Connect with us


Do Algorithms Make Better — and Fairer — Investments Than Angel Investors?



Cactus Creative Studio/Stocksy

Many large venture capital funds use artificial intelligence (AI) to support their investment decisions. Bill Maris, managing partner at Google Ventures, once said that when you “have access to the world’s largest data sets … it would be foolish to just go out and make gut investments.”

Most startup investors, however, do not have access to Google-esque resources and still do things the old-fashioned way. Angel investors, for instance, rely heavily on gut feeling to make investments. But as technology advances and the cost of building powerful algorithms through machine learning decreases, these investors will need to decide whether to incorporate AI. Can it outperform human judgment in making early stage investment decisions? And how should angel investors use it?

To answer these questions, we built an investment algorithm and compared its performance with the returns of 255 angel investors. Utilizing state-of-the-art machine learning techniques, we trained the algorithm to select the most promising investment opportunities among 623 deals from one of the largest European angel networks. The algorithm’s decisions were based on the same data that was available to the angel investors at the time, which included pitch material, social media profiles, websites, and so on. We used this data to predict a startup’s survival prospects — instead of measures such as valuation, which investors often favor — because it allowed us to train the algorithm with a much larger and more reliable dataset.

For our test, we used this prediction model to simulate investments and to compare the returns of the angel investors’ portfolios against the ones that were created by the algorithm. We further investigated how angel investors of varying experience — novices with fewer than 10 investments vs. expert investors with at least 10 investments — faired relative to the algorithm’s performance. Expert angel investors in our sample, on average, made about twice as many investments as novices (12.2 vs. 5.2) and invested double the amount per startup (€10,530 vs. €4,548).

Insight Center

  • AI and Equality
    Sponsored by SAS

    Designing systems that are fair for all.

The results were striking, and offer significant insight into how — and when — algorithmic investing tools might be used to maximum advantage. According to our research, novice investors are easily outperformed by the algorithm — with their limited investment experience, they showed much higher signs of cognitive biases in their decision making. Experienced investors, however, faired far better. As such, our research shows how biases shape the decisions of human investors — and how working with algorithms might help produce better and fairer investment returns.

The Algorithm vs. the Angels

It has been well documented that cognitive biases — meaning systematic deviations from rational behavior — lead to inferior investment performance. We measured five biases: 1) local bias, which describes angel investors’ tendency to make investments that are in close geographic proximity to themselves; 2) loss aversion, meaning angel investors’ tendency to be more sensitive to potential losses than to potential gains; 3) overconfidence, when investors “overcommitted” and spent significantly more money on one startup that they usually would; 4) gender bias; and 5) racial bias. Our data shows that all biases were present among the angel investors with overconfidence — which 91% fell prey to at least once — being the most frequent and strongest bias to affect investment returns.

Because cognitive biases cause investors to make irrational investment decisions, it is not surprising that our investment algorithm outperformed the human average. While the algorithm achieved an average internal rate of return (IRR) of 7.26%, the 255 angel investors — on average — yielded IRRs of 2.56%. Put another way, the algorithm produced an increase of more than 184% over the human average.

Not all investors are equally susceptible to their biases, however. For instance, angel investors with lower signs of irrational behavior in their portfolios performed significantly better than their rather irrational counterparts: the less biased novice group averaged 3.51%, whereas the novice group with higher biases, on average, lost money at -20.52% IRR.

Intrigued by these results, we investigated whether the algorithm would win even when the investors were highly experienced. What we found is that experienced angel investors showed far fewer signs of cognitive biases and therefore achieved significantly better investment returns. This elite group of experienced angel investors achieved an average IRR of 22.75%. Experience alone, however, does not do the trick: Investors who had a good deal of experience but also showed high levels of cognitive biases achieved, on average, only 2.87% IRR. Our results thus show that only experienced investors who can suppress their cognitive biases effectively outperform machine learning algorithms in making early stage investment decisions.

There was one other factor we found to be at play, which may give algorithms an edge. Achieving higher portfolio returns in venture investing has two sides – protecting the downside and increasing the upside. A central thesis and the main focus of venture investing has always been to find statistical outliers (i.e., “unicorns”); our study, however, gives reason to rethink this central investment hypothesis in angel investing. By predicting survival probabilities, the algorithm was able to pick much better portfolios than the large majority of the 255 angel investors. As such, our data suggests that in the greater scheme of things, it might actually be more important to avoid a bad investment than to try to hit a home run. Given their limited funds, angels only invest in a finite amount of ventures and must, therefore, take great care with each investment. Therefore, asking “is this a viable business with very high chances of survival?” might be more valuable in achieving higher portfolio returns than searching for the needle in the haystack.

