Quantocracy

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Quantocracy’s Daily Wrap for 07/15/2020

This is a summary of links featured on Quantocracy on Wednesday, 07/15/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Forex Intraday Seasonality [Dekalog Blog]

    Over the last week or so I have been reading about/investigating this post's title matter. Some quotes from various papers' abstracts on the matter are: "We provide empirical evidence that the unique signature of the FX market seasonality is indeed due to the different time zones market participants operate from. However, once normalised using our custom-designed procedure, we
  • Finance Factors Coordination? Cascade Selection [Quant Dare]

    Currently, strategies based on premium factors are everywhere: from funds or ETFs built on ratios or statistics perfectly specified, trying to exploit specific factor premia, to boutique instruments more or less opaque that following one or more risk premia. In any case, one of the questions we may pose is what the best way to combine several risk premia is and what interaction can expect. In this
  • Left Tail Risk and Left Tail Momentum [Alpha Architect]

    The positive trade-off between risk and expected return is the most fundamental concept in financial economics. Most investors are risk-averse. In order to hold higher-risk securities, they demand higher compensation in the form of higher expected returns. And risk-averse investors are more sensitive to downside risk, the left tail in the distribution of potential outcomes. I covered tail risk

Quantocracy’s Daily Wrap for 07/14/2020

This is a summary of links featured on Quantocracy on Tuesday, 07/14/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How To Be a Quant Trader – Experiments with @QuantConnect [Robot Wealth]

    This post presents an analysis of the SPY returns process using the QuantConnect research platform. QuantConnect is a strategy development platform that lets you research ideas, import data, create algorithms, and trade in the cloud, all in one place. For this research, Ive used their online research notebook, and it came preinstalled with all the libraries and data (intraday) I needed to

Quantocracy’s Daily Wrap for 07/13/2020

This is a summary of links featured on Quantocracy on Monday, 07/13/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Sixty-Forty Over the Long-Run [Two Centuries Investments]

    Based on many years of reviewing investor portfolios, I concluded that most end up closely resembling a 60% Stocks / 40% Bonds Allocation. Yes, many portfolios also have alternatives, nuanced sub-asset classes, individual security selection, and perhaps some tactical components. But when you look at their returns, a simple 60/40 can usually explain 99% of these more diversified allocations. (This
  • Reducing Estimation Error in Mean-Variance Optimization [Alpha Architect]

    As a general rule, we recommend you kick your spidey senses into high gear anytime there is a geek bearing formulas (especially if they are trying to sell you something). Simple is always a nice cheap default because complexity often leads to confusion, which leans to a need to have an expert, which leads to advice fees, and so the game goes. With that disclosure out of the way, complexity is not
  • Cap-Weighted Benchmarks: Good Momentum Bets? [Factor Research]

    After strong momentum rallies, investors frequently ask if cap-weighted benchmarks are good Momentum bets Factor exposure analysis shows this is not the case Investors should seek smart beta and long-short products if they want Momentum exposure INTRODUCTION Old myths are hard to kill. Good old myths are nearly impossible to kill. Good old myths with elements of pseudo credibility are like
  • Portfolio Optimisation with MlFinLab: Theory-Implied Correlation Matrix [Hudson and Thames]

    Traditionally, correlation matrices have always played a large role in finance. They have been used in tasks ranging from portfolio management to risk management and are calculated based on historical empirical observations. Although they are used so frequently, these correlation matrices often have poor predictive power and prove to be unreliable estimators. Additionally, there are also

Quantocracy’s Daily Wrap for 07/12/2020

This is a summary of links featured on Quantocracy on Sunday, 07/12/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Labeling Momentum & Trends [Tr8dr]

    There are times when need to label a time series, identifying periods of momentum, trend, mean-reversion, etc. Directionaly labeling timeseries has a wide variety of applications: labels can be used for supervised learning analysis of microstructure around larger price moves conditional analysis using label (pattern) sequences testing online signals versus idealized ex-post labeled trend /

Quantocracy’s Daily Wrap for 07/10/2020

This is a summary of links featured on Quantocracy on Friday, 07/10/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Testing expectations [OSM]

