ABSTRACT. In this paper, we analyse the interaction between centralised carbon emissive tech- nologies and distributed intermittent non-emissive technologies. A representative con- sumer can satisfy his electricity demand by investing in distributed generation (solar panels) and by buying power from a centralised firm at a price the firm sets. Dis- tributed generation is intermittent and induces an externality cost to the consumer. The firm provides non-random electricity generation subject to a carbon tax and to transmission costs. The objective of the consumer is to satisfy her demand while min- imising investment costs, payments to the firm, and intermittency costs. The objective of the firm is to satisfy the consumer’s residual demand while minimising investment costs, demand deviation costs, and maximising the payments from the consumer. We formulate the investment decisions as McKean-Vlasov control problems with stochas- tic coefficients. We provide explicit, price model-free solutions to the optimal decision problems faced by each player, the solution of the Pareto optimum, and the laissez- faire market situation represented by a Stackelberg equilibrium where the firm is the leader. We find that, from the social planner’s point of view, the high adjustment cost of centralised technology damages the development of distributed generation. The Stackelberg equilibrium leads to significant deviation from the socially desirable ratio of centralised versus distributed generation. In a situation where a power system is to be built from zero, the optimal strategy of the firm is high price/low market-share, but is low price/large market share for existing power systems. Further, from a regulation policy, we find that a carbon tax or a subsidy to distributed technology has the same efficiency in achieving a given level of distributed generation.

ABSTRACT. SREC markets are a relatively novel market-based system to incentivize the production of energy from solar means. A regulator imposes a floor on the amount of energy each regulated firm must generate from solar power in a given period, providing them with certificates for each generated MWh. Firms offset these certificates against the floor, paying a penalty for any lacking certificates. Certificates are tradable assets, allowing firms to purchase / sell them freely. In this work, we formulate a stochastic control problem for generating and trading in SREC markets for a regulated firm and discuss potential takeaways for both a regulated firm under this system and regulatory bodies in charge of designing them.

ABSTRACT. We analyze the impact of renewable generation technologies on wholesale electricity prices. It is fundamental that technologies affect market prices via their marginal production costs, and low-cost wind power thus displaces incumbent gas generators' production whenever available. This cost-based merit-order effect forms the theoretical underpinning behind investment decisions and subsidy policies in the power industry. This paper revisits the merit-order effect with the additional consideration of operational factors, in particular the intermittent availability of renewable (wind) power. We adapt the classic Cournot framework to analyze incumbent conventional producers' competition with emerging low-cost intermittent generators. We find that the cost-based merit-order effect is complemented by a further operational effect on price formation. Specifically, since electricity is traded in both spot (product) and forward (financial) markets, wind intermittency alters the value of forward hedge positions, and thereby affects market prices through producers' strategic forward commitments. As a result, intermittency may cause producers to behave less aggressively in forward trading for fear of unfavorable spot-market positions. Equilibrium prices may then paradoxically increase with more wind power, even though both renewables and forward trading are separately viewed as pro-competitive. We further examine how the merit-order effect depends upon other market fundamentals, repeated forward trading, policies influencing renewable producers' participation in forward markets, and additional generation technologies. Our model also provides results that explain previously contradictory empirical effects of fundamentals on power prices. Overall, our analysis suggests that the cost-based merit-order effect alone is insufficient for evaluating the impacts of diverse technologies on power prices.

ABSTRACT. We tackle the issue of rational destabilization in the commodity markets. Rational destabilization is when rational traders use the presence of trend-followers to create a bubble on the market. We add trend-following traders in a three-period model. We show how a rising weight of trend-followers increases the futures price and impacts the spot market according to informational frictions. Moreover, we show the model exhibits a multiplicity of equilibria with very diverse impacts on pricing and hedging.