Does Better Also Mean Fairer?

There has been ample discussion about whether algorithms are biased by their creators. In our case, the outcomes in the training data were not classified by humans directly (compared, say, to hiring algorithms, where humans decide who has been a good hire in the past). The algorithm was trained on actual survival and performance data of hundreds of ventures. Given this high degree of objectivity, we see that compared to the average investor, the algorithm’s portfolio selection was less influenced by classical investment biases such as loss aversion or overconfidence. That doesn’t mean it didn’t show bias, however. We were surprised to see that the algorithm did tend towards picking white entrepreneurs rather than entrepreneurs of color and preferred investing in startups with male founders.

Given these specific results, we can say that the current controversial discussion around biased algorithms that are being blamed for making unfair decisions is overly simplistic and misses the underlying problem of inflated expectations. Machine learning models are frequently trained to discriminate between different decision alternatives, e.g., good or bad early stage investments. AI itself is, per default, not irrational or biased; it just extrapolates patterns that exist in the real world data that we give it to learn and to exploit these patterns in order to distinguish between the potential decision alternatives.

Thus, AI may be able to counter the flawed decision-making processes of individual investors with low investment experience, e.g., it may help correct investors that overestimate their ability to assess the risk of a given investment. However, using AI as a means for fighting societal inequalities is more challenging. Although all data sources were objective and free of human judgement in our case — and the algorithm was not fed race and gender data — it still came to biased decisions. But the algorithm itself did not make biased decisions; it reproduced societal inequalities that were inherent in our training data. For example, one of the most important factors on which the algorithm based its predictions was prior funding that the startup had received. Recent research shows that women are disadvantaged in the funding process and ultimately raise less venture capital which may lead to their startups not being as successful. In other words, the societal mechanisms that make ventures of female and non-white founders die at an earlier stage are just projected by the AI into a vicious cycle of future discrimination.

Importantly, our results indicate that consciously debiasing decisions for race and gender might increase not only fairness, but also performance of early stage investment decisions. For instance, we found that experienced investors that invest in ventures of non-white founders systematically outperformed our algorithm. Thus, these experienced investors made successful investment decisions that were free of the implicit patterns of discrimination that undermined the results of our algorithm. In general, there is always a tradeoff between fairness and efficiency in resource allocation. This tradeoff is also apparent in algorithmic decision making. We can never expect AI to have a built-in solution to automatically solve societal problems that are inherent in the data that we feed it.

A Hybrid Approach

Our research underscores the advantages of using AI in early stage investing. It can process large amounts of data, correct individual investment biases, and, on average, outperform its human counterpart. At the same time, the most successful individuals — experienced investors able to correct for their cognitive biases — outperform the algorithm in terms of both efficiency and fairness.

Of course, this doesn’t have to be a binary choice between gut feeling and algorithmic decisions. Managers and investors should consider that algorithms produce predictions about potential future outcomes rather than decisions. Depending on how predictions are intended to be used, they are based on human judgement that may (or may not) result in improved decision making and action. In complex and uncertain decision environments, the central question is, thus, not whether human decision making should be replaced, but rather how it should be augmented by combining the strengths of human and artificial intelligence — an idea that has been referred to as hybrid intelligence.

Artificial intelligence in the loop. Our research shows that algorithms could help novice investors in making early-stage investment decisions. To start angel investing with the help of an algorithm enables novice investors to avoid decision caveats and thus to achieve higher returns early in their investment career, which encourages them to continue investing. Angels who keep investing provide important resources to an ecosystem that fosters job creation and innovation. Therefore, we see lots of potential in investment algorithms to train novice investors in making expert-like decisions that result in improved financial returns.

Human intelligence in the loop. For more experienced angel investors who have learned to manage their cognitive biases, our findings show that their intuition should still be considered the gold standard of early-stage investing. So, algorithms should not only be trained on “objective” past performance data that easily reproduce societal biases, but also on the decisions and actions of these selected decision makers. Therefore, at same time, we see potential in experienced investors to train investment algorithms to make better and fairer investment decisions.

