金融代写|交易策略作业代写Trading strategy代考|FINANCE362

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金融代写|交易策略作业代写Trading strategy代考|Concluding Remarks

When we procure different fuels at prices linked to different price indicators, we should understand the spillover effect of the price level and the risk between these indicators. We should determine the diversification effect of procurement based on the total connectedness of an energy portfolio. We must monitor the connectedness of the portfolio, including potential price indicators and grasp the impact of excluding components already in our portfolio. Quantitative measures of risk of such a potential portfolio is extremely important. It is beneficial to consider what components we should have and how much we should hold to reconstruct the portfolio. Moreover, the measurement results may affect the financial strategy.

This chapter describes the connectedness index proposed by Diebold and Yilmaz [4], which can capture the spillover effect between markets. We then introduce Baruník and Křehlík’s [1] spectral decomposition method, which determines when spillover factors occur. Moreover, we explain the EGARCH model, which can generate each volatility series needed to examine the risk spillover effects.

We illustrate two cases: a crude oil portfolio and a natural gas portfolio. We examine each portfolio, which consists of representative markets for Europe, North America, and Asia; specifically, Brent, WTI, and Dubai-Oman to represent crude oil markets and the TTF, HH, and JKM to represent natural gas markets, respectively.
First, we describe the crude oil markets. While Dubai-Oman’s returns and volatility are smaller than those of Brent or WTI, the price series, return series, and volatility series of these three indicators appear to fluctuate synchronously. The total connectedness of the return and volatilities series are $42.95$ and $62.00 \%$, respectively. These crude oil markets appear to be integrated at a relatively high level. The spillover effects of returns and volatility between Brent and WTI are mutually strong. Dubai-Oman receives considerable risk from both Brent and WTI.

We next describe the natural gas markets. The prices, returns, and volatility for the TTF, HH, and JKM fluctuate in three different ways. Although the total connectedness of volatility is $16.90 \%$, that of returns is $1.72 \%$. This result indicates that intercontinental natural gas market liquidity may still be low. Any spillover effect of returns is less than $1 \%$, except between TTF and JKM. The volatility spillover effects larger than $10 \%$, are from $\mathrm{HH}$ to TTF, TTF to JKM, and HH to JKM.

金融代写|交易策略作业代写Trading strategy代考|Hedging Strategy with Futures Contracts

A futures contract is a promise to buy or sell a security at a currently agreed upon price at a predetermined time in the future. Futures are one of the most representative derivatives along with options and swaps. Commodity futures are those whose underlying assets are specific standardized commodities (e.g., precious metals, agricultural products, energy, etc.) and are often listed on commodity exchanges. Although they can be sold and bought within their maturity, they will automatically settle at maturity. The main purposes of trading commodity futures are risk hedging, speculation (e.g., diversified investment beyond traditional financial securities and trading based on market forecasts), arbitrage (e.g., pair trading between highly correlated securities and trading between securities with different maturities considering risks and interest rates), and procurement only in the case of physical settlement.

For many non-financial companies, commodity futures represent a means to hedge risk. Trading futures can eliminate uncertainties arising from price fluctuations because they determine future cash flows. We can not only determine profits in advance but also avoid unacceptable losses by trading futures. For example, firms often buy crude oil futures to avoid losses caused by future spot price increases when procuring crude oil. If the crude oil spot price actually rises, the profit obtained by liquidating the futures can cover the loss from the price increase in the spot market. As a completely opposite example, when selling electricity, firms often sell electricity futures to avoid losses due to future spot price declines. If the electricity spot price actually falls, the profit gained by counter-trading futures can cover the loss from the actual price drop. Many futures trades have the advantage of lowering hedging costs because of margin trading, which itself often reduces hedging costs in futures trades.

If we trade futures to hedge the risk of spot price fluctuations, we must be careful to curb the diversification of the portfolio return consisting of a spot and its futures. The ratio of future positions to the spot position that minimizes this variance is the optimal hedge ratio (OHR). The OHR is obtained by dividing the covariance of the spot and futures returns by the variance of the futures return. Various multivariate generalized autoregressive conditional heteroscedasticity (GARCH) models have been proposed to capture the conditional covariance between multiple asset returns and the conditional variance of each return. Traders can monitor the OHRs calculated from the estimated multivariate GARCH model to design an optimal portfolio.

