Trading Seasonal Price Patterns in Stocks, Futures, & Forex!
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- Filter out the few best seasonally sorted dividend-value-momentum-size investments from 1,100 stocks on the NYSE, NASDAQ, Amex, futures, International equity ETF, and forex markets.
- Put the odds on your side for expected returns of 18% or more!
- Sidestep mindless losses by delaying entry (exit) when the odds are against (for) you.
- A paid subscription to TradeMiner software is highly recommended to get the most out of this course.
Have you ever asked yourself,
“How Can I Get 20% Double Digits Returns Using the Methods of Soros, Buffet, and Keynes?”
The most respected studies by Wall Street come from top business schools using such data as that from the Center for Research in Security Prices (CRSP) with accounting data from Compustat files from Standard & Poor’s. Your problem is that this data is extremely expensive for finance industry outsiders of Wall Street.
Graciously academics from these top schools make their research public to Main Street.
That allows you to gain an unfair advantage over the retail investing public. But knowing what is in these studies is not enough.
You need to know how to convert this information into practice.
This course offers a low-cost solution to creating your virtual investing and trading laboratory for seasonal, value, momentum, size, and dividend signals. The tools and knowledge you will learn inside allow you to distill 3,700 stock to the best few that are most likely to kick out double digit expected gains at the press of a button.
I am Dr. Scott Brown. I hold a Ph.D. in finance from the University of South Carolina. I am an associate professor of finance at the AACSB accredited Graduate School of Business of the University of Puerto Rico.
Discover how to capture 13% expected returns on seasonality alone. Two major money managers used a little known list of value stocks that generated actual returns of 20% -- Benjamin Graham and Warren Buffett.
This course shows you how to find value stocks the exact same way. This has been shown by Fama and French (2012) to generate excess abnormal expected returns of 5.4%.
Sorting on seasonality and value generates an expected portfolio return of 18.4% on average. Buffett and Graham extracted 20% out of the market year after year for three decades.
Then I will show you how to sort on momentum for a 7.4% excess abnormal return. This can be sorted by size for another 1.2% expected kick.
This yields a strategy with an expected return of 21.60%. Your actual returns may be higher or lower.
Here’s what my Udemy students are saying, “Hello Dr. Brown, Thanks - now that I've taken it I realize the majority of my company plan selections are horrible!! Thank you.”
Every day market opportunities come ... and they go!
This course is backed with a 30 day money-back guarantee by Udemy as impartial third party.
Enroll right now to get immediate and direct access to my knowledge and mentoring! -Doc Brown
P.S. WARNING: Every day that passes reduces your possibilities of compounding your wealth!
P.P.S. Every day that passes you grow older and your abilities, memory, and compounding declines. Enroll now before it is too late!
- This course is ideal for single stock investors, option traders, futures traders, and Forex traders at all levels.
A Warm Welcome from Dr. Scott Brown
I am an associate professor of finance from the University of Puerto Rico at the Graduate School of Business. We are AACSB accredited and this is an important fact.
Just 5% of business schools worldwide are AACSB accredited.
I hold a Ph.D. in finance from another AACSB accredited school of business at the University of South Carolina.
My Ph.D. is highly mathematical and allows me to read and interpret research you not only do not have easy access to but you would not likely understand.
Why am I Teaching This Seminal Course on Seasonality in Investments?
My Ph.D. is highly mathematical and allows me to read and interpret research you not only do not have easy access to but would not likely understand. For years the only detected seasonality was higher returns on small stocks around the turn of the year.
But this went in and out of the data like the flying Dutchman.
Then a few years ago research surfaced showing substantial returns to investors based on seasonality. And just this year in the #1 ranked Journal of Finance comes a study from the ultra-prestigious University of Chicago Booth School of Business proving 13% returns from seasonality strategies in stocks. Seasonality is also present in commodity futures.
Who Is This Course for?
This course is for you if you are an independent thinking stock investor or futures trader who routinely performs your own research.
Overview of this Seasonal Investing and Trading Course on Udemy
This course is composed of four parts. Each part builds on the first so I do not recommend that you skip around.
- The first part of this course introduces you to me. Here I explain the basic structure.
