Algorithmic Investing

A Balanced Strategy by Teragon

Teragon
Teragon.io
8 min readJun 9, 2022

--

Algorithmic investing — A balanced strategy by Teragon
Introducing Balance Strategy from Teragon

1. Introduction

Investing in crypto assets is not easy, especially for a beginner. The performance of this new asset class in recent years is attracting a great deal of attention. High returns are often accompanied by volatility and uncertainty that can push investors out early or cause them to continue holding through significant downturns. The goal of Teragon is to smooth out this volatility, eliminate the need to research hundreds of assets and adjust for an individual’s risk profile.

Our approach to accomplishing this is through systematic rule-based strategies. Each strategy is backtested for effectiveness and only the most competent ones are deployed. Psychology plays an outsized role in investing and is consistently the most common way people lose money. The rules that dictate a particular strategy are executed regardless of how we see the day to day market. This removes as much euphoria and fear as possible that are common in short term trading.

Teragon plans to offer a host of blue chip assets from throughout the crypto space, including decentralized finance (DeFi), gaming, innovative and growing blockchains and more. Each asset is vetted to reduce the risk of large drawdowns, exploits and hype. Users can customize which products they wish to invest in and the system takes care of the rest!

Teragon’s algorithms remove the need for investors to continually hold assets. In highly volatile coins this typically results in holders sitting on losing investments for far too long with little spare capital. Investors are left unable to take advantage of market drawdowns. Our solution is systematic portfolio diversification as a tool for stabilizing the portfolio in downturns while reducing risk when markets turn euphoric.

Buying market downturns is simple in practice, but precision and discipline help it shine through bull and bear markets. Teragon plans to answer the following questions to assist investors in getting high returns with less risk:

  • What qualifies as a dip?
  • What entry price should I be looking for?
  • How much of my portfolio should be allocated?
  • When and how much will I sell?
  • Can I get yield on my free capital?

We believe that automated quantitative, rule-based investing is the best way to achieve consistent results over time.

In this article we will describe a systematic balanced strategy which will answer the above questions. This allows one to automatically buy low and sell-high, known as longing gamma, while maintaining target allocations between yield and growth. The long term results indicate a close correlation with holding Bitcoin through one of the greatest bull markets in history with significantly reduced drawdowns and volatility. Backtesting indicates the strategy will handily outperform holding BTC through prolonged market stagnation, crashes, or choppy periods.

The entire process is automated — simply pick a strategy, make a deposit, and watch your portfolio grow! The following section will show the basic process along with a walkthrough of some examples following price action. Results are shown in section three.

2. How it Works

The rules of this example balanced strategy are simple:

  1. There are only two assets involved in the first example — a stablecoin like USDC and BTC for growth.
  2. The strategy allocates 50% of the capital in stablecoins, and 50% in BTC, so that

3. The portfolio rebalances each month at the time of futures and options expiry if the following equation is satisfied:

BTC is the largest coin by market capitalization with a capped supply and very low inflation, accounting for roughly 40% of the total market cap of crypto (as of May 2022). We use this as a proxy for crypto growth for the purpose of our backtest.

We invest only half of our capital in growth assets and keep the rest in non-volatile stablecoins for yields that serve as free capital during market drawdowns.

An example with only BTC and USDC will illustrate the strategy clearly:

In the above example we bought after a 20% correction from our initial investment, so we are implicitly considering -20% to be a dip. But what if the market goes down only 10%?

Following the equation, we can see that we would not rebalance:

The equation also takes profits during rebalancing when markets rally. Let’s see what this looks like with another example:

We have presented the base model for a balanced strategy with only one volatile asset, but this strategy can be generalized to a portfolio where there are many assets in varying proportions according to risk profile.

Let’s illustrate this by adding ETH to our portfolio.

Bitcoin and ETH typically move together, though ETH is known to be more volatile. We will use 25% of each to keep things simple.

Now our planned allocations are:

Let’s look at the dynamic of our portfolio in our next example.

Portfolio rebalancing occurs once per month to reduce volatility exposure, impact of price spreads (the difference between a buy and a sell), and trading fees. The day of the month is chosen to match futures expiry and has a marginal impact on overall performance.

