What are the research questions? Research has shown that dividends constitute a greater contribution to the returns of a value versus a growth strategy. However, the question remains as to whether or not dividends matter within a style category. For style investors, does dividend policy determine

Continuing a previous post, in which we modeled the relationship in the levels of the VIX Index and the Year 1 and Year 2 CBOE Correlation Indices, we next turn our attention to modeling changes in the VIX index. In case you missed it, the post can be found here: Correlation Cointegration We saw

In a world of anemic asset returns, tax management may help significantly contribute to improving portfolio returns. Ideally, asset location decisions would be made with full investor information, including goals, risk tolerances, tax rates, and distribution of wealth among account types. Without

Correlations between Quality and Growth factors are currently elevated Value is more negatively correlated than usual to Quality, Growth and Low Volatility Monitoring correlations is important for maximising diversification benefits INTRODUCTION The rise of ETFs is often associated with higher stock

Hello all, last week I wrote a guest post featured on Dr. Ernest Chan’s blog which highlighted some of my research while working with QTS Capital Management on social media sentiment analysis and its place in financial models. The focus of this research was on how to derive sentiment signals from

Notes on Part-2 The Data Bid-Ask Spread Analysis How Do Aggregate Bid-Ask Spreads Vary with Days To Expiration? How Do Bid-Ask Spreads Vary with Volume? How Do Bid-Ask Spreads Vary with Volatility? Summary Conclusions Notes on Part-2 Some astute readers in the comments noted that analysis based on

In our final blog post, that finishes the trend-following series, we briefly review the results of the forward-tests of the profitability of various trend following rules in different financial markets: stocks, bonds, currencies, and commodities. The results of these tests allow us to better

Following on from my recent posts about trading volatility over weekends, I’m now going to briefly look at trading options overnight. Option traders have always complained when they were too long options overnight, expecting to usually lose money on overnight longs. This doesn’t make sense in a

There has been a recent popularity regarding time windows and it is one I completely agree with! There are certain structural changes that happen throughout the 24 hour session and as a trader it is important to take note of these when designing a system or strategy (or just placing trades). For

This paper develops a portfolio allocation framework to study the benefits of style integration and to compare the effectiveness of alternative integration methods in commodity markets. The framework is flexible enough to be applicable to any asset class for either long-short, long- or short-only

My latest post at http://quantsjourney.blogspot.co.uk/2017/09/time-of-day-effects-in-fx.html was on time of days effects in FX and I was claiming that you can actually make money with simple strategies depending on time of day. Below you will find 2 very simple strategies you can play with and make

Exploring alternative datasets to augment financial trading models is currently the hot trend among the quantitative community. With so much social media data out there, its place in financial models has become a popular research discussion. Surely the stock market’s performance influences the

One question that I am asked frequently is which operating system to use for quantitative trading research and implementation. The short answer, as of the writing date of this article, is if you want to carry out any serious/mathematical quant trading research (machine learning/deep learning) you

I recently had someone email me about the performance of a strategy I created back in late 2005/early 2006 and traded for a few years. I remember the strategy being a daily mean reversion set up with an intraday pullback entry. I figured it probably had not done well over the last decade. I stopped

Time of day is critical for trading, it is even possible building trading strategies solely depending on time of day (I will keep this for another post) I will be using the concept of quality and define a high quality market, from an intraday timing perspective, as a market when trading range and

There are no silver bullets for profiling risk, but drawdown’s properties arguably give this metric a leg up over most of the competition. The combination of an intuitive framework, simplicity, and sharp focus on how markets actually behave is a tough act to beat. Perhaps the strongest argument in

This is another comparison between R and MATLAB (Python also in the mix this time). In previous rounds we discussed the differences in 3d visualization, differences in syntax and input-output differences. Today is about computational speed. Spoiler alert: MATLAB wins by a knockout. A genuinely fair

Everybody would like to see the future. If you’re a portfolio manager, you’d definitely love to see the future. Many posts here on QuantDare deal with the challenge of predicting the future (with Prophet, Random Forests, Lasso, etc). This time, we talk about something different: imagine we are

In the previous article we looked at how one can use Neural Networks to detect jumps present in returns of a particular stock. In this blog post, we build on the thinking established in the previous article and use a Random Forest to detect jumps present in stock market returns. I have build an

If you’re interested in using artificial neural networks (ANNs) for algorithmic trading, but don’t know where to start, then this article is for you. Normally if you want to learn about neural networks, you need to be reasonably well versed in matrix and vector operations – the world of linear

Volume Filters: Part 1 | Trading Strategy (Entry & Exit) I. Trading Strategy Developer: R. D. Edwards, J. Magee (Volume Filters); R. D. Donchian (Price Breakout Channels). Concept: Trading strategy based on price breakouts confirmed by volume filters (i.e. volume breakouts). Research Question:

Our firm is growing rapidly and we’re looking to hire new teammates (one initially, possibly another down the road). If you are passionate about investor education and helping us deliver affordable alpha, please reach out! We just posted a new job for an execution trader/researcher role. Jack and

This post will investigate the idea of reducing leverage when drawdowns are small, and increasing leverage as losses accumulate. It’s based on the idea that whatever goes up must come down, and whatever comes down generally goes back up. I originally came across this idea from this blog post. So,

Summary The low current market outlook for stocks and bonds paints a gloomy picture for retirees under common retirement forecasting assumptions. However, assumptions such as net investment returns and retirement spending can have a large impact on forecasted retirement success, even for small

August 2017 Trend Following: DOWN -1.61% / YTD: -16.60% August was only slightly negative thanks to a late recovery from the mid-month level, where the index was down by over 5%. The YTD performance is still strongly in the red. Below is the full State of Trend Following report as of last month.

