Macroeconomic risk in commodities market

The thesis studies the presence of macroeconomic risk in the commodities futures market. I present strong evidence that there is a strong relationship between macroeconomic risk and individual commodities future returns. Furthermore, long-only trading strategies seem to be strongly exposed to systematic risk, while long-short trading strategies (based on basis, momentum and basis-momentum) are found to present no such risk. Instead, I found a strong sentiment exposure in the portfolio returns of these long-short strategies, mainly during recessions. The advantages of following long-short strategies become even clearer when analyzing different macroeconomic regimes.

Quantile forecasts of daily exchange rate returns from forecasts of realized volatility

Quantile forecasts are central to risk management decisions because of the widespread use of Value-at-Risk. A quantile forecast is the product of two factors: the model used to forecast volatility, and the method of computing quantiles from the volatility forecasts. In this paper we calculate and evaluate quantile forecasts of the daily exchange rate returns of five currencies. The forecasting models that have been used in recent analyses of the predictability of daily realized volatility permit a comparison of the predictive power of different measures of intraday variation and intraday returns in forecasting exchange rate variability. The methods of computing quantile forecasts include making distributional assumptions for future daily returns as well as using the empirical distribution of predicted standardized returns with both rolling and recursive samples. Our main findings are that the Heterogenous Autoregressive model provides more accurate volatility and quantile forecasts for currencies which experience shifts in volatility, such as the Canadian dollar, and that the use of the empirical distribution to calculate quantiles can improve forecasts when there are shifts

Consumption-wealth ratio and expected stock returns: evidence from panel data

This paper investigates the role of consumption-wealth ratio on predicting future stock returns through a panel approach. We follow the theoretical framework proposed by Lettau and Ludvigson (2001), in which a model derived from a nonlinear consumer’s budget constraint is used to settle the link between consumption-wealth ratio and stock returns. Using G7’s quarterly aggregate and financial data ranging from the first quarter of 1981 to the first quarter of 2014, we set an unbalanced panel that we use for both estimating the parameters of the cointegrating residual from the shared trend among consumption, asset wealth and labor income, cay, and performing in and out-of-sample forecasting regressions. Due to the panel structure, we propose different methodologies of estimating cay and making forecasts from the one applied by Lettau and Ludvigson (2001). The results indicate that cay is in fact a strong and robust predictor of future stock return at intermediate and long horizons, but presents a poor performance on predicting one or two-quarter-ahead stock returns.

Consumption-Wealth Ratio and Expected Stock Returns: Evidence from Panel Data on G7 Countries

Using the theoretical framework of Lettau and Ludvigson (2001), we perform an empirical investigation on how widespread is the predictability of cay {a modi ed consumption-wealth ratio { once we consider a set of important countries from a global perspective. We chose to work with the set of G7 countries, which represent more than 64% of net global wealth and 46% of global GDP at market exchange rates. We evaluate the forecasting performance of cay using a panel-data approach, since applying cointegration and other time-series techniques is now standard practice in the panel-data literature. Hence, we generalize Lettau and Ludvigson's tests for a panel of important countries. We employ macroeconomic and nancial quarterly data for the group of G7 countries, forming an unbalanced panel. For most countries, data is available from the early 1990s until 2014Q1, but for the U.S. economy it is available from 1981Q1 through 2014Q1. Results of an exhaustive empirical investigation are overwhelmingly in favor of the predictive power of cay in forecasting future stock returns and excess returns.

Insiders´ views as a predictor of stock performance : can insider trading be used to predict stock performance on the United States stock market?

This thesis studies the possibility of using information on insiders’ transactions to forecast future stock returns after the implementation of Sarbanes Oxley Act in July 2003. Insider transactions between July 2003 and August 2009 are analysed with regression tests to identify the relationships between insiders’ transactions and future stock returns. This analysis is complemented with rudimentary bootstrapping procedures to verify the robustness of the findings. The underlying assumption of the thesis is that insiders constantly receive pieces of information that indicate future performance of the company. They may not be allowed to trade on large and tangible pieces of information but they can trade on accumulation of smaller, intangible pieces of information. Based on the analysis in the thesis insiders’ profits were found not to differ from the returns from broad stock index. However, their individual transactions were found to be linked to future stock returns. The initial model was found to be unstable but some of the predictive power could be sacrificed to achieve greater stability. Even after sacrificing some predictive power the relationship was significant enough to allow external investors to achieve abnormal profits after transaction costs and taxes. The thesis does not go into great detail about timing of transactions. Delay in publishing insiders’ transactions is not taken into account in the calculations and the closed windows are not studied in detail. The potential effects of these phenomena are looked into and they do not cause great changes in the findings. Additionally the remuneration policy of an insider or a company is not taken into account even though it most likely affects the trading patterns of insiders. Even with the limitations the findings offer promising opportunities for investors to improve their investment processes by incorporating additional information from insiders’ transaction into their decisions. The findings also raise questions on how insider trading should be regulated. Insiders achieve greater returns than other investors based on superior information. On the other hand, more efficient information transfer could warrant more lenient regulation. The fact that insiders’ returns are dominated by the large investment stake they maintain all the time in their own companies also speaks for more leniency. As Sarbanes Oxley Act considerably modified the insider trading landscape, this analysis provides information that has not been available before. The thesis also constitutes a thorough analysis of insider trading phenomenon which has previously been somewhat separated into several studies.

