As we move into 2018, we believe macroeconomic conditions will support risk assets. Global growth is becoming more evenly distributed and is expected to return to its historical trend rate of 3.7%, while inflation remains muted.
In Thailand, tick sizes for stock trades are not decimalized but instead fixed over predefined intervals. While changes in tick sizes are exogenous, investors seem to behave differently around such thresholds. Using high-frequency trade and quote data from the Stock Exchange of Thailand between 2002 and 2008, we document that investors are more likely to sell their stocks (as “market” orders) at threshold prices. Despite the influence of price clusters (at round numbers, which are also threshold prices), we show that imbalances are more likely to exist at threshold prices. While investors of all types sell at the thresholds, retail investors tend to also set limit orders to buy at the thresholds as prices approach from below. There is also no evidence that investors can systematically profits from the imbalance, suggesting that the trading activities may increase trading costs without returns to compensate.
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.
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.
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.
Factor-timing strategies in the U.S. produce weak returns and are strongly correlated to the basic factor-holding strategies. We present contrasting evidence from China, where actively managed stock mutual funds successfully time the size factor (small minus big) despite a negative unconditional loading. We show that the timing skill arises from funds’ intra-period trading. Relatedly, funds with bigger return gaps exhibit more timing skill. Furthermore, size-factor timing is an important aspect of manager skill, as it attributes to over 50% of fund alpha. Finally, we show that timing skill matters to funds’ performance persistence, especially among high-alpha funds.
|Following TCL’s Annual General Meeting on 28 April 2017, we rate TCL BUY based on : (i)
our combined dividend discount model (DDM) and earning capitalization model arriving
at the fair price of VND 39,036; (ii) growth supported by container throughput volume of
parent company – Saigon Newport Corporation; and (iii) low-cost land to develop depot
and Inland Container Depot (ICD).