The 4.1% plunge in the S&P 500 yesterday looks ominous, all the more so since it follows last week’s hefty 3.8% decline. But focusing on what just happened distorts our capacity to maintain a healthy sense of historical perspective. As an antidote, let’s step back and consider the latest

Technology moves at a startling speed and it has been the same case in the algorithmic and quantitative trading domain. Traders around the world are making use of Machine Learning, Artificial Intelligence, Blockchain, Neural Networks, Deep Learning and similar techniques to execute their trades. One

SUMMARY Some factors show structural sector exposure while others rotate sectors frequently Sector concentrations explain factor performance and may represent concentration risks Value is currently long Financials, Low Volatility is short Health Care, and Growth is short Energy INTRODUCTION Despite

January 2018 Trend Following: UP +6.94% / YTD: +6.94% Below is the full State of Trend Following report as of last month, opening the year with a strong performance in January. Performance is hypothetical. Chart for January: WSTF 201801 Index And the 12-month chart: WSTF 201801 Index 12months Below

Welcome! If you enjoy these posts, please follow this blog via email and check out my Twitter feed located on the sidebar. All of my previous analysis has focused on US equities, but today we begin the journey into another asset class, futures. Futures are traded via contracts where two parties

We believe that capital efficiency should remain a paramount objective for investors. The prudent use of leverage can help investors employ more risk efficient portfolios without necessarily sacrificing potential returns. Many investors, however, do not have access to leverage (be it via borrowing

How bad was last week’s rout in US equities? The slide is the biggest weekly drop for the S&P 500 Index in over two years. But that’s not saying much, given how calm the upside bias for the equity trend has been lately. Perhaps the bigger surprise is that we’ve gone so long without a

A couple of weeks ago I did a little study that looked at performance following the induction of a new Fed Chairman. With Jerome Powell starting his new job on Monday, I decided to expand on that study below. 2018-02-04 Obviously it appears to be a bit of a mixed bag. The most positive results came

Investors can directly access factor returns via ETFs in the US & futures in Europe However, neither of these come without some investor concerns Realised returns differ substantially from theoretical returns INTRODUCTION Despite factor investing having gained immense popularity in recent years,

Markets have started the month weak. We got spoiled last year. After such an abnormally long period of market calm, it’s natural for investors to feel a little anxious. We have no opinion on where the markets go from here. That’s why we’re quantitative traders. We put a lot of time into

On paper, momentum is one of the most compelling factors: simulated portfolios based on momentum add remarkable value, in most time periods and in most asset classes, all over the world. So, our title may seem unduly provocative. However, live results for mutual funds that take on a momentum factor

Order flow is signed trade size, and it has long been known to be predictive of future price changes. (See Lyons, 2001, or Chan, 2017.) The problem, however, is that it is often quite difficult or expensive to obtain such data, whether historical or live. This is especially true for foreign exchange

Momentum-based investing strategies may be one of the most reliable drivers of alpha, but like all sources of excess return this factor premium waxes and wanes through time. Accordingly, deciding when to exit the trade (or reduce exposure to it) is no less critical than determining when to jump on

Smart beta (or factor investing) seems to be the product du jour in ETFs. There are so many different factor products available that just about every fund company seems to offer them…even Vanguard is launching their own suite of factor-based stock funds. Note that nearly all of these products are

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

When we tell our investors to invest for the long run, we have to make sure the short run doesn’t kill them first… Investing for the long run isn’t bad advice, it’s just unrealistic. It doesn’t take into account human behavior. -Andrew Lo (HT: Andrew Thrasher) Trend following has

What are the research questions? Financial theory asserts a clear link between the risk-free interest rate and the pricing of equity securities, regardless of the time horizon. Therefore, the market’s opinion about the uncertainty of rates should improve models forecasting equity volatility in the

Bond timing has been difficult for the past 35 years as interest rates have declined, especially since bonds started the period with high coupons. With low current rates and higher durations, the stage may be set for systematic, factor-based bond investing. Strategies such as value, momentum, and

Factor timing and factor risk management are related concepts, but have different objectives Factors have unique characteristics that require a tailored risk management approach A multi-dimensional factor risk management model shows consistent increases in risk-return ratios and decreases in maximum

Is bitcoin a bubble? I don’t know. What defines a bubble? The price should drastically overestimate the underlying fundamentals. I simply don’t know much about blockchain to have an opinion there. A related characteristic is a run-away price. Going up fast just because it is going up fast. How

In this article, I am going to explore an alternative forecasting technique that currently has merits in the field of dam displacement, a structural engineering problem. I will then apply this technique and measure its forecasting capability on the S&P/TSX Composite Index (GSPTSE). The model is

Does the increase in number of Bitcoin wallets at a rate that far exceeds growth in number of Bitcoins explain the dramatic rise in Bitcoin price? In the December revision of his paper entitled “Metcalfe’s Law as a Model for Bitcoin’s Value”, Timothy Peterson models Bitcoin price according

XIV is an inverse-VIX ETN. In other words, it was designed to generally trade inversely to VIX futures on a daily basis. Since VIX and SPX typically trade opposite each other, you would think that XIV and SPX would often close in the same direction. And you would be right. Of course, XIV depends on

Merger arbitrage, sometimes known as “risk arbitrage,” is an investing strategy in which the investor bets on announced M&A deals. After a merger is announced, shares of the target tend to trade below the offered price (due to deal uncertainty), representing the arbitrage spread; if the deal

This post will be about comparing a volatility signal using three different variations of implied volatility indices to predict when to enter a short volatility position. In volatility trading, there are three separate implied volatility indices that have a somewhat long history for trading–the

There is a large literature that reports time-specific anomalies in equity markets such as the Monday effect, the January effect and the Halloween effect. This study is the first to report intra-day time-of-day, day-of-week, and month-of-year effects for Bitcoin returns and trading volume. Using

Imagine the following. You spent time developing a strategy with a compounded annual return of 24% and max drawdown of 18%. Profitable 10 of the last 11 years. An average 21 day rolling correlation with the SPY of .20. Passes your out-of-sample testing. Passes your parameter sensitivity testing.

