Categories

Archives

The January Barometer

The January Barometer, sometimes also referred to as January effect (although the January effect is a different thing), is the theory according to which market performances during the month of January can be used to predict the trend for the rest of the year. The January Barometer theory is often summarized by the saying: “As goes January, so goes the year”. The practical implications are rather straightforward: if the asset class under examination has a positive return in January, the theory suggests that it will be a bullish year while a negative performance should predict a bearish trend for the upcoming months. The January Barometer theory is based on the assumption that many fund managers and institutional investors, particularly those who are interested in medium–to–long term investments, at the beginning of each new year, will tend to place their positions already discounting their view on the next 6 to 12 months. Consequentially, the theory suggests that, should the view be negative, portfolio managers will position themselves on the short side of the market at the beginning of January. Otherwise, should they think the price action will go up in the next 6 to 12 months, they will go long. Hence, the theory is based on the fact that the buying or selling pressure generated by the amount of money allocated in the market by big players in January should move the price in the direction of their forecasts. This is the theory but as Albert Einstein stated: “In theory, theory and practice are the same. In practice, they are not”. The present research aims to investigate and study the reliability of the January Barometer theory in order to assess, under a probabilistic point of view, what are the chances to actually earn consistent profits if applied to financial markets. The research has been carried out on major equity indices in the world that have been, in turn, subdivided for geographical location: North America (S&P500, NASDAQ Composite), Europe (DAX30, FTSE100), AustralAsia (Nikkei225, ASX200) and Emerging Markets (Hang Seng, Bovespa, BSE Sensex). The dataset that has been used consists of index prices ranging from January 2004 until December 2014 implying 11 years worth of data. The back testing analyses that will be exposed and commented are simply aimed to understand if January’s market returns matched, if not in size at least in sign, with yearly ones. Hence, the combination negative return in January/negative yearly return as well as the combination positive return in January/positive yearly return will all be calculated as success cases. On the other hand, all non–matching returns will be treated as a failure of the theory. The results of the analyses will be presented and explained by geographical location, hence, the first equity indices that will be analyzed are the North American ones:

yearly returns: S&P500, NASDAQ Composite

The above reported table shows, in the first column, January’s lognormal returns calculated for the S&P500 while the second one lists the total return for each year. The right hand side of the table provides the same calculations but based on the NASDAQ Composite index. First of all, it is worth noting that, over the last 11 years, the average return for the S&P500 index has been +4.89% while the NASDAQ Composite yielded an average of +6.78%. Secondly, both equity indices have experienced similar fluctuations during the crises but the NASDAQ has consistently outperformed the S&P500 since the 2012 so far. The following chart plots the success/failure rates of the January Barometer theory applied to the aforementioned asset classes over the last 11 years:

success/failure rate: S&P500, NASDAQ

The success rate for both S&P500 and NASDAQ Composite is 54.5% while the failure rate is 45.5%. These numbers simply mean that the JB theory held true for 6 years but it unsuccessfully predicted yearly returns in 5 occasions. Nevertheless, the 54.5% success rate definitely does not fall within the category “reliable strategies” but different results could potentially come from different markets. The next table presents the results of our analyses on the German DAX30 and the British FTSE100:

yearly return: DAX, FTSE100

The tables evidently show that during the financial crises in 2008, the selected European markets performed as poorly as their American counterparties (although the British FTSE100 did not violate the –40% threshold). The last 3 years have gone quite well as far as returns are concerned although in the 2014 the British FTSE100 (–2.62%) underperformed the DAX30 (+3.06%). On average, the German index, over the last 11 years, has yielded a +7.26% return while long term investors in the British market managed to gain only +2.34%. The next graph plots the success/failure rates of the January Barometer theory applied on the aforementioned European asset classes:

success/failure rate: DAX, FTSE100

The results are very different from the ones observed for the overseas equity indices. First of all, the JB theory applied to the DAX30 has higher failures (54.5%) than successes (45.5%). In particular, the January Barometer strategy has successfully predicted future returns 5 times but it has failed 6 times implying that even in this market it led to poor results. On the other hand, the JB applied to the British FTSE100 shows a 63.6% winning chance while the losing probability is only 36.4%. In this case, the returns registered in the first month of the year since 2004 proved to be good forecasters for yearly returns. Numerically, the JB strategy would have been profitable in 7 cases while it would have failed only in 4 occasions. The next table lists the historical returns for the AustralAsian region:

