Wednesday, November 29,
2017 8:00AM / Quantitative Financial Analytics
Stock market volatility is one of those words that are being thrown around every now and then when describing stock market behaviours. For example, on January 29th, 2016, The Vanguard had an article entitled, “Stock Market Volatility - Operators Seek Govt Intervention Fund”, and On November 11th, 2017, it also had another article, The ‘Big Oil’ and market volatilities”. In the same way, ThisDay newspaper, on June 23rd, 2014 wrote “Stock Market Volatility Persists”. Even on LinkedIn pages, people write about market volatilities like the one written by Rotimi Fakayejo, MD Enterprise StockBrokers PLC, Sep 9th, 2015 who posted the article “Gainers & Losers of the volatility of the Nigerian Bourse” on his LinkedIn page. The Guardian on its business page wrote, “Equities rise on the Exchange amid volatility” on Feb 8th, 2015. Those are excellent articles both in content and intent although some made it look like market volatility is necessarily a bad thing. But one thing lacking in the articles is the quantification of how volatile the Nigerian market had been or was expected to be.
There have been various explanations for increased or subdued volatilities in the market as some of those articles opined. One reason is the arrival of new and unanticipated information that tends to or alters the expected return on a stock. News items like the Brexit, the Chinese contagion, escalation of the US-North Korea impasse can have remarkable effects on market volatility. Changes in volatility can even emanate from changes in investors’ behaviors like when investors panic in anticipation of an election result or FED or Central bank decisions on interest rates, etc.
Volatility does not imply that the market is collapsing, rather it implies that the market is behaving in such a way that it is more difficult to make accurate predictions about the market based on currently prevailing data and information. Depending on one’s investment strategy and horizon and subject to the availability of tradeable financial instruments, investors can manage and even profit from volatility. In more advanced markets with tradable financial products like variance and volatility swaps, volatility may present opportunities for profit.
It follows therefore that knowledge of volatility of returns in stock markets’ behaviour is of paramount importance to investors because such knowledge helps investors to know or gain more information on the data generating such returns. Knowing how volatile the stock market has been or is expected to be, guides investors in their decision-making process as such knowledge enables them to access both the return potential of the market as well as the uncertainty of such returns.
Volatility is the “magnitude of movements regardless of direction” and stock market volatility relates to the magnitude of price changes without paying attention to whether the change is up or down. Stock market volatility is captured by two broad measures: Implied and Realized volatility. Realized volatility differs from implied volatility. While implied volatility is a forward-looking measure, realized volatility is historical or backward looking. Implied volatility answers the question, what is the expected volatility of the market in so and so time while realized volatility answers the question, what was or is the actual market volatility in so and so period. While realized volatility is based on the actual movement of an underlying, implied volatility is based on a value derived from associated options prices. Realized volatility measures real risk while implied volatility measures anticipated risk. Indices that measure volatility abound the world over especially in more advanced markets. The Chicago Board of Exchange (CBOE)’s VIX, otherwise called the fear gauge, measures implied volatility in the US market while India VIX is a volatility index based on the NIFTY Index Option prices in India and is meant to measure implied volatility in Indian stock market. In the UK, implied volatility is measured with the FTSE IVI and is based on the index’s underlying option prices. In abundance also are realized volatility measures in more advanced markets like those calculated by S&P Dow Jones.
Source: Chicago Board of Exchange (CBOE)
Currently, there is no index that measures implied or realized volatilities of the Nigerian stock market. The absence of an implied volatility measure is understandable as such is derivable from options and options are nonexistent in the Nigerian market. Realized volatility on the other hand, is derivable from historical data. To fill this gap, analysts at Quantitative Financial Analytics have come up with a Realized Volatility Index for the Nigerian Market. The index is a one-month look back volatility measure of the NSE All Share index, (hereinafter called the underlying index). It assumes a 21-day monthly trading period and multiplies the result by 100 to reflect the index as a percentage. The index is calculated daily and for all the trading dates that its underlying index (ASI) is calculated. The index has been calculated from 1998 to present and gives a bird’s eye view of the most and least volatile periods of the Nigerian stock market.
Source: Quantitative Financial Analytics
Comparatively speaking, the S&P 500 1-month realized index as at November 22, 2017 was 5.85, down from 5.87 the previous day while the Quantitative Financial Analytics (QFA) Nigeria All Share Index realized volatility index for corresponding period was 6.45, down from 6.55 the previous day. Now, it is easy to talk about market volatility in Nigeria with some specifics and ability to compare with other markets and periods, at least in realized terms.
Quantitative Financial Analytics continues to add value to the Nigerian market with its many analytics. It will be recalled that not long above, it rolled out its Fixed Income Analytics Report, which is a report with robust data and information on sovereign and corporate bonds trading in the Nigerian market.
For more information on the index and other reports, please contact us at email@example.com
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