A stop-loss order, or stops as is generally said, is an order placed with the broker to sell (or buy) if the stock of a company which you hold, reaches a pre-determined price in order to avoid large losses. In the trading world, the use of stops is seen as an essential part of risk control and money

Asset allocation is a very important decision for investors. Model portfolios are constructed with an optimized asset allocation process to help meet investor needs and preferences. The authors investigate the following research question: How does one construct a model portfolio? What are the

As trading costs have just hit zero, and passive investing overtook active in August, the investment industry is braced for further pressure to deliver alpha after fees. In my view, the potential to build great models today is huge, but constrained by the research cultures of most firms. Here is

While it may be tempting to time allocations to active strategies, it is generally best to hold them as long-term allocations. Despite this, some research has shown that there may be certain economic environments where trend following equity strategies are better suited. In this commentary, we

Option-based strategies have similar characteristics to Low Volatility portfolios Combining these reduces idiosyncratic strategy risks The combinations feature higher risk-adjusted returns and lower drawdowns than the S&P 500 INTRODUCTION Some investment products and strategies can be considered

n the last two posts, we implemented a Kalman filter in R for calculating a dynamic hedge ratio, and presented a Zorro script for backtesting and trading price-based spreads using a static hedge ratio. The goal is to get the best of both worlds and use our dynamic hedge ratio within the Zorro

It’s not a perfect world out there and often times alternative funds are mischaracterized, misused, and not put through a rigorous enough portfolio construction process. It’s my hope that I can forewarn you of the proverbial landmines and better prepare you to invest (or not invest) in the

The problem with spliced futures No doubt, the correct datasets are the key when one does some analysis in the financial markets. For some financial instruments, the data can be found for free and ready for the upcoming process, but on the other hand, some instruments are more complicated. Nowadays,

This month* marks the release of my third book, with the snappy title "Leveraged Trading", and the slightly less snappy subtitle "A professional approach to trading FX, stocks on margin, CFDs, spread bets and futures for all traders". Photo courtesy of Harriman House. As you can

Continuing on from my Ideal Tau for Time Series Embedding post, I have now written an Octave function based on these ideas to produce features for time series modelling. The function outputs are two slightly different versions of features, examples of which are shown in the following two plots,

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

Most factors generated positive returns in Q1-3 2019 Low Volatility produced the best and Value the worst performance year-to-date The factor rotation from Momentum into Value in Q3 was short-lived INTRODUCTION We present the performance of five well-known factors on an annual basis for the last 10

Some background on Bond duration: Duration measures bond’s price sensitivity to interest rates changes. It’s estimated based on the discounted expectations of the bond future cash flows and expressed in the number of years. The longer the duration, the higher the bond interest rate risk. (read

(Both) regular followers of this blog will have been on tenterhooks for many months now, waiting for my next post. I have been busy! First of all, I've been finishing my third book. More detail on that later, in the next post. I've also had a fair bit of holiday time. But mainly over the

The authors do a very nice survey on measures of quality found in the academic literature and in commercially available quality indexes. They examine seven quality categories including: profitability, earnings stability, capital structure, growth, accounting quality, payout/dilution and investment.

While many investors have adopted a multi-factor approach to style investing, some have pushed these boundaries by advocating for an active, rotational approach to factor allocation. In a recent white paper, MSCI suggests several methods that might be conducive for performing style rotation,

Investors are slowly becoming more and more interested in ethical investing. Part of the reason is the industry is starting to care more, but the other reason is that there is a lot of evidence to show that it can produce better or at least equivalent returns. One subset of this type of investing is

In my June 4, 2019 article “The Re-Death of Value, or Déjà Vu All Over?” I noted that one possible explanation for at least part of the poor performance of value stocks over the past decade has been the sharp fall in both the real interest rate (due to weak global growth) and unexpected

In recent years, machine learning, more specifically machine learning in Python has become the buzz-word for many quant firms. In their quest to seek the elusive alpha, a number of funds and trading firms have adopted to machine learning. While the algorithms deployed by quant hedge funds are never

Intraday trading strategies offer great promise as well as great peril. This post explores an intraday trading strategy for crude oil calendar spreads and highlights the impact of transaction costs on its profitability. Background In a previous post, I explored an end-of-day pairs trading strategy

We all have our favorite momentum indicators. One of mine is percent off 1 year high. This requires 252 data points and comparisons, plus a division. Another one is the 200-day moving average. This requires 200 closing prices, 199 additions and a division. A simple momentum indicator is Rate of

Concept: Volatility clustering: Large price moves tend to be followed by large price moves, and small price moves tend to be followed by small price moves. Research Question: Is there a tendency of large price moves in one direction to be followed by large price moves in the opposite direction?

