Quantocracy

Quant Blog Mashup

Quantocracy’s Daily Wrap for 12/06/2015

This is a summary of links featured on Quantocracy on Sunday, 12/06/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Best Links of the Week [Quantocracy]

    The best quant mashup links for the week ending Saturday, 12/05 as voted by our readers: Predicting volatility [EP Chan] Announcing the QuantStart Advanced Trading Infrastructure Article Series [Quant Start] Exploring mean reversion and cointegration with Zorro and R: part 1 [Robot Wealth] The Quantitative Momentum Investing Philosophy [Alpha Architect] * * * My fellow traders, ask not what
  • Predicting Heavy and Extreme Losses in Real-Time for Portfolio Holders (2) [Quant at Risk]

    This part is awesome. Trust me! Previously, in Part 1, we examined two independent methods in order to estimate the probability of a very rare event (heavy or extreme loss) that an asset could experience on the next day. The first one was based on the computation of the tail probability, i.e.: given the upper threshold Lthr find the corresponding ? such that Pr(L In both cases, the lack of

Quantocracy’s Daily Wrap for 12/05/2015

This is a summary of links featured on Quantocracy on Saturday, 12/05/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Using the LASSO to Forecast Returns [Alex Chinco]

    1. Motivating Example A Popular Goal. Financial economists have been looking for variables that predict stock returns for as long as there have been financial economists. For some recent examples, think about Jegadeesh and Titman (1993), which shows that a stocks current returns are predicted by the stocks returns over the previous 12 months, Hou (2007), which shows that the current returns
  • High Valuations and Low Yields [Sharpe Returns]

    This is how your average buy-and-hold investor probably feels right now if they are looking to deploy new capital for the long run. Today, bond yields are puny while stock valuations are rich. In fact, we currently have one of the worst yield and value combinations in history as seen in the charts below dating back to 1880: Source: multpl.com Notice on these charts the years 1921 and 1982, when
  • When can income be growth? [Flirting with Models]

    Summary Traditionally, stocks have been used for growth and bonds for safety Therefore, investors looking for long-term capital appreciation tended to allocate heavily towards stocks while investors concerned about preservation allocate more heavily towards bonds With an anemic forecast for equity returns over the next decade, could the best place to find growth actually be with income? It is

Quantocracy’s Daily Wrap for 12/04/2015

This is a summary of links featured on Quantocracy on Friday, 12/04/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • A First Attempt At Applying Ensemble Filters [QuantStrat TradeR]

    This post will outline a first failed attempt at applying the ensemble filter methodology to try and come up with a weighting process on SPY that should theoretically be a gradual process to shift from conviction between a bull market, a bear market, and anywhere in between. This is a follow-up post to this blog post. So, my thinking went like this: in a bull market, as one transitions from
  • Factors in Other Products [Factor Wave]

    Most of what Ive written about have been equity factors. But factors, persistent price predictors, apply to other investments as well. FactorWave will also offer analyses in volatility, equity options and commodity futures. Volatility Equity volatility (tradeable through the VIX) displays two major pricing factors: The futures tend to collapse towards the cash index. This doesnt make a great
  • Ignore Liquidity At Your Peril [Larry Swedroe]

    Liquidity is valuable to investors. Therefore, investors demand higher expected returns for less liquid stocks. The liquidity of an asset market refers to the ability of investors to buy and sell significant quantities of that asset, quickly, at low cost and without a major price concession. Thus, liquidity risk can be thought of as the risk to investors that an investment cannot be bought or sold
  • Statistics – JavaScript for Financial Analysts [John Orford]

    First draft of 'JavaScript for Financial Analysts' Chapter 11. ~ Finance is a super slow mo movie of investment decision logic colliding into chaotic markets. The narrow space in between is inhabited by statistics. JavaScript has a capable statistics library called jStat which offers a wide range of statistical functions, as well as some very neat features. Async jStat supports

Quantocracy’s Daily Wrap for 12/03/2015

This is a summary of links featured on Quantocracy on Thursday, 12/03/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Markowitz portfolio optimization with VBA code [RRSP Strategy]

    Wouter, Butler and Kipnis [2015] recently demonstrated Classical Asset Allocation (CAA) for long only portfolios, based on Markowitz concepts. The method uses only two parameters thus minimizing the chances of curve-fitting and data snooping. The parameters are lookback period (12 months) and target volatility. http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2606884 Main results from the
  • State of Trend Following in November [Au Tra Sy]

    Last months results for trend following were positive, with a strong performance that took the index back into positive territory for the year. The strategy goes into the last month of the year holding modest gains but 2015 will obviously not be a repeat of the runaway performance from last year. Please check below for more details. Detailed Results The figures for the month are: November

Quantocracy’s Daily Wrap for 12/02/2015

This is a summary of links featured on Quantocracy on Wednesday, 12/02/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Case for an Allocation to Dollar Based EM Debt [EconomPic]

