We apply an encompassing framework to assess the viability of hedging spot biodiesel price risk for four U.S. markets with a conventionally used heating oil futures contract and a soybean oil futures ...contract based on the logic that supply shifts (i.e., price of soybean oil as an input) drive biodiesel prices when binding blending mandates are in place. Results indicate that soybean oil futures should in fact be part of a composite hedge, and that in some instances greater hedging weight should be placed on the soybean oil futures contract than the conventionally used heating oil futures contract.
•Biodiesel price risk is often hedged with heating oil futures, since biodiesel substitutes for heating oil in diesel blends.•But binding renewable fuel standard mandates imply biodiesel price is driven by that of the primary input—soybean oil.•An encompassing framework compares effectiveness of both futures contracts and a composite hedge combining them.•Results favor a composite hedge with greater weight often placed on soybean oil than on heating oil futures contracts.
In this paper we propose a novel self-exciting jump-diffusion model for oil price dynamics based on a Hawkes-type process. In particular, the jump intensity is stochastic and path dependent, implying ...that the occurrence of a jump will increase the probability of observing a new jump and this feature of the model aims at explaining the jumps clustering effect. Moreover, volatility is described by a stochastic process, which can jump simultaneously with prices. The model specification is completed by a stochastic convenience yield. In order to estimate the model we apply the two-stage Sequential Monte Carlo (SMC) sampler (Fulop and Li, 2019) to both spot and futures quotations. From the estimation results we find evidence of self-excitation in the oil market, which leads to an improved fit and a better out of sample futures forecasting performance with respect to jump-diffusion models with constant intensity. Furthermore, we compute and discuss two optimal hedging strategies based on futures trading. The optimality of the first hedging strategy proposed is based on the variance minimization, while the second strategy takes into account also the third-order moment contribution in considering the investors attitudes. A comparison between the two strategies in terms of hedging effectiveness is provided.
•A new model for oil price dynamics including jumps clustering features.•Explicit valuation formulas for futures contracts in the modelling framework proposed.•A Bayesian estimation of the parameters for the model introduced.•An explicit computation of two optimal hedging strategies for the model proposed.
We investigate Japanese life insurance companies’ investment returns or volatilities and their discretionary decisions on foreign portfolio investments. These decisions include the proportion of ...foreign investments in the companies’ proprietary investments and the currency risk hedge. We consider the “carry trade” scenario when the market favors investing in high-yield currencies by borrowing the Japanese yen. We establish three results. First, the currency hedge relates positively to the investment returns under the carry trade scenario but negatively otherwise. Second, the proportion of foreign investments relates positively to the investment returns. Third, the investment returns significantly decrease under the carry trade scenario.
•Japanese local yields are too low, so the lifers must invest in foreign securities.•Currency hedging relates positively to investment returns when carry trades prevail.•Lifers’ proportion of foreign investments relates positively to investment returns.•Lifers’ investment returns significantly decrease under the carry trade scenario.•Lifers’ proportion of foreign investments relates positively to investment risk.
How do you write and present research well? Patience, Gregory S.; Boffito, Daria C.; Patience, Paul A.
Canadian journal of chemical engineering,
October 2015, Letnik:
93, Številka:
10
Journal Article
Recenzirano
Odprti dostop
Research is only half the work; the other half is writing and publishing. Your research is incomplete until you publish your data.1 Publishing is necessary but insufficient: others must cite your ...work.2 Writing well and preparing a coherent story will help your paper get past the first hurdle in the publishing process –the copy editor. The second hurdle is the editor, who checks if it is suitable for the journal, and reviews the , conclusions, and references.3 The final hurdle is the reviewers, who devote more time to validate the hypotheses, results, and interpretation. Rejection rates across journals are increasing.4 Science copy editors send one out of five submissions to the editors, and their overall rejection rate is 93 %. The Canadian Journal of Chemical Engineering rejects close to 3 out of 4 papers researchers submit. Write better so journals accept your papers and researchers cite them.
Utilizing firms in the S&P 500, we study whether greater transparency in the reporting of other comprehensive income (OCI) items, as mandated by ASU 2011-05, resulted in a reduction in information ...asymmetry, a change in the value relevance of this information, or a change in hedging practice. Our results show that while transparent reporting reduced information asymmetry, firms that engage in cash flow hedging do have greater information asymmetry than their counterparts that do not hedge. We find evidence that investors penalize firm value for greater volatility of OCI relative to net income volatility when reported transparently. When permitted, managers were able to mitigate the negative impact by reporting OCI only in the Statement of Shareholders’ Equity. We conclude that managers’ concerns regarding potential confusion surrounding OCI volatility following more prominent reporting led to changes in hedging behavior. After transparent reporting, we find a reduced likelihood of foreign currency cash flow (FXCF) hedges and a reduced level of FXCF hedging among firms experiencing the greatest volatility of unrealized hedging gains and losses.
We study the relationship between Bitcoin and commodities by assessing the ability of Bitcoin to act as a diversifier, hedge, or safe haven against daily movements in commodities in general, and ...energy commodities in particular. We focus on energy commodities because energy, in the form of electricity, is an essential input in the Bitcoin production. For the entire period, results show that Bitcoin is a strong hedge and a safe-haven against movements in both commodity indices. We further examine whether that ability is also present for non-energy commodities and our analysis show insignificant results when energy commodities are excluded from the general commodity index. We also account for the December 2013 Bitcoin price crash and our results reveal that Bitcoin hedge and safe-haven properties against commodities and energy commodities are only present in the pre-crash period, whereas in the post-crash period Bitcoin is no more than a diversifier. In addition to uncovering the time-varying role of Bitcoin, we highlight the dissimilarity in the dynamic correlations between the extreme downward and extreme upward movements.
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