ABSTRACT. We develop a fundamental model for the German continuous intraday electricity market of 15-minute contracts. A unique data set involving intradaily updated forecasts of wind and solar power generation is analyzed. Empirical evidence suggests that, on average, transaction prices of 15-minute contracts exhibit a sawtooth-shaped and trading volumes a U-shaped hourly seasonality. Furthermore liquidity increases sharply within the last trading hour before gate closure. We use a threshold regression model to examine how 15-minute intraday trading depends on the slope of the merit order curve. Our estimation results indicate mean reversion in the price formation process of 15-minute contracts. Additionally prices of neighboring contracts are positively related and exhibit strong explanatory power regarding prices of a given contract. Moreover we observe an asymmetric effect of positive and negative renewable forecast changes on 15-minute prices depending on the merit-order-curve slope. In general renewable forecasts are more relevant at noon than in the morning and evening, but trade data seem to be the main driver of 15-minute intraday trading.

ABSTRACT. This paper evaluates the effect of market integration on prices and welfare, in a model where two Lucas trees grow in separate regions with similar investors. We find equilibrium asset price dynamics and welfare both in segmentation, when each region holds its own asset and consumes its dividend, and in integration, when both regions trade both assets and consume both dividends. Integration always increases welfare. Asset prices may increase or decrease, depending on the time of integration, but decrease on average. Correlation in assets' returns is zero or negative before integration, but significantly positive afterwards, explaining some effects commonly associated with financialization.

ABSTRACT. We show that the innovation in the risk-neutral probability of large downward and upward jumps in oil prices has a considerable predictive power for important economic indicators such as GDP growth, consumption growth, and total investment. In addition, we observe that the upside jump risk probability is a significant predictor of stock market index return and the returns of oil futures. Furthermore, the upside jump probability is a significant and relatively strong predictor of oil market fundamentals including inventory growth, demand growth, and OPEC’s production growth. Upside jump risk is also a driver of the cross-section of stock returns before the U.S. oil production increase in 2011. The average monthly return for the high-low upside jump risk exposure portfolio is -0.94% and -1.13%, using the 1996-2014 and 1996-2011 time periods respectively. The implications of the variance risk for the cross-section of stock returns vanishes after controlling for the large upside and downside jump risks. The shale revolution and considerable increase of US oil production have killed the effect of upside risk premium after 2011. During the sub-period 2011-2014, the variance risk premium gets significant again, like it was before 2000.

ABSTRACT. We employ mixed data sampling structural vector autoregressive models in order to use data sampled in different time frequencies for the calculation and comparison of various connectedness measures based on structural forecast error variance decompo-sitions. We demonstrate the validity and significance of our proposed, mixed data sampling connectedness measures in the context of oil shock propagation to the stock markets of oil-exporting and oil-importing countries from January 1998 to September 2017. Our results suggest that by involving the full potential of the information struc-ture, our proposed MIDAS-SVAR connectedness measures can estimate with greater accuracy than the traditional approaches the dynamic relationships and spillover ef-fects between oil market shocks and stock markets, especially those of oil-importing countries. We also find evidence for new properties of the proposed econometric methods and their relation to more traditional ones.

ABSTRACT. We propose a multi-commodity futures pricing model with both economic variables and pricing variables to study the price co-movement between natural gas and electricity futures prices. Our model can capture the price dynamic of both commodities and illustrate the economics behind the price co-movement. We find both supply and demand variables affect the price dynamic in natural gas and electricity market and demand variable has larger impacts than supply variable. 20% of the price co-movement between the two markets can be attributed to economic variables. Economic variables mainly affect the price co-movement through affecting its risk premium and this effect is larger for futures with longer maturities.

ABSTRACT. This paper analyzes the extent to which the research process is driven by market activity by looking at the relationship between commodity published academic research and commodity derivatives trading activity. The first decade 21st century witnessed an extraordinary boom in commodities futures trading. The increased popularity of commodities instruments as investment and hedging vehicles saw a parallel development in the commodities research literature. This paper exploits the results of a search on title textual analysis to explore interactions between commodities aggregate trading volumes and the number of commodities research articles. We find significant evidence of co-movement over the 2001-2018 period, which is illustrated by means of a cointegration framework using a VECM setting. We show that trading activity as measured by aggregate futures volumes traded drives the publishing process. We additionally explore the relationship between publications and futures volumes in the crude oil market. The number of publications found under a text search for “oil” turns out to be substantially higher than the number of papers found under the “commodity” text search. We also find strong cointegration between between research activity and trading volumes in the oil market. Our paper therefore offers strong evidence demonstrating that academic researchers follow the market activity in their topic decision process.