    While the underperformance of high yield bonds since my post The Case Against High Yield has certainly made high yield bonds more attractive (yields went from sub 6% to north of 8%), I still prefer the risk/return profile of a stock/bond allocation (more here). For those that are looking for a higher yielding fixed income alternative with limited currency risk and the potential for U.S. interest
  • Exploring mean reversion and cointegration with Zorro and R: part 1 [Robot Wealth]

    This series of posts is inspired by several chapters from Ernie Chans highly recommended book Algorithmic Trading. The book follows Ernies first contribution, Quantitative Trading, and focuses on testing and implementing a number of strategies that exploit measurable market inefficiencies. Im a big fan of Ernies work and have used his material as inspiration for a great deal of my own
  • Putting TWAP to the Test [Flirting with Models]

    A few weeks ago, we discussed a method that we implemented to construct more realistic indices using an estimate of time weighted average prices (TWAP) for trade execution. Prior to October, whenever our models required a rebalance, we assumed that it occurred at the opening price on the following day in our hypothetical index calculation. Making this assumption is not necessarily bad, especially
  • Trend Following Via Slope [Relative Value]

    Linear regression slope is another tool one can use to sidestep potentially sticky situations. The following algorithms hold a full position in SPY but liquidate whenever the slope of closing prices turn negative. Starting Capital of $100,000 and backtest period from 2/2003 and 11/2015. Strategy End Bal Gain CAGR Sharpe Sortino Drawdown Buy and Hold 316400 216.4% 9.4% -54.9% 1 Month 182561 82.6%
  • ‘predictions’, ‘forecasts’ or ‘projections’? [Eran Raviv]

    Perhaps it is the different jargon used in different disciplines, not sure. But for some reason, the terms predictions, forecasts and projections are frequently used interchangeably. There should be at least some distinction, here is what I entertain: The word predictions should be reserved for situations where the future is already here. For example, given the
  • Trend Following UP in November and YTD [Wisdom Trading]

    November 2015 Trend Following: UP +6.06% / YTD: +9.86% The Wisdom trend following index gradually made its way up last month to post a strong result for November, and recover a large part of the losses occurred in October. This helped cement the YTD number further in the black. Now nearly in double-digit territory, there is a strong chance that trend following will end 2015 positive. Stay tuned
  • Predictable & Skewed Returns [Larry Swedroe]

    There has been a lot of research recently that investigates the link between stock returns and higher moments of the return distribution, specifically the skewness of returns. This link, unfortunately, is frequently ignored by more standard measures of market risk and volatility. Skewness, if youll recall, measures the asymmetry of a distribution. In terms of the stock market, the asymmetric
  • Student t Distributed Linear Value-at-Risk [Quant at Risk]

    One of the most underestimated feature of the financial asset distributions is their kurtosis. A rough approximation of the asset return distribution by the Normal distribution becomes often an evident exaggeration or misinterpretations of the facts. And we know that. The problem arises if we investigate a Value-at-Risk (VaR) measure. Within a standard approach, it is computed based on the

Quantocracy’s Daily Wrap for 12/01/2015

This is a summary of links featured on Quantocracy on Tuesday, 12/01/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Quantitative Momentum Investing Philosophy [Alpha Architect]

    Our Quantitative Momentum (QM) system seeks to identify stocks with the highest quality momentum. We consider the term momentum to mean a continuation of past returnspast winners tend to be future winners, while past losers tend to be future losers. How can we exploit this phenomenon? At Alpha Architect, we have designed a system to identify the quality of momentum by examining how
  • Reversals and Momentum [Factor Wave]

    Ive recently written a few posts about the persistency of cross-sectional momentum. But it seems that eventually stocks that go up have to come down. Not only is this somewhat intuitive, but the existence of stock price reversals is also well documented. But actually momentum persistence and price reversals are completely compatible if we look at the entire cross section of stocks. In
  • Central Limit Theorem: Visual demonstration [Quant Dare]

    Everybody knows about the Central Limit Theorem, but have you ever seen a visual demonstration? The central limit theorem states that, given certain conditions, the mean of a large number of iterates of independent random variables, will be approximately normally distributed, regardless of the underlying distribution. Formally, Let {X1, , Xn} be a sequence of independent and identically

Quantocracy’s Daily Wrap for 11/30/2015

This is a summary of links featured on Quantocracy on Monday, 11/30/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Announcing the QuantStart Advanced Trading Infrastructure Article Series [Quant Start]

    To date on QuantStart we have considered two major quantitative backtesting and live trading engines. The first arised from the Event-Drive Backtesting series I wrote back in March 2014. The second is QSForex, an open-source backtest and live trading engine that hooks into the OANDA Forex Broker API, which is still being used by many of you. I've had a lot of requests recently for a more
  • Momentum Investing: Why Does Seasonality Matter for Momentum? [Alpha Architect]

