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Weighted average cost of capital

2022.01.25 13:08 chrishazza Weighted average cost of capital

Im looking at this question in the CFA Level 1 2022 curriculum: Cost of capital - Foundational Topics question 21. I don't understand why they are using the 1m shares outstanding + 1m to potentially be raised for a total of 2m as market value of equity. I thought that the marginal cost of capital took the CURRENT market values of debt and equity for the weights, and not those that pertain to the company's situation AFTER the new capital is raised (hence the word marginal); this is indeed how we did things for question 9 prior. Surely we should only be using a market value of equity of 1m and not 2m. Can someone take a look at the book for me please to see if this is errata?
".................................The marginal cost of capital for TagOn, based on an average asset beta of 2.27 for the industry and assuming that new stock can be issued at $8 per share, is closest to:
A.
20.5 percent.
B.
21.0 percent.
C.
21.5 percent.
------
C is correct.
For debt: FV = 2,400,000; PV = 2,156,000; n = 10; PMT = 150,000
Solve for i. i = 0.07748. YTM = 15.5%
Before-tax cost of debt = 15.5%
Market value of equity = 1 million shares outstanding + 1 million newly issued shares= 2 million shares at $8 = $16 million
Total market capitalization = $2.156 million + $16 million = $18.156 million
Levered beta = 2.27 {1 + [(1 − 0.23)(2.156/16)]} = 2.27 (1.1038) = 2.5055
Cost of equity = 0.0525 + 2.5055 (0.07) = 0.2279 or 22.79%
Debt weight = $2.156/$18.156 = 0.1187
Equity weight = $16/$18.156 = 0.8813
TagOn’s MCC = [(0.1187)(0.155)(1 − 0.23)] + [(0.8813)(0.2279)]
= 0.01417 + 0.20083
= 0.2150 or 21.50%
submitted by chrishazza to CFA [link] [comments]


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2022.01.25 13:08 InvestcoreMedia $SWRM Cloud Data Platform for Security

Tulsa, OK, Jan. 25, 2022 (GLOBE NEWSWIRE) -- via NewMediaWire -- AppSwarm, Corp. (OTC: SWRM), a software development company and aggregator of mobile applications, announces the development of cloud data security solutions under TulsaLabs.
TulsaLabs is developing a cloud data platform that among other things will assist clients in protecting enterprise data across multiple environments, meet privacy regulations, and simplify operational complexity.
Data Threat Management
Data Threat Management is a process used by cybersecurity professionals to prevent cyber attacks, detect cyber threats, and respond to security incidents.
Enhanced with automation, and informed by AI, a cyber threat management system will help clients counter some of today’s advanced attacks by cybercriminals, or rogue state actors.
By unifying security data, security teams will be able to navigate and identifying data vulnerabilities across networks on thousands of endpoints, and between clouds.
Incident Response Solutions
Nearly three-quarters of organizations don’t have a consistent, enterprise-wide cybersecurity incident response (IR) plan. Without strong, trusted intelligence, clients are not always able to decipher the insights they need to act swiftly against threats.
IBM Security® QRadar® XDR Connect is the industry’s first comprehensive extended detection and response (XDR) solution built with open standards and automation that unifies endpoint detection and response (EDR), network detection and response (NDR), and security information and event management (SIEM) in one workflow.
This platform allows a client to save valuable time by connecting insights and leveraging AI to automate tasks and respond quickly.
IBM Cloud Pak® for Security can help clients gain deeper insights, mitigate risks, and accelerate response. With an open security platform that can advance a zero-trust strategy, you can use your existing assets while leaving your data where it is — helping your team become more efficient and collaborative.
Leveraging Quantum Computing for Security
Cybersecurity researchers are concerned that some advanced algorithms could easily break through most modern cryptography.
How big of a threat is it? The security algorithms we use today that would take roughly 10 billion years to decrypt could take as little as 10 seconds with a quantum computer using Shor’s algorithm, which has exponential speed over classical algorithms.
To prepare for what comes next, government policymakers and industry leaders need to look to mitigate against these risks by future-proofing their systems in the present.
TulsaLabs will explore practical cryptographic solutions that are resistant to the threats posed by quantum computers. These include lattice-based cryptography, hash trees, multivariate equations, and super-singular isogeny elliptic curves.
The key advantage of such quantum-safe schemes is the absence of exploitable structure in the mathematical problem an attacker needs to solve in order to break the encryption.
Tom Bustamante, the Founder and CEO of AI Venturetech and head strategic advisor to TulsaLabs commented, "With current international events unfolding now more than ever enterprises need to review the data security policies to offset threats such as cyber or ransomware attacks. TulsaLabs anticipates deployment of a private encrypted telecommunication and cloud platform geared specifically for the aerospace and space technology research sometime in Q1 2022.
https://www.stocktitan.net/news/SWRM/tulsa-labs-announces-development-of-cloud-data-security-solutions-fph9uli53wxm.html
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