Evaluate your hopper efficiency.
Advanced self-guidance: factors to consider to optimize your hopper for the long run.
Note: this section is supplementary to our Template Setup Guide.
Trade volume
The trade volume of your hopper is roughly calculated by multiplying your percentage buy amount under config settings by the amount of sells that your hopper made in a day. For example, if your percentage buy is 3%, and your hopper made 30 sells, your volume of that day was 90% of your portfolio. There is a caveat, as if your hopper doubled down on a position 1 sell would equal 2 buy portions, concealing some trading volume.
If you trade agressively, trade portions will be bigger and thus net volume higher, too. In a bull market this is desirable as it allows your hopper to immediately compound profits in to the next trade. If a market is very bullish, strategies like Bull Power allow to do so, aiming for a high frequency and thus a high volume. In these conditions daily traded volume can effortlessly reach a multitude of your portfolio (up to 5x) your portfolio size, naturally increasing profitability.
When to trade with high volume
High volume is not always desirable. Increased volume means increased risk. Thus in a bear market traders may want to trade with low volume, low exposure and high liquidity. These considerations are included in our Bull and Bear templates.
Transaction costs and risk-reward
Although high volume may be desired in bullish conditions, transaction costs will also be more significant. Keep an eye on your transaction cost ratio and maintain a healthy risk-reward ratio.
Exposure & liquidity
In order to keep everyone on the same page, Gainscrypt maintains the following definitions for exposure and liquidity.
Total exposure
This is the intitial percentage of funds you allow to be exposed to the market at once, simply calculated by multiplying the percentage buy amount by the maximum of postions in your hoppers config settings.
(Note: if your hopper doubled down on several positions after a market downturn, the actual exposure may be higher at that point in time)
We then subdivide exposure in 'DCA exposure' and 'liquid exposure' using cryptohopper config pools (check out our Advanced Template Settings Guide to learn more).
DCA exposure
In the DCA config pool, risk is managed by Dollar Cost Averaging (DCA), which means positions are doubled down on when markets fall. The advantage of DCA is that your position doesn't get stopped out unnecessarily due to a brief volatile downswing. The downside of DCA is that risk is not contained clearly, and during extended bear markets positions can become 'bags'. General recommendation is to only apply DCA to coins or projects you fundamentally know well and have a long term vision for.
Liquidity
These are the funds you keep in reserve in order to be able to double down on positions (even multiple times) by means of backup. Liquidity simply the substraction of the exposure from your total funds.
Liquid exposure
Of course, many traders don't just want to sideline their funds. To increase your exposure to market movements, a config pool can be mounted for coins that you only wish to trade for price action, but would limit your risk on by applying a stop-loss to this pool. Hence, we refer to this as liquid exposure as it allows your hopper to keep trading, but with a more direct and absolute control of downside risk.
Considerations
As a simple rule of thumb, one could argue that having high liquidity in your portfolio reduces risk but may yield lower reward in the short term. Conversely, high exposure may yield bigger rewards but brings more risk. There is no ideal solution here, as for each trader this is different. Ultimately it is up to you to decide how to build your setup in relation to your personal risk profile as well as current market conditions.
Transaction cost efficiency ratio
For each trade you make, both the buy and sell order, a transaction fee will be paid to your exchange to make the trade. These fees are typically small, but not negligible. On Binance these fees are small than 0.1% per order. This means, to make a full trade, this amount will have to be paid twice. If your trade has been rather profitable, this won't amount to much. But if your trade targets are low (<1%) these fees may significantly impact your risk-reward ratio.
Example
Your hopper purchases of 0.1 Bitcoin for $1000 on Binance, then $1.00 is paid for fees (using Binance). Then your target of 1% profit is met, and the hopper sells your Bitcoin position for 1010$, resulting in another $1.10 in fees. So your net profit was only $7.90, although you exposed $1000 position. Meaning your transaction fees ate over 20% of your profits, which is not very efficient.
If your risk-reward ratio was (on the surface) 1:1 and your stop-loss thus a neat -1%, your risk was in fact a $11.90! (10$ + $1.00 buy fee and $0.90 sell fee). Your real risk vs. reward ratio thus 1.19 : 0.79, NOT 1:1.
Conclusion
This example illustrates how a seemingly perfect 1:1 risk vs. reward ratio may turn out to be skewed due to an inefficient transaction cost ratio. Don't let exchanges earn money over risk that you are taking!
Therefore, it is recommendable when considering your risk-reward ratio to include the transaction inefficiency in your calculation. Because although algorithmic trading presents wonderful opportunities to exploit smaller market movements, going crazy with micro scalping evidently will bleed your profits over to the exchange, and not your pocket.
Hence, in our vision, trades targeting +2% profits are minimal when using Binance, in order to keep the transaction loss under 10% (see scheme). Trades targeting 4 to 5% profit are preferable in order to further reduce transactional inefficiency.
On the flipside, the lower profit target may have the advantage of trading higher volumes (check the volumes section), allowing to compound faster in certain market conditions.