The parameters of the automated strategy cause it to buy low and sell high for us in a simple and systematic way. Our portfolio will grow over time using this approach. The stablecoin portion of the portfolio has two main purposes: it acts as a stabilizer to the portfolio and as a cash reserve, giving us the possibility to buy when the market corrects. The results of our testing indicate a 60/40 BTC/cash portfolio performs as well as or better than a 100% BTC holder with much less volatility!

The following data includes additional conservative strategies that can be deployed to earn yield on stablecoins in DeFi. This usually involves providing liquidity (letting other users swap between stablecoins) or lending. We can put our spare cash to work while waiting for monthly rebalances.

3. Backtesting and Results

3.1. Methodology

Market prices for Bitcoin and Ethereum from Coinbase were used, which provide prices starting from 2016.

We also downloaded daily rates from DeFiPulse, which contains historical data for lending rates on three of the major money market protocols in DeFi: Compound, Aave, and CREAM Finance.

Data from DeFiPulse contains the daily annual percentage rate (APR) for lending assets on their platforms. The mean of the three given rates was used to approximate stablecoin yields.

The highest APR in the historical dataset is around 10%, but over the last year, yields on stablecoins have been considerably higher.

Our simulation starts on 3 March 2020 and ends on 30 June 2022, comprising more than two years of data.

The cash parameter was optimized from a 50/50 portfolio to 60/40 (BTC/cash). More conservative holdings performed poorer in this historic bull market than more aggressive ones. They will provide more safety during market corrections.

We determined the strategy with an allocation of 40% in stablecoins as having the best risk-adjusted return.

3.2. Results

In this section we compare the performance of BTC and the balanced strategy through various statistics. This chart shows the example strategy with 60% capital in BTC and 40% in stablecoins earning 10% APR. Note the endpoint (or total return) is nearly identical.

  • March 2020 — June 2022

The table below breaks down the overall performance of holding all capital in BTC versus the balanced strategy. The balanced strategy performs similar to Bitcoin in absolute terms, but outperforms in risk-adjusted terms. Drawdown sustained by the balanced strategy is markedly lower. The Sharpe ratio measures reward versus risk taken (higher is better). Over the period, Bitcoin almost doubled in price. The balanced strategy was able to perform near parity while being underleveraged. During these drawdowns, lacking cash, people tend to reduce risk at the worst possible times. The balanced strategy is able to take advantage of lower prices while always maintaining a healthy cash cushion. This boosts performance in the long run.

More insight can be gained from looking at periods of large price action to the upside and downside:

  • November 2020 — February 2021

This was a period of parabolic growth for Bitcoin and, as we might expect, the balanced strategy fell behind in performance and risk-adjusted terms. The absolute performance was 228% for Bitcoin and 121% for the balanced strategy with Sharpe ratios of 4.6 and 4.3 respectively.

But the balanced strategy experienced a contained max drawdown of -19.7% compared to that of Bitcoin at -25.2%.

This protection is more clear by looking at a period with a move to the downside:

  • January 2022 — June 2022

The absolute performance of Bitcoin over this period was -50.1%, while the balanced strategy returned a much less scary -24.5%. The Sharpe ratios are -2.13 for Bitcoin and -2.1 for the balanced strategy. Considering every other risk adjusted metric, the balanced strategy shines.

4. Conclusion

BTC and the crypto market as a whole have experienced tremendous growth in recent years. Many investors buy during market run ups but have trouble holding through long periods of steady declines and stagnation. Teragon’s algorithms aim to fix that by profit taking during moves up with limited exposure to drawdowns during corrections and bear markets.

The entry level strategy shown here provides those benefits without the need to be actively managed. It allows one to effectively long gamma by buying low and selling high using a few easy to understand parameters that increase returns while reducing risk.

Much of one’s portfolio is holding cash due to the nature of the strategy. This allows the opportunity to earn additional yield using DeFi while still having free capital to buy during market corrections to maintain growth.

--

--

Teragon
Teragon.io

Teragon creates novel strategies by marrying traditional investment literature with the world of DeFi