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## 金融代写|金融衍生品代写Financial Derivatives代考|FOREIGN EXCHANGE FORWARD AND FUTURES CONTRACTS

The foreign exchange forward market is an over-the-counter (OTC) market that trades on a worldwide basis and is dominated by large financial institutions. Typical contract amounts are quite large, and the market sees very few individual investors. By contrast, there are foreign exchange futures markets in many countries. In comparison with the forward market, these futures markets are quite small. The discussion of these markets will focus on the forward market, which will be contrasted with a single foreign exchange futures market, the Chicago Mercantile Exchange in the United States. ${ }^1$

## 金融代写|金融衍生品代写Financial Derivatives代考|FOREIGN EXCHANGE OPTIONS

\begin{aligned} C_t & =e^{-r_F(T-t)} F C N\left(d_1\right)-X e^{-r_d(T-t)} N\left(d_2\right) \ P_t & =X e^{-r_F(T-t)} N\left(-d_2\right)-F C e^{-r_F(T-t)} N\left(-d_1\right) \ d_1 & =\frac{\ln (F C / X)\left(r_D-r_F+0.5 \sigma^2\right)(T-t)}{\sigma \sqrt{T-t}} \ d_2 & =d_1-\sigma \sqrt{T-t} \end{aligned}

\begin{aligned} C_t & =\text { price of a call option (priced in the domestic currency) on } \ & \text { foreign currency } F C \ P_t & =\text { price of a put option (priced in the domestic currency) on } \ & \text { foreign currency } F C \ F C & =\text { a quantity of the foreign currency } \ r_D, r_F & =\text { domestic and foreign interest rates, respectively } \ X & =\text { exercise price } \ T-t & =\text { time until expiration } \ \sigma^2 & =\text { variance of the foreign currency value } \ \mathrm{N}(\bullet) & =\text { cumulative normal function } \end{aligned}

## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

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## 金融代写|金融衍生品代写Financial Derivatives代考|Single-Stock Futures

Single-stock futures have been developed as an alternative for managing the risk of investing in stocks. Single-stock futures offer a market to buy or sell the underlying stock at some future date, typically at some short horizon (within a year). They represent a somewhat lower-cost alternative to stock options, since entering into a futures contract requires only margins. Worldwide, and most predominantly in South Africa, single-stock futures trade on a wide variety of stocks. As with stock options, however, trading is likely to be concentrated in firms where uncertainty is greatest.

Although in the United States, single-stock futures typically are settled on a $T+3$ basis with the delivery of the underlying stock, the use of single-stock futures facilitates short positions in stock. By using single-stock futures, an investor avoids the costly logistics required for borrowing shares in a short sale arrangement. Further, the relatively low ( 20 percent) margins on U.S. single-stock futures make for a low-cost competitive alternative to options for hedging purposes.

Single-stock futures are priced with a simple present value/future value relation. More specifically, the price of a single-stock future should represent the present value of today’s stock price along with the present value of any future dividends that might be paid out before the futures contract expires. Mathematically, we can state that the value of a single-stock future $F$ is
$$F=\left(S_o-D\right) e^{r T}$$
where
$S_o=$ current stock price
$D=$ present value of dividends paid during the life of the futures contract
$T=$ time to maturity (in years)
$r=$ continuously compounded risk-free rate of interests over the life of the futures contract

## 金融代写|金融衍生品代写Financial Derivatives代考|Futures on Stock Indexes

Some of the most actively traded futures contracts involve stock index futures. Stock index futures range from broad-based to narrow-based indexes. The most broadly traded index futures are based on country-specific indexes such as the S\&P 500, the Financial Times Stock Index FTSE 100 (London-listed companies), the Deutschen Actien Index DAX 30 (Frankfurt-listed companies), and the Cotation Assistee en Continu CAC 40 (Euronext Paris-listed companies). Stock indexes based on other countries typically are narrower in scope. For instance, the Portugese Stock Index PSI-20 index includes 20 Euronext Lisbon-listed companies, with the top 5 firms representing approximately 75 percent of the market capitalization of the entire index.

In the United States, OneChicago lists a number of narrow-based index futures. The indexes traded here are typically comprised of portfolios of four to seven stocks, many slanted toward Canadian stocks.

Portfolio managers at mutual funds, hedge funds, insurance companies, and other institutions face systematic portfolio risks when they hold equity portfolios. Likewise, market makers and dealers who sell index products to clients also can be exposed to systematic risk. Stock index futures provide an efficient mechanism for managing this portfolio risk at a relatively low cost. Since entering into a futures contract requires only margin payments, these institutions can avoid the premium payment that accompanies index options.

## 金融代写|金融衍生品代写Financial Derivatives代考|Single-Stock Futures

$$F=\left(S_o-D\right) e^{r T}$$

$S_o=$当前股价
$D=$在期货合约有效期内支付的股息的现值
$T=$成熟期(年)
$r=$在期货合约有效期内连续复合无风险利率

## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

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## 金融代写|金融衍生品代写Financial Derivatives代考|Theory of Normal Backwardation

According to the theory of normal backwardation, speculators in commodity futures will receive a positive return as compensation for the price risk transferred to them by the hedger. Keynes’s (1930) original theory assumed that the hedger, as a producer, would sell futures. The risk premium would be paid to the long speculator by setting the futures price below the expected future spot price: The futures prices would, on average, rise through time, resulting in a positive rate of return for the long speculator.

