Hard to believe, but it has been five and a half years since I had to go to an office to manage other peoples money, and exactly five years since I began systematically trading my own. Time then for another annual review. Perhaps it is confusing for overseas readers, but these reviews follow the UK

Understanding classification of market regimes is fairly important in finance. It all comes down to correctly predicting the way prices are going to move. But prediction isn’t the only crucial thing; knowing how to describe what has already happened is also of great importance. In this QuantDare

For those interested in the literature on factor-based investing, a new paper by Robert Arnott, Campbell Harvey, Vitali Kalesnik and Juhani Linnainmaa, “Alice’s Adventures in Factorland: Three Blunders That Plague Factor Investing,” focuses on why, in some ways, it has failed to live up to its

Marcos Lopez de Prado, recently named 2019 Quant of the Year by the Journal of Portfolio Management, has released a presentation entitled The seven reasons most econometric investments fail. Lopez de Prado’s overall point is that many widely used econometric approaches in finance either rely on

A factor exposure of Berkshire Hathaway reveals structural factor tilts Long Value, Size, Quality, and Low Volatility factors and short Growth and Dividend Yield Warren Buffet generated little alpha, but is highly skilled at harvesting factor returns SAINTS AND STAR INVESTORS The Vatican waits at

What are the Research Questions? A common assumption in finance theory is that agents in the stock market behave rationally. Even if temporary mispricing occurs, due to irrational beliefs or incomplete information of some agents, arbitrageurs swiftly restore equilibria. In contrast, the history of

Trend following is “mechanically convex,” meaning that the convexity profile it generates is driven by the rules that govern the strategy. While the convexity can be measured analytically, the unknown nature of future price dynamics makes it difficult to say anything specific about expected

In 1921, University of Chicago Professor Frank Knight wrote the classic book “Risk, Uncertainty, and Profit.” An article from the Library of Economics and Liberty described Knight’s definitions of risk and uncertainty as follows: Risk is present when future events occur with measurable

QuantMinds International heads to Vienna on 13-17 May! Now in it’s 26th year, QuantMinds International brings together 400+ global quant finance experts from banks, buy-side, academia and beyond, to cover every hot topic in quant finance over the course of 5 days. Quote VIP code FKN2595QCYMU for a

Alphabet, the largest Internet-based company, has based its success on sophisticated information retrieval algorithms since its origins. Now, 20 years later, one of its divisions is open-sourcing part of its secret sauce, drawing attention from developers all over the world. Since Google was founded

I saw some bullish studies emerge last night. But there was a study below that was not favorable that I thought readers would find interesting. One potential issue with Tuesday’s decline is that it included an unfilled gap down. Generally, an unfilled gap down from a high has more trouble quickly

Everyone knows that the risk profile of systematic strategies can change considerably when equity markets turn down and volatilities spike. For an example, a smooth profile of a short volatility delta-hedged strategy in normal regimes becomes highly volatile and correlated to equity markets in

S&P500 – when to be invested The stock market shows some astonishingly stable date based patterns. Using a performance heat map of the S&P500 index, these patterns are easily found. Date based performance The chart below shows the profit factor of a long only strategy investing in the

The barrier to entry into the factor zoo has increased exponentially. Prof. Harvey (now working with RAFI) made this clear at the 2017 AFA address, when he highlighted the issue with data-mining in front of a room full of academics from top-flight research programs in the country. Prof. Harvey and

Should investors trust academic equity factor research? In their February 2019 paper entitled “A Census of the Factor Zoo”, Campbell Harvey and Yan Liu announce a comprehensive database of hundreds of equity factors from top academic journals and working papers through January 2019, including a

What is the most significant risk in quant (and all active) investing today? The First Moment (the mean) The Second Moment (under-estimating tracking error) The Third Moment (skewness, left tails, crash risk) Mis-specified risk model (hidden factor biases, factors ‘eating’ alphas) Sub-optimal

In today’s video, we examine three articles from last week. The first article, written by Larry Swedroe, examines the Momentum of News. The second article, written by Wes, examines an out-of-sample test on Momentum by looking at Russian stocks in the 19th century. The third article, written by

A few years ago, we blindly applied mean-variance optimization to a set of capital market assumptions, and The Weird Portfolio was born. This portfolio is weird because it does not look like typical investor portfolios since it tilts heavily toward credit-based and alternative asset classes. Despite

Investors have leaned towards multi-factor over single-factor products in recent years The factor selection and portfolio construction of multi-factor ETFs can be challenged Multi-factor ETFs often feature factors, such as growth, which are not supported by academic research while lacking exposure

Many algorithmic traders justifiably worship the legends of our industry, people like Jim Simons, David Shaw, or Peter Muller, but there is one aspect of their greatness most traders have overlooked. They have built their businesses and vast wealth not just by sitting in front of their trading

Python is not the only language In the past, I’ve published stories on Medium showing how to write algorithms that trade stocks based on company fundamentals and how to run a technical analysis day trading algorithm in the cloud. Both of those articles assumed that: Python was the language the

Years ago, strong overbought readings during an uptrend were easily sold – especially when volume came in very light. But that has not held true in recent years. There were several studies I examined last night that noted the low volume, but they have all lost their edge over the last several

In my last post I said that this next post would report the results of tests on a Constant Acceleration model Kalman filter, and the results are: fail, just like the Constant Velocity model, so I won't bore readers with reporting the details of the failed tests. However, tests of a Variable

Slightly negative result for the State of Trend Following last month, leaving the YTD number in slight positive territory. Please check below for more details. Detailed Results The figures for the month are: March return: -0.22% YTD return: 2.55% Below is the chart displaying individual system

Since the development of the capital asset pricing model (CAPM) in the 1960s, hundreds of anomalies (what John Cochrane famously called a “zoo of new factors”) have been uncovered in the cross-section of stock returns. While some of the anomalies (such as the size and value factors) have