- The second section delves into the academic literature to piggy back on the work of the finest finance minds with large budgets for data and programming beyond the scope of any small investor or trader.
- The 3rd part shows you how I use my own special software for finding seasonality.
- The fourth section is filled with special topic lectures designed to tie the academic facts into cohesive investing and trading strategies put into practice with the same screening software I use.
Your Palpable Benefits as My Student of this Udemy Course
Because of the recent nature and complexity of this information you will finish this program with an understanding of seasonality in investing and trading few on Wall Street enjoy. You will have specific strategies intended to help you in your application of this material.
The end goal is to make you a competent seasonal stock investor or futures trader.
A very important body of research led by a recent publication from the University of Chicago shows that 13% raw returns are possible by simply buying stocks that have been rising in the same calendar month looking back a year.
Researchers ask the simple question of “was the trend up or down in that month?”
- See Keloharju, Matti, Juhanni Linnainmaa, and Peter Nyberg. 2016. Return Seasonalities. Journal of Finance (forthcoming).
This is an updated version of the plot in Heston and Sadka (2008) See Heston, Steven and Ronnie Sadka. 2010. Seasonality in the cross-section of stock returns: The international evidence. Journal of Financial Economics 87. 418-445.
What is very interesting about this chart is that there are pronounced peaks every twelve months in stock expected returns. Expected returns are what we anticipate on average not what we will actually get on a particular stock investment.
Buying stocks based on the same-calendar-month historical returns yields an average raw return of 13% per year from 1963 into 2011. This represents a 3.79% and a 2.72% seasonal premium over the 9.21% geometric average return as reported in the finance textbook Essentials of Investments by Bodie, Kane, and Marcus from 1926 to 2010 and 10.28% from 1956 to 1985.
These are not driven by differences in seasonality of quarterly occurrences such as earnings and dividends. Seasonality has to be exposed to systematic risk to work.
Interestingly these patterns you see here are just as strong regardless of bullish or bearish sentiment. This shows that there are a lot of different sources of risk and premiums impacting seasonality.
The researchers explain that the risk reward tradeoffs of seasonal strategies are not just risky but also highly attractive due to the possibility of very high returns. You can gain an immense benefit in this even if you never enter the market based on a seasonal trigger.
Delaying a purchase (exit) to wait for a high (low) return month keeps you in cash when the odds are more (less) favorable due to negative return seasonality. In futures you can delay a trade or tighten stops when you know you are in a month that is not favorable to the market direction.
Forex is the weakest market among futures and stocks for anomaly or seasonal trading but can be mixed with a 10 day moving average on a daily chart. Research widely supports the anomaly that stock markets tend to rise in the cold winter months.
It is important that you understand that seasonality must be combined with known anomalies for the highest impact with dividend yield, value, or momentum. I will cover each in this course.
This study uses data from the Center for Research in Security Prices spanning from January 1963 through December 2011. Accounting data comes from annual Compustat files from Standard & Poors.
The data alone for this study is extremely expensive for anybody outside Wall Street or the ivory tower. I am very grateful that there is a large body of academics willing to make this kind of research public.
Momentum yields an astonishing 23.04% expected return per year.
Panel B in Table IV shows that using anomaly strategies based on same-calendar-month seasonality is profitable. Other-calendar-month seasonality is not.
Panel B of Table V shows that momentum is by far the strongest anomaly. This is the simplest signal to detect since it relies on looking for a positive trend in a stock looking a year back.
But the vast majority collapse in what are known as price reversals.
Notice that seasonality is pretty much as robust as momentum. Dividend yield and value also pack a punch.
I will show you how to combine each of these core anomalies with seasonality to enhance returns to investing in …
2. Dividend Yield Sorted on Size
Notice that the returns are generally lower in the last time period of 2003 to 2011 due to the market crash in equities, commodities, and real estate. Very few investors in the public understand what you are learning now. Wall Street has more knowledge on their side and this course is intended to level the playing field.
Trading commodities based on seasonality is much more profitable than country indexes. The futures commodities analyzed in the study are …
· Crude Oil
· Feeder Cattle
· Heating Oil
· Kansas Wheat
· Lean Hogs
· Live Cattle
· Natural Gas
The country indexes include different political economies that are foreign with respect to the dominant United States equity market …
· United Kingdom
Notice that the t-statistic is weaker for commodities but nonetheless above the 5% level of significance of 1.96 for both commodities and foreign stock indexes as measured by the MSCI.