Note that this use of the term backwardation differs from that used in describing the basis or futures curve. Backwardation occurs when the current spot price is greater than a futures price. Normal backwardation, however, describes the relationship between the forward price and the expected spot price: The forward price is set below the expected spot price, and this persistent downward bias in the forward price rewards the long speculator with positive returns.

A modification of the normal backwardation model argues that not all markets will return a risk premium to the speculator (Telser 1958). Competition between speculators normally will drive the risk premium to zero, so only markets in which there are too few speculators willing to take on hedger risk will pay a risk premium to a long position. Such a thin market would be characterized by low liquidity, with few transactions, a low volume of trade in the commodity relative to its production, and consequently large price fluctuations.

Keynes’s original model has been modified to recognize that not all hedging interest will be short. Hedgers can be producers or consumers, and speculators will garner positive returns if they take a position opposite to the majority of hedgers in the market. If hedgers are net short, then a long speculative position should result in a positive return, as in the original backwardation model. If hedgers are net long in a particular market, then speculators are paid to go short, and a short position will reap positive returns. Thus, to reap consistently positive returns, speculators must be able to tell where hedging net interest will be in a particular market.
It is important to recognize that the risk premium on commodity futures contracts can be linked to convenience yield. We have seen that if futures prices are at less than full carry because of inadequate inventories, then convenience yield will be relatively large; this implies increased uncertainty and a demand for risk transference. If speculators are to be rewarded for providing a risk transfer function, then periods of high convenience yield (when futures are driven below the current spot price- the traditional definition of backwardation) may also be periods in which long futures positions exhibit positive returns. The size of the risk premium will depend on inventory levels, which drive the convenience yield, and the relative risk sensitivities of inventory holders (hedgers) and investors (speculators).

## 金融代写|金融衍生品代写Financial Derivatives代考|COMMODITY INVESTMENT STRATEGIES

Commodity indexes are used to track commodity prices and to represent a portfolio of commodity positions. Since commodities are extremely heterogeneous, the behavior of a particular index, and comparisons of index performance, can be very sensitive to how a given index is constructed. Indexes vary by the selection and weighting of constituent components, and how components are rebalanced.

The Standard \& Poor’s Goldman Sachs Commodity Index (SP-GSCI) and the Dow Jones-AIG Commodity Index (DJ-AIGCI) are the most widely used in structuring tradable commodity index products, and futures are traded on these indexes at the CMEG. Other indexes include the Reuters/Jeffries Commodity Research Bureau (CRB) and the Deutsche Bank Liquid Commodity Index (DBLCI).

All the indexes just mentioned include a range of commodity sectors, but specific commodities and their weights differ. Component selection involves a trade-off between the index’s ability to represent commodities as an asset class and the ease with which the index can be replicated. For instance, the CRB gives a broad picture of overall commodity price movements while the DJ-AIG selects components based on the liquidity of the futures contract. TheSP-GSCI contains the largest number of commodities (25), while the DJ-AIG constrains the weighting that any individual sector can have in the index. Many indexes use only nearby prices, but others (CRB) include other delivery months. A different index approach is taken by the Nasdaq/OMX Global Agriculture Index, which tracks the performance of shares in companies with activity in agriculture or farming. Since a commodity index cannot use market capitalization for a weighting scheme (all futures involve an equal long and short position), weights are determined by other means. The CRB uses equal weighting, but other indexes use world production or consumption data to reflect relative economic importance.

Changes in relative prices can alter the original weighting scheme over time, so an index may be rebalanced periodically. However, how an index is rebalanced can affect its performance since rebalancing can imply a particular investment strategy for the index portfolio. Rebalancing an equally weighted portfolio, for instance, necessitates selling appreciating commodities and buying depreciating commodities. Similarly, infrequent rebalancing can mimic a momentum investment strategy.

## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

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## 金融代写|投资组合代写Portfolio Theory代考|ESTIMATING MODELS WITH EXCESS RETURNS

When excess returns $\left(R^e\right)$ are used to estimate and test asset pricing models, the moment conditions (pricing equations) are
$$E\left(m R^e\right)=0_N \cdot$$
Let $m=\theta_0-\left(\theta_1 f_1+\cdots+\theta_K f_K\right)$. In this case, the mean of the SDF cannot be identified or, equivalently, the parameters $\theta_0$ and $\left(\theta_1, \ldots, \theta_K\right)$ cannot be identified separately. This requires a particular choice of normalization. One popular normalization is to set $\theta_0=1$, in which case $m=1-\left(\theta_1 f_1+\cdots+\theta_K f_K\right)$. An alternative (preferred) normalization is to set $\theta_0=1+\theta_1 E\left(f_1\right)+\cdots+\theta_K E\left(f_K\right)$, in which case $m=1-\theta_1\left[f_1-E\left(f_1\right)\right]-\cdots-\theta_K\left[f_K-E\left(f_K\right)\right]$ with $E(m)=1$. These two normalizations can give rise to very different results (see Kan and Robotti, 2008; Burnside, 2010).

Kan and Robotti (2008) argue that when the model is misspecified, the first (raw) and the second (de-meaned) normalizations of the SDF produce different GMM estimates that minimize the quadratic form of the pricing errors. Hence, the pricing errors and the $p$-values of the specification tests are not identical under these two normalizations. Moreover, the second (de-meaned) specification imposes the constraint $E(m)=1$ and, as a result, the pricing errors and the $\mathrm{HJ}$-distances are invariant to affine transformations of the factors. This is important because in the first normalization, the outcome of the model specification test can be easily manipulated by simple scaling of factors and changing the mean of the SDF. This problem is not only a characteristic of linear SDFs but also arises in nonlinear models. The analysis in Burnside (2010) further confirms these findings and links the properties of the different normalizations to possible model misspecification and identification problems discussed in the previous two subsections.

