This paper tackles the role inclusive businesses play in our economic growth. We shall also be tackling specific companies and their programs geared towards inclusive business and poverty alleviation. Lastly, we shall seek means on promoting this business model so that more would participate in this initiative.
|市值最大的 20 只中国概念股年初至今回报率达 27%
We develop a theoretical model that shows that in the near future, the monetary policies of some key central banks in advanced economies (AEs) will have two dimensions—changes in short-term policy rates and balance sheet adjustments. This will affect emerging market economies (EMs), especially those with a pegged exchange rate, as these EMs primarily use a single monetary policy tool, i.e., the short-term policy rate. We show that changes in policy rates and balance sheet adjustments in AEs may differ in their respective financial spillovers to pegged EMs. Thus, it will be difficult for EMs to mitigate different types of spillovers with a single monetary policy tool. In that context, we use the model to show how EMs might use additional tools—capital controls and/or macro-prudential policy—to complement their monetary policy and financial stability toolkit. We also discuss how balance sheet adjustments that affect long-term interest rates may percolate to influence short-term interest rates via financial plumbing.
|In the latest issue (Issue 13 – August 2017), it covers the stories of:|
|Financial Crime Risk : Anti-Money Laundering Practices in Banking
To understand anti-money laundering, we have to understand what money laundering is. Money Laundering is the process of converting illegal funds into seemingly legitimate assets with the purpose of concealing the ownership or original source of these funds. This makes it difficult for the authorities to trace the origins of the funds. To counter this, the banking sector has established a set of internal regulations and system known as anti-money laundering. These are legal controls taken by financial institutions to investigate suspicious transactions to help prevent money laundering activities within the banking sector.
|The Rise of Text Mining in Financial Markets
The world is awash in data. Financial markets are awash in data. We are generating around 2.5 quintillion (2.5×1018) bytes of information every day, and there is an average of 4,000 brokerage reports a day comprising around 36,000 pages in 53 languages. As market participants try to maximize their competitive edge from the growing mountain of information, the nancial world increasingly feels there is a need to harness the power of big data and it has been shaping the way they acquire, analyze and utilize data. The recent development is the rapid expansion of text mining. Hence, this article will focus on the development of Text Mining technology as well as Text Mining technique.
Title: A Resolution to the Problem of Multiple IRR: A Modified Capital Amortization Schedule (MCAS) Method for Non-Normal Cash flow (NNCF) to Obtain a Unique IRR
The problem of multiple IRR remained unresolved for almost a century. This problem is associated only with some of the non-normal net cash flow (NNCF) that wrongly includes reinvestment income as income or benefit stream. The reinvestment income, which is not a benefit from the investment or project under analysis, causes the multiple IRR problem. This is often misinterpreted as problem of IRR but its neither a problem with IRR nor NPV. It is a problem associated with some NNCF data and the failure to update the discounted cash flow (DCF) or capital amortization schedule (CAS) methods to handle such problem.
Using NNCF data, analyses are conducted with special emphasis on topics such as:
a. A modified CAS (MCAS) method that eliminates multiple IRR associated with NNCF data;
b. Multiple IRR problem and the Descartes rule of sign and Norstrom’s criteria;
c. A NNCF data with a unique IRR under DCF / CAS methods vs IRR by MCAS method;
d. Resolving the problem of multiple IRR by MCAS Method Versus MIRR; and
e. A critical review of the GIRR and AIRR Methods to Estimate NNCF.
The salient findings of the present analysis are:
a. The MCAS method, presented in this paper, identifies and eliminates the reinvestment income associated with NNCF investments (with positive opening balance in one or more years in the CAS) from the benefit stream;
b. This new method overcomes the multiple IRR problem and leads to a unique and real IRR; The effectiveness of MCAS to handle the NNCF data is illustrated with numerical analysis;
c. The assumption of reinvestment at IRR or at hurdle rate in NPV are false assertions in the cases of normal NCF and some of the NNCFs. However, such reinvestment is evident only with NNCFs with positive opening balance in one or more years under the CAS.
d. The reinvestment income under the benefit stream causes multiple IRRs and multiple NPVs too. As NPV is a static point estimate (at hurdle rate) the multiple NPVs are not exposed. Without eliminating the reinvestment income, none of the criterions viz. NPV, IRR or MIRR, is useful as a decision criterion. Neither NPV or MIRR is a preferred criterion, under such circumstances, as recommended in some published works.
e. The MCAS method is appropriate for both normal NCF and NNCF as illustrated in this paper. CAS or DCF method is appropriate only for normal NCF investments.
f. Even when there is no multiple IRRs with some NNCFs under DCF/CAS method, the MCAS method estimated IRR or NPV, without reinvestment income, are different from that of the DCF/CAS estimated IRR and NPV. For a consistent estimate of IRR and NPV, the MCAS method is most appropriate both for NCF and NNCF investments.
g. The generalized IRR (GIRR) and the Average IRR (AIRR) are also not appropriate estimates for NNCF and they are not NCF consistent as discussed in this paper. The problem of multiple IRR associated with the popular cases of NCF investments used in GIRR and AIRR, are also resolved now.
In conclusion, the MCAS method resolves the problem of multiple IRR and leads to a unique IRR that is real and NCF-consistent. Neither the NPV nor the MIRR could resolve the problem of multiple IRR.
Financial Technology (FinTech) is here – sweeping through finance and, if some are to be believed, threatening traditional edifices that have stood for centuries.
This great surge is being fronted by a host of new start-ups taking their lead from the big tech innovators. Their maverick approach is helping to push the FinTech industry into new territory across the financial services landscape, raising billions of dollars and worrying the incumbents.
So what are the main trends and driving forces shaping FinTech today? Fintech – transforming finance explores the features of this new landscape, highlighting the many ways in which this revolution is taking place.
For professional accountants, this new terrain will provide many opportunities as it permeates deeper and deeper into the fabric of society. From the promise of blockchain, to the demands of valuation in a digital era, finance more than ever needs an experienced, knowledgeable guide to make the most of the opportunities ahead.
During the 2015 stock market crash, the Chinese government conducted an opaque bailout by injecting over ¥1.25 trillion ($200 billion) into the stock market. Sixty-three out of 1,406 government-purchased companies actively announced their bailout status in August 2015. The other government-purchased companies passively disclosed their bailout status through earnings reports in October 2015. We find a significantly positive market response to the first wave of active announcements of government bailout. Following the second wave of passive disclosure, the positive response deteriorated and eventually disappeared. Finally, retail investors reacted slowly and eventually overreacted to the bailout news, whereas institutional investors reacted promptly to profit from the opportunity.
Valuation Insights is a quarterly e-newsletter that provides you with the latest news from Duff & Phelps and the trends and changes in valuation and accounting that could affect your business transactions in Asia.
In this edition, our top stories cover the Financial Accounting Standards Board issuing an Accounting Standards Update, robust fair value measurement, the International Valuation Standards Council releasing the 2017 edition of its International Valuation Standards, and a recent Duff & Phelps study about fairness opinions.
We will also look at important Duff & Phelps reports and articles, including a recorded forum presentation by Professor Damodaran and the Duff & Phelps Global Regulatory Outlook 2017.