This table is very good news for investors. Seasonality has very low correlation with U.S. equities. This means that stock investors can diversify returns to an equity portfolio by simply adding seasonal strategies to a retirement portfolio.
Panel B shows that strategies that trade seasonality in monthly or daily stocks in the United States can obtain dramatic advances in diversification due to extremely low correlations between United States stocks, foreign stock indexes, and commodities.
Exchange traded funds are best known as ETFs.
ETFs allow individual 401(k) and Roth IRA investors to easily add both commodities and foreign stock indexes to their retirement portfolio. This course teaches you how to analyze which to select.
Most investors trade across daily charts.
Correlations of seasonality across daily stocks are no higher than 1% for commodities. This is remarkably low and offers investors tremendous advantages in diversification.
Employing a half and half mix of a strategy of Seasonal Dividend Yield Sorted on Size generates a Sharpe ratio of 1.24. This is nearly triple that of the market of 0.46.
The highest Sharpe ratio for a single seasonality strategy is 0.95 for that of value stocks. The baseline for reasonable Sharpe ratios for seasonal portfolios is 1.52 because this is the level for the mean-variance efficient portfolio of all nine seasonal strategies.
The Sharpe ratio is the actual return on a portfolio scaled by volatility as measured by the standard deviation of those same actual returns. Volatility is in the denominator (undesirable) and the actual return is in the numerator (desirable).
The Sharpe ratio measures the fact that investors prefer higher to lower returns. Stock investors and futures traders also prefer lower return volatility to higher due to reduced uncertainty of end wealth.
In a nut shell you prefer higher Sharpe ratios to lower.
Now that you understand this let’s look at the results with regard to Sharpe ratios. The optimal weight (for this study not your portfolio) is 46% against 12% in momentum, 24% in Value, 10% in Size, and 8% in the Market portfolio. This generates a Sharpe ratio of 1.67.
An alternate portfolio of 3% market (such as the ETF SPY), 2% in Size, 23% in Value, 4% in Momentum, 21% in the Monthly U.S. Equity seasonal factor, 1% in the Commodities seasonal factor, 4% in the foreign stock seasonal factor, and 41% in the U.S. Daily equity seasonal factor yields the highest Sharpe ratio at 2.75.
Remember that this is a rigidly controlled scientific study. Application of this knowledge will generate portfolio compositions that are far different. Novy-Marx and Velikov (2015) explain that you can lower turnover and increase returns by simply delaying a trade when the strategy signals selling (buying) a stock with a season pattern of strength (weakness) in the upcoming month.
Adding seasonality to these experimental portfolios constructed with actual historic returns pumps up the Sharpe ratio from 1.04 up to 2.75.
But this takes courage. The mean-variance optimal portfolio shifts to half following seasonality with just a tenth in an indexed mutual fund or ETF such as VFINX or SPY.
There is no way to teach you value investing without introducing you to the now deceased finance professor of Columbia University who took Warren Buffett under his wing (reluctantly at first). His name is Benjamin Graham.
Professor Graham of Columbia was the most influential in the development of the field of finance before professor Harry Markowitz of the University of Chicago.
Security Analysis is his most important book written for public consumption with another faculty member David Dodd in the depths of the depression in 1934. This coincided with the creation of the SEC and the laws that now force companies to divulge financial information.
Their book became the leading guide for the analysis of financial information gathered by the Security Exchange Commission disseminated free of charge to the public. Graham believed that careful introspective study of this public information allowed an intelligent investor to find stocks trading below their true worth.
He used ratios and time series comparisons to find meaning in different levels of financial information to discover which stocks in the market were of true value.
He clarified and codified the many rules that professional accountants and financial advisors were using behind the scenes. This alone created a fairer (liquid and efficient) market.
