Window dressing is a strategy used by mutual fund and other portfolio managers near the year or quarter end to improve the appearance of a fund’s performance before presenting it to clients or shareholders. To window dress, the fund manager sells stocks with large losses and purchases high-flying stocks near the end of the quarter. These securities are then reported as part of the fund’s holdings. Source – Investopedia
Does this phenomena apply to the Malaysian stock market?
My personal view is that fund managers usually do their typical window dressing in the month of December. I have decided to analyse the FBMKLCI December data from year 1994.
Step 1 : Tabulation of December FBMKLCI Data (since 1994)
On average, the number of trading days in the month of December is up to twenty (20) days. To ensure consistency in the comparison, it is assumed that every year’s December has a total trading days of 20. As such, we fill the gaps (i.e shaded in orange) with the last available trading index number for December of the particular year.
Step 2 : Averaging Process
For each year:
- We divide index price for each trading day by the last trading day’s index price
- We perform a simple averaging of the computed ratios (1994 – 2016), as shown below:
Based on the averaging process, it appears that from 1994 till 2016, there seems to be a “consistent pattern” whereby there was a 1% oscillation in the index between 1st day till the 12th trading day, to be followed by a significant spike in the index from 12th trading day till the end of the month. I will consider the 12th trading day as the most probable date for the commencement of window dressing activities.
Based on this method, what will be the possible end target for the FBMKLCI FYE 2017?
We may potentially see the index ending at 1,740 (only time will tell whether I am right or wrong?)
Key Risks To My Analysis
This rather simple desktop analysis assumes no occurrence of unexpected major events (including black swans) in the month of December. This assumption may appear unrealistic given the uncertainties associated with the financial markets.
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