Quantitative Arbitrage Trading Strategy Analysis

In this literate review the most important papers about explaining stock returns from 1952, when Markowitz came up with Modern Portfolio Theory, till around 2011 will be discussed. As stated in Chapter 2, Jack Treynor was one of the first economists that started to work on the CAPM model. When he developed the CAPM in 1961, there was no way yet to fully test it. Because there were no samples large enough or of sufficient quality, the real testing of the CAPM started in 1970. In 1973, the world was shown the famous Black and Scholes options pricing model. One of the first studies that gave a different answer than the CAPM was the research by Basu (1977). While he agrees with the Efficient Market Hypothesis, Basu reaches another

One of the fundamental mainstays of financial economics is arbitrage. An arbitrage is the simultaneous purchase and sale of an asset to profit from a difference in the price. This is a form of trade that produces profits through the exploitation of the price differences of identical financial instruments on different markets in different forms (Reverre, 2011). Arbitrage is often referred to as risk free due to the fact that speculations are done on market movements by participants. As an alternative, betting is being done on the mispricing of a share/asset that has occurred between two related markets (Aarheim and Johnsen, 2013). Arbitrage therefore exists as a result of market inefficiencies. Randall (2006) also referred to Arbitrage as the

The stock market simulation game is an online game that teaches students how to invest their money. The game gives each student 100,000 dollars to start investing in different stocks. It was very important to diversify the money into different stocks, because a person does not want to spend all their money in one place. The game is played over a six weeks period, and in that six weeks we lost 8,832.53 dollars. We may have lost money; however, we invest into twenty-eight different stocks.

Investors tend to use triple-leveraged ETF to obtain triple the return yield of the investments. However, they are discouraged to invest on triple-leveraged ETF as the disadvantages overwhelm the advantages. One of the advantages of triple-leveraged ETF is that it gives three times the return whereas one of the disadvantages of triple-leveraged ETF is that it could lose triple of the tracked index. According to Cummans (2015), ‘The additional risks come in the form of counterparty risk, liquidity risk, and increased correlation risk’. Thus, ETF has higher risk as it may lose three times the return and increases bankruptcy rate. Result shows that the annual return to the triple-leveraged ETF is expected to be triple the annual return to the S&P 500 index, it is only applicable to theory where everything is in constant. In reality the tracked index fluctuating frequently, it will not be three times of the

LTCM’s board of directors included many geniuses in from the financial world, who collectively created complex models allowed them to calculate risk of securities much more accurately than others. LTCM’s trading strategy was featured by the divergence in price between long-term U.S. Treasury bonds. It shorted the more expensive “on-the-run” bond and purchased the “off-the-run” security at the same time to exploit the price divergence. In order

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Though a study of cycles offers the trader a broader picture of the stock market’s performance during various periods, it is difficult to place trades based on these numbers alone.

Throughout the Stock Market Game experience, I learned how to invest intellectually and for a reason. The goal of investments is so make money and gain capital. On the other hand, there are a lot of risks that take part as well. We started using fundamental analysis at first to determine which stock, bonds, and mutual funds to purchase. Fundamental analysis gives us insight on a company’s revenues, earnings, future growth, return on equity, profit margins and other data to determine a company's underlying value and potential for future growth. In terms of stocks, fundamental analysis focuses on the financial statements of the company being evaluated meaning P/E, Market Caps, and PEG Ratios are considered and calculated. We also took into consideration of the risks imposed when investing.

(10) While computing covariances among the returns of several stocks can be complicated, the covariance of a stock's return with itself is always one.

Over the past 5 years, ETFs have surged in popularity as they continue to grow and evolve. Just this past year, the global exchange traded products industry reached another milestone, topping $3 trillion in combined assets under management. Now investors are searching for the next asset class which will expected to explode on the scene as ETFs have recently. They may have found it last week when Eaton Vance rolled out the first of its Nextshares products. The funds, commonly called exchange traded mutual funds, are actively managed and traded at the funds net asset value but carry low fees found with traditional ETFs.

that they pop on two moving averages, and only buy or sell once price is in the middle

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Ever since Ross (1976) proposed the Arbitrage Pricing Theory (APT) as an alternative to the capital pricing model, many economists and investors have applied APT across different markets. Whereas the traditional capital pricing model explained asset returns with one beta, sensitivity to the market return, APT decomposes the return with a multiple number of factors. This idea became particularly popular for investors who aim to gain systematic risk other than market risk. However, the model specification aspect has been challenging to many practitioners as the theory does not require any specific sets of variables to be used (Azeez 2006).

Among the most fundamental risks, associated with exchange-traded derivatives, is variable degree of risk. According to Ernst, Koziol, & Schweizer (2011), the transactions in

If the assets exist to help meet a liability, the liability should be considered in the process; 3. Basing one’s decision solely on an asset allocation’s mean and variance is insufficient to base one’s decisions, in a world in which asset class returns are not normally distributed; and, 4. Most investors have multi-period objectives and the mean-variance framework is a single period model. These potential shortcomings are the likely reasons that practitioners have not fully embraced meanvariance optimization. For a number of practitioners, mean-variance optimization creates the illusion of quantitative sophistication; yet, in practice, asset allocations are developed using judgmental, ad hoc approaches. Recent advances significantly improve the quality of typical mean-variance optimizationbased asset allocations that should allow a far wider audience to realize the benefits of the Markowitz paradigm, or at least the intent of the paradigm. In this article, we focus on the first issue: the lack of diversification that can result from traditional meanvariance optimization. We begin with two examples in which traditional mean-variance optimization