yearly return: NIKKEI225, ASX200

The equity indices that have been used as a proxy for the AustralAsian geographic region are the Japanese Nikkei225 and the Australian ASX200. The 2008 was a very negative year also in AustrlAsia, in fact, both yearly returns are very close to the –50% threshold. However, also the European credit crisis in 2011 has dramatically influenced the aforementioned indices: –20.58% for the Nikkei225 and –13.16% for the ASX200. The data for the average returns, calculated over the last 11 years, show that the Nikkei225 yielded a +2.89% while the Australian equity index returned an average of +3.57% to potential long term investors. Did the January Barometer strategy provide any extra gains? The next chart will attempt to answer this question:

success/failure rate: NIKKEI225, ASX200

The Japanese index displays the usual 54.5% / 45.5% split between success and failure rates implying that the JB strategy proved profitable only 6 times and failed in 5 cases. Conversely, the success rate for the ASX200 is 63.6% (7 successes) while the failure rate is only 36.4% (4 failures) implying that the JB strategy was definitely more profitable when applied to the Australian index than to its Japanese equivalent. The last table of the present research focuses on the past performances of a geo–economic, rather than merely geographic, area: emerging markets.

yearly return: Hang Seng, Bovespa, BSE Sensex

The equity indices that have been selected for this section are the Hang Seng (Hong Kong), the Bovespa (Brazil) and the BSE Sensex (India). The first thing to notice is that during the crisis the losses incurred by these markets have been larger than the ones observed for the indices we have mentioned so far. In fact during the credit crunch, with the exclusion of the Brazilian Bovespa that in 2008 had a negative return of “only” 46.25%, the Hang Seng yielded a –55.43% while the Indian return for the same year was a remarkable –70.64%. However, the scenario considerably changes if the 2011–2014 time interval is taken into account. In fact, the Indian equity index, even including the drop in the 2011, has consistently outperformed the other two. As far as long term average returns are concerned, since the 2004 so far, the Hong Kong’s Hang Seng yielded a +5.43%, the Brazilian Bovespa returned a +5.81% while the Indian BSE Sensex averaged an impressive +13.68%. Emerging markets average returns are clearly very high but the BSE managed to outperform all other equity indices considered in the present research (the German DAX30 ranks second with a +7.26% and it is immediately followed by the NASDAQ Composite index that yielded an average return of +6.78%). The next chart plots the success/failure rates obtained by running the January Barometer strategy on the Hang Seng, Bovespa and BSE Sensex:

success/failure rate: Hang Seng, Bovespa, BSE Sensex

The success rates for the BSE Sensex (54.5%) and Bovespa (45.5%) do not really seem to provide a hedge (although the strategy proved more profitable on the Indian equity index than on the Brazilian one). The most significant information that can be extracted from this analysis is the high failure rate on the Hong Kong’s index (63.6%). In particular, the January Barometer strategy has consistently failed to predict yearly returns on the Hang Seng index for 7 years while it proved successful only in 4 cases.

All in all, the analyses just conducted on the 9 equity indices considered in the study seems to point out that the JB strategy does not to provide any particular hedge for investors. Nevertheless while wrangling data some interesting patterns have emerged. The patterns that have been detected can be grouped in two categories: the winning pattern and the losing pattern.

Winning Pattern

The January Barometer strategy can only yield two mutually exclusive outcomes: it is either profitable or not (there is a chance that the yearly return could eventually be 0% but the associated probability, over 252 trading days, is so low that we have voluntarily excluded it from the scenario analysis). The winning pattern has been extracted by simply running a frequency analysis on the times the JB strategy proved to be profitable. The JB strategy basically states that January’s return should match the yearly one, however, it makes no difference between negative or positive returns. Consequentially, as stated at the beginning of the research, a positive January’s return in a positive year would be counted as a success but a negative January’s return in a negative year would be also counted as a success. The most important thing for the strategy to work is a match between returns. The questions this section is trying to give an answer to are: is there a pattern among success cases? Do success cases have anything in common? Do bullish success cases outnumber bearish ones or vice versa? Before showing the results, it is worth reminding that 11 years worth of data on 9 different asset classes have been filtered implying a total of 99 observations. 52 out of 99 observations fall into the winning pattern category while the remaining 47 are axiomatically assigned into the losing pattern one. The following pie chart attempts to summarize the results obtained from data mining the data associated to the first pattern:

successes: bullish year vs bearish year

The success cases, for the combination January’s positive return in a positive yielding year (green area called BULL), are 34 while the success cases, for the combination January’s negative return in a bearish year (red area called BEAR), are only 18. Clearly, the outcome of this frequency analysis is a consequence of the overall trend in each year but it seems that the JB strategy, when profitable, works best in positive performing years rather than in negative ones (winning pattern). In order to understand why this is the cases we have to proceed and mine the data for failure cases.

Losing Pattern

In the previous section it has been observed that, numerically speaking, the majority of success cases happened during the combination January’s positive return in a positive yielding year. It has also been stated that the JB strategy “works best in positive performing years rather than in negative ones”. However, in order to understand why this is case, the present section will analyze all failure cases. If the JB strategy did not work, it axiomatically implies that January’s return did not match the sign of the yearly one. Consequentially, there are only two scenarios to consider when analyzing failure cases: the return in January was positive but the yearly one turned out to be negative or the year started by yielding a negative return in January but it ended with a positive performance. The next pie chart plots all the failure cases and groups them into two categories: BEAR TO BULL (negative return in January but positive on a yearly basis) and BULL TO BEAR (positive return in January but negative on a yearly basis):

failures: bear to bull years vs bull to bear years

The above reported chart is evidently displaying that, among failures, there is a very frequent pattern: the vast majority of failures in the JB strategy are due to years starting out with a negative return but that subsequently yield a positive one (losing pattern). Numerically speaking, the BEAR TO BULL cases counted 39 observations while the BULL TO BEAR ones are only 8.

Conclusion

  • The January Barometer strategy does not seem to provide consistent profits at least for the considered asset classes and the selected time frame
  • The January Barometer strategy successfully predicted yearly returns in 52 cases (52.5% of the total observations)
  • 34 of the 52 success cases come from the combination January’s positive return in a positive yielding year while only 18 come from the combination January’s negative return in a negative yielding year
  • The January Barometer strategy failed to predict yearly returns in 47 cases (47.5% of the total observations)
  • 39 of the 47 failure cases fall within the BEAR TO BULL category where January yielded a negative return but the year ended up with a positive performance
  • Only 8 failure cases fall within the BULL TO BEAR category where January yielded a positive return but the year ended up with a negative performance

 

The present research can be expanded in many ways. In fact, potential research developments could come from increasing the datasets in order to allow 20 or 30 years worth of observations, from including more equity indices or by expanding the analysis to different types of asset classes such as treasury bonds, commodities and currencies.

E-Mini Nasdaq Futures Volatility Forecast (05/10/2011)

E-Mini Nasdaq futures opened at 2,227 on Monday, touched 2,254 on Tuesday, dropped to 2,220 on Wednesday, settled around 2,192 on Thursday and closed at 2,123 on Friday.

The current volatility is 1.7% (26.9% annualised) and the TGARCH plot is now showing an upward sloping curve which is suggesting that further market swings could be expected in the upcoming days. However, this level has been hardly violated in the past and it is reasonable to guess that a retracement of the volatility curve will occur.

The HyperVolatility team is moderately bullish E-Mini Nasdaq futures because the conditional variance should plunge and favour a recovery of the price action which could eventually retest the 2,300 threshold by Friday.

 

E-Mini Nasdaq Futures Volatility Forecast (19/09/2011)

E-Mini Nasdaq futures opened at 2,196 on Monday, jumped to 2,220 on Tuesday, rose to 2,250 on Wednesday, achieved 2,291 on Thursday and closed at the same price on Friday.

The current volatility is 1.3% (20.6% annualised) and the TGARCH plot is clearly displaying a downward sloping curve which implies that the upcoming days could see a diminished rate of volatility and welcome a recovery of the price action. However, this level proved to be a strong support level in the past and a failure to break through the 1.1% – 1.2% area (17.4% – 19% in annual terms) would probably signal that the volatility could keep going up and eventually retest the 2% area (31.74% annualised).