And as the market became more efficient it became harder and harder to find deals. Professor Benjamin Graham stated as a speaker at an academic conference in 1976 “I am no longer an advocate of elaborate techniques of security analysis in order to find superior value opportunities. This was a rewarding activity, say, forty years ago, when our textbook “Graham and Dodd” was first published; but the situation has changed a good deal since then. In the old days any well-trained security analyst could do a good professional job of selecting under-valued issues through detailed studies; but in light of the enormous amount of research now being carried on, I doubt whether in most cases such extensive efforts will generate sufficiently superior selections to justify their cost to the very limited extent I’m on the side of the “efficient market” school of thought now generally accepted by professors.”
Professor Graham then explained a simplified way to find value stocks that you can apply,
“My first, and more limited, technique confines itself to the purchase of common stocks at less than their working-capital value, or net current-asset value, giving no weight to the plant and other fixed assets, and deducting all liabilities in full from the current assets. We used this approach extensively in managing investment funds, and over a thirty-odd-year period we must have earned an average of some 20% per year from this source. For a while, however, after the mid-1950s, this brand of buying opportunity became very scarce because of the pervasive bull market. But it has returned in quantity since the 1973-1974 decline. In January 1976 we counted over 1000 such issues in the Standard & Poor’s Stock Guide — about 10% of the total. I consider it a foolproof method of systematic investment — once again, not on the basis of individual results but in terms of the expectable group outcome.”
Read the full transcript in Financial Analyst Journal Vol. 32, No. 5 (Sep-Oct., 1976), pp. 20-23. You can find these stocks in Standard & Poor’s Outlook or on the Bargain Basement List of stocks trading below their net working capital in the Value Line print version available at your local library.
The Dogs of the Dow Method of Michael B. O’Higgins sparked an investing revolution because this was the first book that showed that a highly diversified portfolio really could beat the averages. Value and momentum are extremely hard stocks to find.
There is no easy method to assemble a portfolio for value or momentum.
It is extremely easy to form a highly diversified portfolio based on dividend yield. Dividend yield is essentially the dividend price ratio. There is an expected 11% Dow Return. This gets a 1.5% Boost with a simple Dogs of Dow strategy of picking the lowest priced highest dividend paying third of the thirty stocks that comprise the Dow.
This obtains the Diversified 10 Stock Dogs of the Dow Portfolio.
The S&P 10 Method by University of Pennsylvania Wharton Professor Jeremy Siegel extends this concept into a much broader universe of stocks. The S&P index is comprised of 500 stocks.
Dr. Siegel studied high dividend price ratio stocks. He found that you can receive a 3% boost over the 12% expected return of the S&P 500 index. This implies an expected return of 15% on high dividend yield stocks selected from a pool of 500 stocks.
This can be further enhanced with seasonal analysis of high dividend yield stocks.
Notice that the expected return is much higher on dividend yield stocks from a broader index. This allows you to further sort on size for even higher expected returns.
Diversification eats into returns. This section introduces you to a 3 stock portfolio for even higher Diversified-Focused Returns.
Momentum is very easy to spot. Just look at a daily price chart looking a year back. If the price is higher today than a year ago you have found a momentum stock.
There are 3,700 worthwhile firms in the market across the NYSE, NASDAQ and Amex.
There are often over a thousand equities that qualify as momentum stocks during a bull market. There are yet a hundred or more in a bear market.
Your problem is ferreting out the ONE which is going to continue to rise. This is because academic research tells you that momentum stocks are rife with reversal patterns after a year of strong rise over run.
But a handful of highly profitable momentum stocks rising fast on high volume do not reverse. You want these.
In October of 2000 Cornell Finance professor Charles Lee and Stanford Finance professor Bhaskaran Swaminathan published an important research article entitled “Price Momentum and Trading Volume” in the Journal of Finance Vol. IX No. 5. This work shows how a large list of momentum stocks can be dramatically parsed down with a high volume winner filter.
The volume and trend pattern is as easy to spot as the simple strategy is to apply.
You buy and hold when volume is pushing prices up. You exit or delay entry when volume is pushing prices down.
Nicolas Darvas used this insight in the 1950s to earn two and half million dollars in just six and a half months in the 1950s.
The first step to finding seasonal opportunities involves scanning the market. I have two ways to scan for stocks. I can scan market wide.
Think of this as a form of top-down analysis to find seasonal opportunities. In this case we don’t care what we find.