ABSTRACT. We examine systematic and idiosyncratic drivers of cross-sectional and time series variations in commodity futures liquidity. In terms of systematic drivers, we examine whether the liquidity of specific commodity futures markets is influenced by broad market liquidity. For idiosyncratic drivers, we use proprietary position data and examine how market makers’ (non-commercials) and hedgers’ (commercials) deviations from their target inventory levels affect liquidity of the contract market and isolate the price impact resulting from temporary hedging pressure versus permanent price impact. We find that increased hedging needs hamper liquidity due to commercial participants’ deviations from their target inventory. In contrast, there is weak evidence that temporary price impact increases as non-commercial participants deviate from their median inventory. These results reject the zero-inventory model of market making and are instead consistent with the notion of active position taking by non-commercial speculators.

ABSTRACT. What is the role of economic factors in the volatility of the crude oil futures markets? To answer this question, we first develop and estimate a multi-factor futures pricing model with stochastic volatility which is able to disentangle long-term, medium-term and short-term variations in commodity markets volatility. The volatility estimates reveal that in line with theory, these volatility factors are unspanned, persistent and carry negative market price of risk. After 2004, short-term volatility of futures prices is driven by industrial production, credit spreads and US dollar index, along the traditional drivers (of futures price returns) of hedging pressure and VIX, while oil sector variables such as inventory and consumption affect the medium-term volatility term structure due to significant structural changes in the economy and the oil sector. Interest rates matter in the long-term futures price volatility.

ABSTRACT. The investment volume from 200 billion $ in 2008 for commodity indices has more than tenfold in the past ten years. Many studies analyse financialization of commodities. Our idea is that we can observe an index effect concerning the reweighting. Because the traders have to adjust their positions and these directly affects the prices. As is customary in literature we use an event study. The investment growth takes places in the largest index, therefore the Bloomberg Commodity Index is analysed from 1999 to 2016 with 157 positive and 163 negative changes and the S&P Goldman Sachs Commodity Index from 2007 to 2016 with 105 positive and 93 negative positions. Open interest, volume and prices for each commodity are used as variables but the results show no significant impact for the rebalancing days. Therefore, we cannot find any evidence for an index effect with this study against our expectations.

ABSTRACT. We analyze 3,183 estimates from Granger causality tests on the impact of financial speculation on commodity markets obtained from 67 prior studies. Our results reveal that there is no aggregated price effect of speculation across the literature as a whole. However, when breaking down the effect by certain aspects of data and study design, speculation might have a price distorting effect. Moreover, our meta-regression shows that the heterogeneity in the speculation effect can be largely explained by the commodity type under examination, the source of speculation data, the measurement of speculation, the publication status of a paper, as well as the affiliation of the authors. These findings help to disentangle the previous contradictions in empirical results and provide an aggregated picture of the literature.

ABSTRACT. Recent financialization in the commodity market makes it easier for institutional investors to trade a portfolio of commodities via various commodity index products. Using news-based sentiment measures, we find that such trading can propagate non-fundamental shocks from some commodities to others in the same index, giving rise to price overshoots and subsequent reversals, or "excessive co-movement" at daily frequency. Excessive co-comovement results in negative daily commodity return autocorrelations even at the index level (but not for nonindexed commodities) and such autocorrelations move with our commodity index exposure measures. Taking advantage of the fact that index weights of the same commodity can vary across different indices in a relatively ad-hoc and pre-determined fashion, we provide causal evidence that index trading drives excessive co-movement. Finally, we confirm that our results are not driven by the large commodity boom-and-bust during the recent financial crisis.

