Momentum investing – betting on the persistence of price trends in the short to medium term — has captured the crowd’s attention in recent years. Consider, for instance, the strong growth in ETF assets in the niche. The first fund launched a bit more than five years ago; today, there are

In the last article, posted way back in August, I looked at the Iron Condor structures that appeared to perform the best for each of the seven metrics I tracked. Recall that I tested 3024 different Iron Condor strategy variations over the period from January 2007 through September 2016. This testing

Traditionally, investors have used a balance between stocks and bonds to govern their asset allocation. Expanding this palette to include other asset classes can allow them to potentially both enhance return and reduce risk, benefiting from diversification. Modern portfolio theory tells us, however,

In most parts of Canada we have very distinct seasons. Some months of the year are temperate and relatively dry, while other months are cold and snowy. As a result, most Canadian towns of any size have stores that sell skis and bikes. Of course, they don’t inventory both skis and bikes at the same

Before spending much Monday selling off, the SPX managed to make a new intraday all-time high. The new high followed by a poor and downward close triggered the study below, from the Quantifinder. Results are all updated. 2017-12-05 Results here seem to suggest an upside edge over the next 1-2 weeks.

Shawn McKay, Robert Shapiro, Ric Thomas A version of this paper can be found here Want to read our summaries of academic finance papers? Check out our Academic Research Insight category. What are the research questions? Diversification is often thought of as the only “free lunch” in finance and

We provide further evidence that markets trend on the medium term (months) and mean-revert on the long term (several years). Our results bolster Black’s intuition that prices tend to be off roughly by a factor of 2, and take years to equilibrate. The story behind these results fits well with 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

Focusing purely on Value is a difficult strategy Sorting by multiple factors improves performance and risk-metrics However, factor selection and allocation remain challenging topics INTRODUCTION Value is likely the most common strategy for equity fund managers as the principle of buying something at

ADC 18 is an event for institutional investors and business professionals working to stay on top of the radically evolving landscape of alternative data. Signal Graphic Alternative Data Vizualization The alternative data landscape is evolving quickly. In less than one year, we've seen rapid

VIX related products (ETNs, futures and options) are becoming popular financial instruments, for both hedging and speculation, these days. The volatility index VIX was developed in the early 90’s. In its early days, it led the derivative markets. Today the dynamics has changed. Now there is strong

Any serious quant trading research with machine learning models necessitates the use of a framework that abstracts away the model implementation from the model specification. This is particularly crucial for deep learning techniques as production-grade models require training on GPUs to make them

Kory Hoang is not a veteran trader—he’s not someone who has been doing this 10-20 years. He’s someone who has been doing this for only a few years, yet he’s begun to make decent gains on his trading capital. Kory is also not a full-time trader …well, at the time of recording this—a few

Much has been made of Factor Investing, and even Vanguard is launching a suite of actively-managed factor ETFs. But even now, with Vanguard offering factor ETFs, there are many investors that only invest passively into an index fund, such as the SP500 or EAFE index. These investors will cite the

In the last post we introduced the concept of using adaptive volatility in order to have a flexible lookback as a function of market conditions. We used the R-squared of price as a proxy for the strength of the trend in the underlying market in order to vary the half-life in an exponential moving

Models are useful. They help us understand the world around us and aid us in predicting what will happen next. But it’s important to remember that models don’t necessarily reflect the underlying reality of the thing we’re modeling. The Ptolemaic model of the solar system assumed the Earth was

A subscriber requested review of an analysis concluding that combining economic trend and market trend signals enhances market timing performance. Specifically, per the example in the referenced analysis, we look at combining: The 10-month simple moving average (SMA10) for the broad U.S. stock

Many investors, investment professionals, and pundits make comments regarding the relationship between stock correlations and opportunities for active stock pickers. For example, here is a recent example from the Financial Times: Correlation crash clears way for stockpickers. The basic (albeit

Factor investing, and the associated intellectual battles, have raged for decades in academic finance journals. However, now that factor investing has gone mainstream via ETFs, the debate has broader interest among the investing public. Some investors question the very existence of factor premiums.

SPY gapped up and closed lower Monday after leaving an unfilled up gap on Friday. This triggered the study below that examined similar price action in SPY with regards to how it gapped and finished

Last month we launched Meta Strategy, our own smart approach to combining the 40+ tactical asset allocation strategies tracked on our site. Each month, Meta selects 10 strategies and then trades their combined asset allocation. Members can follow Meta in near-real time. Each month’s 10 strategies

In this article we’ll look into a real options trading strategy, like the strategies that we code for clients. This one however is based on a system from a trading book. As mentioned before, options trading books often contain systems that really work – which can not be said about stock or forex

This article series provides an opportunity to move towards more interactive analysis. My plan is to integrate more Jupyter notebooks and Github repos into my research/publishing workflow. For datasets that are too big to share through github I will provide a download link both here and in the

Most researchers create factor portfolios by taking the top & bottom 30% of stocks, which results in large portfolios Portfolios can be reduced, but firm risks start influencing factor returns with too few stocks Most investors are likely better of buying factor products then building factor

Using historical data from the options market along with realized subsequent returns, we can translate risk-neutral probabilities into real-world probabilities. Market implied probabilities are risk-neutral probabilities derived from the derivatives market. They incorporate both the probability of

Short selling frictions cannot explain the persistence of seven prominent stock anomalies. Long-only investing is robust and profitable and can be further enhanced by using a synthetic short. Moreover, portfolios restricted to stocks that are easy to short sell continue to have large and significant

One of the tenets of modern portfolio theory is that you cannot generally beat the market after transaction costs. Yet academic researchers have shown that momentum consistently beats the market. Other factors besides momentum have also cast doubt on the efficacy of the efficient market hypothesis.

