Commodity Derivatives Valuation with Autoregression and Moving Average in the Price Dynamics

In this paper we develop a continuous time factor model of commodity prices that allows for higher order autoregression and moving average components. The need for these components is documented by analyzing the convenience yield's time series dynamics. Making use of the affine model structure, closed-form pricing formulas for futures and options are derived. Empirically, a parsimonious version of the general model is estimated for the crude oil market using futures data. We demonstrate the model's superior performance in pricing nearby futures contracts in- and out-of-sample. Most notably, the model improves the pricing of long horizon contracts with information from the short end of the futures curve substantially.Commodity Pricing, CARMA, Futures, Crude Oil

Integrating Multiple Commodities in a Model of Stochastic Price Dynamics

In this paper we develop a multi-factor model for the joint dynamics of related commodity spot prices in continuous time. We contribute to the existing literature by simultaneously considering various commodity markets in a single, consistent model. In an application we show the economic significance of our approach. We assume that the spot price processes can be characterized by the weighted sum of latent factors. Employing an essentially-affine model structure allows for rich dependencies among the latent factors and thus, the commodity prices. The co-integrated behavior between the different spot price dynamics is explicitly taken into account. Within this framework we derive closed-form solutions of futures prices. The Kalman Filter methodology is applied to estimate the model for crude oil, heating oil and gasoline futures contracts traded on the NYMEX. Empirically, we are able to identify a common non-stationary equilibrium factor driving the long-term price behavior and stationary factors affecting all three markets in a common way. Additionally, we identify factors which only impact subsets of the commodities considered. To demonstrate the economic consequences of our integrated approach, we evaluate the investment into a refinery from a financial management perspective and compare the results with an approach neglecting the co-movement of prices. This negligence leads to radical changes in the project's assessment.Commodities; Integrated Model; Crude Oil; Heating Oil; Gasoline; Futures; Kalman Filter

How aggregate volatility-of-volatility affects stock returns

A stylized theoretical model with stochastic volatility suggests the existence of a trade-off between returns and volatility-of-volatility. Using the VVIX, a measure of the option-implied volatility of the volatility index, we confirm this prediction and detect that time-varying aggregate volatility-of-volatility commands an economically substantial and statistically significant negative risk premium. We find that a two-standard-deviation increase in aggregate volatility-of-volatility factor loadings is associated with a decrease in average annual returns of about 11%. These results are robust to controlling for aggregate volatility, jump risk, and several other characteristics and factor sensitivities, as well as various additional tests

Essays on Systemic Risk

Chapter 1: Introduction Chapter 2: Systemic Risk: Is the Banking Sector Special? In this paper we empirically investigate the degree of systemic risk in the banking sector versus other industry sectors in the United States and in Germany. We characterize the systemic risk in each sector by the lower tail dependence of stock returns. Our study differs from the existing literature in three aspects. First, we compare the degree of systemic risk in the banking sector with other sectors in the economy. Second, we analyze how the systemic risk depends on the state of the economy. Third, we address the problem of systemic risk in an international context by comparing the US and the German banking system. Our study shows in most cases considered that the systemic risk of the banking sector is significantly larger than in all other sectors. Especially it differs from the systemic risk in the insurance sector, the second strongly regulated financial subsystem. Moreover, the degree of systemic risk is higher under adverse market conditions. Finally, we find that the banking sector in Germany shows a lower systemic risk than the US banking sector. Chapter 3: Intra-Industry Contagion Effects of Earnings Surprises in the Banking Sector In this paper we investigate whether contagion is present in the banking sector by analyzing how banks are affected by negative earnings surprises from their competitors. The banking sector is of crucial importance for the economy and, thus, highly regulated on an individual bank level. However, a high degree of contagion risk should call for a regulation of the financial network rather than solely regulating on an individual level. To be able to make a judgment about the magnitude of possible contagion effects we compare the results of the banking sector with the results of the non-banking industries. We find that earnings surprises cause significant contagion in the banking sector. In contrast, we do not find this effect in the non-banking sectors, including the insurance sector. The magnitude of contagion in the banking sector is positively related with the size of the bank reporting an earnings surprise, as well as the size of the affected banks. Chapter 4: Portfolio Management in the Presence of Systemic Risk In this paper we empirically investigate the consequences of systemic risk for stock market investors. To tackle this issue, we consider two different investment strategies. One strategy being crisis conscious, i.e. taking the possibility of systemic events into account - the other one being crisis ignorant and thus, disregarding systemic risk. We compare the optimal portfolio choices and investment results of these strategies in an historical simulation, using almost three decades of historical stock price data. Our main findings are as follows: the crisis conscious investor tends to choose less extreme portfolio weights for individual stocks than the ignorant investor. The overall risky investment is, however, of similar size for both. By ignoring the possibility of systemic events, the crisis ignorant strategy performs significantly worse from the viewpoint of expected return as well as expected utility. Chapter 5: Concluding Remark

