The Application Of Risk

Risk is an elusive concept to cover, and certainly a much misunderstood one. It is defined in different ways for different purposes but it is critical to fully understand what constitutes risk in order to find sustained success in any speculative venture.

Depending on the context, risk can mean the expectation of volatility and illiquidity: This market is one of great risk. It can also be an albeit abstract measurement of the likelihood of success or failure: I believe this is a low-risk proposition. Lastly, risk can be a calculation related to exposure and downside versus upside potential: I have £5,000 at risk here, though my returns could be as great as £15,000. This latter definition is the one most commonly used by traders, but I believe an understanding of them all is particularly useful for profitable speculation. Only by seeing the full picture of market volatility, exposure and risk versus reward can we then come to some sort of conclusion on the second definition; whether our current speculations will prove successful. In fact, part of the full picture of risk is illuminated by the price-history of the market, depicting where, in the past, similar scenarios to those we are presently expecting have seen success or failure.

This post will, I hope, serve as foundational material for those who are unfamiliar with applying the many aspects of risk to their speculative positions. I will run through the process for each of the three relevant definitions of risk and how they each relate to the full picture.

Firstly, however, I’d like to emphasise the most essential point concerning risk: Particularly when speculating in the cryptosphere, the thing that determines whether one masters risk management or not is whether one invests money they cannot afford to lose. If you start out with non-discretionary income, you’ve already lost the game. The other components of risk management are only relevant if your speculations are comprised of money you can afford to lose. If this is not the case, the likelihood is that no amount of searching out low-risk, high-reward opportunities is going to save you, as your emotions are inextricable from your positions.

For those that the above applies to, stop reading and reorganise your portfolio until it resembles something that you could lose the entirety of tomorrow and it would not affect your quality of life. For the rest of you, let’s crack on.


Risk, as in volatility and illiquidity:

When a market experiences high levels of volatility (as is the case with all cryptocurrencies), it is said to be risky. Similarly, when a market is highly illiquid, there is inherent risk in exposing your capital to said market, as there is a possibility that, once a position is entered, it would be very difficult or costly to exit until market conditions improve sufficiently.

These aspects of risk management are critical to one’s speculative positions, as they are very much linked to personality and thus the quality of the decisions one makes. If you are highly risk-averse by nature, entering a position in a more volatile and illiquid market is perhaps not the brightest idea; if you are risk-tolerant, an illiquid market may not bother you and high volatility may not affect your trading decisions. In either case, having a clear understanding of these aspects of risk prior to entering a new position is a contributing factor to the likelihood of success.

But how can one determine volatility and illiquidity as a component of risk management? Most commonly, these are abstract terms for the general market participant, relative to the more concrete calculations one makes for exposure and reward-to-risk. However, simple calculations can be made to make things clearer.

For volatility:

  1. I tend to first determine the duration that I’m expecting to hold a position for. In my case, this almost always tends to be over a month. We’ll use a month for the purposes of clarification.
  2. Given this trade duration, I collate (in a spreadsheet) 30 days of historical price data for the coin I’m interested in using Coinmarketcap’s Historical Data tab.
  3. I delete everything except the Close Price data.
  4. I then calculate the average Close Price for the 30 days. This is my benchmark figure.
  5. Using this average Close Price, I calculate the percentage change from it to the highest Close Price during the month.
  6. I do the same for the lowest Close Price, also.
  7. For example, if the average price was $1, the highest price was $1.50 and the lowest price was $0.30, this would give me figures of 50% and -70%.
  8. The final step is to multiply these figures together to find a volatility ratio for the given duration. In this case, it would be -0.35 over the past 30 days.
  9. The closer to 0, the less volatile the market during that period of time, and vice-versa.

This process is particularly useful for cross-comparing the volatility of altcoins over the same time-period. It is rudimentary in its methodology, but gives us some form of concrete figure to apply to our risk management. Those that are risk-averse may opt to only enter positions in coins that have volatility between 0 and -0.1, for example.

For liquidity:

  1. This is even simpler than the calculations made for volatility. The first step is to calculate the buy support across listed exchanges for the coin you’re interested in, within 10% of the current price. Calculate this in BTC-denomination.
  2. Now divide this figure by the market cap of the coin (again, use the BTC figure).
  3. Multiply the result by 100 to get the buy support as a percentage of the market cap.
  4. Anything lower than 0.1% is highly illiquid. Anything higher than 1% is highly liquid. Most altcoins tend to be between these two figures.
  5. Do this once a day for a week and calculate the average to get a more reliable figure.

Now, the most important thing to do with this information is devise a benchmark that works for your personal relationship with risk. And stick to it. For some, this will be a commitment to only entering positions in coins with greater than 0.5% liquidity and between 0 and -0.05 volatility. Just make sure you know what works for you.


Risk, as in likelihood of success or failure:

This second definition of risk is, as mentioned earlier, more abstract than the other two. We often use low-risk synonymously with high-probability in everyday conversation, or high-risk synonymously with low-probability. The utility for speculators comes from finding historically similar scenarios to those we are expecting to profit from and evaluating their successes and failures. To make this clearer, let’s use a simplistic example:

First we must define the terms of the position we are considering. Let’s say I am considering an entry on X at 3000 satoshis. I am anticipating prices above 6000 satoshis, and would consider my trade idea incorrect below 2000 satoshis (which would be my soft stop-loss). I am willing to hold the position for 3 months.