Let’s say that we are scanning for seasonal trading opportunities in stocks. The objective of scanning is to produce a list of trades from a pool of 1,100.
But I can also zoom in on specific market sectors.
These sub-segments of the market include,
- The S&P 500 — These are the stocks that you think of when you hear the words Fortune 500.
- NASDAQ 100 — Dig through the largest OTC traded stocks.
- Dow Jones Composite Average —Thirty of the largest stocks in the world comprise this group.
- Exchange Traded Fund —You can add commodities, currencies, stocks, and many other assets then these can be levered with ETF options.
- Basic Materials — Basic materials are commodities and manufacturing inputs with very little assembly or mix.
- Conglomerates — Firms that span multiple industries are in this sector.
- Consumer Goods — Cash-flow is the name of the game for these household products that even you have come to know and love.
- Financials — Three areas of finance are goods, services, and financials.
- Healthcare — Products that help mankind heal or remain healthy fall into this bin.
- Industrial Goods — Business to business activities make up a large part of our economy.
- Services — We are seeing the first world shift to service export economies and manufacturing into the third world.
These segments allow you to slice-and-dice the markets for effective top down financial analysis.
Drill down to find the best investing opportunities. Separate the wheat from the chaff, the diamonds from the rocks, the gold from the black sand.
The second way to scan is to first find potential value or momentum stocks.
Once I have a small list of these stocks — 20 is too many — I can scan each individually for periods in which the asset is seasonally bullish or bearish.I can sort any factor by clicking the header just like a spreadsheet. Here are the factors,
- Score — This tells me how strong the seasonality is for a particular asset and time period for that asset. The highest score is +5 and is bullish. Bullishness is associated with the color green. Negative five is the lowest score and is bearish. Bearishness is associated with the color red.
- Trend — States bullishness or bearishness.
- Symbol — Each stock, futures, or forex asset has an associated identifier code known as a symbol.
- Company — Every stock has an associated company name. This is not so with futures or forex.
- Win% — The percentage win ratio is represented in this metric.
- Years — Some seasonal trades have endured for many years quantified with this count.
- Cal Days — The number of calendar days a seasonal trade persists is listed in this column.
- Avg Profit (%) — Central tendencies of profitability by trade are measured on a percentage basis.
- Avg Profit ($) — Central tendencies of profitability by trade are measured in USD.
- Risk:Reward — A risk to reward ratio divulges the ratio of the amount of capital put at risk in the form of cash or margin.
- Avg Daily Profit (%) — This metric shows you the profitability you expect on a daily basis expressed as a percentage.
- Avg Daily Profit ($) — This metric shows you the profitability you expect on a daily basis by USD.
- Biggest Profit (%) — Shows you the biggest win by percentage.
- Biggest Profit ($) — Shows you the biggest win by USD.
- Max Gain (%) — This is the biggest gain.
- Avg Draw (%) — This calculates your mean loss over the path of the trade in percentage terms.
- Avg Draw ($) — This calculates your mean loss over the path of the trade in USD.
- Max Draw ($) — You can find a representation of the largest loss over the trade path here in USD.
- Max Draw (%) — You can find a representation of the largest loss over the trade path here in %.
- Total Wins — A count of total wins.
- Total Losses — A count of total losses.
- Trading Days — A count of total trading days by seasonal opportunity.
- Quantity — This is the recommended position size based on your personal preference and starting capital.
- Total Net Profit (%) — A report of the profits sans trading costs yields the total net profit on a percentage basis.
- Total Net Profit ($) — A report of the profits sans trading costs yields the total net profit in USD.
- Previous Close — This is the close of the prior session.
- Amount/Trade — This metric measures the amount of shares or contracts in play on any seasonal trade or investment.
- Optionable — If the stock, futures or forex contract is option-able you will see it so here.
- Sector — This tells you the sector the stock or futures contract spans.
- Industry — You can see which industry a stock is involved in here.
These factors allow me to carefully sort my results to cherry pick the best seasonal opportunities.
The dividend aristocrats have one major fact in common. These firms have management committed to increasing dividends year after year for a minimum of twenty-five years. Many investors have never heard of such stocks.