Occupational futures? Divesting real estate and corporate PFI

Property ownership can tie up large amounts of capital and management energy that business could employ more productively elsewhere. Competitive pressures, accounting changes and increasingly sophisticated occupier requirements are building demand for new and innovative ways to satisfy corporate occupation needs. The investment climate is also changing. Falling interest rates and falling inflation can be expected to undermine returns from the traditional FRI lease. In future, investment returns will be more dependent on active and innovative management geared to the needs of occupiers on whom income depends. Occupier and investor interests, therefore, look set to coincide, but unlocking the potential for both parties will depend on developing new finance and investment vehicles that align their respective needs. In the UK, examples include PFI in the public sector and off-balance sheet financing in the private sector. In the USA, “synthetic lease” structures have also become popular. Growing investment market experience in assessing risks and returns suggests scope for further innovative arrangements in the corporate sector. But how can such arrangements be structured? What are the risks, drivers and barriers?

The impact of R&D in firm value across Europe

In this thesis the impact of R&D expenditures on firm market value and stock returns is examined. This is performed in a sample of European listed firms for the period 2000-2009. I apply different linear and GMM econometric estimations for testing the impact of R&D on market prices and construct country portfolios based on firms’ R&D expenditure to market capitalization ratio for studying the effect of R&D on stock returns. The results confirm that more innovative firms have a better market valuation,investors consider R&D as an asset that produces long-term benefits for corporations. The impact of R&D on firm value differs across countries. It is significantly modulated by the financial and legal environment where firms operate. Other firm and industry characteristics seem to play a determinant role when investors value R&D. First, only larger firms with lower financial leverage that operate in highly innovative sectors decide to disclose their R&D investment. Second, the markets assign a premium to small firms, which operate in hi-tech sectors compared to larger enterprises for low-tech industries. On the other hand, I provide empirical evidence indicating that generally highly R&D-intensive firms may enhance mispricing problems related to firm valuation. As R&D contributes to the estimation of future stock returns, portfolios that comprise high R&D-intensive stocks may earn significant excess returns compared to the less innovative after controlling for size and book-to-market risk. Further, the most innovative firms are generally more risky in terms of stock volatility but not systematically more risky than low-tech firms. Firms that operate in Continental Europe suffer more mispricing compared to Anglo-Saxon peers but the former are less volatile, other things being equal. The sectors where firms operate are determinant even for the impact of R&D on stock returns; this effect is much stronger in hi-tech industries.

Dois ensaios em finanças

In the first chapter, we test some stochastic volatility models using options on the S&P 500 index. First, we demonstrate the presence of a short time-scale, on the order of days, and a long time-scale, on the order of months, in the S&P 500 volatility process using the empirical structure function, or variogram. This result is consistent with findings of previous studies. The main contribution of our paper is to estimate the two time-scales in the volatility process simultaneously by using nonlinear weighted least-squares technique. To test the statistical significance of the rates of mean-reversion, we bootstrap pairs of residuals using the circular block bootstrap of Politis and Romano (1992). We choose the block-length according to the automatic procedure of Politis and White (2004). After that, we calculate a first-order correction to the Black-Scholes prices using three different first-order corrections: (i) a fast time scale correction; (ii) a slow time scale correction; and (iii) a multiscale (fast and slow) correction. To test the ability of our model to price options, we simulate options prices using five different specifications for the rates or mean-reversion. We did not find any evidence that these asymptotic models perform better, in terms of RMSE, than the Black-Scholes model. In the second chapter, we use Brazilian data to compute monthly idiosyncratic moments (expected skewness, realized skewness, and realized volatility) for equity returns and assess whether they are informative for the cross-section of future stock returns. Since there is evidence that lagged skewness alone does not adequately forecast skewness, we estimate a cross-sectional model of expected skewness that uses additional predictive variables. Then, we sort stocks each month according to their idiosyncratic moments, forming quintile portfolios. We find a negative relationship between higher idiosyncratic moments and next-month stock returns. The trading strategy that sells stocks in the top quintile of expected skewness and buys stocks in the bottom quintile generates a significant monthly return of about 120 basis points. Our results are robust across sample periods, portfolio weightings, and to Fama and French (1993)’s risk adjustment factors. Finally, we identify a return reversal of stocks with high idiosyncratic skewness. Specifically, stocks with high idiosyncratic skewness have high contemporaneous returns. That tends to reverse, resulting in negative abnormal returns in the following month.