ABSTRACT. This paper studies volumetric risk hedging strategies for solar power under incomplete market settings with a twofold proposal of temperature-based and solar power generation-based models for solar power derivatives and discusses the basis risk arising from solar power volumetric risk hedge with temperature. Based on an indirect modeling of solar power generation using temperature and a direct modeling of solar power generation, we design two types of call options written on the accumulated non cooling degree days (ANCDDs) and the accumulated low solar power generation days (ALSPGDs), respectively, which can hedge cool summer volumetric risk more appropriately than those on well-known accumulated cooling degree days. We offer the pricing formulas of the two options under the good-deal bounds (GDBs) framework, which can consider incompleteness of solar power derivative markets. To calculate the option prices numerically, we derive the partial differential equations for the two options using the GDBs. Empirical studies using Czech solar power generation and Prague temperature estimate the parameters of temperature-based and solar power generation-based models, respectively. We numerically calculate the call option prices on ANCDDs and ALSPGDs, respectively, as the upper and lower price boundaries using the finite difference method. Results show that the call option prices based on a solar power generation process are bigger than the call option prices based on a temperature process. This is consistent with the fact that the solar power generation approach takes into account more comprehensive risk than the temperature approach, resulting in the bigger prices for the solar power generation ap- proach. We finally show that the basis risk premiums, i.e., solar power generation-based call option prices minus temperature-based call option prices, decrease in line with initial temperature greater than around 25 ◦C. This may be because the uncertainty in solar power generation by temperature decreases due to the cancellation between the increase in solar power generation due to the increase in solar radiation and the decrease in solar power generation due to the decrease in solar panel efficiency.

ABSTRACT. Solar energy generation is growing in many markets, as a result of increasing efficiencies with decreasing costs and the presence of government regulations. The growth of residential solar energy in a market benefits the environment but not necessarily the (utility or transmission) firms in that market. It reduces the residential power demand and hence hinders the coverage of fixed part of generation and transmission costs with reasonable energy prices. In real life, the firms tend to raise the retail prices and make electricity less affordable for their consumers. This adverse effect is even more pronounced for less privileged consumers that cannot afford to invest into solar power and remain as captured customers. Higher solar power penetration into markets, despite being an environmentally desirable outcome, paradoxically can be socially undesirable. Having both environmental and social accountability, market regulators face challenges with deciding on the structure and amount of prices. We provide a novel revenue maximization formulation for a regulated firm and analytically reveal the connection between price increases and solar penetration. We also extend this formulation to take into account new price structures that mitigate price increases by allowing for the coverage of fixed costs in part or full.

ABSTRACT. Prominent companies have committed to procuring a percentage of their power demand from renewable sources by a future date in the face of uncertain power demand and stochastic power and renewable energy certificate (REC) prices. We study procurement portfolios based on two dominant strategies to achieve this target: long-term procurement of power and RECs at a fixed price using corporate power purchase agreements (CPPAs) and short-term purchases at volatile prices. We analyze a two-stage model to understand the behavior of procurement costs when using financial and physical CPPA variants employed in practice, which informs the structuring of these contracts. We subsequently formulate a Markov decision process (MDP) that optimizes the multi-stage procurement of power to reach and sustain a renewable procurement target. Our MDP is intractable because its action space is non-convex and its state space has high-dimensional endogenous and exogenous components. Although approximate methods to solve this MDP are limited, a procurement policy can be obtained using an easy-to-implement ``primal'' reoptimization strategy, which solves a deterministic model with stochastic quantities in the MDP replaced by forecasts. This approach does not, however, provide a lower bound on the optimal policy value. We propose a novel ``dual'' reoptimization heuristic which computes both procurement decisions and a lower bound while retaining the desirable implementation properties of primal reoptimization. On realistic instances, the dual reoptimization policy is near-optimal and outperforms policies from primal reoptimization and other heuristics. Our numerical results also highlight the benefits of using CPPA contracts to meet a renewable target.

ABSTRACT. We develop a heterogeneous-beliefs asset pricing model with microeconomic foundations that reproduces asset prices, cash flows and trading activity in a real asset economy. In contrast to the majority of financial markets’ behavioural models, and in line with the nature of the shipping industry, in this model agents extrapolate fundamentals. Formal estimation of the model indicates that an economy where a small fraction of agents significantly extrapolates fundamentals can explain the positive relation between earnings, vessel prices, and trading activity.

