Arbitrage Trading: How Hedge Funds Should Use AI Based Algorithms For Arbitrage Trading

The article was written by David Shabotinsky, a Financial Analyst at I Know First, and enrolled at an undergraduate Finance program at the Interdisciplinary Center, Herzliya.

Arbitrage Trading

All things excellent are as difficult as they are rare.”-Benjamin Graham, The Intelligent Investor

Free lunch, or riskless profit. The idea seems theoretically impossible, as any intro economics course will explain that free lunch is impossible. This article will come to explain; why seemingly riskless strategies should incorporate AI based algorithms.

Summary:

  • Arbitrage opportunities are hard to locate but knowing which types exist can help investors watch for them
  • Hedge Funds today too many errors for the high costs that accompany them
  • I Know First Algorithm’s competitive advantages and usage in the market can subsitute/assist hedge funds
  • Barrier of entry for algorithmic trading firms

Within the realms of finance other theories, such as The Law of One Price, dictate that the price of a security, commodity or another asset will have the same price after exchange rates. It as well goes further in explaining that one should not be able to profit, for example, from bond stripping T-bills and buying/selling coupon bonds.

Arbitrage Trading

However, opportunities to buy and sell two of the same instruments simultaneously in two different markets, and profit, exist. The most prominent investors who perform such market actions are hedge funds.

Essentially, what arbitrate entails, is if a security is trading in two different markets simultaneously, with different prices. The arbitrageur can then lock in the ‘difference’, by shorting the higher price and buying long the lower priced one, simultaneously. As a result of globalization and currency pegging, arbitrage has become much more complicated to capture in its original form. Many individuals today as well consider other forms of arbitrage outside the financial market, such as drop shipping arbitrage and/or international trading. The first involves taking advantage of the price disparity in different e-commerce sites, more notably between EBay and Amazon, of which one buys a good off of one and immediately sells the good off the other site, profiting the price difference. The seller as well saves shipping fees, as he/she simply ships the good they bought off of the first site to the address they sold from the second site.

Today, Hedge Funds have advanced their technological and financial tools to search for arbitrage opportunities across financial markets.

For example, convertible bond arbitrage is a popular choice for most hedge funds today. Convertible bonds are those that firms issues that can be exchanged for equity. The aim of this strategy is to take advantage of the mispricing that occurs with convertible bonds. Normally, one would employ a delta-neutral hedging of which one buys the convertible bond (undervalued) and sells short the underlying equity at the current delta. This type of arbitrage specifically thrives a lot on volatility, as the easier, it is then to adjust the delta-neutral-hedge and book trading profits. Other popular arbitrages conducted amongst hedge funds are as well merger arbitrage (profiting from a parent company and target company) as well as fixed income arbitrage.

However, with advancement in technology and new financial instruments being used every day, more arbitrage opportunities are being revealed. Although ones such as ETF arbitrage are more simple, in that you buy/sell the actual underlying stocks in the basket of securities; other ones such as future vs. spot market- convergence arbitrage is one that requires more skill to capture and can easily be ruined.

In addition to ETF arbitrage, today, many arbitrageurs practice arbitrage through a futures market of a certain index. A futures contract, is a traded agreement for the buying/selling of assets, like securities and commodities, and it specifies and underlying quantity, a maturity, and a price.

The specific arbitrage is called Futures versus “Cash Market” (or “Spot Market”) Convergence Arbitrage. The cash market refers to an underlying stock basket, such as an ETF. The fair value being the difference price difference between the basket and futures contract, as all futures contracts converge at contract expiry to the price of the basket of stocks (for example in the S&P 500).

Arbitrage Trading

I Know First Algorithm’s competitive advantages

I Know First has a premium algorithm that incorporates why investors need to be able to achieve high returns with cost efficiency as well. The algorithm, was developed by Dr. Roitman, who has a vast 35+ years pf experience in the field of AI and machine learning. Every day, the self-learning and self-adjusting algorithm produces market forecasts with trends of stocks, commodities, and indices over 6 different time horizons ranging between a few days and a year. The kind of analysis and pattern recognition that the system does each day could never be accomplished by a human in any amount of time. On August 25, 2016, an article was published detailing the competitive advantages that directly apply to investors.  Through a mixture of chaotic system and efficient patterns found in the market, the algorithm is able to successfully detect trends to enable investors to understand entry and exit points in investing.

Through the data based machine learning, the algorithm is clearly able to find opportunities reduce risk through arbitrage opportunities. The main underlying problems that are associated with how the class hedge funds conduct their operations, is the inescapable human flaws (greed and fear) and operational costs. For example, earlier this year, during Brexit, many money managers had anticipated the UK to not leave and incorrectly applied data into their investment strategies. Moreover, even if money managers had correctly predicted the vote outcome, many fund managers, specifically technical analysts, had applied a ‘Castle In The Air Theory’, and bet they could make money off of others inability to accurately invest. Essentially, they had fallen into the trap that many investors do not cancel out the ‘noise’ of the financial market. This refers to short-term (daily or intra-day) fears, worries, and negative fueled perception regarding the price of a security or general market atmosphere.

Although there are hedge funds that solely focus on arbitrage strategies, they still underperform the S&P500 Index as whole, after fees. A large component to this is not just because they perform poorly as a result of the natural human error, but as well due to a poor investment culture and not a high conviction relative to the market. On average, most fund managers focus largely on short-term profits and too much on pleasing their own investors, by just following the Conesus of the market. This causes them to further propagate the Efficient Market Hypothesis (EMH), by not thinking differently than the general population and simply act like sheep that merely leverage the market as a tool to for profits. The successful minority are ones that have a strong conviction and focus on long term aspects. The AI-based algorithms are able to establish these focus long-term trends at a faster pace than humans are, and at a much lower cost, causing margins for users to expand greatly.

As expressed through the recent interviews, such as with Euro Money, I Know First’s AI-based algorithm clearly has advantages over other algorithms in today’s financial market.

Barrier of Entry

Although many see the hard facts in front of them, they refuse to change. There are those who simply refuse to acknowledge that algorithms or something man made can outperform its own ‘creator’. However, high-profile Wall Street fund managers, go further to claim that if there were algorithms that are successful that could easily be duplicated by the rest of the financial world, and soon be traded away. However, that logic fails to note the reason behind the rise and success of prominent active investors. A Large part of the success of investors such as Warren Buffett and Carl Icahn is that act differently than the rest of the market with a thought out strategy that is able to adapt with times. By having an Artificial Intelligence based algorithm that uses machine learning, one is able to capture the trends in the market and know how to adapt the investment strategy accordingly.

Conclusion

Throughout the past decade, new arbitrage trading strategies have emerged. As a result of market efficiencies with more technological advancement, locating these opportunities has become ever so challenging. Using AI based algorithms, has a proven track record of reducing costs and increasing returns. Although skepticism still remains amongst Hedge Funds, these barriers will become broken as culture dynamics shift in favor of adapting towards better investment strategies.

 


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