    With Januaries (a month in which lagged "losers" typically outperform lagged "winners") excluded, the average monthly return to a momentum strategy for U.S. stocks was found to be 59 bps for non-quarter-ending months but 310 bps for quarter-ending months. The pattern was stronger for stocks with high levels of institutional trading and was particularly strong in December. The
  • Overnight Trading in the E-Mini S&P 500 Futures [Jonathan Kinlay]

    Jeff Swanson's Trading System Success web site is often worth a visit for those looking for new trading ideas. A recent post Seasonality S&P Market Session caught my eye, having investigated several ideas for overnight trading in the E-minis. Seasonal effects are of course widely recognized and traded in commodities markets, but they can also apply to financial products such as the
  • Recovery of Financial Price-Series based on Daily Returns Matrix in Python [Quant at Risk]

    As a financial analyst or algo trader, you are so often faced with information on, inter alia, daily asset trading in a form of a daily returns matrix. In many cases, it is easier to operate with the return-series rather than with price-series. And there are excellent reasons standing behind such decision, e.g. the possibility to plot the histogram of daily returns, the calculation of daily
  • Momentum Based Strategies for Low and High Frequency Trading [Quant Insti]

    It is important to know the difference between high frequency and low frequency trading before discussing the specific trading strategies. Opinions tend to differ on what constitutes high frequency but by and large there is a consensus that the duration of asset holding period is very low, ranging from seconds to minutes. High frequency trading revolves around market microstructure and order book
  • Longer Lives Lower Interest Rates [Larry Swedroe]

    Ever since the global financial crisis, the real interest rates of developed economies have remained in negative territory. Nominal interest rates hover near zero, and inflation rates, although quite low for historical standards, have remained positive (in most countries, at least on average). Whats more, negative nominal interest rates have even been observed in some developed countries for
  • D3 – Javascript for Financial Analysts – Chapter 10 [John Orford]

    First draft of 'JavaScript for Financial Analysts' Chapter 10. ~ D3 is a foreboding beast. It eschews classic programming styles in favour of a more functional approach. Luckily however, if you have come this far, get ready to sit back and enjoy of the fruits of your labour. Almost every charting library is descriptive, they give you several chart templates which you can configure and
  • Real Estate = A Real Good Time [Jay On The Markets]

    OK, I will admit I am a bit late with this one. Ill go ahead and blame The Holidays. Anyway, if you were wondering when it might be a good time to hold real estate stocks, the answer might well be, um, Now. (Jay Kaeppel Interview at BetterSystemTrader.com) Favorable Seasonal Period for Real Estate Stocks *A favorable seasonal period for real estate stocks tends to occur between the
  • Ivy Portfolio December Update [Scott’s Investments]

    The Ivy Portfolio spreadsheet track the 10 month moving average signals for two portfolios listed in Mebane Fabers book The Ivy Portfolio: How to Invest Like the Top Endowments and Avoid Bear Markets. Faber discusses 5, 10, and 20 security portfolios that have trading signals based on long-term moving averages. The Ivy Portfolio spreadsheet tracks both the 5 and 10 ETF Portfolios listed in

Quantocracy’s Daily Wrap for 11/29/2015

This is a summary of links featured on Quantocracy on Sunday, 11/29/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Best Links of the Week [Quantocracy]

    The best quant mashup links for the week ending Saturday, 11/28 as voted by our readers: Frog in the Pan: Identifying the Highest Quality Momentum Stocks [Alpha Architect] Better Tests with Oversampling [Financial Hacker] Bring More Data [Dual Momentum] A framework for rapid and robust system development based on k-means clustering [Robot Wealth] Predicting volatility [EP Chan] * * * My fellow
  • [Academic Paper] Stop-Loss Strategies with Serial Correlation, Regime Switching, and Transactions Costs [@Quantivity]

    Stop-loss strategies are commonly used by investors to reduce their holdings in risky assets if prices or total wealth breach certain pre-specified thresholds. We derive closed-form expressions for the impact of stop-loss strategies on asset returns that are serially correlated, regime switching, and subject to transactions costs. When applied to a large sample of individual U.S. stocks, we show
  • [Academic Paper] Dissecting Investment Strategies in the Cross Section and Time Series [@Quantivity]

    We contrast the time-series and cross-sectional performance of three popular investment strategies: carry, momentum and value. While considerable research has examined the performance of these strategies in either a directional or cross-asset settings, we offer some insights on the market conditions that favor the application of a particular setting.
  • [Academic Paper] Rethinking Performance Evaluation [@Quantivity]

    We show that the standard equation-by-equation OLS used in performance evaluation ignores information in the alpha population and leads to severely biased estimates for the alpha population. We propose a new framework that treats fund alphas as random effects. Our framework allows us to make inference on the alpha population while controlling for various sources of estimation risk. At the
  • Interview with Andrew Gibbs [Better System Trader]

    Andrew Gibbs has been involved in the financial markets since 2001 and is the founder and CEO of Halifax New Zealand. Andrew has extensive experience in all forms of equity and derivative contracts, managing millions of dollars and trading a number of markets around the world. In this episode we discuss volatility and methods to trading the VIX plus the benefits and methods of including