EquBot

Founded by Chida Khatua, Art Amador and Chris Natividad in 2017, EquBot uses a proprietary AI-model and IBM's Watson to manage exchange traded funds (ETF), AI Powered Equity, and AI Powered International Equity. EquBot is part of the 'Startup with IBM' program which involved their AI model with IBM's Watson. Their AI-model and Watson allow EquBot's ETFs to manage over a million data points a day and perform similar to a team of 3,000 researchers working around the clock.

The AI Powered Equity Fund ETF (AIEQ) was introduced to the market on October 18, 2017. The Fund focuses on the broader US stock market. AIEQ is the first ETF to leverage AI for stock selection. Traditional funds and traders are beginning to use AI for stock advice, but few, other than AIEQ, use AI for stock selection with limited human interference. AIEQ's AI is able to analyze over a million points of data in a day. These data points include SEC filings, earning reports, news stories and social media posts. The analyzed data works to build models and projections of those companies. Companies which fit AIEQ's risk and profitability profile are included in their fund. EquBot co-founder Art Amador said in interview with CNBC:

The idea is to recognize patterns across management teams, across financial statements, across news [and] things like social media, to identify trends that are occurring in the marketplace and capture the companies that are going to appreciate the most over the next six to twelve months.

AIEQ currently has $117.21 million in assets under management. The funds average daily trading volume is $979.92 thousand.

The investment fund aims for long-term capital appreciation. AIEQ maintains risk constraints to match the risk and growth of the broader US equity markets. The fund invests in companies which, based on their analyses and modelling, show good probabilistic growth with minimal risk indicators and low volatility. AIEQ works to balance its portfolio across industries and sectors to reduce the volatility of individual sectors.

AI allows the fund to outperform human researchers in volume of research and modelling. The AI further protects the fund against human error and human bias. Both are cited as major reasons traditional ETF's fail to perform to market norms.

AIEQ holds around 130 stocks at a given time. None of these exceeds their top asset – Alphabet Inc. – at 3.55% to avoid concentration risk. AIEQ lists and regularly updates their list of their 130 holdings.

ETF Managers Group LLC, out of New Jersey, act as adviser to AIEQ. Equbot LLC act as sub-advisor. ETF Managers Group LLC are responsible for overall management of the fund and subject to oversight by the Shareholders Board. EquBot, in their role as sub-advisor, are described as a provider of investment advice. Neither of these advisers, though listed as management, interfere with stock selection or veto stock selection. Rather, as part of machine learning and deep learning, they provide guidelines and allow EquBot's proprietary AI-model and IBM's Watson to learn and grow.

Samuel R. Masucci, III, Chief Executive Officer of ETF Managers Group LLC has managed AIEQ since January 2018. James B. Francis, CFA, Chief Investment Officer and Senior Portfolio Manager of ETF Managers Group LLC has managed AIEQ since May 2018. Devin Ryder, Portfolio Manager of ETF Managers Group LLC has managed AIEQ since May 2018.

AIEQ has a current fund rating of BBB (The ratings scale from CCC to AAA) with a score of 5.34 out of 10 as rated by MSCI ESG. This ranks AIEQ in the 48th percentile in its peer group. AEIQ ranks in the 44th percentile in the broader universe of funds covered by MSCI ESG.

In 2017 and early 2018 AIEQ learned what an equity fund was and what that meant. Although neither Chida Khatua or Art Amador have detailed what "learning to be an equity fund" details, AIEQ's early performance was poor. In 2017 and early 2018, AIEQ failed to match the S&P 500, the benchmark for many index and equity funds.

During this period – October 18, 2017 to September 30, 2018 – the fund's portfolio turnover rate was 260%. This compares to S&P 500's annual turnover rate of around 3.1%. AIEQ is an actively managed fund, compared to the S&P 500 which is an unmanaged fund, and should have higher turnover rates. But high turnover rates lead to high transaction costs which make a fund more expensive to hold.

During early 2018's downturn, the S&P 500 lost 6% compared to AIEQ's loss of 16%. During this period, AIEQ sold six of its top ten holdings which went on to outperform the S&P 500. Holding these positions would have put AIEQ ahead of the index.

However, Artificial Intelligence is able to learn from it's mistakes without falling into the human pitfall of ego-recover. And all signs point to AIEQ's learning.

By October 2018, AIEQ was up 11.81% on the S&P 500 and outperformed 87% of active managers. AIEQ achieved this result by buying relatively small or unknown companies who performed well. Ten of AIEQ's top performing fifteen holdings were too small to be in the S&P 500 index. AIEQ continued this performance through 2019 where it has grown 19% against S&P 500's 17%.

AIEQ's stock selection, from small stocks providing big gains in late 2018 has changed to larger companies holding key positions in its portfolio. Many of these holdings, such as Alphabet Inc, Amazon, Intuit and Brown-Forman have provided the fund greater stability. Whereas its holdings in companies such as Coupa Software – which is up 117% by mid 2019 – has fuelled its growth.

AIEQ's holdings in Q3 2019 are weighted towards technology, financial and health care sectors. This leaves traditionally defensive sectors such as utilities and real estate with light allocation.

Some analysts, such as Sarah Ponczek writing for Bloomberg, warn against judging AIEQ by its 2019 success. The markets in 2019 have been on historic highs making it relatively easy for funds to perform well. Although it remains equally easy for funds to perform poorly. Sarah Ponczek cautions investors to wait almost ten years before AIEQ and AI-drive stock selection can be properly judged a success or a failure.

Although it's yet to be known if two suits out against ETF Managers Group LLC (ETFMG) will impact the management fee of AIEQ, there are a few ETF's in ETFMG's portfolios which have seen increased management fees to cover legal costs. ETFMG has included a brief statement outlining both cases on the front page of AIEQ's Prospectus.

On January 19, 2018 PureShares suit against ETFMG was dismissed. PureShares sought damages in unspecified amounts and injunctive relief based on breach of contract, wrongful termination, defamation and emotional distress. The suit started in a decision on behalf of ETFMG to reduce a funds expense ratio to make it more competitive. Nasdaq protested the fee change, but ETFMG elected to go through with the change regardless. During the change, they rebranded PureShares' and PureFunds' ETF's under ETFMG's name. The suit was dismissed for failure to provide documentation on the part of Pureshares. PureShares CEO Andrew Chanin plans to revive the litigation and ETFMG on their Prospectus lists the suit as open and ongoing.

Nasdaq filed against ETMG over the PureShares litigation. Nasdaq accused ETFMG of failing to turn over profits from their ETFMG Prime Cyber Security ETF (HACK). Nasdaq also accused ETFMG of breaching a wholesaling agreement by hiring ETFMG Financial, an affiliate owned by ETFMG CEO Samuel Masucci, III.

Presented to the exchange in June 5, 2018 by EquBot, AIIQ has the same model as AIEQ and has faced many of the same challenges as AIEQ. The major differentiation between the two exchange funds is their portfolio focus: AIEQ focuses on US based companies whereas, as its name implies, AIIQ focuses on International companies from developed and stable countries, such as South Korea and Canada.

Unlike AIEQ, AIIQ is solely managed by EquBot Inc. Their sub-advisor is Vident Investment Advisory who manage the day-to-day management of the fund based on the recommendations and information provided by EquBot.

On June 10, 2017 EquBot completed their seed funding round with $335,000 in funding from Multiple Angels, Moe Khosravy, and Greg Flat. At the time of receiving their seed funding EquBot had a pre-money evaluation of $6.5 million.