In the end, despite AI is rapidly entering the financial markets, best-in-class early-stage investments are still dominated by experienced angel investors. The key to building an investment algorithm that can ultimately replace even the most experienced angel investors in making their investment decisions does not only lie in counteracting human biases but also in mimicking experts’ intuition in finding the most promising investment opportunities.

Source:- Harvard Business Revi

Source link

Continue Reading


The Biggest Investment Opportunity for Americans Is China, Bridgewater’s Karen Karniol-Tambour Says – Barron's



Karen Karniol-Tambour

Franco Vogt


Director of Investment Research,

Bridgewater Associates

Westport, Conn.

Karen Karniol-Tambour, director of investment research at Bridgewater Associates, the worlds’ largest hedge fund, is known for idea generation. Her boss, Ray Dalio, once likened her to a “vacuum cleaner of learning.” At 35, Karniol-Tambour is one of the youngest and highest-profile women on Wall Street.

Barron’s: What trends will dominate the investment world after the pandemic?

Karen Karniol-Tambour: When you get to a point where interest rates are zero and you’ve already printed a lot of money, the most valuable thing you can do to get the economy moving is what we call Monetary Policy 3, or MP3: You need to have coordinated monetary and fiscal policy. They can be extremely effective together, but there are huge implications for investors.

The most important mechanism that underlaid everything in the past 60 to 70 years was that monetary policy worked through interest rates. Now it doesn’t. The most direct implication [relates to] asset allocation. The standard investor owns a stock/bond portfolio that’s something like 60/40. Historically, most of the risk was in stocks, and bonds were a growth diversifier. If growth slowed and the market underperformed, you had the backstop of monetary policy; lower rates meant that bonds would perform well. That basically stops working when bond yields are so low that they can’t fall much further to offset a large decline in stock prices.

What offers the best diversification today?

[Central-bank policies] will create enough liquidity that assets such as gold and inflation-linked bonds will probably still be good to hold. And if they do well and succeed, then stocks will do great, so you don’t have to worry.

What does more fiscal spending mean for investors?

The fact that the U.S. election resulted in less of a Democratic majority in Congress and a Democratic president would have mattered so much less at any other point in history. Now it is extremely important because the ability to get legislation passed is so important if fiscal policy is more important than it has been in 70 years. Politics matters more to the market because fiscal policy is the most powerful lever. There are also structural reasons [for politics to matter] if we look at the global competition with China. So much of what drives China’s economy is [government] policies—and a top-down industrial policy. It is hard to see how that doesn’t permeate other countries.

Are you suggesting the U.S. will move toward a government-directed industrial policy?

It may not happen in five years, but there will be a shift in how the U.S. and Europe stay competitive, and a realization that it means more government involvement in industries and technology. Competitiveness policies will have to matter more to the market in the next five years.

China’s new five-year plan came out around our election. What they are saying about dual circulation [an economic strategy that emphasizes increased domestic demand, self-reliance for high-tech goods, and selectively opening up the economy to foreign companies] is very important for investors to understand. They are saying they are going to think about whether their domestic ecosystem is self-sustaining. [They] aren’t giving up on their second ecosystem of exporting abroad. They are thinking more holistically. That is a bigger competitor and competitive ecosystem than the U.S. has faced since World War II. It’s a game changer, and hasn’t been internalized by investors.

What will be the greatest investment opportunity post-Covid?

Diversifying into China. In five to 10 years, unlike during the Cold War with the Soviet Union, investors can have a stake in both sides. You can say, “I’m sure the U.S. is going to come out on top no matter what, and U.S. technology will be better, and that’s where the growth is,” or you can say, “Why would I take that risk? I would much rather be diversified.” It’s a fundamentally different economy that runs on its own clock because it has its own monetary and fiscal policy.

Yet, there are measures under consideration here to restrict investments in China.

It is hard to stop that floodgate because every investor in the world wants to be diversified. China’s markets are so big—it has the second-biggest stock market in the world, the second-biggest bond market—and that’s not even reflective of how big an economy it is. Sure, government pension funds may never be diversified, but for many other investors it will be the sensible pathway. As for financial-system risk, the Chinese are particularly well placed to handle it because everything they own is in their own currency and their regulatory arms are extremely strong.

What is the most important public policy issue the U.S. will face post-Covid?

Can we get past partisanship and get things done? The U.S. benefits from having strong institutions. Will that be the case over the next 10 years? If in 10 years we are sitting here and saying we can’t get anything done, no matter who we vote for, how much will that erode America’s ability to be a leader in ways that matter to markets?