## 金融代写|投资组合代写Portfolio Theory代考|CONDITIONAL MODELS WITH HIGHLY PERSISTENT PREDICTORS

The usefulness of the conditional asset pricing models crucially depends on the existence of some predictive ability of the conditioning variables for future stock returns. While a large number of studies report statistically significant coefficients for various financial and macro variables in in-sample linear predictive regressions of stock returns, several papers raise the concern that some of these regressions may be spurious. For example, Ferson, Sarkissian, and Simin (2003) call into question the predictive power of some widely used predictors, such as the term spread, the book-to-market ratio, and the dividend yield. Spurious results arise when the predictors are strongly persistent (near unit root processes) and their innovations are highly correlated with the predictive regression errors. In this case, the estimated slope coefficients in the predictive regression are biased and have a nonstandard (nonnormal) asymptotic distribution (Elliott and Stock, 1994; Cavanagh, Elliott, and Stock, 1995; Stambaugh, 1999). As a result, $t$-tests for statistical significance of individual predictors based on standard normal critical values could reject the null hypothesis of no predictability too frequently and falsely signal that these predictors have predictive power for future stock returns. Campbell and Yogo (2006) and Torous, Valkanov, and Yan (2004) develop valid testing procedures when the predictors are highly persistent and revisit the evidence on the predictability of stock returns.

Spuriously significant results and nonstandard sampling distributions also tend to arise in long-horizon predictive regressions, where the regressors and/or the returns are accumulated over $r$ time periods so that two or more consecutive observations are overlapping. The time overlap increases the persistence of the variables and renders the sampling distribution theory of the slope coefficients, $t$-tests and $R^2$ coefficients, nonstandard. Campbell (2001) and Valkanov (2003) point out several problems that emerge in long-horizon regressions with highly persistent regressors. First, the $R^2$ coefficients and $t$-statistics tend to increase with the horizon, even under the null of no predictability, and the $R^2$ is an unreliable measure of goodness of fit in this situation. Furthermore, the $t$-statistics do not converge asymptotically to well-defined distributions and need to be rescaled to ensure valid inference. Finally, the estimates of the slope coefficients are biased and, in some cases, not consistently estimable. All these statistical problems provide a warning to applied researchers and indicate that the selection of conditioning variables for predicting stock returns should be performed with extreme caution.

## 金融代写|投资组合代写Portfolio Theory代考|ESTIMATING MODELS WITH EXCESS RETURNS

$$E\left(m R^e\right)=0_N \cdot$$

Kan和Robotti(2008)认为，当模型被错误指定时，SDF的第一次(原始)和第二次(去均值)归一化会产生不同的GMM估计，从而使定价误差的二次形式最小化。因此，在这两种归一化下，规范测试的定价误差和$p$ -值是不相同的。此外，第二个(去均值)规范施加了约束$E(m)=1$，因此，定价误差和$\mathrm{HJ}$ -距离对因子的仿射变换是不变的。这很重要，因为在第一个归一化中，模型规范测试的结果可以通过简单的因子缩放和改变SDF的平均值来轻松地操纵。这个问题不仅是线性sdf的一个特点，而且在非线性模型中也会出现。Burnside(2010)的分析进一步证实了这些发现，并将不同归一化的特性与前两小节中讨论的可能的模型错误规范和识别问题联系起来。

## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

Posted on Categories:Investment Portfolio, 投资组合, 金融代写

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## 金融代写|投资组合代写Portfolio Theory代考|GMM Estimation and Evaluation of Asset Pricing Models in SDF Form

Using Equation 3.11, the pricing errors of the $N$ test assets can be expressed as
$$g(\theta)=E[m(1+R)]-1_N=E\left[(1+R) \tilde{f}^{\prime} \theta\right]-1_N=D \theta-1_N,$$
where $D=E\left[(1+R) \tilde{f}^{\prime}\right]$. Let $t=1,2, \ldots, T$ denote the number of time series observations on the test assets and the factors. The sample analog of the pricing errors is given by
$$g_T(\theta)=\frac{1}{T} \sum_{t=1}^T\left(1+R_t\right) \tilde{f}t^{\prime} \theta-1_N .$$ For a given weighting matrix $W_T$, the GMM estimator of $\theta$ minimizes the quadratic form $$g_T(\theta)^{\prime} W_T g_T(\theta)$$ and solves the first-order condition $$D_T^{\prime} W_T\left(D_T \theta-1_N\right)=0$$ where $D_T=\frac{\partial g_T(\theta)}{\partial \theta^{\prime}}=\frac{1}{T} \sum{t=1}^T\left(1+R_t\right) \tilde{f}_t^{\prime}$. Solving this system of linear equations for $\theta$ yields
$$\hat{\theta}=\left(D_T^{\prime} W_T D_T\right)^{-1}\left(D_T^{\prime} W_T 1_N\right)$$