Yet they regularly purchase goods and services from these eight dividend aristocrats,
- Nucor (NUE)
- McDonalds (MCD)
- Consolidated Edison (ED)
- Proctor & Gamble (PNG)
- Chevron (CVX)
- Coca-Cola (KO)
- Wal-Mart (WMT)
- Johnson and Johnson (JNJ)
These are large Fortune 500 stocks. This means that they are very liquid.
Such stocks are also a safe harbor in the storm. Dividend aristocrats fall less when a black swan soils the pond.
Momentum stocks have to fulfill three criteria to be serious candidates for a test purchase by Dr. Scott Brown. The first is that the stock must be rising into new high levels looking back one quarter or many years.
Next the stock price must be up-trending on high volume.
Trend analysis can be smoothed with a 10-day moving-average. This allows you to (1) see the trend easier and (2) buy when above or sell when below.
This simple rule has been shown by academic studies to yield significant expected profits.
Dr. Brown analyzes two such volume winner candidates. The first is Facebook (FB) and the second is Smith & Wesson (SWHC).
These two stocks also fulfill Scott’s third rule of excellent earnings quality.
This lecture focuses on chart analysis of the Value-Line Bargain Basement list from November 6 of 2015. Notice that there are just thirty four such stocks on the list.
This is far fewer than over a thousand reported by professor Benjamin Graham in the mid-1970s. The list is very compact today due to the bullish stock market. Dr. Brown analyzes the following value stock candidates,
- Avnet (AVT)
- Franklin Resources (BEN)
- Big 5 Sporting Goods (BGFV)
- Benchmark Electronics (BME)
- Beazer Homes (BZM)
- CalAtlantic (CAA)
- China Automotive Systems (CAAS)
- Canon (CAJ)
- Celestica (CLS)
- Coherent (COHR)
- Dri-Quip (DRQ)
- EZCORP (EZPW)
- Finish Line (FINL)
- First Solar (FSLR)
- Goldman Sachs (GS)
- Haynes International (HAYN)
- Ingram Micro (IM)
- KB Home (KBH)
- Kulicke and Soffa Industries (KLIC)
- MKS Instruments (MKSI)
- Movado Group (MOV)
- Marvel Technology (MRVL)
- Meritage Homes (MTH)
- Insight Enterprises (NSIT)
- PC Correction (PCCC)
- Pulte Group (PHM)
- Piper Jaffray (PJC)
- Plexus (PLXS)
- Skullcandy (SKUL)
- Stage Stores (SSI)
- Tech Data (TECD)
- Taylor Morison Home Corporation (TMHC)
- TRI Pointe Group (TPH)
- Winnebago Industries (WGO)
Dr. Brown deems the only two stocks on the list as worthwhile candidates as value stocks to be Coherent (COHR) and Ingram Micro (IM). Watch his chart analysis for extra insight.
Dr. Brown has laser focus when it comes to the futures markets. He watches and trades just seven markets at a time.
- S&P Stock, Mini (ES)
- Oil, Light Crude, NYMEX (GCL)
- Cattle, Feeder (GF)
- Gold, COMEX (GGC)
- Sugar #11 (SB)
- Corn (C)
- US T-Note 10 yr (ZN)
Staying focused on these few markets will dramatically increase your odds of success in futures. Test these seven for seasonality.
Dr. Brown shows you how to laser focus your portfolio on the seven most important world currencies. He does this by eliminating any pairs that include the Swiss Franc (CHF). Swiss central bankers cratered thier currency last year with a forced devaluation.
Currency traders should avoid this currency like the plague. Ditto for the Mexican Peso (MXN) for similar central banker problems.
The next to go overboard is the Swedish Krona (SEK). This currency is stable but has too little trading volume and thus poor liquidity.
Ditto for kissing cousin the Norwegian Krone (NOK).
Scott eliminates the Turkish Lira (TRY) for similar reasons. But he admits to loving Turkish cuisine … go Fatmagul (Fatmagül'ün Suçu Ne?)!
The next purge is the Hong Kong Dollar (HKD). This currency is redundant in Asia when compared to the yen (JPY). This leaves you with a short list of just seven acceptable world currencies for seasonal testing,
These are combined into a series of trading pairs of which the most important are the majors,
Stick to this tightly woven core and you will be better off in your currency trading.