The traditional fixed incomes considered are low-grade corporate bonds, treasury bonds, and high-grade corporate bonds. The liquidity of these bonds in normal market conditions is likely to be different. Treasury bonds have more investors. Most investors prefer the treasury bonds because they belong to the government and hence have a lower risk. As a result of this preference, the treasury bonds' liquidity will be higher than that of low-grade corporate bonds and high-grade corporate bonds. During a financial crisis, the liquidity of these bonds fluctuates differently. The liquidity of corporate bonds tends to rise during a credit crisis, while the treasury bonds' liquidity tends to fall. However, high-grade corporate bonds perform better than the low-grade corporate bonds during a credit crisis. This better performance results from its higher ratings and low default risk (Adrian, Fleming, Shachar, & Vogt, 2017).
Derivative markets
The complexities of market derivatives are reporting and economic complexities. A high economic complexity refers to when a minimum of two derivatives are used. Otherwise, that will be a low economic complexity. On the other hand, using scarce and ambiguous directions from set standards, to initiate a derivative when giving a financial report is considered a high reporting complexity. Otherwise, that is a low reporting complexity. Complexity can be considered in the context of the report user. This complexity refers to the challenges or difficulties incurred by the reader in understanding the transactions listed and the standards used in the case of the report given (Chang, Donohoe, & Sougiannis, 2016).
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Financial and transaction data is very complicated. Therefore, analysts' reports may be misleading or deceiving to potential investors. When the derivative is not analyzed properly, misleading information about the derivative earnings is produced. If the output information or report produced by the analyst is appealing and promising, the investor will go ahead and invest in that derivative. In the event where the analyst data was overrated, the investor will incur a loss. As a result of this risk to the investor, it is necessary that the analyst involved, produce an accurate report. An analyst can produce accurate predictions by relying on their expertise when giving a prediction, rather than imitating other analysts. Another way of ensuring accurate predictions is by screening the earnings from unsuitable and surprising modifications in risk factors.
Option contracts
Options contracts are divided into a bidirectional, call, and put options. Option contracts refer to a buyer's ability to purchase or sell a commodity within a specified time at a given price. A call option is when a buyer can buy an item at a given price within a given time. On the other hand, a put option refers to the ability of a buyer to sell an item at a given price. For example, a person can buy flowers at a lower cost in a season when the demand is high and sell the flowers at a higher selling price than buying price. As a result, the investor will gain profit (Chang et al., 2016; Yang, Tang, & Chen, 2017).
Different models are used in valuing stock options such as Binomial, Black-Scholes, and Monte Carlo simulation model. These models can be used in other underlying assets, such as stock indexes. The procedure of applying these models in stock indexes is the same, as in valuing stock options. The difference will only be in the value of the dividend yield.
References
Adrian, T., Fleming, M., Shachar, O., & Vogt, E. (2017). Market liquidity after the financial crisis. Annual Review of Financial Economics, 9 , 43-83.
Chang, H. S., Donohoe, M., & Sougiannis, T. (2016). Do analysts understand the economic and reporting complexities of derivatives? Journal of Accounting and Economics, 61 (2-3), 584-604. doi:10.1016/j.jacceco.2015.07.005
Yang, L., Tang, R., & Chen, K. (2017). Call, put, and bidirectional option contracts in agricultural supply chains with the sales effort. Applied mathematical modelling., 47 , 1-16.
