The rise and rise of artificial intelligence

The rise and rise of artificial intelligence

By Silvan Schumacher, founder and CEO of Swanest 

Robots are on the rise and will fundamentally impact our society. We are still far away from a human-like intelligence, but arrived at a state where machines become smarter than people in analysing huge amounts of data to find answers to very specific questions.

Considering that, financial services offer a perfect breeding ground for algorithms to flourish. Therefore, wouldn’t it be exciting to know where a robot would make its next investment bet? Let’s figure it out!

Making a robot to understand risk and return

To understand how a robot would place its bet, we use the example of the investment robot from Swanest.

First thing it needs to know is an exact question, so it can look for an answer. What we want to find are the assets that promise the highest possible return for a certain amount of risk we take. 

To illustrate, if there are two investments, first promises 2% return, the other one 4% and the risk of both is to lose 10% in the upcoming months, then the second option is clearly the winner.

However, if the second investment has a risk of losing 50% in the upcoming month, whereby the risk of the first option remains losing 10%, then the first option would provide a better return compared to the risk we take.

Now as we clarified what we want the robot to achieve, we need to teach him what risk and return actually is.

Traditionally, risk in investing is often associated with volatility. That means how much the price of an asset jumps up and down over time. As financial theories progressed, the assessment of risk got more refined. This resulted in so called multi-factor models. Hence, volatility does not remain the only factor in the analysis anymore.

For instance, the liquidity of an asset might be an additional risk factor to take into account. Liquidity simply means how easily you can buy and sell an asset in a market. Similar to a traditional market, you are very likely to find a buyer if the market is crowded. But in case of market stress, where people walk away from it, you might experience that it becomes difficult to find a buyer. Consequently, you start decreasing the price in the desperate move to find a buyer. At the end, you find yourself dumping the asset. This is additional risk that you want to take into account when analysing investment opportunities.

As you can imagine, there are more than two risk factors that modern financial models take into account. Our robot will consider the following seven indicators:

Risk and reward

Liquidity

Market capitalisation

Level of diversification

Ability to recover from losses

Length of the performance history

Highest losses in the past

 

The above provides our robot with a concept to measure risk. On the other side, we need to understand how to estimate future returns. This part is a bit more tricky. If we knew for certain what opportunity delivers the highest returns, then we would all be retiring on some beautiful islands already. There are, however, concepts that help us to approximate future returns.

 

The Capital Asset Pricing Model looks at the relationship between an asset and the market performance in the past and assumes such a relationship to be similar in the future.

To put it simply, if in the past the overall market collapsed by 50%, and our asset did so too, but only by 25%, then the model would assume that the value of our investment will collapse again in the future if the markets are diving, but only to half of its extent.

Certainly, such models are not perfect. On the one side, it is difficult to fully grasp risk, on the other side it might not always be true that assets react in a similar way to the market as they did in the past.

However, such financial models represent a good approximation of risk and return and can therefore serve as a basis to enhance someone's own decision making.

The robot’s favorites

To wrap up, we want to find the investments that promise the best returns for the risk we take. To find them, we thought a robot how to analyse risk and return. The final step is to provide him with a set of data to let him analyse and evaluate the opportunities.

In this case, we focus on stocks that are quoted on the New York Stock Exchange or on Nasdaq. To refine the results, we distinguish between stocks that represent large corporations and those that represent smaller businesses.

The winning large-cap stocks are:

MasterCard (MA)

NVIDIA (NVDA)

BroadCom (AVGO)

 

The winning small-cap stocks are:

2U Inc. (TWOU)

Inogen Inc (INGN)

Pinnacle West Capital Corporation (PNW)

 

What does that mean for you?

In general, the winners seem to have provided high rewards for the risk you took in the past, can easily be traded in times of market stress, recovered quickly from losses in the past, have been quoted long enough to assume that they will not suddenly vanish from the market and kept their highest loss in the past in check. Moreover, when markets were raising in the past, these assets tended to outperform other stocks. It is therefore that the robot concludes that these investment might promise good results in the future.

Be aware that robots are not able to take everything into account. For instance, they cannot assess the quality of the management, do not consider their vision and cannot look at megatrends.

Please be aware that the above does not constitute investment advice. Rather it shall illustrate how robots might take investment decisions.

Therefore, take the results with caution and enhance your own investment decision!

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