In our previous post, we looked into implementing a Kalman filter in R for calculating the hedge ratio in a pairs trading strategy. You know, light reading… We saw that while R makes it easy to implement a relatively advanced algorithm like the Kalman filter, there are drawbacks to using it as a

e have already traveled a good part of the trip, but there is still an important part. In this post, I tell you where we are and how much we have left. Courage, we sure got it! The Machine Learning Workflow The following diagram provides a high-level overview of the stages in a machine learning

One dirty little secret that has been hiding behind the curtains of finance for a long time, is that high-risk stocks do not have higher returns than low-risk stocks. Back in 1975 Haugen and Heins first recognized the low-risk anomaly: Our emperical efforts do not support the conventional hypothesis

Over the last few months, much of the financial press expressed concerns about the impact of inverted yield curves on financial markets, in particular, the stock returns. Some previous academic literature has shown that there exists a link between yield curves and economic growth (see references

Recent research suggests that equity factors exhibit positive autocorrelation, providing fertile ground for the application of trend-following strategies. In this research note, we ask whether the same techniques can be applied to the active returns of long-only style portfolios. We construct

Investment portfolios can be simplified by separating alpha from beta Alpha + beta portfolios offer higher risk-adjusted returns than smart beta The main hurdle for better portfolios is investor behaviour, not a lack of products INTRODUCTION In Buddhist teaching, the primary obstacles that prevent

Financial markets are not information efficient with respect to macroeconomic information because data are notoriously ‘dirty’, relevant economic research is expensive, and establishing stable relations between macro data and market performance is challenging. However, statistical programming

As I have shown many times in the past, there isn’t a more reliable time of the year to have a selloff than this upcoming week. I have often referred to is as “The Weakest Week”. Since 1960 the week following the 3rd Friday in September has produced the most bearish results of any week. Below

In the last post we showed that trend-following tends to be mean-reverting in the short-term. Data analysis also shows that trend-following has an even stronger mean-reverting effect using a 6-month or 120-day window using the same methodology. Take a look at the chart below using the BarclayHedge

Anyone who’s tried pairs trading will tell you that real financial series don’t exhibit truly stable, cointegrating relationships. If they did, pairs trading would be the easiest game in town. But the reality is that relationships are constantly evolving and changing. At some point, we’re

Finding complex chart patterns has never been an easy task. This article will give you a simple indicator for complex chart pattern recognition. You will have the freedom to detect any pattern with any pattern length. Not just 2-bar candlestick formations, but complex stuff like V-Tops spread over

In a recent post I showed that the momentum factor has been mean-reverting in the short-term, and that this effect can be used to trade both the factor and momentum strategies effectively. An obvious extension is to see whether trend-following as a factor is also mean-reverting. After all,

Yes, Artificial Intelligence (AI) is here to stay. Previously on this blog, I have written about the Basis of the Scientific Trading System as well as the Artificial Intelligence Trading Systems. Since then, I have designed a trading system model which I believe could satisfy all requirements of the

There is a substantial debate on the topic of factor investing and whether or not the “backtested” excess returns are actually achievable in practice. Much of the research on the topic suggests that practitioners in the field are unable to capture any of the so-called “factor premiums”. For

Hardly a month goes by without some pundit trumpeting that the VIX is broken. But before you worry too much, consider some of the non-obvious characteristics of the Cboe’s Fear Gauge. First a Summary These charts list possible explanations for perceived VIX “brokenness” Complaint Market in Low

It’s no secret that value has had a bad bout of performance in recent memory. This underperformance has been thoroughly examined by multiple research teams and we’ve done some of our own work on the subject. We’ve also done in-depth rebuttals to “value investing is dead” articles in the

Value and momentum equities exhibited significant performance last week raising short-term questions about factor crowding and long-term questions about appropriate factor diversification. We explore the idea of appropriate factor diversification through the lens of a retiring investor, asking the

In Part I Risk Parity, I discussed the“Chasing Diversifiers” problem that harms investors’ performance. This week, I apply the “Relevance of the Long-Run” concept to Risk Parity. First, let me acknowledge upfront that deep historical data is messy and is not precise. Depending on the

As we explained in an earlier Mathematical Investor blog, “target-date funds” are currently the rage in the finance world. The term refers to a mutual fund that targets a given retirement date, and then steadily shifts the allocation of assets from, say, a 80%/20% mix of stocks and bonds at the

The Low Volatility factor exhibited significant exposure to Value since 1989 The factors were highly correlated in the 1990s, but less after the financial crisis Quantitative easing was positive for Low Volatility, but negative for Value INTRODUCTION Riding the Ferris wheel in an amusement park is

In general, machine learning is a form of artificial intelligence that allows computers to improve the performance of a task through data, without being directly programmed. Reinforcing learning is a specialized application of (deep) machine learning that interacts with the environment and seeks to

Chart patterns have long been a favourite of the technical analysis community. Triangles, flags, pennants, cups, heads and shoulders…. Name a shape, someone somewhere is using it to predict market behaviour. But, is there a grain of truth or reliability in these patterns? Can it really give you a

In the last post we used the data available for the momentum factor using an ETF (ticker: MOM) which seeks to replicate The Dow Jones Thematic Market Neutral Momentum Index to time when to be in or out of high momentum stocks. Alpha Architect recently did some interesting analysis of the

new concepts in quantitative research Home CSSA Investor IQ When Should You Buy Momentum? Mean-Reversion in The Momentum Factor September 12, 2019 by david varadi Recently there was a good post by Bespoke Research highlighting the “Momentum Massacre” that we recently witnessed in the market.

Value and Momentum each had back to back extreme returns (five sigma) days on Monday, September 9th and Tuesday, September 10th. The Dow Jones Thematic Market Neutral Value Index (“Value”) started the week up 3.45%, its best day since inception on December 31st, 2001. The Value Index followed

Risk management has become a high priority for many investors over the past decade. The worst financial crisis and recession since the Great Depression in 2008-2009 clearly has the power to focus minds. Research shops have moved heaven and earth to search for solutions that attempt to limit risk

From showing related articles at the end of the article you have browsed through to creating a personalised recommendation based on your viewing habits, you would be surprised of the number of times you have been interacting with the K-means algorithm without even realising it. The above examples