## 金融代写|投资组合代写Portfolio Theory代考|Beta-Pricing Models and Two-Pass Cross-Sectional Regressions

From Equation 3.13, the expected-return errors of the $N$ assets are given by
$$e=E[R]-B \gamma .$$
A popular goodness-of-fit measure used in many empirical studies is the crosssectional $R^2$. Following Kandel and Stambaugh (1995), this is defined as
$$R^2=1-\frac{Q}{Q_0},$$
where $Q=e^{\prime} W e, Q_0=e_0^{\prime} W e_0, e_0=\left[I_N-1_N\left(1_N^{\prime} W 1_N\right)^{-1} 1_N^{\prime} W\right] E[R]$ represents the deviations of mean returns from their cross-sectional average and $W$ is a positive-definite weighting matrix. Popular choices of $W$ in the literature are $W=$ $I_N$ (ordinary least squares $[\mathrm{OLS}]$ ), $W=\operatorname{Var}[R]^{-1}$ (generalized least squares $[\mathrm{GLS}]$ ), and $W=\Sigma_d^{-1}$ (weighted least squares [WLS]), where $\Sigma_d$ is a diagonal matrix containing the diagonal elements of $\Sigma$, the variance-covariance matrix of the residuals from the first-pass time series regression. In order for $R^2$ to be well defined requires assuming that $E[R]$ is not proportional to $1_N$ (the expected returns are not all equal) so that $Q_0>0$. Note that $0<R^2<1$ and it is a decreasing function of the aggregate pricing-error measure $Q$. Thus, $R^2$ is a natural measure of goodness of fit.

As emphasized by Kan and Zhou (2004), $R^2$ is oriented toward expected returns whereas the HJ-distance evaluates a model’s ability to explain prices. With the zero-beta rate as a free parameter, the most common approach in the asset pricing literature, Kan and Zhou show that the two measures need not rank models the same way. Thus, both measures are of interest, with the choice depending on the economic context and perhaps the manner in which a researcher envisions applying the models.

## 金融代写|投资组合代写Portfolio Theory代考|GMM Estimation and Evaluation of Asset Pricing Models in SDF Form

$$g(\theta)=E[m(1+R)]-1_N=E\left[(1+R) \tilde{f}^{\prime} \theta\right]-1_N=D \theta-1_N,$$

$$g_T(\theta)=\frac{1}{T} \sum_{t=1}^T\left(1+R_t\right) \tilde{f}t^{\prime} \theta-1_N .$$对于给定的权重矩阵$W_T$, $\theta$的GMM估计量最小化了二次形式$$g_T(\theta)^{\prime} W_T g_T(\theta)$$并解决了一阶条件$$D_T^{\prime} W_T\left(D_T \theta-1_N\right)=0$$，其中$D_T=\frac{\partial g_T(\theta)}{\partial \theta^{\prime}}=\frac{1}{T} \sum{t=1}^T\left(1+R_t\right) \tilde{f}_t^{\prime}$。求解$\theta$产量的线性方程组
$$\hat{\theta}=\left(D_T^{\prime} W_T D_T\right)^{-1}\left(D_T^{\prime} W_T 1_N\right)$$

## 金融代写|投资组合代写Portfolio Theory代考|Beta-Pricing Models and Two-Pass Cross-Sectional Regressions

$$e=E[R]-B \gamma .$$

$$R^2=1-\frac{Q}{Q_0},$$

## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

Posted on Categories:Investment Portfolio, 投资组合, 金融代写

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## 金融代写|投资组合代写Portfolio Theory代考|THE EFFICIENT FRONTIER AND ASSET PRICING

The previous section detailed the various scenarios of portfolio optimization available to an investor. The chapter now adds the assumptions of homogeneous information about $\mu, V, R_f$, market efficiency, and frictionless and costless trading to show the implications for equilibrium of portfolio theory.

Recall the case with $N$ risky assets and a risk-free asset. This section now shows how the Sharpe-Lintner CAPM (Sharpe, 1964) follows directly. If all investors have the same information $\mu, V$, they all agree on the tangency portfolio, which is $T$ in Figure 2.3. In equilibrium, demand meets supply and this tangency portfolio must be the capitalization-weighted portfolio of all risky assets, also known as the market portfolio. Therefore, the cap-weighted market portfolio is the tangency portfolio on the efficient frontier. It is the mean-variance efficient portfolio because no other portfolio has a higher Sharpe ratio. This is the basis for indexing investment. The CAL defined by the market is called the capital market line (hereafter, the CML). It is the optimal CAL given the assumptions made at the beginning of the section.

Consider now a risk-free rate $R_f$ and a frontier of two risky assets, $i$ and $M$. Quadratic optimization shows that the portfolio with the maximum Sharpe ratio, the tangency portfolio, has a weight as shown in Equation 2.6:
$$w_i^=\frac{\left(\mu_i-R_f\right) \sigma_M^2-\left(\mu_M-R_f\right) \sigma_{i M}}{\left.\left(\mu_i-R_f\right) \sigma_M^2+\left(\mu_M-R_f\right) \sigma_i^2-\mu_i+\mu_M-2 R_f\right) \sigma_{i M}}$$ Let us apply this result to the context of equilibrium, with $M$ representing the market portfolio, and $i$ representing any security. In equilibrium, $M$ already contains $i$ in the optimal amount because it is already the mean-variance efficient, tangency portfolio of the frontier of all securities in the economy. Therefore, the weight $w_i^$ must be zero in equilibrium. Now set the numerator in Equation 2.6 to equal to zero. This immediately yields the well-known CAPM equation
$$\mu_i=R_f+\left(\mu_M-R_f\right) \beta_{i M}$$
where beta $\left(\beta_{i M}\right)$ is now considered with respect to the market portfolio. In Figure 2.4 , the solid lines show a two-asset frontier of the market and a security $P_1 \cdot M$ is the tangency portfolio of that frontier because the expected return of $P_1$ was set equal to the CAPM.