The HyperVolatility team is moderately bullish E-Mini Nasdaq futures because the decrease in the conditional variance should keep the price action up. Specifically, there is a chance that the 2,350 – 2,370 area get retested before the end of the week but the movement is likely to be very weak and choppy.

The fact that the volatility is diminishing does not mean that short term retracement of futures prices are to exclude. The nervousness amongst investors is palpable and any negative news could change the direction of this fragile market.

Needless to say that the FOMC statement is going to play a key role this week and it is definitely worth watching.

VXN Index Volatility Forecast (19/09/2011)

The VXN Index opened at 37.97 on Monday, dropped to 36 on Tuesday, plunged to 33.36 on Wednesday, touched 30.67 on Thursday and closed at 29.36 on Friday.

The current volatility is 6.1% (21.1% monthly) and the volatility curve seems now ready to complete its mean reverting journey which should end around the 4% – 4.5% threshold (13.8 -15.5% monthly) although some short term retracements are still likely to occur over the next trading hours.

The volatility of the VXN Index is clearly signalling that in the upcoming hours the implied volatility of the Nasdaq100 options should diminish but such a scenario is going to hold only if the concerns regarding European debt are going do not unleash an ulterior sell off.

The HyperVolatility team is moderately bearish the VXN Index which could eventually retest the 25% level by Friday. Nevertheless, the likelihood of a short term explosion of the conditional variance remains pretty high because despite the numerous meeting European politicians appear unable to come up with a concrete plan which would save Greece and prevent a domino effect which would destroy the entire old continent economies.

E-Mini Nasdaq Futures Volatility Forecast (06/09/2011)

E-Mini Nasdaq futures opened at 2,220 on Monday, touched 2,226 on Tuesday, rose to 2,246 on Wednesday, plummeted to 2,218 on Thursday and closed at 2,165 on Friday.

The actual volatility is 1.5% (23.8% annualised) and the TGARCH plot is now displaying a slightly upward sloping curve which should keep its upward trend over the next trading hours. The conditional variance, having found support around the 1.5% threshold, seems now ready to bounce back up again and eventually retest the 2% level (31.7% in annual terms) by Friday.

The HyperVolatility team is bearish E-Mini Nasdaq futures because a further increase in the conditional variance is quite likely to occur over the next trading hours.

The price action is likely to retest the 2,100 level by Friday and the fact that the VXN Index will experience an upward moves make this forecast even more reliable.

Maximum attention will be needed on Thursday because, as previously mentioned, Obama’s speech can radically change the overall market sentiment in a matter of a few hours.

VXN Index Volatility Forecast (06/09/2011)

The VXN Index opened at 32.1 on Monday, settled at 32 on Tuesday, dropped to 31.3 on Wednesday and remained at the same level even on Thursday but on Friday it closed at 33.

The actual volatility is around 7.9% – 8% (27.3% – 27.7% monthly) and the TGARCH plot is displaying a curve which is downward sloping and right in the middle of a mean reverting process. However, the speed at which the conditional variance tend to collapse towards its long term equilibrium point has substantially diminished because, particularly during the final stage of the above mentioned movement, the volatility tend to fall down much more quickly than it is and therefore this phenomenon should be interpreted as a warning signal.

The big and violent spike the volatility experienced on Friday (from 31% to 33%) is a great indicator for investors ‘nervousness. The volatility usually rises or declines gently but these unexpected and sharp jumps are clearly indicating that the situation is not looking good.

The HyperVolatility team is bullish the VXN Index because the decreased mean reverting speed and high fear will probably push the index towards the 35% by Friday.

On the other hand, the volatility could decrease and retest the 30% level if Obama is going to announce big changes in the fiscal policy measures.

E-Mini Nasdaq Futures Volatility Forecast (30/08/2011)

E-Mini Nasdaq futures opened at 2.047 on Monday, rose to 2,123 on Tuesday, touched 2,139 on Wednesday, dropped back to 2,111 on Thursday and closed at 2,165 on Friday.

