Price Dynamics & Trading Strategies in the Commodities Market

This thesis makes new observations of market phenomena for various commodities and trading strategies centered around these observations. In particular, our results imply that many aspects of the commodities markets, from delivery markets to producers and consumer derivative based ETFs can be modeled eectively using nancial engineering techniques. Chapter 2 examines what drives the returns of gold miner stocks and ETFs. Inspired by our real options model, we construct a method to dynamically replicate gold miner stocks using two factors: a spot gold ETF and a market equity portfolio. We find that our real options approach can explain a significant portion of the drivers of firm implied gold leverage. Chapter 3 studies commodity exchange-traded funds (ETFs). From empirical data, we find that many commodity leveraged ETFs underperform significantly against our constructed dynamic benchmark, and we quantify such a discrepancy via the novel idea of realized effective fee. Finally, we consider a number of trading strategies and examine their performance by backtesting with historical price data. Chapter 4 studies the phenomenon of non-convergence between futures and spot prices in the grains market. In our proposed approach, we incorporate stochastic spot price and storage cost, and solve an optimal double stopping problem to understand shipping certificate prices. Our new models for stochastic storage rates explain the spot-futures premium

LEVERAGED ETF IMPLIED VOLATILITIES FROM ETF DYNAMICS

The growth of the exchange-traded fund (ETF) industry has given rise to the trading of options written on ETFs and their leveraged counterparts (LETFs). We study the relationship between the ETF and LETF implied volatility surfaces when the underlying ETF is modeled by a general class of local-stochastic volatility models. A closed-form approximation for prices is derived for European-style options whose payoffs depend on the terminal value of the ETF and/or LETF. Rigorous error bounds for this pricing approximation are established. A closed-form approximation for implied volatilities is also derived. We also discuss a scaling procedure for comparing implied volatilities across leverage ratios. The implied volatility expansions and scalings are tested in three settings: Heston, limited constant elasticity of variance (CEV), and limited SABR; the last two are regularized versions of the well-known CEV and SABR models

Entropy and Efficiency of the ETF Market

We investigate the relative information efficiency of financial markets by measuring the entropy of the time series of high frequency data. Our tool to measure efficiency is the Shannon entropy, applied to 2-symbol and 3-symbol discretisations of the data. Analysing 1-min and 5-min price time series of 55 Exchange Traded Funds traded at the New York Stock Exchange, we develop a methodology to isolate residual inefficiencies from other sources of regularities, such as the intraday pattern, the volatility clustering and the microstructure effects. The first two are modelled as multiplicative factors, while the microstructure is modelled as an ARMA noise process. Following an analytical and empirical combined approach, we find a strong relationship between low entropy and high relative tick size and that volatility is responsible for the largest amount of regularity, averaging 62% of the total regularity against 18% of the intraday pattern regularity and 20% of the microstructure

Risk-Return Dynamics Using Leveraged ETF Options

This study uses barbell strategies on the S&P 500 and the NASDAQ 100 to explore if funds invested primarily in fixed income assets with a portion of the investment placed in in-the-money call options can participate in upside potential, while also reducing risk. This study examines call options on the underlying indexes as well as their leveraged, 2x and 3x, counterparts. The barbell strategy studied, 88% in fixed income bonds and 12% in call options, does not have a higher return than the underlying index, and adds additional risk. However, a weighted portfolio with combinations of a risk-free asset and leveraged ETF does provide a higher return on investment, with a decreased risk as compared to the underlying index

The tracking ability of oil and gas exchanged traded funds (ETFs)

Apesar do vasto reportório de trabalhos existentes sobre Exchanged Traded Funds (ETFs), poucos são aqueles que têm analisado commodities ETFs e a respetiva adequabilidade como substitutos de investimentos diretos em commodities. Para analisar se esta classe específica de ETFs é uma boa alternativa, analisámos uma amostra de 11 ETFs e se seguiam os respetivos benchmarks. Para tal procedemos a uma análise de regressão linear, ao cálculo do tracking error, e uma análise de cointegração, sendo esta última focada na relação de longo prazo entre variáveis. As análises de regressões e tracking error evidenciam uma forte ligação com os benchmarks na maior parte dos ETFs, mas os testes de cointegração apresentam resultados díspares, sugerindo uma relação mais fraca no longo prazo para a maior parte dos ETFs. Por outro lado os ETFs que têm como benchmarks índices de commodities apresentam melhores resultados do que aqueles que seguem as commodities propriamente ditas. O uso de produtos derivados, nomeadamente futuros nestes ETFs, e o facto de os mesmos terem de ser constantemente renegociados (Roll Over) são uma das razões para a diferença de performances entre os ETFs e respetivos benchmarks.Despite the vast literature on Exchanged Traded Funds (ETFs), few are those focused on commodities ETFs and their suitability as a replacement for direct investments in commodities. To examine whether this specific class of ETFs is a good alternative we have analyzed the tracking ability of a sample of 11 ETFs and their respective benchmarks. To this end, we have performed a linear regression analysis, a tracking error analysis, and a cointegration analysis, the latter being focused on the long-term relationship. Regressions analyses and tracking error show a strong relationship in most ETFs, but cointegration tests show uneven results, suggesting a weaker relationship in the long run between ETFs and their benchmark. On the other hand the ETFs that follow benchmarks indexes have better results than those who follow the commodities themselves. The use of derivative products such as futures in these ETFs, and the fact that those must be constantly renegotiated (Roll Over) are one of the reasons for the difference in performance between ETFs and their benchmarks

Portfolio optimisation models

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University LondonIn this thesis we consider three different problems in the domain of portfolio optimisation. The first problem we consider is that of selecting an Absolute Return Portfolio (ARP). ARPs are usually seen as financial portfolios that aim to produce a good return regardless of how the underlying market performs, but our literature review shows that there is little agreement on what constitutes an ARP. We present a clear definition via a three-stage mixed-integer zero-one program for the problem of selecting an ARP. The second problem considered is that of designing a Market Neutral Portfolio (MNP). MNPs are generally defined as financial portfolios that (ideally)exhibit performance independent from that of an underlying market, but, once again, the existing literature is very fragmented. We consider the problem of constructing a MNP as a mixed-integer non-linear program (MINLP) which minimises the absolute value of the correlation between portfolio return and underlying benchmark return. The third problem is related to Exchange-Traded Funds (ETFs). ETFs are funds traded on the open market which typically have their performance tied to a benchmark index. They are composed of a basket of assets; most attempt to reproduce the returns of an index, but a growing number try to achieve a multiple of the benchmark return, such as two times or the negative of the return. We present a detailed performance study of the current ETF market and we find, among other conclusions, constant underperformance among ETFs that aim to do more than simply track an index. We present a MINLP for the problem of selecting the basket of assets that compose an ETF, which, to the best of our knowledge, is the first in the literature. For all three models we present extensive computational results for portfolios derived from universes defined by S&P international equity indices with up to 1200 stocks. We use CPLEX to solve the ARP problem and the software package Minotaur for both our MINLPs for MNP and an ETF