ABSTRACT. In efficient markets, asset prices are equal to their fundamentals. This classical view is considered valid for agricultural commodities’ spot and futures markets. However, fragmentation of orders impacts price dynamics, leading to modification in spot and futures’ trade frequency, relative trade frequency, and quantities exchanged. To highlight public policies on the impacts of fragmentation of orders, it is necessary to improve the understanding of its theoretical consequences. Based on a sequential trading framework, our main result showed that unbiased prices and a minimal volatility of fundamental basis are achieved not with optimal trade frequencies but with an optimal relative trade frequency.

ABSTRACT. We investigate nonzero sum stochastic differential games that arise in competitive equilibria of commodity market oligopolies. Our first setting is motivated by strategic capacity expansion between two production sectors (e.g. different electricity producers) which we model through repeated timing options that represent investment epochs. Our second setting is motivated by the consumer-producer interaction in the crude oil market; consumers control the drift (long-term trend) of the price, while producers generate instantaneous impulses through supply shocks. In both settings, we distinguish between a continuous stochastic factor X (price) that modulates instantaneous revenue rates and the discrete-state market regime M. We then show how to construct a market equilibrium that link local fluctuations in X to the emergent long-run dynamic equilibrium market organization described by M. We focus our attention on Markov feedback Nash equilibria of threshold type which allow tractable characterization of stationary equilibrium strategies. Explicit computations and comparative statics are provided when prices are locally described through (geometric) Brownian motion with drift.

ABSTRACT. In this paper, we take into account the interaction between stock market returns, exchange rates and oil price shocks in the model to consider the simultaneous response of stock market returns and exchange rates to local and global oil shocks and examine the difference between oil-exporting and oil-importing countries. We decompose global oil price shocks into demand and supply shocks, using a structural vector autoregressive model (SVAR) developed by Kilian (2009), and decompose local oil price shocks into demand and supply shocks following Ready’s (2018). Our findings show that local and global oil price shocks have different impacts on both stock market returns and exchange rates depending on the level of oil dependence of each country and the source of oil price changes. When the spillover effects are allowed for, changes in oil prices driven by local demand shocks have positive effects on stock market returns in both oil-exporting and oil-importing countries while global demand shocks have negative effects. But both global and local supply shocks have positive impact on stock market returns for oil-exporters while the results are mixed for oil-importers. Interestingly, local supply shocks have a significantly stronger impact than global supply shocks. For the effect on currencies, local demand and supply shocks contribute to an appreciation of local currency. Moreover, global demand shocks lead to the U.S. dollar appreciation while there is depreciation in the U.S. dollar following global supply shocks. Overall, we document important contemporaneous linkages across stock market returns and exchange rates to oil shocks.

ABSTRACT. Energy risks carry systematic effects in the cross-section of equity portfolios and individual stocks. Using a recursive framework we endogenously derive expected returns from investors' preferences for uncertainty and expectations about distress states of the economy, which we estimate from the crude oil options market. Increasing distress risks decrease firms' energy usage, triggering an amplification mechanism that impact expected returns. We empirically confirm this channel, stocks with lower exposure to energy risks exhibit higher returns months ahead, indicating that investors demand extra compensation to hold these assets. Energy risk exposure remains significant after controlling for stock market, commodity-specific and global risk factors, as well as abnormal media coverage. With the financialization of commodities, energy risk premia decrease and return predictability increases, strengthening the commodity-equity markets link.

ABSTRACT. We show that ETF arbitrage distorts market reaction to fundamental shocks. We confirm this hypothesis by creating a new measure of intensity of arbitrage transactions and using an event study analysis to estimate market reaction to economic shocks. Our measure of intensity of arbitrage is the empirical probability of simultaneous trading of ETF shares with its individual constituents calculated using high frequency data. Our measure accounts for statistical arbitrage, passive investment strategies, and netting of arbitrage positions over the day, which other measures cannot do. We conduct several empirical tests, including using a quasi-natural experiment, to confirm that our measure captures fluctuations in intensity of arbitrage transactions. 