Gräs från våtmark som additiv i bränslepellets : Effekter på pelletskvalitet och energiförbrukning

Because of global warming the energy production development has progressed towards more renewable energy sources. Biomass has great potential in this matter and pellet is already a big market that has increased seven times the past decade. A periodically strained woodchip resource market and statements of short supply in the future has got actors exploring opportunities with other commodities. Grasses such as Canary grass has shown great potential in this matter and in this study a wetland grass is tested as an additive, 0,5, 1,0, 1,5, and 1,9%, with spruce woodchips. The test production series was performed at a production unit located at the department of environmental and energy system at Karlstad University, Karlstad. Quality was controlled accordingly to the European standard and parameters such as energy consumption, moisture content, mechanical durability and bulk density was tested. For comparison, a sample with only spruce wood chips was produced, and a sample containing 1% of a commonly used additive, potato starch. The results showed that a decrease in energy consumption with 14% when 2% wetland grass was added, part of the decline may be due to the increased production flow compared with the reference sample. The positive effects on decrease in energy consumption, that 1% potato starch results in, is equal to reults from 1% wetlandgrass. This indicates lubricating properties in wetlandgrass. This is attributed to that herbaceous plants have a high content of extracts such as waxes and that they cause less friction in the press. Tests also showed that pellet with wetland grass did not qualify the European standard in terms of mechanical durability. Extracts can form a weak boundary layer in the pellet and cause this. A possible trend shows a better mechanical durability with more grass in pellets. The presence of different size of particles can be a reason. Moisture content qualifies according to the European standard but is below optimum 8%. This despite to relatively high moisture content in the mixer. Higher moisture content in the press would certainly result in a generally higher quality. Suggestions for future studies are to produce pellets with greater distribution on the wetland grass added, to easier interpret a connection. Also examine the extracts behavior with different moisture content. For a sustainable development accordingly renewable energy it is important to ensure the future commodity market for pellets. Further studies should be performed to help the development of alternative raw materials in conjunction with pellet production.

Commodity Future Price Premiums – Case EU ETS

The purpose of this thesis was to study commodity future price premiums and their nature on emission allowance markets. The EUA spot and future contracts traded on the secondary market during EU ETS Phase 2 and Phase 3 were selected for empirical testing. The cointegration of spot and future prices was examined with Johansen cointegration methodology. Daily interest rates with a similar tenor to the future contract maturity were used in the cost-of-carry model to calculate the theoretical future prices and to estimate the deviation from the fair value of future contracts, assumed to be explained by the convenience yield. The time-varying dependence of the convenience yield was studied by regression testing the correlation between convenience yield and the time to maturity of the future contract. The results indicated cointegration between spot and future prices, albeit depending on assumptions on linear trend and intercept in cointegration vector Dec-14 and Dec-15 contracts. The convenience yield correlates positively with the time-to-maturity of the future contract during Phase 2, but negatively during Phase 3. The convenience yield featured positive correlation with spot price volatility and negative correlation with future price volatility during both Phases 2 and 3.

The future returns for property required by UK pension funds

In the 1970s Real Estate represented over 17% of the average pension funds total assets. Today such funds hold less than 4%, a figure not seen since the 1960s. This reduction in Real Estate holdings is mainly attributable to the relatively poor performance of Real Estate against other asset classes since the 1980s. Whether pension funds will increase their holding at any point in the future depends therefore on the expected return of Real Estate by comparison with that required to justify a particular asset holding. Using the technique of Modern Portfolio Theory (MPT), this paper assesses the required return that Real Estate would have to offer to justify a 15% holding in a mixed asset portfolio. This figure and the risk/return characteristics of the major asset classes is taken from survey data. Under a number of scenarios it is found that Real Estate can play a part in a mixed asset portfolio at the 15% level. In some cases however, the expected returns of Real Estate are not sufficient to justify a weight of 15% in this asset.

The future returns for property required by UK pension funds: the BHS data

Previous studies of the place of Property in the multi-asset portfolio have generally relied on historical data, and have been concerned with the supposed risk reduction effects that Property would have on such portfolios. In this paper a different approach has been taken. Not only are expectations data used, but we have also concentrated upon the required return that Property would have to offer to achieve a holding of 15% in typical UK pension fund portfolios. Using two benchmark portfolios for pension funds, we have shown that Property's required return is less than that expected, and therefore it could justify a 15% holding.