Given these points-of-reference, we would simply backtest the trade using the coin’s price-history. Every time price reaches 3000 satoshis, we would enter an imaginary trade; does price reach 6000 satoshis? Does it reach it within 3 months? How many times would the position be stopped out? Ask all the relevant questions and compile an historical evaluation of your trade idea. If we’re looking at a trade that has been successful 80% of the time in the coin’s price-history, it gives us some degree of confidence that our own position will be successful, also. Of course, to be able to evaluate your idea to this degree, you first need to know all the critical information regarding exposure, entries, exits and risk versus reward. As such, the most important aspect of risk management outside of using capital you can afford to lose is found in the third definition.


Risk, as in exposure and returns:

Risk management for traders is mostly concerned with this third definition of risk that concerns all things quantitative, and for good reason. For me, calculating exposure is a prerequisite to entering a new position. It is the primary element upon which the rest of the trade is structured. Speculating without a clearly defined plan for capital exposure is a sure-fire way to wipe out your portfolio, and we don’t want that, if we can help it…

I will, at a later date, be writing an in-depth post on position sizing, which itself is a integral part of managing exposure, but for now let’s consider the basics. You could, of course, create an intricate plan of position sizing based on the volatility and liquidity calculations I mentioned earlier – almost as though you’re basing your risk on, well… risk itself. Riskception. But for the purposes of this post, let’s stick to the most common method of determining position size, which is focused on market cap or network value, however you like to refer to it:

  1. Firstly, you need to calculate the value of your portfolio. This is the base figure that you will use to calculate exposure for a new position. Let’s say it is 10 BTC, or ~$40,000 at current prices.
  2. Now, figure out whether the coin you are considering a position in is a microcap, lowcap, midcap, highcap or megacap. These are arbitrary terms, of course, but I can only offer my approach here. I categorise these using the following figures: microcap = 0-25 BTC; lowcap = 25-250 BTC; midcap = 250-2500 BTC; highcap = 2500-25,000 BTC; and megacap = 25,000 BTC or higher. These, again, are subjective numbers based on my own experiences in the space. If you wanted to use $ figures (though I advise against it, as these are heavily dependent upon the price of Bitcoin), then I’d opt for 0-$250k for a microcap; $250k-$2.5mn for a lowcap; $2.5mn-$25mn for a midcap; $25mn-$250mn for a highcap; and $250mn or higher for a megacap.
  3. Now, for each of these market cap-based groups, I have a different band of exposure based on the original value of my portfolio prior to entering the position: 0-1% for microcaps; 1-3% for lowcaps; 3-5% for midcaps; 5-10% for highcaps; and 10% or more for megacaps. I do not commit to the minimum percentage exposure within these bands, but I explicitly do not exceed the maximum for the given market cap. For example, I might choose to only allocate 5% of my capital to a megacap, but I would never allocate 5% of my capital to a microcap.
  4. Of course, there are some caveats here. Firstly, this approach is known as fixed-risk, wherein one allocates a fixed percentage of capital to a position often in lieue of setting a stop loss (but not always, as we’ll come to shortly). The position is then held until: it reaches its target price(s); it fails to reach its target within the predetermined duration of the trade, at which point it is exited; or, the coin dies. This is a common approach with microcaps and lowcaps, but makes less sense when one is concerned with the larger coins.
  5. When it is these larger coins that are being considered, the bands of exposure are still used, but a stop-loss (hard or soft) is added as a second risk-mitigator. My approach to stop-losses is that they should be based on technical factors rather than predetermined percentages, such as the break of long-term support or something similar, but it is often useful to have a maximum percentage stop-loss in place. For example, let’s say we were looking to enter a position in ABC. ABC is a highcap and so our capital exposure is a maximum of 10% of the value of our portfolio. Further, since it is a highcap, we choose to place a stop-loss. The maximum we are happy to lose is 25% of the initial capital, and thus a stop-loss is placed 25% below the average entry price. This equates to 2.5% of the value of our portfolio, which is our maximum capital loss.

Now, there are numerous other avenues one could go down when devising an approach to risk management, but I believe this approach will suffice for most. The issue is that stop-losses can and must (in my opinion) be linked to the risk versus reward of the trade. So let’s discuss the final aspect of risk for this post: returns.

The goal in investing is asymmetry – Howard Marks

Asymmetrical opportunities are the real secret to profitable speculation and proper risk management. Finding opportunities that present returns many multiples greater than the potential risk is what is so special about this space – they are ubiquitous.

Reward is almost always predicated on the price paid for the position, which is why buying low is so important. It allows for the low-risk (here meaning minimal amount of capital loss), high-reward opportunities. The most important thing to take away about risk versus reward is to exclusively go after opportunities that offer at least twice the reward against the risk. So, if, after calculating your capital exposure and your stop-loss, you have a maximum capital loss of 2.5% of the value of your portfolio (as in the earlier example), then your opportunity must present a reward equating to 5%. This is why the fixed-risk approach is suitable for the smaller altcoins; the potential rewards are so large that the trades are often asymmetrical in our favour despite the potential loss of the entire position.

Now, to conclude this post, how do we tie it all together? Well, what you can do is create a risk framework that all future trades must adhere to, and this would be based on your own level of risk tolerance. For example, you could decide to only enter positions in coins that have 0.5% liquidity, between 0-0.1 volatility over the past 90 days, at least one instance of success of a similar scenario in the coin’s price-history and at least 3:1 reward-to-risk. Play around with the numbers to see what works for you – the important thing is to have a consistent framework to which you always adhere.

I hope this post has proved useful. Feel free to leave any comments and questions below and I’ll get back to you!


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6 thoughts on “The Application Of Risk”

  1. Happy New Year Nik – hope it’s a great one for you!

    Thanks for the post which helped me get a really clear pragmatic handle on risk management for alts.

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