{"id":13712,"date":"2020-01-20T00:00:26","date_gmt":"2020-01-20T05:00:26","guid":{"rendered":"http:\/\/leavittbrothers.com\/blog\/?p=13712"},"modified":"2020-01-20T00:00:26","modified_gmt":"2020-01-20T05:00:26","slug":"wayne-whaleys-toy-barometer-2","status":"publish","type":"post","link":"https:\/\/blog.leavittbrothers.com\/?p=13712","title":{"rendered":"Wayne Whaley's TOY Barometer"},"content":{"rendered":"

Wayne Whaley was a quant before quants existed. He has a math background and has been managing money since the late 1980’s.<\/span>
\nHe considers the TOY Barometer to be the single most reliable seasonality barometer of forward stock market returns – so much so that he’s said if he could only make one trade\/year based on one indicator, this is the indicator he’d use.<\/span>
\nWhaley’s goal was to identify what he called the “kingpin of seasonal barometers.” He stated: \u201cI implored my computer to take a few seconds to exhaustively study S&P performance over every time period of the year and determine which time frame\u2019s behavior was proprietor of the highest correlation coefficient relative to the following year\u2019s performance.\u201d<\/span>
\nWhat he found was there was a high correlation between the S&P 500’s returns between November 19th and the following January 19th and the S&P’s performance the 12 months following January 19. And since the 2-month period straddled the turn of the year (TOY) and the gift giving season, he called it the TOY Barometer.<\/span>
\nSpecifically, the period studied is November 20 – January 19 (if Nov 20 is on a weekend, use the Monday after the weekend, and if Jan 19 is on a weekend, use the Friday before). He only considered the price-only return (no dividends).<\/span>
\nIf the return during this 2-month period was greater than 3%, a bullish signal was given, and the market was very likely to do well over the following 12 months. If the return was 0-3%, the signal was considered neutral, and results were somewhat random and in line with what is considered average. And if the return was negative, a bearish signal was given, and returns tended to be very poor.<\/span>
\nSince 1950, there have been 36 bullish signals (including the one that just triggered), 19 neutral signals and 16 bearish signals. Let’s look at each signal group. <\/span>
\nBullish Signals<\/strong><\/span>
\nThe 35 completed bullish signals have led to gains 33 times the following 12 months. The losses were in 1987, the year of one of the biggest single-day crashes in history, and 2018, that year that included a 20% drop during the fourth quarter. <\/span>
\nThe average and median gains of the 12 months following the bullish signals were 17.7% and 15.1%. This isn\u2019t much better than the \u201call years\u201d stats, but the win rate (94%) is much higher than the \u201call years\u201d win rate (73%). <\/span>
\n\"\"
\nNeutral Signals<\/strong><\/span>
\nThere have been 19 neutral signals. The following year was positive 12 times (63%) and negative 7 times (37%). The overall average and median returns were 6.0% and 7.1%. But among the “up” years, the average and median gains were 14.4% and 9.4%, while the “down” years\u2019 average and median losses were -8.5% and -7.8%. There were several big up years (1995, 1996, 1998, 2003), and two big down years (1973, 1977), so even if there is a neutral signal, there’s still a decent chance the following 12 months will venture far from its January 19 print. <\/span>
\n\"\"
\nBearish Signals<\/strong><\/span>
\nThere have been 16 bearish signals. Only 6 (38%) of the following years posted a gain while 10 posted losses \u2013 and 6 of those 10 posted double digit losses. The overall average and median returns were -3.6% and -6.0%. The “up” years posted average and median gains of 14.6% and 15.5%, while the “down” years posted average and median losses of -14.6% and -12.9%. So despite the low win rate, when the market does well, it has the ability to do very well, as was the case this past year. <\/span>
\n\"\"
\nHere’s a summary.<\/span>
\nThe bullish years have a very high win rate (94% vs 73% for \u201call years\u201d). The average gain (17.7%) isn\u2019t much higher than the \u201call years\u201d gain (16.6%), so a bullish signal increases the odds of an up year but doesn\u2019t increase the gain itself. <\/span>
\nThe bearish years have a low win rate (38%). The gains during those up years (14.6% vs 16.6% for all years) are very good, but the losses during the down years are noticeably bigger than when a bullish or neutral signal is signaled (-14.6% vs -6.2% for bullish years and vs -8.5% for neutral years). So the odds of a down year are much higher, and the losses that follow are much bigger. <\/span>
\nThe neutral years are mixed. The win rate is 63% (vs 72% for \u201call years\u201d), with the gains during up years being pretty good (14.2% vs 16.6% for \u201call years\u201d) and the losses during down years being moderate (a little worse than bullish years but much better than bearish years).<\/span>
\nIn summary, most notable \u2013 and yes this table is a little confusing \u2013 is the following: When a bullish signal is in play, odds heavily favor solid gains over the following 12 months, but when there\u2019s a bearish signal, odds favor a down year with a relatively big loss. But regardless of the signal, \u201cup\u201d years tend to be very good.<\/span>
\n\"\"
\nThe most recent TOY period just concluded. The current signal is bullish (see the top line of the “bullish” table above). <\/span>
\nOdds favor the next 12 months posting a solid gain. <\/span>
\nJason Leavitt
\nJason@leavittbrothers.com<\/span><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Wayne Whaley was a quant before quants existed. He has a math background and has been managing money since the late 1980’s. He considers the TOY Barometer to be the single most reliable seasonality barometer of forward stock market returns – so much so that he’s said if he could only make one trade\/year based […]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[3],"tags":[],"_links":{"self":[{"href":"https:\/\/blog.leavittbrothers.com\/index.php?rest_route=\/wp\/v2\/posts\/13712"}],"collection":[{"href":"https:\/\/blog.leavittbrothers.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blog.leavittbrothers.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blog.leavittbrothers.com\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/blog.leavittbrothers.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=13712"}],"version-history":[{"count":0,"href":"https:\/\/blog.leavittbrothers.com\/index.php?rest_route=\/wp\/v2\/posts\/13712\/revisions"}],"wp:attachment":[{"href":"https:\/\/blog.leavittbrothers.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=13712"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blog.leavittbrothers.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=13712"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blog.leavittbrothers.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=13712"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}