## 金融代写|投资组合代写Portfolio Theory代考|ACTIVE MANAGEMENT AND THE INFORMATION RATIO

This section discusses active management and portfolio performance evaluation. The best-known measure of performance, the Sharpe ratio, discussed in the previous sections, is only valid to rank mutually exclusive investments. The Sharpe ratio does not indicate how to optimally combine competing funds.

The previous section explains how in equilibrium, the capitalization-weighted market portfolio $\mathrm{M}$ achieves the best Sharpe ratio. In the active asset allocation framework, the manager identifies securities that may help improve upon the market portfolio’s Sharpe ratio. This section introduces the information ratio, widely used in quantitative active asset management, which indicates how a security contributes to the Sharpe ratio of a portfolio. The reasoning will parallel the Sharpe-Lintner CAPM proof seen above, incorporating the fact that the expected returns of some securities differ from the CAPM prediction and therefore will improve upon the Sharpe ratio of the market. Departures from the CAPM are modeled via Jensen’s (1968) apha, $a$, as shown in Equation 2.9:
$$\mathrm{E}\left(\mathrm{R}{\mathrm{i}}\right)=\alpha_1+\mathrm{R}_f+\beta_i \mathrm{E}\left(\mathrm{R}{\mathrm{M}}-\mathrm{R}{\mathrm{f}}\right)$$ Equation 2.9 nests the CAPM, in which case $a$ is 0 . To estimate alpha and beta, Jensen runs the time series regression shown in Equation 2.10: $$R{i t}-R_{f t}=\alpha_i+\beta_i\left(R_{M t}-R_{f t}\right)+\varepsilon_{i t},$$
where $R_{i t}$ is the return on the asset $\mathrm{i} ; R_{f t}$ is the risk-free rate; $R_{M t}$ is the market index return; and $\varepsilon$ is the random error of the regression, also known as the unsystematic or idiosyncratic return. The regression in Equation 2.10 also estimates the standard deviation of the idiosyncratic return $\sigma_{\varepsilon}$. In fact, it performs the variance decomposition for security $i$, shown in Equation 2.11:
$$\sigma_i^2=\beta_i^2 \sigma_M^2+\sigma_{\varepsilon, i}^2$$

## 金融代写|投资组合代写Portfolio Theory代考|THE EFFICIENT FRONTIER AND ASSET PRICING

$$w_i^=\frac{\left(\mu_i-R_f\right) \sigma_M^2-\left(\mu_M-R_f\right) \sigma_{i M}}{\left.\left(\mu_i-R_f\right) \sigma_M^2+\left(\mu_M-R_f\right) \sigma_i^2-\mu_i+\mu_M-2 R_f\right) \sigma_{i M}}$$让我们把这个结果应用到均衡的背景下，$M$代表市场投资组合，$i$代表任何证券。在均衡中，$M$已经包含了最优数量的$i$，因为它已经是经济中所有证券边界的均值-方差有效切线投资组合。因此，在平衡状态下，权重$w_i^$必须为零。现在将方程2.6中的分子设为0。这立即产生了著名的CAPM方程
$$\mu_i=R_f+\left(\mu_M-R_f\right) \beta_{i M}$$

## 金融代写|投资组合代写Portfolio Theory代考|ACTIVE MANAGEMENT AND THE INFORMATION RATIO

$$\mathrm{E}\left(\mathrm{R}{\mathrm{i}}\right)=\alpha_1+\mathrm{R}f+\beta_i \mathrm{E}\left(\mathrm{R}{\mathrm{M}}-\mathrm{R}{\mathrm{f}}\right)$$公式2.9嵌套CAPM，此时$a$为0。为了估计alpha和beta, Jensen运行了公式2.10所示的时间序列回归:$$R{i t}-R{f t}=\alpha_i+\beta_i\left(R_{M t}-R_{f t}\right)+\varepsilon_{i t},$$

$$\sigma_i^2=\beta_i^2 \sigma_M^2+\sigma_{\varepsilon, i}^2$$

## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

Posted on Categories:Corporate Finance, 企业融资, 公司金融学, 金融代写

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## 金融代写|公司金融学代写Corporate Finance代考|Position of the Creditors in a Solvent Company

As will be seen from the discussion in chapter two, there are many different types of creditors, who advance money to the company based on different contractual and proprietary structures. All creditors, however, have one thing in common: they are owed money by the company to which they have a legal right to payment at some time. ${ }^{139}$ This right is usually, but not always, based on a pre-existing contract. Some creditors, such as trade creditors and tort claimants, have a right to a single payment, which they would like to be paid as soon as possible. However, most lenders who are in the business of providing finance do so in order to obtain an income stream, which, depending on the terms of the loan, will comprise interest or repayment of capital or a combination of both. In a sense, then, this contractual right to periodic payments can be compared and contrasted with the shareholders’ right to a dividend, which is not contractually enforceable until the dividend is declared. ${ }^{140}$

Further, the payments to which the lender has a right are fixed, at least in the sense that they do not depend upon whether the company has made profits, although they may depend on other variables such as the current rate of interest. This means that, in relation to the lenders’ right to income, they have no incentive for the company to engage in risky activity which increases profits, provided that sufficient profits are generated to meet the company’s contractual obligations. In most financing structures, the profit which the lenders make comes from these periodic payments (here loosely called ‘interest’), and so the lenders’ incentive while the company is solvent is to keep the capital part of the loan outstanding for as long as possible so that they can make as much profit as possible. However, the lenders also have an incentive to ensure that the company remains solvent, since on insolvency it will lose not only the future profit of interest payments, but possibly also the capital repayment.

