Investing strategies run the gamut, but every portfolio shares a common goal: delivering optimal results. The catch is that there’s a wide range of possibilities for defining optimal and so your mileage may vary, depending on preferences, assets, and other factors. Eran Raviv offers a useful

This post explores a concept at the heart of quantitative financial research. Most qfin researchers utilize statistical techniques that require varying degrees of stationarity. As many of you are aware financial time series violate pretty much all the rules of stationarity and yet many researchers,

One of the first tests I did when I got AmiBroker twenty years ago was a mean reversion test. It was a classic set up, a stock in an uptrend, followed by a pullback. But the entry differed from what I do now. The entry waited for a confirmation of the trend back up. The trade would enter when the

What is the body of academic research on crypto-assets? In their March 2018 paper entitled “Cryptocurrencies as a Financial Asset: A Systematic Analysis”, Shaen Corbet, Brian Lucey, Andrew Urquhart and Larisa Yarovaya review available research on cryptocurrencies as financial assets. They define

We wanted to take a moment to highlight a post from the always smart JW Keuning describing a novel approach for measuring how well a strategy has performed relative to drawdowns (losses): Presenting the Keller Ratio. Our preferred method for assessing a strategy’s return relative to drawdown has

As evidenced by the image below, interest in momentum research has taken off since the original 1993 Jegadeesh and Titman paper: Source: “Two Centuries of Multi-Asset Momentum (Equities, Bonds, Currencies, Commodities, Sectors and Stocks)”

SPY’s move lower over the last 3 days has set up a potential “Turnaround Tuesday” scenario. The fact that it made a lower high, lower low, and lower close for at least the 3rd day in a row triggered the following study. 2018-04-241 The numbers are impressive and the bounces couldn’t get much

We document that several well known asset-pricing implications of accruals differ for investment and non-investment-related components. Exposure to an investment-accruals factor explains the cross-section of returns better than the accruals themselves, and this factor’s returns are negatively

While investors are often concerned about catastrophic risks, failing to allocate enough to risky assets can lead investors to “fail slowly” by not maintaining pace with inflation or supporting withdrawal rates. Historically, bonds have acted as the primary means of managing risk.However,

The tax efficiency of the Value factor can be improved by reducing exposure to dividend-yielding stocks Improving the tax efficiency reduces the performance in Europe and Japan, but not in the US Reducing turnover can be considered for minimising capital gains and stamp duty taxes INTRODUCTION Tax

Many traditional return to risk measures are not apt for intuitive interpretation The Keller ratio is expressed as an adjusted return and therefore easy to interpret The Keller ratio allows for strategy selection optimally aligned with an investor’s risk appetite In our VAA-paper we introduced a

Developer: Richard Wyckoff; Toby Crabel. Source: Crabel, T. (1990). Day Trading with Short Term Price Patterns and Opening Range Breakout. Greenville: Traders Press, Inc. Concept: Trading strategy based on reversal patterns. Research Goal: Performance verification of reversal patterns.

Friday’s action caused SPY to close in an interesting position. Traders could look at the chart and say it is “short-term oversold” due to the fact that it closed at a 5-day low for the 1st time in a while. They might also say it is “short-term overbought” since it closed above its 10-day

This year marks the 10th anniversary of the R/Finance Conference! As in prior years, we expect more than 250 attendees from around the world. R users from industry, academia, and government will joining 50+ presenters covering all areas of finance with R. The conference will take place on June 1st

If you’ve been following me on Twitter you know that I’ve finally had it with Amazon. There is a silver lining of course, and the good news for my readers is that all of my books are now free to download.(Sadly I cannot control the two I didn’t self publish…) If you care to understand why

Yield. Within almost any asset class, investors want to know, what is the “yield” on the investment? For some investors, this is the most important and only screen used when sorting funds. Mutual fund companies have found ways to feed the beast by “juicing” the dividend yield on equity