金融代写|交易策略作业代写Trading strategy代考|FINANCE362

交易策略代考

金融代写|交易策略作业代写Trading strategy代考|Concluding Remarks

当我们以与不同价格指标挂钩的价格采购不同的燃料时,我们应该了解价格水平的溢出效应以及这些指标之间的风险。我们应该根据能源组合的总连通性来确定采购的多元化效应。我们必须监控投资组合的关联性,包括潜在的价格指标,并掌握排除我们投资组合中已有成分的影响。这种潜在投资组合的风险量化措施极为重要。考虑我们应该拥有哪些成分以及我们应该持有多少来重建投资组合是有益的。此外,计量结果可能会影响财务策略。

本章介绍 Diebold 和 Yilmaz [4] 提出的连通性指数,该指数可以捕捉市场之间的溢出效应。然后,我们介绍 Baruník 和 Křehlík 的 [1] 谱分解方法,该方法确定溢出因子何时出现。此外,我们解释了 EGARCH 模型,它可以生成检查风险溢出效应所需的每个波动率序列。

我们举例说明两个案例:原油组合和天然气组合。我们检查每个投资组合,其中包括欧洲、北美和亚洲的代表性市场;具体而言,Brent、WTI 和 Dubai-Oman 代表原油市场,TTF、HH 和 JKM 分别代表天然气市场。
首先,我们描述原油市场。虽然迪拜-阿曼的收益和波动率小于布伦特或 WTI,但这三个指标的价格序列、收益序列和波动率序列似乎同步波动。收益和波动率序列的总连通性是42.95和62.00%, 分别。这些原油市场似乎在一个相对较高的水平上整合。布伦特和 WTI 之间回报和波动的溢出效应是相互强烈的。迪拜-阿曼从布伦特原油和 WTI 原油中承担了相当大的风险。

我们接下来描述天然气市场。TTF、HH 和 JKM 的价格、回报和波动性以三种不同的方式波动。尽管波动率的总连通性是16.90%, 回报率是1.72%. 这一结果表明洲际天然气市场的流动性可能仍然很低。任何回报的溢出效应都小于1%, TTF 和 JKM 之间除外。波动溢出效应大于10%, 来自HH到 TTF,TTF 到 JKM,HH 到 JKM。

金融代写|交易策略作业代写Trading strategy代考|Hedging Strategy with Futures Contracts

期货合约是承诺在未来预定时间以当前商定的价格买卖证券。期货是与期权和掉期一样最具代表性的衍生品之一。商品期货是标的资产为特定标准化商品(如贵金属、农产品、能源等)的商品期货,通常在商品交易所上市。虽然它们可以在到期时买卖,但它们会在到期时自动结算。商品期货交易的主要目的是风险对冲、投机(如超越传统金融证券的多元化投资和根据市场预测进行交易)、套利(如

对于许多非金融公司而言,商品期货是一种对冲风险的手段。交易期货可以消除价格波动带来的不确定性,因为它们决定了未来的现金流量。我们不仅可以提前确定利润,还可以通过交易期货来避免不可接受的损失。例如,企业在采购原油时,往往会买入原油期货,以避免未来现货价格上涨带来的损失。如果原油现货价格真的上涨,平仓所获得的利润可以弥补现货市场价格上涨带来的损失。举一个完全相反的例子,在出售电力时,公司通常会出售电力期货,以避免因未来现货价格下跌而造成损失。如果电力现货价格真的下跌,反向交易期货获得的利润可以弥补实际价格下跌带来的损失。由于保证金交易,许多期货交易具有降低对冲成本的优势,而保证金交易本身通常会降低期货交易中的对冲成本。

如果我们交易期货来对冲现货价格波动的风险,我们必须小心遏制由现货及其期货组成的投资组合收益的多元化。使这种方差最小化的期货头寸与现货头寸的比率就是最优对冲比率 (OHR)。OHR 是用现货和期货收益的协方差除以期货收益的方差得到的。已经提出了各种多元广义自回归条件异方差 (GARCH) 模型来捕获多个资产收益之间的条件协方差和每个收益的条件方差。交易者可以监控从估计的多元 GARCH 模型计算出的 OHR,以设计最佳投资组合。

金融代写|交易策略作业代写Trading strategy代考

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