Risk : Reward ratio
Risk versus Reward ratio is a vital element to consider when setting up your automated trading system. Although TA strategies give signal with a statistically favourable outcome, proper tail risk management will ultimately determine your hoppers succes in the long-run.
Reward (Target - transaction fees)
The reward is easy to understand. This is your target profit (TP), but minus the transaction fees as explained in the Transaction Cost Efficiency Ratio section.
Risk (Stop-loss + transaction fees)
The risk is clearly defined when setting a stop-loss, to which the transaction fees should also be added.
However, when using 'arm trailing stop-loss' (ATSL), sell signals and/or DCA, the risk vs. reward becomes more ambiguous. To keep things simple, we compare ATSL to regular Take Profit and a double-down trigger to stop-loss.
Positive or negative ratio?
Depending on your trading style a negative (e.g. 2:1 ratio) or positive (e.g. 1:2 ratio) could be used. If you're aim is to trade longer timeframes and projects with high fundamentals, you may want to opt for a positive ratio. Conversely, if you're aim is to trade high volumes and take quick exits, but want to give downside room for your trades to bottom out, a negative ratio can be used. This may be benificial for succesful trades, but individual losses will hurt more.
Rule of thumb
In order to achieve a real 1:1 risk-reward the net reward should be equal to the total risk as described above. A balanced or positive risk-reward ratio is a good starting point for new traders, meaning the net reward is equal or greater than the risk.
Backtesting
For backtesting, we typically use a 1:1 ratio to be able to establish the accuracy of a strategy.
Exactness
Of course, this risk-reward can be a proximation and does not have to be exact to the decimal. Trading is not predictable that way. But keep an eye on this ratio on an abstract level, and avoid unrealistic disbalance.
Trailing efficiency ratio
Trailing stop-loss is designed to increase the profit of a trade, by capturing as much of it's upside as possible.
By Trailing Efficiency Ratio we consider the ratio between Arm Trailing Stop-Loss (ATSL and Trailing (TSL).
For example, if your ATSL in your config is set to 6, and trailing to 1.5, then the Trailing Efficiency is 4 to 1, which we classify as balanced. ATSL2.5/TSL0.5 is a 5:1 ratio and so on.
However, to some extend, loose trailing may not always be so efficient. Imagine that in order to capitalize your profits, a price must first move up enough to arm your trailing stop-loss (ATSL), but then may fall under your ATSL target, effectively reducing the profitability of a given trade. In a way this can be perceived as opportunity cost, as the trade could have been more profitable. Additionally, your time in the trade was longer as well, which might reduce your overall trading volume.
When to give/reduce room for trailing
If markets are trending up, time is on your side and the likelyhood of increased profitability accrues with time. In these conditions it is therefore benificial to give some extra room to your Trailing settings. In a sideways or downtrending we can assume that time is not on our side, and we probably want to take profits when we can, tightening the trailing settings.
How do I evaluate if my trailing is efficient?
If you notice that more often than not your positions are sold as a result of the Trailing Stop-Loss trigger, but with a lower average profit than your ATSL target, then this suggests that your trailing settings could be further optimized (example 2). If your trade profits are generally bigger than your ATSL target, than this implies that your trailing settings are working well (example 1)!
Annual operation cost efficiency ratio
A question we often get is, "How much should I invest?"
First and foremost, only invest what you can afford to lose." You want to sleep well at night. For a trading system to work well, it should not be disturbed by emotional indiscipline.
If you have a portfolio to play around with, then the question arises how much should you spend on operation costs?
The total yearly operation costs (CH subscription, signal subscriptions, templates & srategies) effectively sets your portfolio back right from the start. This is especially noticable for smaller portfolio's.
If you spend 10% of your budget on operation, this means that your hopper requires an annual ROI which at least makes up for the costs. This is crypto, and starting at the right time this might be made up for in a day. Those in crypto long enough will have seen their portfolio double a multitude of times. But like always, we're here to highlight risk and downside. If you're starting out you don't want to have to depend on a bull market. In an extended bear market your portfolio may drag its feet a while before seeing any upside, whilst costing you money to keep the show running.
This begs the question: How to adequately proportionate your operation costs to your portfolio size? In this diagram we've abstractly marked down a rule-of-thumb to keep in mind when determining your willingness to spend on trading tools. Our general recommendation is to keep operation costs under 20%, and ideally even under 10%.
Of course, having more tools and strategies to your disposal may increase your profitability, but even a simple, affordable setup can be very effective and allows for your capital to actually be traded instead of spent.
If you're budget including your portfolio is 3000$, then spending half of it on a hero subscription + strategies and signals might not be the most efficient thing to do. Could you still make a net profit? Sure. But the more inefficient your setup, the more unfavourable your risk-reward becomes.
If you're starting out
If you're just starting out and just look to trade small and experiment, simply get on your way with a balanced Core Strategy like Wave Gainer and a explorer hopper. We offer free strategies too!
Other tips to reduce operation costs
- Paying Cryptohopper annually saves -20% on subscription fees.
- Use code gkJ50LeA for another -30% discount upon checkout.