000 account. Since they are a low time-frame trader, they likely make a lot of round trips. To keep things overly simple, our trader risks 1% of their account on each trade, and trades with the full account value.
Scalpers might take anywhere from 50-300 trades a week. For the sake of this experiment, let’s pick a random low number and say our scalper takes 75 trades a week, which is about 10.71 trades a day. That is around 37 round trips, meaning open a position to buy, sell a position to close, and vice versa. In this case, our trader is trading on an extremely popular exchange that charges a maker fee of .10%, or 10 basis points.
With a simple python exercise, we can see how our trader’s performance looks over time. This is before any losses or gains and assuming that all trades were closed at the break even point, which obviously would not be the case.
In this example, the trader lost 722$ just from fees alone. Of course, once again, this assumes all trades were closed at break even. Now imagine how this would be incorporated into a system that would incur losses as well and how that might exacerbate any negative compounding that is already built-in through transaction costs alone. You would rightly assume that especially in the case of traders who operate at a higher frequency, that fees can completely chew away at any returns.
It should be quite clear now, that on top of all the other considerations a trader must pay attention to, finding a way to mitigate cost would yield a substantial advantage. Don’t know where you could spot trade cryptos with no fees? We do.
This is one of the benefits of Phemex.
By Ryan Scott (@CanteringClark)