Historical antisemitism, ethnic specialization, and financial development

Historically, European Jews have specialized in financial services while being the victims of antisemitism. We find that the present-day demand for finance is lower in German counties where historical antisemitism was higher, compared to otherwise similar counties. Households in counties with high historical antisemitism have similar saving rates but invest less in stocks, hold lower saving deposits, and are less likely to get a mortgage to finance homeownership after controlling for wealth and a rich set of current and historical covariates. Present-day antisemitism and supply-side forces do not fully explain the results. Households in counties where historical antisemitism was higher distrust the financial sector more—a potential cultural externality of historical antisemitism that reduces wealth accumulation in the long run

The conditional capital asset pricing model revisited: evidence from high-frequency betas

When using high-frequency data, the conditional CAPM can explain asset-pricing anomalies. Using conditional betas based on daily data, the model works reasonably well for a recent sample period. However, it fails to explain the size anomaly as well as 3 out of 6 of the anomaly component excess returns. Using high-frequency betas, the conditional CAPM is able to explain the size, value, and momentum anomalies. We further show that high-frequency betas provide more accurate predictions of future betas than those based on daily data. This result holds for both the time-series and the cross-sectional dimensions

Curve momentum

We propose a momentum strategy that operates within commodity futures curves. The diversified curve momentum strategy generates a significantly positive average excess return and a (annualized) Sharpe ratio of 1.28. The profitability of the strategy has increased markedly in the more recent years. These excess returns are difficult to reconcile with risk based explanations, as evidenced by the significantly positive alpha after controlling for exposure to several well-known risk factors. The average excess return on the diversified curve momentum strategy remains significantly positive even after accounting for transaction costs

Jump and variance risk premia in the S&P 500

We analyze the risk premia embedded in the S&P 500 spot index and option markets. We use a long time-series of spot prices and a large panel of option prices to jointly estimate the diffusive stock risk premium, the price jump risk premium, the diffusive variance risk premium and the variance jump risk premium. The risk premia are statistically and economically significant and move over time. Investigating the economic drivers of the risk premia, we are able to explain up to 63 % of these variations

Variance risk in commodity markets

We analyze the variance risk of commodity markets. We construct synthetic variance swaps and find significantly negative realized variance swap payoffs in most markets. We find evidence of commonalities among the realized payoffs of commodity variance swaps. We also document comovements between the realized payoffs of commodity, equity and bond variance swaps. Similar results hold for expected variance swap payoffs. Furthermore, we show that both realized and expected commodity variance swap payoffs are distinct from the realized and expected commodity futures returns, indicating that variance risk is unspanned by commodity futures

The Memory of Beta Factors

Researchers and practitioners employ a variety of time-series processes to forecast betas, using either short-memory models or implicitly imposing infinite memory. We find that both approaches are inadequate: beta factors show consistent long-memory properties. For the vast majority of stocks, we reject both the short-memory and difference-stationary (random walk) alternatives. A pure long- memory model reliably provides superior beta forecasts compared to all alternatives. Finally, we document the relation of firm characteristics with the forecast error differentials that result from inadequately imposing short-memory or random walk instead of long-memory processes