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 the(...)

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, executive(...)

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 technique(...)

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(...)

Guest: Corey Hoffstein. Corey is the founder and CIO of Newfound Research. He’s a frequent speaker on industry panels and contributes to ETF.com, ETF Trends, and Forbes.com’s Great Speculations blog. He was named a 2014 ETF All Star by ETF.com. Corey holds a Master of Science in Computational(...)

Traders often debate whether short out-of-the-money (OTM) or at-the-money (ATM) puts are riskier. The argument for OTM put options being riskier is that their Speeds (or dGamma/dspot) are higher than the ATMs’ ones, thus the Gamma, which is negative, can increase (in absolute value) substantially(...)

In this post, I want to explain the intuition behind some famous theorems in mathematical finance. I will not explain any proofs, since you can find these in books, but rather for what the theorems can be used. Girsanov’s theorem Let us start with Girsanov’s theorem. We need a Brownian motion Wt(...)

A common question asked in the factor investing field is the following — “how much of the model’s performance is driven by sector allocations, and how much is driven by security selection?” Our answer is to simply buy Value stocks or Momentum stocks, regardless of sector constraints. Why? Well a(...)

In this new article series Imanol Pérez, a PhD researcher in Mathematics at Oxford University, and an expert guest contributor to QuantStart delves into high-frequency trading and introduces the concept of market microstructure. Nowadays, a significant number of financial instruments are traded in(...)

I propose a theoretical explanation for the puzzling pre-announcement positive drift that has been empirically documented before scheduled Federal Open Market Committee (FOMC) meetings. I construct a general equilibrium model of disagreement (difference-of-opinion) where two groups of agents react(...)

In a previous blog post I mentioned the VVIX/VIX Ratio, which is measured as the ratio of the CBOE VVIX Index to the VIX Index. The former measures the volatility of the VIX, or the volatility of volatility. A follow-up article in ZeroHedge shortly afterwards pointed out that the VVIX/VIX ratio had(...)

What are the research questions? By studying the trading data (provided by a German brokerage house) of a large (6,949) group of individual self-directed investors over the period from 2005-2010, the authors attempt at answering:(1) Do ETFs provide performance benefits to individual investor(...)

Under a simple model of asset prices, expected returns and volatilities can be used to calculate expected maximum drawdowns over a given timeframe. However, these expected drawdowns do not line up with the drawdowns investors have experienced. Simple models have underestimated drawdown risk in(...)

SUMMARY Investors seek smart beta products for risk reduction However, smart beta products are effectively long-only products with full equity risk Only factor products, i.e. long-short portfolios, offer true diversification benefits and downside protection INTRODUCTION FTSE Russell’s 2017 Smart(...)

In this piece, I’m going to share a mental exercise that we can use to increase the truthfulness of our thinking. The exercise is intended primarily for traders and investors, given their obvious (financial) reasons for wanting to think more truthfully about the world, but it has the potential to(...)

We consider an investor and a financial market that consists of only two assets: one risky asset and one safe (or risk-fee) asset. An example of a risky asset is an investable stock market index. When it comes to the safe asset, even though financial theory assumes its existence, there are no(...)

Do stock scammers use Twitter to manipulate prices of microcap stocks? In his August 2017 paper entitled “Market Manipulation and Suspicious Stock Recommendations on Social Media”, Thomas Renault performs an event study to analyze returns for microcap stocks around spikes in Twitter activity about(...)

This paper uses S&P100 data to examine the performance of pairs trading portfolios that are sorted by the significance level of cointegration between their constituents. We find that portfolios that are formed with highly cointegrated pairs, named as "supercointegrated", yield the(...)

Recent graduates, postgraduates and those in early-career positions with a technical background are now faced with a wide choice of exciting and well-compensated career paths in a diverse set of industries. Quantitative finance remains an attractive option but the competition for top talent is(...)

SUMMARY Smart beta ETFs are based on factor investing research Excess returns from smart beta ETFs are different from factor returns Investors need to be aware that smart beta ETFs offer little diversification for an equity-centric portfolio INTRODUCTION Blackrock, a provider of active and passive(...)

In order to analyze and build ‘crypto’ based trading strategies we need to get historical data for Bitcoin and other ‘large-cap’ coins such as Ether, Ripple, Dash, Monero, etc. But also for up and coming coins such as Neo, Stratis, IOTA and many more. In this post I will point you to two solutions:(...)

What are the research questions? Can the concepts contained in equity “factors” translate to the corporate bond market? Do single factor bond portfolios generate alpha? Do multifactor bond portfolios contribute additional value? What are the Academic Insights? YES. Using bond characteristics only,(...)

While valuation-based market timing is notoriously difficult, present and future retirees should prepare for muted U.S. stock and bond returns relative to historical experience. High valuations suggest that retirement withdrawal rates that were once safe may now deliver success rates that are no(...)

... is now ready for pre-order. For more information see the website, here: https://www.systematicmoney.org/smart To pre-order you can go here: https://www.harriman-house.com/smart-portfolios

Years ago, when was asked to recommend investment books, I often suggested some about the psychological issues influencing investor behavior. They focused on investor fear and greed to show “what fools these mortals be.” Here are some examples: Devil Take the Hindmost: A History of Financial(...)

A trend following strategy is based on switching between a financial asset and cash depending on whether the asset prices trend upward or downward. Specifically, when the strategy identifies that prices trend upward (downward), it generates a Buy (Sell) trading signal. A Buy signal is a signal to(...)

Using a newly constructed unique dataset, this study is the first to document returns of the market portfolio for a long period and with a high level of detail. Our market portfolio basically contains all assets in which financial investors have invested. We analyze nominal, real, and excess return(...)

Similar to some better-known factors like size and value, time-series momentum is a factor that historically has demonstrated above average excess returns. Time-series momentum, also called trend-momentum or absolute momentum, is measured by a portfolio long assets that have had recent positive(...)

In this article series QuantStart returns to the discussion of pricing derivative securities, a topic which was covered a few years ago on the site through an introduction to stochastic calculus. Imanol Pérez, a PhD researcher in Mathematics at Oxford University, and an expert guest contributor to(...)

‘Once you have a system, the biggest obstacle is trusting it.’ Tom Wills ‘What is the last thing you do before you climb on a ladder? You shake it. And that is Monte Carlo simulation.’ Sam Savage, Stanford University Introduction In my early days of looking at trading strategies, getting to the(...)