As the US Fed withdraws its quantitative easing, two economic drivers are in play that will replace the monetary stimulus: the business-oriented 2017 tax cut and growing productivity, according to a quarterly forecast by Pinebridge Investments.
Value-at-Risk (VaR) and Performance Predictability:Evidence on Skewed distribution mutual fund in Thailand
The Indian debt market has grown to USD 1.5 trillion over the past decade, largely due to the issuances from the central and state government. The ratio of government securities to corporate issuances is about 75 to 25, reflecting the subdued state of corporate bond markets in India. With a lack of participation, the Indian debt market remains smaller than the equity market—an anomaly among other global markets.
It turns out that “America First” has been an apt way of thinking of markets in 2018. US dollar strength is being attributed to emerging markets’ (EM) financing issues, commodity weakness, and seemingly anything else that cannot easily be explained. This leads many to wonder when the dollar’s upward trajectory will have run its course.
With quantitative easing peaking soon, growth and rate differentials are mattering more. The US came into 2017 as the global growth laggard, yet quickly moved to the front of the pack in 2018 by accelerating while others plateaued. Much of this non-US pause probably rests as much with the powers that be in Beijing as it does with those in Washington.
Before pulling back late in 2017 and early 2018, China’s policy initiatives pushed for growth in the lead up to the 19th Party Congress. With Europe and EM depending more on trade with China than they do with the US, China’s success or failure in handling its debt, managing its currency, and dealing with tariff issues will have a far greater impact on those nations than it will on the US.
Europe’s current slow growth, in fact, can be attributed in large measure to China’s careful steps to encourage slow domestic growth, which has cooled demand for goods from Europe and constrained the performance of many European companies that are export dependent.
Worries about EM dependence on China are partly the reason EM has underperformed developed markets (DM) in all asset classes by about 10% in the past year. Turkey and Argentina’s woes are unique and self-inflicted, yet still fuel fear that the Federal Reserve is on an overly ambitious pursuit of the dot plot, eventually crushing all EM.
Optimal Mean Reversion Trading
with Transaction Costs and Stop-Loss Exit
In pre-crisis days, market participants understood that central bankers had their hands on the short-term end of the yield curve and knew how to react when rates were dialed down to boost a sluggish economy or up to cool an overheated one.
In response to the financial crisis, mission creep set in. Leading central banks moved into the long end of the curve, where rates traditionally had been determined solely by market forces. Yesteryear’s yield curve, therefore, was a transparent comparison between the market’s view of the economy down the road versus the Federal Reserve’s. When the 10-year Treasury rate fell below the two-year rate, creating an inverted yield curve, recession typically followed 18 months later – a report card suggesting that the market had superior forecasting powers. Today’s yield curve may have morphed into a kind of financial funhouse, where the rates we see are distorted images of market-determined rates.
Non-Monotonic NPV Function Leads to Spurious NPV and Multiple IRR Problems: A Critical analysis using a modified capital amortization method that Resolves These Problems
This analysis is conducted using some popular non-normal net cash flow (NNCF) investment data available in public domain and other hypothetical NNCF data. The methodology is mainly based on capital amortization schedule (CAS) and modified CAS (MCAS) methods along with a comparison of the results with the common DCF method. The findings are summarised here:
a. The problem of multiple IRR is caused by reinvestment income and the resultant non-monotonic NPV function. The CAS methods clearly indicate whether there is any reinvestment. Non-monotonic NPV function of NNCF investment leads to multiple IRRs or spurious IRRs, NPVs and MIRRs. With non-monotonic NPV functions the DCF estimated criteria are all spurious.
b. The MCAS method eliminates the reinvestment thereby leads to monotonic NPV function and resolves the problem of reinvestment, spurious NPVs, MIRRs, IRRs and or multiple IRR.
c. Neither the NPV nor the MIRR could resolve the problem of multiple IRR. With normal NCFs and some of the NNCFs also, there are no reinvestment at IRR or at hurdle rate as wrongly asserted in many published works.
d. It is normal for the estimated IRR to be either ‘nil or zero or negative’ when the sum of net benefits or NCF is zero or negative. Such IRRs are consistent with NCF or net benefit. IRR of ‘zero or negative or no’ is not a weakness or problem but it reveals the real or consistent return.
e. MCAS is an appropriate method to estimate the rate of return (IRR and NPV) for both normal NCF and NNCF and resolves the multiple IRR problem and eliminates spurious NPVs and MIRRS. The estimated IRR and NPV by MCAS method are consistent with NCF.
f. Ultimately, IRR and NPV, estimated by MCAS, are the best criteria available to investment, project and cost-benefit analysis.
In summary, NPV and IRR estimated by MCAS method are equally appropriate and therefore one cannot be the best substitute for the other. The multilateral and bilateral organizations and corporate managements may wish to revisit their recommendation to use the NPV only and not the IRR while dealing with multiple IRRs associated with NNCF investments.