The actual volatility is 2% (31.7% annualised) and the TGARCH plot is showing a slightly upward sloping curve which would normally imply an increase in market fluctuations. The price action has been significantly affected by Bernanke’s speech and many traders either adjusted their positions or closed their existing ones before the conference causing a sensible augment in the oscillation rate.

However, the chart is still displaying a mean reverting process which has not completed its journey towards the long term equilibrium point but that is likely to do so in the upcoming hours.

The HyperVolatility team is bullish E-Mini Nasdaq futures because the volatility should soften over the next trading hours favouring a recovery of the price action which should eventually retest the 2,250 points by Friday.

Needless to say that the macroeconomics news that are going to be released will have a massive impact on the price action and some negative figure could drag futures prices back down into the 2,100 area.

VXN Index Volatility Forecast (30/08/2011)

The VXN Index opened at 42 on Monday, dropped to 35.4 on Tuesday, settled at 35.6 on Wednesday, rose to 39.4 on Thursday and closed at 34.4 on Friday.

The actual volatility is 12% (41.5% monthly) and the TGARCH plot is showing a volatility curve which has now created a double top and seems ready to continue its mean reverting journey towards the 4% level (13.8% monthly).   The very last part of the curve displays an insignificant retracement that was caused by fear and nervousness before Bernanke’s speech but that should not alter the overall process.

The HyperVolatility team is bearish the VXN Index because the large up move should start mean reverting at an increased pace over the next trading hours implying that, given the positive correlation between the Nasdaq100 implied volatility index and its stochastic volatility movement, we should see readings around the 30% threshold around Friday, macroeconomics news permitting.

E-Mini Nasdaq Futures Volatility Forecast (22/08/2011)

The market jumped up at the open and the price action remained at a fairly high level before Germany and France prime ministers decided to destroy what it was left of investors’ confidence whilst US manufacturing data made sure to scare away all buyers left on this planet.

E-Mini Nasdaq futures opened at 2,203 on Monday, touched 2,199 on Tuesday, dropped to 2,176 on Wednesday, kept plummeting on Thursday where it touched 2,084 and closed at 2,042 on Friday.

The current volatility is around 3% (47.6% annualised) and the TGARCH plot, even in this case, is showing a sharp augment in the conditional variance which seems it will increase, given the slope of the curve, over the next trading days. The chart is obviously displaying an extremely high level of market fluctuations and the fact that the impact of the mean reverting process has been so weak is a very important warning signal which should not be ignored.

The HyperVolatility team is bearish E-Mini Nasdaq futures because the conditional variance is likely to augment in the short term and the price action is probably going to retest the 1,970 – 2,000 area by Friday.

Investors will concentrate their attentions on Europe’s debt problems and the European Central Bank whilst on Friday all eyes will be on Bernanke.

The oscillation rate could easily augment during the announcement of the aforementioned news and increase the magnitude of any potential drop of E-Mini Nasdaq futures.

VXN Index Volatility Forecast (22/08/2011)

Needless to say that the sharp, violent and unexpected explosion of the conditional variance is the natural consequence of what happened the last week: ridiculous politicians and bad macroeconomics news. In particular, the VXN Index opened at 30.44% on Monday, rose to 31.55% on Tuesday, touched 31.17% on Wednesday, jumped to 41.61%, on Thursday and climbed to 43.47% on Friday.

The actual volatility is 15.8% (54.7% monthly) and the TGARCH plot is clearly displaying a steep upward sloping curve which highlights the fact that wild market swings and violent retracements are very probably to occur in the upcoming days. Moreover, it is worth noting that the current volatility level is very close to the one achieved during the big drop occurred in equity markets during March 2010: a very strong warning signal.

The implied volatility of the high-tech index should increase over the next hours as many market participants will keep buying protections against their stock portfolios.

The HyperVolatility team is bullish the VXN Index and we expect the Nasdaq100 implied volatility to touch the 48% – 50% by Friday.

There could be unexpected good news which is going to smooth the volatility curve but even the most insignificant bad macroeconomics data would twist investors’ mood in a matter of a few minutes.

Figures from US and Germany will be crucial this week whilst Bernanke’s speech on Friday would be of absolute importance.

Go back to top