There are not too many creative opportunities to leave a person applying for a quant role dumbfounded with the interview question directly related to his CV. First of all, we want to test his quant skillset, check his ability to read a code, analyse the model, listen to his judgement on the

Pim van Vliet posted a link to my 1994 dissertation, noting it was an early documentation of the low-vol effect. One may wonder, why did this early evidence fall flat? Clearly, lots of things, but I'll try to highlight the keys. Here's my lead paragraph, which makes clear I saw the low vol

Benchmarks can be a very difficult subject to pin down. Choosing different ones can create drastically different backdrops to frame both short and long-term results. This was even true in our 2018 March Madness Bracket Challenge, with the value-weighted benchmark taking the top place. As investors,

A growing number of investors are seeking to construct portfolios that simultaneously capture the 1) long-term factor premia ( value, momentum, size etc.) and 2) have attractive ESG profiles. The main research questions of the paper are as follows: Is the relationship between ESG and factor stable

The interest rate-sensitivity of the Low Volatility factor has increased in recent years Mainly due to the sectoral biases from the long portfolio Sector-neutrality reduces the interest rate-sensitivity, albeit at the cost of performance INTRODUCTION Low Volatility strategies have become popular

Time flies, and it's time for another annual update on the performance of my own investment and trading. Previous updates can be found here, here and here. These updates follow the UK tax year; from 6th April to 5th April, as I have to do my taxes anyway it makes sense to analyse everything at

This paper examines the day of the week effect in the crypto currency market using a variety of statistical techniques (average analysis, Student's t-test, ANOVA, the Kruskal-Wallis test, and regression analysis with dummy variables) as well as a trading simulation approach. Most crypto

Last month I shared a table that showed performance of opex weeks by month. April was one of the most bullish. The study below looks specifically at April opex week. I last showed it on the blog in 2016. Results are all updated. 2018-04-15 The numbers are impressive, and suggest a bullish edge.

First, the bad news: Google Finance no longer provides data for historical prices or financial statements, so we say goodbye to getSymbols.google() and getFinancials.google(). (#221) They are now defunct as of quantmod 0.4-13. Now, the good news: Thanks to Steve Bronder, getSymbols() can now import

My favorite moment of the film The Social Network takes place when Mark Zuckerberg asks his roommate Eduardo Saverin to explain the Elo system to him. This algorithm is used to rank chess players. At that time, Zuckerberg was developing the just-for-fun website Facemash, an early predecessor of

Friday the 13th is upon us. Known for bad luck and horror movies, I decided to go back and see how SPX has performed on this day. What I found was scary… 2018-04-13 Good luck trading today!

For those of you wanting to get started/familiar with the Julia language. I wrote a small script to import .csv data using the Alphavantage API. In this example we demonstrate how to download a single .csv file as well as batch download multiple .csv files and export as .csv. First lets download a

Constructing a portfolio means allocating your money between few chosen assets. The simplest thing you can do is evenly split your money between few chosen assets. Simple as it is, good research shows it is just fine, and even better than other more sophisticated methods (for example Optimal Versus

Long-horizon return regressions have effectively small sample sizes. Using overlapping long-horizon returns provides only marginal benefit. Adjustments for overlapping observations have greatly overstated t-statistics. The evidence from regressions at multiple horizons is often misinterpreted. As a

A fairly neutral month for the index after the up-and-down start of the year, leaving the index in slight negative mode for the year. Please check below for more details. Detailed Results The figures for the month are: March return: 0.9% YTD return: -1.1% Below is the chart displaying individual

How will systematic (“coordinated”) investing affect prices? What is the risk of increasingly coordinated holdings (crowding)? How does coordinated investing affect market microstructure and optimal execution? Is factor timing possible? What are the issues in the design of factor-based

Momentum is one of the most researched topic in financial market literature. A search of the SSRN database on momentum will turn up around 1000 papers written over the past three years and 3000 papers in total. With so much information available, it should not be surprising that many analysts have