Many lenders will also have a long-term contractual right to repayment of capital. This may be deeply subordinated or have a very long maturity date, as in a hybrid security. ${ }^{141}$ Conversely, capital may be repaid totally through periodic payments, but the lender will usually have the right to accelerate repayment of the whole amount due if the borrower company defaults. ${ }^{142}$ If the company remains solvent, this capital debt will eventually have to be repaid (unlike the capital contributed by the shareholders). This will often be by refinancing, whereby the company just rolls over the debt with the same lenders or takes out new debt with different lenders. As mentioned above, most lenders do not have an incentive to seek early repayment, and would wish the lending relationship to go on for as long as possible if the company is solvent. However, the risk of losing the capital repayment if the company becomes insolvent is severe, and it is largely the protection against this risk that is discussed below. It is a risk which all creditors bear equally although their claims rank ahead of all shareholders. Creditors are not, on the whole, protected by the general law, although the legal capital rules, discussed in chapter five, are one significant exception to that principle. Creditors generally have the ability to protect themselves by a variety of means, which are discussed generally in chapter two, as well as in the discussion following and in more detail in chapters six and seven.

To see who these non-adjusting creditors are, it is instructive to consider the types of creditor that exist. One could see creditors as falling into three categories: those who consciously extend credit to the company (whether in the form of loans or trade credit or otherwise); those who deal with the company without intending to extend credit, but who become creditors because the company becomes liable to them for breach of contract or otherwise (such as customers of goods or services); and those who have no prior contact with the company before becoming creditors (this category is mainly tort victims and the tax authorities).
The ability of some members of the first category (lenders, investors and other financiers) to protect themselves and to influence the company’s activities is discussed extensively throughout this book. Two categories of lenders other than financiers or suppliers may also be present. Directors may extend loans to the company, particularly when it is in difficulties. Such loans are usually unsecured. Other companies in the same group may also lend to the company, and often this lending will be unsecured and, maybe, subordinated. ${ }^{148}$ It should be remembered that directors and group companies may also guarantee loans to the company, and so will be unsecured creditors in any insolvency through their right of subrogation. $^{149}$

Trade creditors also have means of protection at their disposal, although they may not be able to use them fully because of market pressure. ${ }^{150}$ First, they can reflect the credit risks they face in the prices that they charge, either generally for all customers or in relation to a particular customer. ${ }^{151}$ If they supply goods, they can protect themselves by the use of retention of title clauses, which are effective in relation to the goods themselves though not usually as regards the products of the goods or the proceeds of sale. ${ }^{152}$ Certain protection is also afforded by the general law: under the Sale of Goods Act an unpaid seller has a lien on the goods before delivery, ${ }^{153}$ and a right to stop the goods in transit if the buyer becomes insolvent. ${ }^{154}$ These devices are not available to those who supply services, and they have to rely on more general measures (which are also available to those supplying goods). These include requiring payment in advance (if the market will bear this), spreading the risk of customer default by contracting with a wide number and variety of customers, and monitoring the credit of customers so that they can refuse to supply to a customer in difficulties. This latter device depends on the terms of the original contract: either the supplier has to protect itself with a term enabling it to terminate the contract if the customer gets into difficulties, or it has to operate on the basis of separate contracts for each supply, which involves the risk of losing the business for reasons other than the customer’s financial position.

## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

Posted on Categories:Corporate Finance, 企业融资, 公司金融学, 金融代写

## avatest™帮您通过考试

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## 金融代写|公司金融学代写Corporate Finance代考|The Debt/Equity Mix

A company’s capital structure comprises its mix of debt and equity. The question then arises as to whether an optimal capital structure exists for all companies that will maximise every company’s value.

It is suggested by financial economists that a company’s cost of capital, ie the total return expected by the providers of its debt and equity finance, is unaffected by its debt to equity ratio. ${ }^{325}$ The Modigliani-Miller propositions suggest that no combination of debt and equity is better than any other, and that a company’s overall market value is independent of its capital structure. Although borrowing increases the expected rate of return on shareholders’ investments, adding debt to a company’s capital structure increases the risk of insolvency, and shareholders, whose investment will be wiped out first in the event, require compensation for this risk. According to Modigliani and Miller, although debt financing can be regarded as a cheaper source of finance than equity, due to its reduced risk (for example, as a result of its prior ranking on insolvency), the additional return expected by equity investors as a result of the increased risk which they face exactly offsets this advantage. If this is correct then the amount of debt entered into by a company should be irrelevant and debt to equity ratios should vary randomly from company to company and from industry to industry. Yet this is not what is observed in practice. Almost all banks, for example, rely heavily on debt ${ }^{326}$ whereas in other sectors, such as pharmaceuticals and advertising, almost all companies have traditionally been mainly equity financed.