ABSTRACT. Idiosyncratic skewness and coskewness are both important and widely studied in asset pricing. Furthermore, idiosyncratic skewness is closely related to the gambling preference. However, in commodity market, only the performance of total skewness has been studied until now. Thus, we examine the ability of idiosyncratic skewness and coskewness to further explain the cross-section of commodity returns at characteristics and factor levels. We find that idiosyncratic skewness has the explanatory power for the cross-section of commodity returns, while coskewness does not. Furthermore, we construct a tradeable factor based on idiosyncratic skewness, it is being positively priced cross-sectionally in commodity futures. In addition, the new measure of idiosyncratic skewness (IE) is better and robust in capturing skewness effect at both characteristics and factor levels. It implies that the gambling preference is the underlying driver of the skewness effect.

ABSTRACT. We present an empirical examination of the causal relations between oil futures prices and petroleum product futures prices, specifically gasoline and heating oil futures prices. The results of estimating a model that includes weekly price data spanning a 30-year period and which are divided into two subperiods split at year-end 2005, provide consistent evidence of causality running from oil futures prices to product futures prices. An extended model based on weekly data is estimated that includes the three price series along with additional potentially endogenous real market factors related to supply and demand in the oil, heating oil and gasoline markets. Inferences based upon the extended model are the same as those based on the models including prices alone. The conclusions are further supported by the estimation and analysis of price responses generated from a structural vector autoregressive model of the oil, heating oil and gasoline markets. The evidence suggests that the causal relations identified did not change during the period following 2005 when investment funds pursued active policies resulting in increased investment in oil futures.

ABSTRACT. Diamonds are considered a new investment asset, providing great opportunities for trading, investing and diversification. Hedge funds and financial intermediaries have shown increased interest in the diamond market offering diamonds as a successful hedging tool. However, the lack of standardization and creation of a reference tradeable asset prevented the existence of an exchange regulated trading platform for diamonds. In a previous study D’Ecclesia and Jotanovic (2017) suggest the creation of a Standardized Diamond basket index which may represent a tradeable asset for investors. At the moment a possible alternative to the polished diamond market index may be represented by diamond producing companies which are listed on the major stock Exchanges. (Neil, 2014; Wilson and England, 2014). The aim of this paper is to verify if Diamond producing companies may provide a proxy for the diamond market. Using time series econometric models and an Asset pricing framework we investigate if diamond mining stocks’ prices represent a robust proxy for diamond investments and if they do represent a hedge or safe haven. Our results show that the market of diamond stocks does not represent a valid investment alternative to the diamond commodity, and their dynamic is mainly driven by the stock market volatility.

ABSTRACT. We propose that - in equilibrium - changes in uncertainty can affect investment costs rather than levels. The conventional view of investment under uncertainty overlooks this effect. First, we develop a model to demonstrate this possibility. Next, we collect a unique dataset of oil rig rates to test this prediction. Detailed empirical analysis reveals that, after we control for several relevant variables, price uncertainty negatively affects our investment cost variable. We then highlight the channel underlying this effect, noting this cost endogenously adjusts to an exogenous shock to capital demand. Finally, we demonstrate the effect's economic significance by documenting its impact on investment values.

ABSTRACT. In this paper, we propose a risk-neutral multi-factors stochastic model for commodity demand. The model estimation is able to incorporate informations from demand historical time series as well as market prices of commodity financial derivatives. Then, the risk-neutral model is applied to the case study of crude oil commodity. Inspired from the empirical literature, we consider a two factors model for the demand dynamic. The factors are the commodity spot price and the real per capita gross domestic product. The factors coefficients are estimated using historical series. Furthermore, the risk-neutral model of crude oil spot price is calibrated on derivatives prices quoted in the market (Futures and options written on crude oil). Finally, we apply the risk-neutral demand dynamic to a real project valuation, e.g. a crude oil production plant. We assess the optimal operating capacity and the maximum expected profit of the production plant. Moreover, we evaluate the expected profit of the plant, considering an option of expansion and its optimal timing. In the real option valuation, we assess the impact of adopting average type options and we compare different risk neutral price/demand dynamics (e.g. diffusive and jump-diffusive processes) and different plausible values of the factors coefficients.