Smart beta ETF investors seem to ignore empirical evidence Excess returns from smart beta are substantially different from factor returns Smart beta ETFs offer little diversification for an equity-centric portfolio INTRODUCTION Assets under management in smart beta products surpassed $1 trillion in

For most investors, long-term “failure” means not meeting one’s financial objectives. In the portfolio management context, failure comes in two flavors. “Slow” failure results from taking too little risk, while “fast” failure results from taking too much risk. In his book, Red Blooded

In a quest for speed enhancements over R. I opted to look at the Julia language. It is a high level programming language touting similar speed to C. I find the syntax not at all that different from Python and R. If you have knowledge of the ‘how’ to solve many problems using those languages, the

A different strategy for each day of the week? Sounds crazy, but is it? I have wrote about “Turnaround Tuesday” before: https://www.seeitmarket.com/turnaround-tuesday-wall-street-cliche-media-fiction-17013/ This simple strategy is actually at new highs since this was published over 10 months

Returns to the simplest domestic capitalization weighted indexes have dominated virtually all active strategies over the nine years since the Global Financial Crisis. It’s not hard to understand why many investors have opted to eschew active strategies altogether, and instead have migrated en

This article proposes tail risk hedging (TRH) as an alternative model for managing risk in investment portfolios. The standard risk management approach involves a significant allocation to hiqh-quality bonds. However, this approach has historically reduced expected returns over the long term (see

This post is a bit of an experiment. My good friend Steven Wood and I started discussing some collaborations a few months ago. We hope that it ups the quality of our research and also brings some new insights into each of our philosophies. Below is his recent post, for which I helped provide some

When traders set in-sample and out-of-sample periods for their backtests, it’s common just to pick some dates that split the data into a pre-defined percentage or range. The trouble with this approach is that it often doesn’t take into account the type of market environments that exist in those

We have talked about outliers several times in this blog. Examples include how to detect them or how to transform the data to remove them. Here we have another technique to detect outliers in our big data set: the isolation forest algorithm. The idea behind the isolation forest method The name of

We wanted to take a moment to highlight two must read posts from Newfound Research. Newfound is a thought leader in the TAA space and we highly recommend following them now. The Diversification Dangers of DIY Tactical – and – Diversifying the What, How, and When of Trend Following Newfound

We develop a strong diagnostic for bubbles and crashes in bitcoin, by analyzing the coincidence (and its absence) of fundamental and technical indicators. Using a generalized Metcalfe’s law based on network properties, a fundamental value is quantified and shown to be heavily exceeded, on at least

Buy cheap. This is a motto many live by, not only in their daily lives but also in their investment philosophy. Historically, “buying cheap” stocks was a good idea (i.e., the so-called “value” premium). But how might valuation matter when it comes to country allocations? In other words,

What are the research questions? By studying tweets on thirty companies in the Dow Jones Index, the authors ask the following research question: Is it possible to develop a system for the detection and discovery of the popularity of special events on Twitter that may influence the financial markets?

In this post we look at the one plot that proves that technical analysis (TA) is useless. TECHNICAL ANALYSIS AND HOROSCOPES As volatility has made a come back in recent months, investors have sought advice to asset managers. In many instances, such advice consists in technical indicators. Charles

Naïve and simple long/flat trend following approaches have demonstrated considerable consistency and success in U.S. equities. While there are many benefits to simplicity, an overly simplistic implementation can leave investors naked to unintended risks in the short run. We explore how investors

2018 started negative for the majority of factors Momentum, Quality and Growth showed the strongest performance Low Volatility, Dividend Yield and Value generated negative returns INTRODUCTION We present the performance of seven well-known factors on an annual basis for the last 10 years and the

This is a summary of the recent performance of a wide range of excellent tactical asset allocation strategies. These strategies are sourced from books, academic papers, and other publications. While we don’t (yet) include every published TAA model, these strategies are broadly representative of