Clearly, the original Modigliani-Miller propositions do not explain these observations. In part this is because the Modigliani-Miller model was developed on the basis of certain restrictive assumptions, including the existence of well-functioning capital markets ${ }^{328}$ and the absence of taxes, transaction costs and insolvency costs. These assumptions are highly artificial. In practice these issues are important and will affect the relative cost of debt and equity to a company and are very likely to affect the debt to equity ratios within a company. In relation to taxes, for example, companies can deduct the interest payable on debt from their profits for the purpose of assessing corporation tax: dividends are not deductible in this way. Once these assumptions are relaxed, it becomes clear that some debt can be added to a company’s capital structure without affecting the return expected by its shareholders. ${ }^{329}$ As the proportion of debt in the company increases, however, it becomes more likely that the company will default and enter into insolvency. At a certain point these costs of distress will outweigh the tax benefit of debt. Financial distress and insolvency is costly, in terms of the direct costs of lawyers, courts and insolvency practitioners, as well as the reduction in the value of the company associated with insolvency. There are also the indirect costs attached to the difficulties of running a company while going through this process. ${ }^{330}$ Even if the company avoids insolvency it will still face the costs of financial distress-for example, the suppliers may demand more protection, creditors may charge more and employees may leave and look for other jobs. When considering the costs of distress it is also important to have regard to the nature of the company’s assets. If the assets are ‘real’, such as property, then there will be reduced distress costs because this will provide at least some of the creditors with the assurance that even if the company is distressed there are assets available which can be used to repay their debts. By contrast, in companies such as high tech companies where the principal assets are ideas and people, it is much more difficult on insolvency to cash in by selling off the assets. In order to understand the debt to equity ratio adopted by companies it is therefore relevant to consider not only the likelihood of insolvency, but also the value of the company that is likely to be realisable if insolvency occurs.

## 金融代写|公司金融学代写Corporate Finance代考|The Relationship between Equity and Debt in a Solvent Company

In this section the rights and roles of shareholders and creditors in a solvent company are compared and contrasted. It is important to separate the solvent and insolvent scenarios because, as will become apparent, the positions of shareholders and of creditors in these two periods change markedly.

For these purposes a slightly more constrained view of solvency is adopted than is required if the strict legal definition is applied. A company is insolvent for the purposes of the law if it becomes unable to pay its debts. ${ }^9$ There are two different approaches that can be adopted to determine when a company becomes unable to pay its debts. The first is the balance sheet test. This test measures the excess of liabilities over assets and considers whether the company’s assets are insufficient to discharge its liabilities ‘taking into account its contingent and prospective liabilities. ${ }^{10}$ The second is the cash flow test, which assesses the ability of the company to meet its debts and liabilities as they become due. ${ }^{11}$ Both tests operate in the UK. ${ }^{12}$ Nevertheless, it is recognised that there is likely to be a period prior to formal insolvency when the roles of creditors and shareholders begin to change, and when the analysis entered into in this section will not necessarily be appropriate. A discussion of this twilight period prior to insolvency, and when that twilight period can be said to begin, is undertaken in the following section, 3.3. In this section, then, the concept of solvency is intended to encompass the scenario outside insolvency (as strictly defined), but also outside this twilight period; that is, for the purposes of this section solvency encompasses the scenario in which there remain significant shareholder funds within the company and the company remains a profitable going concern.

In order to determine the position of shareholders in a solvent company, it is first necessary to understand the rights that are typically held by those shareholders. The rights attaching to shares are laid down in the company’s constitution, in case law and in statute. It is usual for a company’s share capital to comprise different classes of shares, the most common being ordinary shares and preference shares, ${ }^{13}$ although under English law a company has practically unlimited freedom to create the capital structure that it wishes for itself.

The rights attached to shares can usefully be divided into three types: rights to capital, rights to income and voting rights. ${ }^{14}$ The capital, income and voting rights typically attached to ordinary and preference shares are discussed next. These rights will generally be class rights. ${ }^{15}$ According to the Companies Act 2006, shares will be regarded as being of one class where the rights attached to them are uniform. ${ }^{16}$ Consequently, preference shares carrying different rights to dividend and/or to capital will be treated as constituting a different class of shares from the ordinary shares. Equally, however, there may be different classes of ordinary shares, for example where some ordinary shares carry rights to vote but others do not, and different classes of preference shares, for example where different preference shares carry different entitlements to a particular dividend.

The significance of this differentiation is that there is a statutory procedure that needs to be followed where class rights are varied. ${ }^{17}$ A class right found in the articles, for example, can only be changed by at least a 75 per cent majority of the class concerned. Any other right found in the articles can prima facie be altered by a 75 per cent majority of all members. ${ }^{19}$ This appears to provide significant protection to the holders of class rights. This potential protection is diminished, however, due to the extremely restrictive interpretation of the concept of ‘variation’ adopted by the courts for this purpose. ${ }^{20}$ The courts have drawn a distinction between varying a right (in which case the statutory procedure must be followed) and merely varying the enjoyment of the right (in which case the procedure need not be followed). For example, the courts have determined that issuing new preference shares pari passu to existing preference shareholders might vary the enjoyment of the rights of the existing shareholders, but does not vary the right itself, and so the statutory procedure need not be followed.

## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

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## 金融代写|公司金融学代写Corporate Finance代考|Asset Finance

Whether a company which needs money issues equity or debt securities depends on a number of factors. ${ }^{202}$ One particular advantage of debt securities over equity securities is that the interest paid on debt securities is tax deductible for the company, unlike dividends, which cannot be deducted. ${ }^{203}$ This makes debt a much cheaper option than equity, at least up to a certain point. ${ }^{204}$

In one sense, the tradability of debt securities makes them similar, from an investor’s point of view, to equity securities. Debt securities are traded on the secondary market and are frequently listed on a stock market, although much of the trading takes place over the counter (OTC). ${ }^{205}$ The big difference is that the owner of equity securities has a stake in the company and shares its profits and its losses. Another advantage of debt securities, particularly for private companies, is that the existing shareholders do not dilute their control of the company (or the value of their shares). The owner of debt securities does not share in the profits, and, as a creditor, ranks above shareholders if the company is insolvent. These issues are discussed further in chapter three. The exact priority of the owner of debt securities will depend on various matters, such as whether the securities are backed by security over other assets and whether they are the subject of a subordination agreement. There is also a twilight zone occupied by what are known as ‘hybrid’ instruments. ${ }^{206}$ These are securities which have some characteristics of debt and some of equity, and are an attempt to give investors some of the best of both worlds, although, of course, they end up without the full benefits of either. For example, securities may be deeply subordinated, or perpetual, or convertible into equity.