Equity markets continue to normalize. But midway through 2018, this normalization process is more nuanced than it was at the start of the year, exacerbated by the rise in tensions on trade and geopolitics. For investors, this has created an even greater need to focus on company fundamentals over the medium to long term.
At the equity index level, we believe that valuations are fair, and even attractive in some cases, after the recent de-rating of many stocks. We also consider the current environment for stock selection as being attractive due to the high dispersion in valuation multiples relative to history.
CFA Institute and PRI survey on ESG integration in Asia
In 2017, CFA Institute and the PRI agreed to undertake an ESG investing study that entails a survey, a series of workshops and the release of four reports: one case study report and three regional reports. The aim of the study is:
We would like you to help us by responding to the survey: https://start.yougov.com/refer/vXwDHpNl4ZBrY2
The results of the study and the feedback from the workshops will be published in the regional reports. There will also be regional and country guidance and case studies on how investors are integrating ESG issues into their investment analysis and decisions. These reports will be readily available for all CFA members and PRI signatories.
The survey contains two sets of questions that should take roughly 8 – 10 minutes to complete. It covers the impact of ESG investing at the financial market level and firm level. It is being completed by participants across seventeen countries.
If you like to fill out the survey, please do so by 15 June. We appreciate your response.
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ESG Integration Explained: An Alpha-Generating and Risk-Reducing Tool
The term “ESG integration” is often used when talking about ESG investing. Practitioners new to ESG investing are sometimes uncertain what ESG integration is and how it is performed—so much so that they may not realize they are already performing integration techniques informally.
One definition of ESG integration is “the explicit and systematic inclusion of ESG issues in investment analysis and investment decisions.” Put another way, ESG integration is the analysis of all material factors in investment analysis and investment decisions, including environmental, social, and governance (ESG) factors.
What does that mean? It means that leading practitioners are:
What does that not mean? It does not mean that
Safeguards against the Introduction of a Dual-Class Shares Structure
As revealed in a survey conducted in Asia Pacific by CFA Institute in March, a majority (60%) of the 450-plus respondents have not had any experience investing in firms with a DCS structure, which signalled the urgency for and need to educate investors and the general public on the implications of DCS structures.
The survey, “Dual-Class Shares and the Demand for Safeguards,” revealed that respondents in the region were divided when asked whether DCS structures should be introduced to the market, with 53% opposing the introduction and 47% in favour. Regardless of their position on DCS, almost all (97%) respondents considered it necessary to enact additional safeguards if DCS structures are permitted.
Among different possible safeguards, more than 90% of respondents considered it appropriate to implement enhanced mandatory corporate governance measures as well as time- and event-based sunset provisions, such as automatic conversion of shares with super voting rights to ordinary voting rights. Specifically, 94% of respondents considered it appropriate to introduce a time-based sunset provision; among which, 91% of such respondents considered it appropriate to convert shares with super voting rights to ordinary shares within 10 years. Separately, 93% of respondents considered introducing a maximum voting differential appropriate; 63% of these respondents found a 2:1 maximum voting differential optimal.
Although selecting ETFs can be challenging due the wide variety of products, they can be used as tactical and strategic tools for asset allocation. Market participants have recently been moving funds from underperforming products into more cost-effective ETFs. The sweet spot appears to be the intersection between active and passive smart beta products.
Manager selection is a critical step in implementing any investment program. Investors hire portfolio managers to act as their agents, and portfolio managers are then expected to perform to the best of their abilities and in the investors’ best interests. Investors must practice due diligence when selecting portfolio managers. They need to not only identify skillful managers, but also determine the appropriate weights to assign to those managers. This book is designed to help investors improve their ability to select managers. Achieving this goal includes reviewing techniques for hiring active, indexed, and alternative managers; highlighting strategies for setting portfolio manager weights and monitoring current managers; and considering the value of quantitative and qualitative methods for successful manager selection.
Translated into Mandarin June 2017.
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. |
温氏17-21年,预计五年生猪活鸡累计净利润785.79亿,平均每年157.158亿。温氏集团当前股本52.20亿股(市值1034.67亿)。1只考虑这两项业务情况下,7-21年,每股净利润(EPS)分别为:1.18元,2.47元,3.6元,3.83元,3.98元。
当前10年期国债收益率3.6%附近,2倍于10年期收益率,要求投资收益率等于7.2%。也即E/P=7.2%, P/E=13.89。按照13.89倍P/E,17-21年末的期望价格为,16元,34元,50元,53.2 元,55.2 元。考虑到当前的价格为19.82,当前买入持有该标的,到17-21年,每年末期对应的理论收益为:-17%,73%,152%,168%,179%。考虑到一定的交易策略,未来2-3年的时间,投资温氏股份,可以实现200%的收益率。再考虑到温氏集团作为大公司,市场系统性风险Beta低,而高市值对应的流动性很强。因此,投资温氏集团在接下来2-3年可以获得,低风险下的200%收益。
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.