Please find this month’s report of the Wisdom State of Trend Following. Performance is hypothetical. Chart for March: The chart for the first quarter: And the 12-month chart: Below are the summary stats: Horizon Return Ann. Vol. Last month 1.49% 12.99% Year To Date -6.21% 12.56% Last 12 months

Do retail investors rationally account for risks as modeled in academic research when choosing actively managed equity mutual funds? In their March 2019 paper entitled “What Do Mutual Fund Investors Really Care About?”, Itzhak Ben-David, Jiacui Li, Andrea Rossi and Yang Song investigate whether

Quantitative investment researchers often seek uniquely optimal parameterizations of their strategies amongst a broad “robust” region of parameter choices. However, this ignores a critically important feature of investing – Diversification. By diversifying across many equally legitimate

I was talking to my trading buddy about the annoying part of trend following strategies. They may get you out of the major sell off but then you miss part of the run up. Using a 200-day moving average on the SPY would have got you out in late 2018. This would have been within 10% from the top and

Topology could be used to gain insight on the shape of our data, as we explained in our last post. Today, we will put this theory into practice by analyzing the 2008 financial crisis. Persistence diagrams We will start by giving an equivalent representation of the persistence barcode that we saw

The SPX made a Golden Cross formation on Monday. A Golden Cross occurs when the 50ma crosses over the 200ma. Having the 50ma above the 200ma is commonly considered a bullish market condition – and generally it is. I used my Norgate data and Amibroker software to look back as far as 12/31/1928.

In a situation where you wish to determine the returns on investment, one may have all the expertise to do this but without certain information (missing pieces) it would not be possible to derive to a conclusive figure. In practical terms “assume you have the value of all returns of all assets in

This is a summary of the recent performance of a wide range of excellent Tactical Asset Allocation (TAA) strategies, net of transaction costs. These strategies are sourced from books, academic papers, and other publications. While we don’t (yet) include every published TAA model, these strategies

What are the research questions? Is there a relationship between short selling activity and insider selling? What is the impact of short selling trading strategies that are conditioned on insider trading signals? Does the price impact of short selling subsume that of insider trading? Is the price

In addition to market valuation ratios like CAPE, the slope of the yield curve is one of the most talked about signals used to estimate future recessions and market returns. During the second half of last month (March 2019), the yield curve has inverted by about 5 basis points with the 10-year rate

Due to their highly active nature, trend following strategies are generally assumed to be tax inefficient. Through the lens of a simple trend equity strategy, we explore this assertion to see what the actual profile of capital gains has looked like historically. While a strategic allocation may only

Following on from my previous post, this post is a more detailed description of the testing methodology to test kinematic motion models on financial time series. The rationale behind the test(s) which are described below is different from the usual backtesting in that the test(s) are to determine

2019 has started favorable for factor investors, compared to 2018 Low Volatility generated the best and Value the worst performance Factor performance is comparable in the US & Europe, but different in Japan INTRODUCTION We present the performance of five well-known factors on an annual basis

Algorithmic trading adds noise to the markets we have known. So why not add some noise to your historic market data? This way you can check if your algorithmic trading strategies are fit for the future. Learn how to generate noisy data and how to test your strategies for stability in a noisy market.

The algorithmic strategy business likes quoting academic research to support specific trading factors, particularly in the equity space. Unfortunately, the rules of conventional academic success provide strong incentives for data mining and presenting ‘significant’ results. This greases the

When trading options, we often use the VIX index as a measure of volatility to help enter and manage positions. This works most of the time. However, there exist some differences between the VIX index and at-the-money implied volatility (ATM IV). In this post, we are going to show such a difference

It is worth noting that Friday is the last trading day of the quarter. And the last day of the quarter has some interesting characteristics. I often hear the term “window dressing” mentioned by the media when referring to end of quarter activity. The suggestion is that fund managers will make

Consider a market-timing strategy which supposedly predicts the direction of the stock market trend. Such a strategy generates Buy and Sell signals. A Buy signal is the signal to buy stocks, whereas a Sell signal is the signal to sell. Simple enough, but how does one evaluate the forecast accuracy

Quite a few of my recent blog pieces have been picked up by the lovely folk at allocate smartly. So I thought I'd write an asset allocation piece, as the readers of my second book "Smart Portfolios" probably feel neglected with the lack of articles on investment rather than trading.

One of the hardest and most frequent tasks for anyone in the quantitative finance world is to summarize or visualize in a simple way a vast amount of data to represent a company. In this blog, we have covered different Machine Learning techniques that allow us to summarize information through

Having just attended a great AI conference in New York, here are some observations: First about AI Most quants prefer the term Machine Learning (ML) instead of AI. Questions still remain of where AI (ML) adds value in a quant investment process. For example, Man’s CIO Sandy Rattray said that it

Information does not flow into the market at a constant frequency or with constant magnitude. By sampling data using a constant time horizon (e.g. “200-day simple moving average”), we may over-sample during calm market environments and under-sample in chaotic ones. As an example, we introduce a

With regards to seasonality, we are in an interesting period right now. The last couple of weeks the market played out well according to seasonal patterns. We saw March opex week put in nice gains as it often does. And then we saw the week after Quad-witching suffer losses this past week.

It is questionable if investors should prepare for catastrophic events Factor returns are almost random after black swan and major events Simple diversification is likely the best option for the expected and unexpected INTRODUCTION Investors fear black swan events, although it can be argued that

Systemic financial crises arise when vulnerable financial systems meet adverse shocks. A systemic risk indicator tracks the vulnerability rather than the shocks (which are the subject of ‘stress indicators’). A systemic risk indicator is by nature slow-moving and should signal elevated