What kinds of stocks will investors be talking about in five to 10 years?

Everything digitized will be priced in. What will be new will be whatever companies Europe and the U.S. are supporting for strategic, competitive reasons—and there will be a continued acceleration into companies that solve issues like climate. As everything becomes more digital, there will be more revenue with fewer employees. We also don’t know where employment will be in 10 years, and if it will be through some universal basic income.

What longer-term scars will Covid-19 leave on investors of your generation?

I suspect Covid will have left us with a sense that really unexpected things outside of the main analysis can happen. Studies of pandemics pre-Covid would have concluded that the vast majority don’t have a big impact on the market. Hopefully, this [crisis] will impact our generation’s thoughts on climate change. There are a lot of scenarios in which climate change isn’t a particularly big deal, and there are tail risks. We will be more comfortable looking at tail outcomes.

You look at a huge amount of data. What will be the more relevant data points in the future?

Gross domestic product has been a good proxy of human well-being. If GDP slows, there is misery and policy responds. There is a recognition that we are at a turning point in wealthier countries where it’s not as good a proxy, whether because of inequality, quality of life and education, or pollution. If you look at the past 20 to 30 years, we have had good GDP outcomes, but the main quality-of-life outcomes aren’t rising. I can imagine a future, to take an extreme, where pollution stats are a big market driver because as soon as you see them, you will think, we need to shut down factories or provide stimulus [if pollution measures are bad.]

How else will investing change?

There will be more investing that tries to achieve goals beyond profits, and thinks about how we are affecting the planet. In the U.S. there has been more shyness in saying clearly, “I care about having impact with my money.” There is more comfort [about that] in Europe. I think that will accelerate.

You have spent part of the pandemic in Israel. What is the one place on Earth that you’d most like to visit when the pandemic ends?

I’m really curious to see India postpandemic.

Thanks, Karen.

Show names

Select a person to go to the profile.

Share your thoughts on the post-pandemic world: What do you think will be the greatest investment opportunity post-Covid? What will be the most important public policy issue that the U.S. will face? Where would you most like to visit once the virus is no longer a threat to travel? Click here to share your thoughts with us.

Write to Reshma Kapadia at

Let’s block ads! (Why?)

Source link

Continue Reading


Climate Change Is the Biggest Investment Opportunity Post-Covid, the CEO of RockCreek Says – Barron's



Afsaneh Beschloss

Simon Dawson/Bloomberg


Founder and CEO, RockCreek

Washington, D.C.

Afsaneh Mashayekhi Beschloss, founder and CEO of RockCreek, has a history of spotting investment trends early. At the World Bank, she invested in clean energy decades before climate change was a global priority. An Oxford-trained economist, Beschloss, 65, also held senior roles with


and the

Carlyle Group

before founding Washington, D.C.-based RockCreek in 2003. Today the firm manages $15 billion on behalf of pensions, endowments, and foundations, with a focus on multi-asset, sustainable, and emerging-markets strategies.

Barron’s: What will be the greatest investment opportunity post-Covid?

Afsaneh Mashayekhi Beschloss: Climate. It is going to be huge in terms of investments—both in the move toward efficiency and making sure systems are such that they less gas gets into the environment—and everything related to water and energy. The private sector is going to lead. Companies are moving toward clean energy because they know it’s not just regulation; it’s their consumers [demanding it].

With the amount of interest even today in solar energy, there aren’t enough service companies producing parts for wind and solar [energy]. We will see growth in the next three to five years, and those are [areas] that are more job-creating. A World Resources Institute study found that for every $1 million you spend on [clean energy], you create more than two times as many jobs as when the money is spent in traditional energy.

RockCreek had been investing heavily in education, including distance learning; biotech and telemedicine; and renewable energy. What investment trends will we be talking about in the next five to 10 years?

The pandemic put on a different slope a lot of things, particularly biotech and health. The technology to develop [a vaccine] faster is also being directed to other medicines. In five to 10 years, in emerging markets, the health sector, which has grown from 1% to 3%-4% [of GDP], will probably be closer to 10%. We have been making direct investments and co-investing with venture capital in both health-care delivery systems and biotech. Also, the delivery of education will be different. With around 45% of the world not having access to the internet, governments will have to provide more of [the digital infrastructure], and that means investing in the delivery system for the internet for that last mile.

How will ESG investing evolve?