Machine Learning is one of the most popular approaches in Artificial Intelligence. Over the past decade, Machine Learning has become one of the integral parts of our life. It is implemented in a task as simple as recognizing human handwriting or as complex as self-driving cars. It is also expected

Rankings are everywhere. They are sometimes useful and, at other times, contradicting. In such a case, we need to come up with a consensus ranking but… how do we evaluate ranking consensus? The other day I was reading about something called rank aggregation, which is just a fancy name for

This is the third in a multi-part series in which we explore and compare various deep learning tools and techniques for market forecasting using Keras and TensorFlow. In Part 1, we introduced Keras and discussed some of the major obstacles to using deep learning techniques in trading systems,

Many individual investors employ mutual funds as an alternative to direct ownership of stocks or bonds. Indeed, mutual funds have some advantages: Diversity: Even a single fund can encapsulate a large sector of the market. Peace of mind: One is less likely to stress out about sudden bad news

The start to 2018 has been fairly remarkable. The SPX has only closed down 3 days so far, while closing up 11 days. That is a substantial hot streak, and one might think that such a strong run to start the year would almost certainly have to pullback soon. So I checked. 2018-01-23 The imminent

When two managers implement identical strategies, but merely choose to rebalance on different days, we call variance between their returns “timing luck.” Timing luck can easily be overcome by using a method of overlapping portfolios, but few firms do this in practice. We believe the magnitude of

Is it possible to predict where the Gold price is headed? Yes, let’s use machine learning regression techniques to predict the price of one of the most important precious metal, the Gold. We will create a machine learning linear regression model that takes information from the past Gold ETF (GLD)

Jerome Powell is expected to take over for Janet Yellen as the new Fed chairman on Feb 3rd. A few days ago in the letter I looked at SPX performance after a new chairman takes over. I used the SPX and looked back to 1970. Tonight I decided to take the analysis back to 1923 using my Dow data. Like

Over the last ten years, a number of congress members have been elected on a fairly nihilistic platform, voting against practically any spending bill (unless it buys tanks). This is a good way to get elected but it makes it hard to govern. The government has to spend money. While the Republicans

This notebook will walkthrough the algorithm implementation process on the quantconnect platform. Please be advised that this notebook will not actually run the algorithm as I have not installed the quantconnect backtesting engine locally. This is a demonstration of the process. The script is

Wes asked that I contribute to the ongoing debates regarding the construction of value and momentum portfolios. There are three key research pieces on the topic, all with different viewpoints: Alpha Architect’s take AQR’s take Newfound Research’s Take I encourage everyone to dig into the three

Writing this, I can’t believe how quickly the year 2017 has gone by. Also weird, we are already three weeks into 2018, unreal. Time flies when you’re having fun I guess. The analytics report shows that the three most popular posts for 2017 are: – Understanding False Discovery Rate (4 minutes

Fama-French Factors and Business Cycles Arnav Sheth and Tee Lim (Saint Mary’s College of California) December 4, 2017 We examine the behavior of Fama-French factors across business cycles measured in various ways. We first split up the business cycles into four stages and examine the cumulative

This is the beginning of a three part series that I completed towards the end of 2017 as a learning module for Quantinsti.com. The purpose of the series is to demonstrate a research workflow focused around the theory and application of mixture models as the core framework behind a algorithmic

J.P. Morgan researchers, Marko Kolanovic and Zhen Wei, produced an incredibly detailed report on all aspects of momentum (one of our favorite topics!) Here is a link to the report 188 pages of pure effort and information. Here is a summary of what is examined in the research: As the virtually

This paper proposes a risk-based explanation of the momentum anomaly on equity markets. Regressing the momentum strategy return on the return of a self-financing portfolio going long (short) in stocks with high (low) crash sensitivity in the USA from 1963 to 2012 reduces the momentum effect from a

Wednesday saw both SPX and VIX close at 40-day highs (about 2 months). Since they commonly trade opposite each other, to have them both be extended up like this is very rare. In fact, it has only happened 4 other times. Below is a list of those instances along with their 4-day results. 2018-01-18

This is the beginning of a three part series that I completed towards the end of 2017 as a learning module for Quantinsti.com. The purpose of the series is to demonstrate a research workflow focused around the theory and application of mixture models as the core framework behind a algorithmic

A covered call is used by an investor to make some small profit while holding the stock. Mostly the reason why a trader would want to create a covered call is because the trader is bullish on the underlying stock and wants to hold for long-term, but the stock doesn’t pay any dividend.The stock is

The relationship between series can be measured by different methods. The most common is to check if both series move in the same way. We’d like to go further, and see if the difference between them is always the same. We call it cointegration. In many cases, we are interested in expressing one

This is the beginning of a three part series that I completed towards the end of 2017 as a learning module for Quantinsti.com. The purpose of the series is to demonstrate a research workflow focused around the theory and application of mixture models as the core framework behind a algorithmic

What are the research questions? According to Datamonitor (2010), the influence of peer-based advice, such as user-generated ratings on Amazon.com or Yelp.com, is increasing while traditional advice (e.g., from Consumer Reports or the Michelin guide) is decreasing. This trend is starting to emerge

Factor investing seeks to balance specificity with generality: specific enough to have meaning, but general enough to be applied broadly. Diversification is a key tool to managing risk in factor portfolios. Imprecision in the factor definitions means that unintended bets are necessarily introduced.