Slightly positive month for the State of Trend Following index but still negative Year-To-Date performance, in the double digits. Please check below for more details. Detailed Results The figures for the month are: August return: 0.79% YTD return: -11.1% Below is the chart displaying individual

September 18th is the official publishing date of my second book, "Smart Portfolios: A practical guide to building and maintaining intelligent investment portfolios (Harriman House, 2017)". This blog post will give you some more information about the book, and more importantly help you

SUMMARY Investors can either combine single-factors into a portfolio or sort stocks for several factor characteristics Double-sorting seems to work better for Value & Quality than for Value & Momentum The combination portfolios show the highest risk-return profiles, albeit at lower returns

It’s the fall of 2011. Investors are caught up in fears of another 2008-style financial crisis, this time arising out of schisms in the Eurozone. The S&P 500 is trading at 1200, the same price it traded at in 1998, roughly 13 years earlier, despite the fact that its earnings today are almost

Way back in 2009 I showed a study that suggested Labor Day week performance has been somewhat dependent on whether the market has rallied over the 20 trading days leading up to it. I decided to take a new look at that study today. Below are updated results of post-Labor Day action when the previous

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

Identifying and building a portfolio of uncorrelated trading strategies is the main aim of many quantitative hedge funds. Given that one would like to add a new strategy to an existing set of strategies, what is the marginal gain the can be expected over the status quo? In addition, how can one

Do changes in the U.S. federal regulatory burden predict U.S. stock market returns? To check, we consider two measures of the regulatory burden: Annual number of pages in the Federal Register (FR) during 1936-2016 – “…in which all newly proposed rules are published along with final rules,

The Standard and Poor’s (S&P) 500 index is a value-weighted stock index based on the market capitalizations of 500 large companies in the US. This index was introduced in 1957 and intended to be a representative sample of leading companies in leading industries within the US economy. Stocks in

In their seminal 1993 paper, “Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency,” Narasimhan Jegadeesh and Sheridan Titman reported significant returns to buying winners and selling losers in the U.S. equity market, now referred to as the “cross-sectional

Summary­­ The current outlook for stocks, bonds, and traditionally allocated portfolios is near all-time historical low levels. Even though short-term performance may vary, investors looking for long-term success may have to expand their investment palette to earn returns anywhere close to those

We investigate the correlation structure of anomaly strategy returns. From an initial 434 anomalies, we select 116 anomalies that are significant in the mean and not highly correlated with other anomalies. Cluster analysis reveals 24 clusters and 29 singleton anomalies that can be grouped into 3

In a previous post I looked at ways of modeling the relationship between the CBOE VIX Index and the Year 1 and Year 2 CBOE Correlation Indices: The question was put to me whether the VIX and correlation indices might be cointegrated. Let’s begin by looking at the pattern of correlation between the

What are the research questions? Is there a consistent and reliable long term overreaction pattern in global equity markets? In US equity markets, buying long term losers and selling long term winners (also called long term price reversal) is a well-documented anomaly. Does it also exist in global

There are very few algo trading firms/strategies that are operating in the Mexican stock exchange. I believe this should provide great opportunities as there is little competition. Contrary to a more developed market, arbitrage opportunities aren’t readily realized which suggests there might be

In this article we will look at a subset of the 3024 iron condor strategy variations that were tested between January 2007 and September 2016. Specifically, we will look at the 1512 iron condor strategy variations that used both stop losses and profit targets. Out of these 1512 variations we will

SUMMARY Most smart beta products exhibit correlations of > 0.9 to the S&P 500 Factors show correlations of zero on average However, factor correlations are highly volatile across the market cycle INTRODUCTION In our recent research note “Smart Beta vs Factors in Portfolio Construction” we

Delta hedging is a technique used by trades to reduce the directional risk of a position. This delta hedging strategy results in the reduction of the variability of the profit and loss (pnl) of the position. A position that is delta hedged is said to be delta neutral. In this blog we will look at

Pairs trading is one of the simplest forms of statistical arbitrage which involves exploiting relative mispricings between two similar assets. It operates based on the assumption of the law of one price; that anomalies among securities valuation will occur in the short run but in the long run, will

The difficulty in testing the profitability of trend-following rules stems from the fact that the procedure of testing involves either a single- or multi-variable optimization. Specifically, any trading rule considered in Part 3 has at least one parameter that can take many possible values. For

During my review of several quantitative trading books and papers, I kept on seeing information on two classes of trading strategies: mean reversion and momentum. I thought the things I read explained mean reversion quite clearly, but I wasn’t entirely clear on how to implement momentum investing

Last week we stated that market makers don't fully account for weekend decay in equity options. Today we show specific results. Christopher Jones and Joshua Shemesh studied this issue and presented the findings in a paper that they presented to the 2010 American Finance Association meeting.

You may have noticed over the past few weeks of ‘Thursday Trading Thoughts’ that we’ve been following a theme. In episode 113 we heard about a test Kevin Davey calls the ‘Monkey test’, which can be used to measure the effectiveness of entries and exits. Then in episode 114 we reviewed a

In this post we discuss portfolio “tranching” (i.e. dividing a portfolio into overlapping slices of the same underlying strategy) to minimize “timing luck”. This is an under discussed but important topic in tactical asset allocation. For more smart thoughts on portfolio tranching, see this

Several readers asked for additional tests to be done on the strategy on Sector trading using the 200-day moving average. We will be testing allocated 11% per ETF instead of 10%, using asymmetric number of days and adding IEF to the SPY MA200 10 day test. SPY MA200 10 day Buy Rule: Buy SPY when it