There will be a lot more businesses run by black and brown people and women in five years. Covid and the recent U.S. election are going to accelerate the trend. Sustainable and ESG investing will be mainstream in public and private investments.

What is the most important public policy issue the U.S. will face post-Covid?

The biggest risk to our system is education. Investing in education is key if we don’t want to lose our edge in innovation.

How should investors think about diversification?

Bonds offer no return in the next five to 10 years. Governments are encouraging companies to take on more loans. The International Monetary Fund is encouraging countries to take on more loans. At all levels, there’s more leverage. The risks that investors are taking are around leverage, credit, and illiquidity—and they aren’t measuring them well enough. It’s one thing if private equity is 10% of a portfolio; if it is 30%, that’s very different.

What will investors need to own to boost returns in the future?

Think about the 10 largest companies 10 or 20 years ago. What will they be in 10 years? We know they will be different.

Exxon Mobil

[XOM] has shown it won’t be one of the largest companies in the next five years because it didn’t invest in renewables in the way that


[BP] and

Royal Dutch Shell

[RDS.B] have. Energy has gone from 10% to 3% of the

S&P 500


Now, it will be about technology—its use in education, health, cities, buildings, and energy. Those will be the jobs of the future. If you are an investor and don’t continue to find the companies of the future, you will be left behind. The speed of innovation is going to increase. That’s a risk because a lot of big institutional investors haven’t been oriented toward venture [capital].

You have long focused on emerging markets, an asset class now dominated by China, North Asia, and India. Should EM investors cast a wider net?

China and North Asia should be their own group. You have to look to frontier markets and countries like Vietnam. India will be very interesting; Eastern Europe and Latin America will be interesting. I worry about Africa because a lot of the attention to [it] went away during Covid and a lot of debt that African countries owe is to China.

How will investors approach China in five years?

You can’t not invest in China. The [renminbi] could be not a reserve currency but a more important currency to hold in your portfolio. It will be more common for 30% to 40% of a portfolio to be in [different] currencies rather than [fully] hedged in the next few years because of the size of our debt versus other countries.

Our focus has been on companies that benefit from local growth. If there are restrictions from the West [on Chinese technology], it won’t affect local companies and trends. Companies that are highly political, or defense or state-owned enterprises, or telecom-oriented, could be tricky. In five years, I think government restrictions will be replaced by investor restrictions—similar to investors who don’t want to own stocks of private-prison companies now.

What is the one place that you’d most like to visit when the pandemic ends?

That is really hard. I really would love to be in Europe.

Thanks, Afsaneh.

Show names

Select a person to go to the profile.

Share your thoughts on the post-pandemic world: What do you think will be the greatest investment opportunity post-Covid? What will be the most important public policy issue that the U.S. will face? Where would you most like to visit once the virus is no longer a threat to travel? Click here to share your thoughts with us.

Write to Reshma Kapadia at

Let’s block ads! (Why?)

Source link

Continue Reading


Funding the fight against global warming – Investment Executive



It finds that meeting the commitments made under the Paris Agreement to limit global warming will require a fundamental transformation of the global economy, requiring much greater investment.

The overall estimate of US$100-trillion to US$150-trillion worth of new investment translates into at least US$3 trillion to US$5 trillion of investment per year, which would be between five and eight times higher than current levels, the report said.

To generate this sort of investment, “the price of carbon must rise to fully price in emissions,” it suggested.

Moreover, the report said that climate finance needs aren’t linear, meaning that a lack of action now will translate into even greater investment needs in the future.

Given the scale of the challenge, the report called for coordinated action by the government and the private sector to significantly grow the climate finance market, with a view to developing the financial and risk management tools that are needed to catalyze investment.

“The unprecedented call to action aims to help mitigate substantial mis-pricing and potential financial stability risks which would undermine the long-run ability of the financial system to direct finance to fully support the Paris-aligned transition,” the GFMA said.

The paper also sets out the role for capital markets firms and other market participants to facilitate the transition, while continuing to serve investors and clients.

“[T]o meet the targets set out in the Paris Agreement, we need to act quickly to build a high-functioning market structure that can facilitate a significant increase in the level of investment in the climate transition,” said Steve Ashley, GFMA chairman and head of the wholesale division at Nomura, in a release.

“It’s important to note that, while the banking and capital markets sector stands ready to facilitate change, we need the support of policy-makers and the wider private sector to create the incentives to make this work,” he said. “We hope this report will act as a call to action.”

Let’s block ads! (Why?)

Source link

Continue Reading