Last month I presented a detailed roadmap for the redevelopment of QSTrader, our open-source systematic trading simulation engine. Today I want to discuss our progress in the month since that article was published and what still remains to be completed prior to the initial 0.1.0 alpha release.

This article is a departure from the quantitative research that usually appears on the Robot Wealth blog. Until recently, I was working as a machine learning consultant to financial services organizations and trading firms in Australia and the Asia Pacific region. A few months ago, I left that world

This is a simple reference article for readers that might wonder where I get/got my options data from. In this regard I would like to shout out the contributors to the pandas-datareader, without their efforts this process would be much more complex. Intuitive Explanation So this code consists of

Developer: Larry Williams (“All in one: Price, volume and open interest”); R. D. Donchian (Breakout Channels). Concept: Trading strategy based on price breakouts confirmed by POIV (Price, Open Interest, and Volume) filters. Research Question: Can combined filters improve price breakouts?

Assigning weights to portfolio assets is challenging when we have to consider multiple constraints. Asset allocation may be seen as a constraint satisfaction problem (CSP), and some algorithms allow us to define our own restrictions and look for an optimal weight distribution. In this post, we will

We present some empirical evidence for short volatility strategies and for the cyclical pattern of their P&L. The cyclical pattern of the short volatility strategies produces an alpha in good times but collapses to the beta in bad times. We introduce a factor model with risk-aversion to explain

Risk parity portfolios attempt to diversify across asset classes and strategies by risk contribution as opposed to dollar allocation. Implementing a risk parity strategy requires making a number of important construction decisions. A key question we have to answer is “How are we going to measure

Allocate Smartly tests and tracks asset allocation strategies sourced from books, academic papers and other publications. Most of the strategies that we test though never make it on to this site. There are a variety of reasons that might be, but often it’s simply because they’re not very good.

The year 2017 might be regarded as the year where cryptocurrencies became mainstream. Investment funds focused on cryptocurrencies were launched, the CBOE announced Bitcoin futures for the end of the year and some everyday expenses like booking flights at Expedia can be paid in Bitcoins.

I have long been frustrated by the lack of an "out of the box" solution for plotting OHLC candlestick charts natively in Octave, the closest solution I know being the highlow plot function from the financial package ( which does not yet implement a candle function ) over at Octave

By considering the same risk measure, ϱ, applied to two or more portfolios (credit loss distributions, profit-and-loss distributions, etc.) one desires to have a subadditivity property in place: ϱ(X1+X2)≤ϱ(X1)+ϱ(X2) i.e. meaning that two combined portfolios should never be more risky than the

Optimizing the parameters of a trading strategy via backtesting has one major problem: there are typically not enough historical trades to achieve statistical significance. Whatever optimal parameters one found are likely to suffer from data snooping bias, and there may be nothing optimal about them

On most mainstream finance websites, a good chunk of the stories discuss the FED and where interest rates are going. Intuitively, this makes sense: The FED is arguably an extremely influential component of U.S. economy. But how do markets respond to the FED? Is the response rational, irrational, or

One of the inherent challenges in designing strategies is the need to specify certain parameters. Volatility parameters tend to work fairly well regardless of lookback, but there are inherent trade-offs to using short-term versus longer-term volatility. The former is more responsive to current

A reader emailed me about testing a weekly mean reversion rotation strategy on S&P500 stocks. My first thought was, why had I not done this type of test before? The very first strategy that I worked on with Larry Connors was this type of strategy. The strategy I will be testing today is a

The current equity bull market has not been kind to non-U.S. allocations. At a recent conference I attended, the term ‘TINA: there is no alternative’ came up more than once in the context of allocating investor portfolios. It captures the collective sentiment that equities, despite a massive

Ensemble methods are learning algorithms that construct a set of classifiers and then classify new data points by taking a (weighted) vote of their predictions. This is with the intention that ensembles will achieve better prediction accuracy than individual classifiers. In machine learning

This post will be about comparing strategies from the paper “Easy Volatility Investing”, along with a demonstration of R’s table.Drawdowns command. First off, before going further, while I think the execution assumptions found in EVI don’t lend the strategies well to actual live trading

The subject of asset bubbles and market crashes has fascinated me for more than 20 years. As an options market maker for Susquehanna International Group (“SIG”), extreme price movements were a daily source of concern. I sat next to Jeff Yass for years and watched him manage option positions in

Equity hedge fund returns have been disappointing over the last 14 years An exposure analysis shows no structural factor exposure, but frequent factor rotation Multi-factor long-short products are an interesting alternative, depending on the fee level INTRODUCTION Hedge fund assets reached an

Peng Wang and Jon Spinney A version of this paper can be found here Want to read our summaries of academic finance papers? Check out our Academic Research Insight category. What are the research questions? Investors following a purely quantitative approach to asset allocation are often left with

We find that when measured in terms of dollar-turnover, and once beta-neutralised and Low-Vol neutralised, the Size Effect is alive and well. With a long term t-stat of 5.1, the “Cold-Minus-Hot” (CMH) anomaly is certainly not less significant than other well-known factors such as Value or

We’ve read a number of outlooks and commentaries lately from firms arguing for investors to take a tactical tilt away from U.S. equities and towards International equities. The logic behind this tilt is largely driven by relative valuations: international equities appear significantly cheaper than