While they can be used for any sort of tangible asset, finance leases are often used for ‘big ticket’ items, such as aeroplanes ${ }^{262}$ and large vehicles. An alternative, though similar, structure is hire purchase. Here the financier retains ownership of the item, but, as with a finance lease, all the risks and rewards are transferred to the company. The company (the ‘hirer’) makes periodic payments which in part reflect the hire charge and in part reflect the capital value of the item. At the end of the hire period the hirer has the option to purchase the item for a nominal fee. This structure does not attract the favourable tax and accounting treatment of a finance lease: the financier cannot claim capital allowance, and the payments made by the hirer are treated as partly rent (which is deductible from profits) and partly capital expenditure (on which capital allowance can be claimed) ${ }^{263}$

A similar structure, less common in the commercial sector than in the consumer sector, is conditional sale, where the owner agrees to sell at the beginning, but title is not transferred until the end of the agreed period, once all the instalment payments have been made. $^{264}$

## 金融代写|公司金融学代写Corporate Finance代考|Stock Finance

Stock finance is a term that can cover a number of different structures based on the concepts already discussed. One, which is a variant of acquisition finance, involves the company entering into a hire purchase or conditional sale agreement as a temporary measure in order to fund the period between obtaining the item to display to potential customers and selling the item to a customer, rather than in order to own the item. This form of finance is usually provided in relation to motor vehicles, and the financier is likely to be a company associated with the manufacturer of the vehicles.

Another possible model is where, in order to ‘lend’ money against stock already owned by the company, the financier buys the stock from the company and the company sells it to customers as the undisclosed agent of the financier. ${ }^{266}$ The company then holds the proceeds of sale on trust for the financier, in a similar way to an invoice discounting arrangement. Both of the arrangements discussed in this section are alternatives to a lender taking a charge over stock; while this will normally be floating, it may be fixed if sufficient control methods are put in place.

The funding of the period between acquisition of raw materials or stock and the point at which these goods are disposed of (in their original state or after manufacture into something else) can be achieved, at least partly, by credit extended to the buyer by the seller. The seller is then exposed to the credit risk of the buyer. To protect itself, the seller will usually retain title to the goods in the sale agreement. ${ }^{269}$ While the goods are in the possession of the buyer, if the buyer does not pay, the seller has the right to retake the goods, and, since the seller has a proprietary right, this will survive the buyer’s insolvency. However, this form of protection has its limitations. Any attempt by a seller to gain proprietary protection in the products of the raw materials supplied, ${ }^{270}$ or in the proceeds of sale ${ }^{271}$ of the stock supplied, is very likely to be characterised as a charge and will therefore be registrable. Since it is impractical to register every sale agreement, this registrability means that the seller’s proprietary protection is limited to an interest in the goods themselves.

## 金融代写|公司金融学代写Corporate Finance代考|Asset Finance

Whether an individual or company is hedging agricultural commodities, energy commodities or financial assets, hedges using derivatives contracts, whether they are futures traded on an organized exchange or swaps traded off of an exchange, all function in generally the same fashion: They allow hedgers to hold a financial contract that fluctuates in value opposite that of the commodity or asset they are trying to hedge. In some cases, like the example of the farmer, the asset or commodity being hedged is already held by the hedger, who faces the financial risk that the commodity or asset being held will fall in value before it is sold. Under such circumstances, the hedger would sell a futures contract to hedge this exposure. Such hedges are referred to as short hedges because the hedger has sold, or “gone short,” the futures contract.

## 金融代写|金融衍生品代写Financial Derivatives代考|SPECULATION

If the classic depiction of hedging is the farmer locking in a sale price for a crop, the classic speculator is the commodities trader who buys a pork bellies contract for no other reason than he believes prices will rise. Years ago, such speculators were limited to agricultural products or precious metals. Today, individuals wanting to chase profits have a panoply of choices available to them, ranging from physical commodities-agricultural products, metals and energy-to financial products-interest rate instruments, stocks, and foreign currencies. In today’s markets, one can even take a view on temperature, rainfall, or even election results.
For the moment, as with the case of hedgers in the previous section, we will consider speculation in its purest form. That is, speculation is the taking on of a price risk for the simple purpose of trying to profit based on expectations of which way prices will move. Speculators who expect prices to rise will enter into long positions, while those believing they will fall short the market.

Speculators can be categorized in several different ways. One common way is to classify them by how they form their price expectations. Those relying on basic economic conditions to form expectations are referred to as fundamental traders. Traders in an alternate group, which form expectations based on analyses of price patterns and other market statistics, are called technical traders.

Fundamental traders operate on the premise that futures prices reflect the underlying conditions related to the supply and demand of commodities and the valuation of financial assets. The goal of the fundamental trader is first to identify the key economic conditions and variables that affect prices and second to observe changes in those conditions, it is hoped, before they are incorporated into the market price. For example, a fundamental trader interested in trading Eurodollar futures would be concerned with Fed policy, inflation rates, and other economic indicators that would signal upcoming changes to Eurodollar rates. A fundamental trader of physical commodities similarly would be concerned with factors that would increase or decrease the supply or demand for a commodity. If the trader can gain an edge in terms of gathering information on these factors and take a position in the market before the market has incorporated the information, she stands to gain from her efforts.

## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。