ABSTRACT. We study the impact of operational flexibility on capital structure in a dynamic model in which a firm has multiple debt issues and the equityholders choose the timing and financing of future growth options for production, as well as the operating policy for assets in place. We show that, all things being equal, firms with operational flexibility will use less debt than firms with inflexible assets. Ignoring asset flexibility in dynamic tradeoff models results in theoretical leverage ratios being biased high. We find that the least leveraged firms are flexible firms that are highly profitable and have substantial growth options.

ABSTRACT. This paper establishes game-theoretical (i.e., subsidy design and mechanism design) models to evaluate the economic value of a national strategy that combines solar energy integration and poverty mitigation in developing economies. With stylized models of households selling extra solar energy back to the grid, we investigate how the overall adoption levels would interact with potential barriers, including high adoption cost, “merit-order effect”, geographical heterogeneity, generation uncertainty, and asymmetry private information. Enabled by the blockchain technology, “smart contracts” contingent on solar uncertainties can be applied for “self-executing” the subsidy distribution process.

ABSTRACT. Renewable energy generation at the point of consumption (i.e., distributed generation) reduces consumer's electricity expenditure, and eliminates the cost, complexity, and inefficiency associated with power transmission and distribution. In this paper, we address the problem of how a consumer should invest in distributed renewable power generation to minimize the total expected cost of meeting his electricity demand. In contrast to the existing literature that focuses on grid-connected, large-scale investments in renewable power generation in the wholesale electricity market, we address investment in stand-alone, distributed renewable energy by an an individual consumer who participates in a regulated retail electricity market. We formulate an infinite-horizon, continuous-time model, where the utility moves first, and announces a retail electricity rate. Each consumer then acts strategically in deciding if, when, and how much distributed renewable generation capacity to install. We determine the structure of the consumer’s optimal stopping time for this investment decision, and the resulting optimal capacity of his installed distributed generation. We evaluate the impact of the investment in distributed renewable generation on the revenue received by an electric utility, and arrive at the structure of the pricing policy that maximizes that revenue. Using our results, we quantify the benefit to the consumer from using the optimal investment policy derived in our paper instead of the traditional rules for investing in renewable power generation. The resulting cost savings to the consumer are shown to be quite significant across a range of model parameters.

ABSTRACT. Quadratic hedging is a practically appealing approach for approximately replicating the random payoffs of European options in incomplete markets. This work broadens this methodology to the case of Bermudan options, for which an exercise policy needs to be optimized. This extension relies on constructing date specific approximate replicating portfolios. This modeling idea leads to a decomposition finding that enables adapting known quadratic hedging results to the date specific cash flows and formulating an option exercise policy optimization model. Optimal option exercise policies are in general time inconsistent. Time consistent option exercise policies can be optimized recursively. The proposed approach is relevant to both financial and real options.

ABSTRACT. We develop a normative framework for the optimal design, value assessment, and risk management integration of combined contingent claims. A risk-averse firm faces a mix of financially insurable and noninsurable risk. They seek optimal positioning in a pair of custom claims, one written on the insurable term, and another written on any listed index correlated to the noninsurable term. We prove that a unique optimum always exists unless the index is redundant, and the optimal payoff schedules satisfy a design equation which is dual to the partial differential equation arising in asset pricing. We derive a tight lower bound and an estimate of the firm's utility gain over the best single-claim hedges available so far: incremental benefit monotonically increases with the correlation of the index to the noninsurable term and decreases with the correlation of the index to the insurable term. We show that by integrating our optimal combined hedge with optimal operations management in a generalized newsvendor model, a firm may translate the corresponding utility enhancement into a significant reduction of operational effort. Our theoretical development unifies two strands of research in the interface between finance and operations.