Commodity risks and the cross-section of equity returns

The article examines whether commodity risk is priced in the cross-section of global equity returns. We employ a long-only equally-weighted portfolio of commodity futures and a term structure portfolio that captures phases of backwardation and contango as mimicking portfolios for commodity risk. We find that equity-sorted portfolios with greater sensitivities to the excess returns of the backwardation and contango portfolio command higher average excess returns, suggesting that when measured appropriately, commodity risk is pervasive in stocks. Our conclusions are robust to the addition to the pricing model of financial, macroeconomic and business cycle-based risk factors.

Mercados de futuros: su utilidad y sus limitaciones para el comercio de productos básicos de América Latina = Future markets: their usefulness and limitations for Latin American commodity trade

Incluye Bibliografía

Price risk management in the copper market using commodity derivatives and options strategies

Metals price risk management is a key issue related to financial risk in metal markets because of uncertainty of commodity price fluctuation, exchange rate, interest rate changes and huge price risk either to metals’ producers or consumers. Thus, it has been taken into account by all participants in metal markets including metals’ producers, consumers, merchants, banks, investment funds, speculators, traders and so on. Managing price risk provides stable income for both metals’ producers and consumers, so it increases the chance that a firm will invest in attractive projects. The purpose of this research is to evaluate risk management strategies in the copper market. The main tools and strategies of price risk management are hedging and other derivatives such as futures contracts, swaps and options contracts. Hedging is a transaction designed to reduce or eliminate price risk. Derivatives are financial instruments, whose returns are derived from other financial instruments and they are commonly used for managing financial risks. Although derivatives have been around in some form for centuries, their growth has accelerated rapidly during the last 20 years. Nowadays, they are widely used by financial institutions, corporations, professional investors, and individuals. This project is focused on the over-the-counter (OTC) market and its products such as exotic options, particularly Asian options. The first part of the project is a description of basic derivatives and risk management strategies. In addition, this part discusses basic concepts of spot and futures (forward) markets, benefits and costs of risk management and risks and rewards of positions in the derivative markets. The second part considers valuations of commodity derivatives. In this part, the options pricing model DerivaGem is applied to Asian call and put options on London Metal Exchange (LME) copper because it is important to understand how Asian options are valued and to compare theoretical values of the options with their market observed values. Predicting future trends of copper prices is important and would be essential to manage market price risk successfully. Therefore, the third part is a discussion about econometric commodity models. Based on this literature review, the fourth part of the project reports the construction and testing of an econometric model designed to forecast the monthly average price of copper on the LME. More specifically, this part aims at showing how LME copper prices can be explained by means of a simultaneous equation structural model (two-stage least squares regression) connecting supply and demand variables. A simultaneous econometric model for the copper industry is built: {█(Q_t^D=e^((-5.0485))∙P_((t-1))^((-0.1868) )∙〖GDP〗_t^((1.7151) )∙e^((0.0158)∙〖IP〗_t ) @Q_t^S=e^((-3.0785))∙P_((t-1))^((0.5960))∙T_t^((0.1408))∙P_(OIL(t))^((-0.1559))∙〖USDI〗_t^((1.2432))∙〖LIBOR〗_((t-6))^((-0.0561))@Q_t^D=Q_t^S )┤ P_((t-1))^CU=e^((-2.5165))∙〖GDP〗_t^((2.1910))∙e^((0.0202)∙〖IP〗_t )∙T_t^((-0.1799))∙P_(OIL(t))^((0.1991))∙〖USDI〗_t^((-1.5881))∙〖LIBOR〗_((t-6))^((0.0717) Where, Q_t^D and Q_t^Sare world demand for and supply of copper at time t respectively. P(t-1) is the lagged price of copper, which is the focus of the analysis in this part. GDPt is world gross domestic product at time t, which represents aggregate economic activity. In addition, industrial production should be considered here, so the global industrial production growth that is noted as IPt is included in the model. Tt is the time variable, which is a useful proxy for technological change. A proxy variable for the cost of energy in producing copper is the price of oil at time t, which is noted as POIL(t ) . USDIt is the U.S. dollar index variable at time t, which is an important variable for explaining the copper supply and copper prices. At last, LIBOR(t-6) is the 6-month lagged 1-year London Inter bank offering rate of interest. Although, the model can be applicable for different base metals' industries, the omitted exogenous variables such as the price of substitute or a combined variable related to the price of substitutes have not been considered in this study. Based on this econometric model and using a Monte-Carlo simulation analysis, the probabilities that the monthly average copper prices in 2006 and 2007 will be greater than specific strike price of an option are defined. The final part evaluates risk management strategies including options strategies, metal swaps and simple options in relation to the simulation results. The basic options strategies such as bull spreads, bear spreads and butterfly spreads, which are created by using both call and put options in 2006 and 2007 are evaluated. Consequently, each risk management strategy in 2006 and 2007 is analyzed based on the day of data and the price prediction model. As a result, applications stemming from this project include valuing Asian options, developing a copper price prediction model, forecasting and planning, and decision making for price risk management in the copper market.