ABSTRACT. This paper aims to provide alternative explanations for the Dutch disease by attributing the slower growth of the resource-abundant country to its real exchange rate movements in response to export price changes. While an increase in the world prices of primary commodities brings about higher export revenue for their exporters, an induced real currency appreciation can crowd out the exports of non-commodity industries (e.g., manufacturing) by undermining their price competitiveness in world trade. Our three-sector small open economy model predicts that a sufficiently high commodity price increase will lead to a decline in manufacturing sector due to the labor reallocation effect. Moreover, it suggests that a positive and large real exchange rate response also contributes to contraction in manufacturing sector. By how much a commodity price should increase and the real exchange rate should appreciate to cause a ‘disease’ is an empirical question, and we examine the patterns in 63 commodity-exporting countries during the period 1980-2010. Empirical results from the dynamic system GMM and Hansen (1999) threshold regression models provide supporting evidence for our propositions.

ABSTRACT. Global commodity and energy market prices are subject to currency rate fluctuations apart from other factors related to supply, demand, and storage economies. Therefore, for global commodity trading and trading in commodity futures and derivatives, firms need to account for currency rate fluctuations. We propose a new method of forecasting that can be used to forecast exchange rate variations and commodities. In many investment scenarios such as energy derivatives, and commodity derivatives it is important to forecast the prices of the underlying product or asset in local currencies. Currency rates have been known to be best described by random walk behavior and is difficult to beat the random walk forecast, the naive forecast, which is mean squared error (MSE) optimal. In this paper, we propose a novel method which builds on the naive forecast by introducing a local drift adjustment term. We call this method Not-So-Naive (NSN) forecast and illustrate, both theoretically, via simulations and empirical examples, that it can offer performance improvements - both in terms of statistical performance but also on economic performance.

ABSTRACT. This paper develops a new theoretical approach to calculate the optimal hedge ratio based on mean-swap variance optimization. Swap variance is a generalized risk measure equivalent to a polynomial combination of all return-moments. Using data of the S&P 500 index and the WTI crude oil, we find that minimizing-swap variance hedging deviates the traditional minimizing-variance hedging, especially during market downturns when volatilities are high, suggesting the necessity of an efficient hedging using the swap variance to measure risks. Mean-swap variance hedging realized a superior post-hedging performance in the crude oil market when considering a realistic risk aversion level, further confirming the hedging efficiency using swap variance.

ABSTRACT. We examine the role of entropy risk in explaining the cross-section of commodity returns motivated by a theoretical model. We show that the commodity's entropy, a summary of all higher moments of returns, captures the dispersion of the stochastic discount factor and therefore affects expected excess returns. We compute entropy risk premiums as the difference between the physical and risk-neutral measures of entropy, estimated from the commodity futures and options market. We form entropy-based portfolios, and find that commodities with high ex-ante entropy risk premium have higher subsequent returns. The results from the strategy hold after controlling for variance and skewness risk premiums, and are robust to global and commodity specific risk factors.

ABSTRACT. Cryptoassets attract more and more investors due to their large returns and diversification benefits. In this paper we analyse the dynamics and syn- chronization of regimes of a large cross-section of cryptoassets. Contrary to popular believe, only a minority of cryptoassets are cryptocurrencies. Thus in our study, we distinguish between payment cryptoassets (i.e. cryptocurren- cies), platform cryptoassets and protocol cryptoassets. In light of the hetero- geneity of cryptoasset, we show that they present different dynamics. That is, the analysis yields four regimes with different levels of variance: ranging from extremely low through "neutral" and high volatility regimes up to "explosive" volatility. Cryptoassets distinguish themselves by the time they spend in the "explosive" and "neutral" volatility regime.

ABSTRACT. Arbitrary speculative attacks on currencies can arise from self-fulfilling expectations (as in Obstfeld (1996)). This is a well-studied source of currency crises. In this paper, we show that blockchain distributed ledger technologies, such as those which support Bitcoin and Ethereum, may be adapted to eliminate self-fulfilling speculative attacks on a currency. Using a partial devaluation strategy, we show how to develop a stable currency peg. We show the peg is immune to speculative attacks arising from self-fulfilling prophecies. We show how to develop an implementation of the peg using smart contracts within the Ethereum protocol and estimate the size of (dollar) reserves and transaction costs needed to support the peg. Our theory and implementation reveal how a government may develop a stable currency peg, such as Pesos to Dollars (by way of a cryptocurrency), or how cryptocurrency issuers may develop a protocol which mitigates a large source of variation in cryptocurrency prices.