    In our last post, we analyzed the performance of our portfolio, built using the historical average method to set return expectations. We calculated return and risk contributions and examined changes in allocation weights due to asset performance. We briefly considered whether such changes warranted rebalancing and what impact rebalancing might have on longer term portfolio returns given the drag

Quantocracy’s Daily Wrap for 07/09/2020

This is a summary of links featured on Quantocracy on Thursday, 07/09/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • March for the Fallen 2020: Sign-Up for The Virtual Version! [Alpha Architect]

    We are going to help make March for the Fallen a virtual event this year (September 26, 2020 at 8am). COVID is bad news, but we can turn lemons into lemonadeand we can still show gratitude for Gold Star Families by breaking into smaller groups and marching outdoors! Weve already have 20 local MFTF groups set up around the country (see below in the google sheet and at the end of this post) 1.
  • SPX Golden Cross History Since 1928 [Quantifiable Edges]

    SPX will post a Golden Cross on Thursday afternoon. A Golden Cross occurs when the 50ma crosses over the 200ma. Having the 50ma above the 200ma is commonly considered a bullish market condition and generally it is. In the 4/2/19 blog post I looked at SPX Golden Crosses dating all the way back to 12/31/1928. I have updated that research tonight with Amibroker Software and Norgate Data. Below is

Quantocracy’s Daily Wrap for 07/08/2020

This is a summary of links featured on Quantocracy on Wednesday, 07/08/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Gold Price Prediction Using Machine Learning In Python [Quant Insti]

    Is it possible to predict where the Gold price is headed? Yes, lets use machine learning regression techniques to predict the price of one of the most important precious metal, the Gold. Machine Learning in Trading We will create a machine learning linear regression model that takes information from the past Gold ETF (GLD) prices and returns a prediction of the Gold ETF price the next day. GLD

Quantocracy’s Daily Wrap for 07/07/2020

This is a summary of links featured on Quantocracy on Tuesday, 07/07/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Market Return Around the Clock [Alpha Architect]

    Get your popcorn ready, the quants are about to do battle As with all good questions in academic research, there are two sides to the story. We recently published Matthew Bartolinis blog post explaining the impacts of trading costs on the Overnight Return Anomaly. This paper, takes the opposing view, providing evidence that equity market returns are positive overnight and close to zero
  • The Livermore System: Part 2 | Trading Strategy (Filters) [Oxford Capital]

    Source: Kaufman, P. J. (2020). Trading Systems and Methods (Chapter 5: The Livermore System). New Jersey: John Wiley & Sons, Inc. Concept: Trading strategy based on Jesse Livermores approach to swing trading with DeMark pivots. Research Goal: Performance verification of Pivot Size and Penetration Filter. Specification: Table 1. Results: Figure 1-2. Trade Entry/Exit: Table1. Portfolio: 42

Quantocracy’s Daily Wrap for 07/06/2020

This is a summary of links featured on Quantocracy on Monday, 07/06/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Beyond Risk Parity: The Hierarchical Equal Risk Contribution Algorithm [Hudson and Thames]

    As diversification is the only free lunch in finance, the Hierarchical Equal Risk Contribution Portfolio (HERC) aims at diversifying capital allocation and risk allocation. Briefly, the principle is to retain the correlations that really matter and once the assets are hierarchically clustered, a capital allocation is estimated. HERC allocates capital within and across the right number of
  • Heads I Win, Tails I Hedge [Flirting with Models]

    For hedging strategies, there is often a trade-off between degree, certainty, and cost. Put options have high certainty and typically offer a high degree of protection, making them costly to hold and roll over the long run. In this note, we briefly explore the application of different tactical signals to a 9-month, 25-delta rolling put strategy in an effort to reduce long-term costs. We find that
  • Factor Olympics 1H 2020 [Factor Research]

    Momentum & Quality are leading the performance scoreboard in 1H 2020 Value & Size generated negative returns, like in recent years Low Volatility failed to preserve capital during the COVID-19 crisis INTRODUCTION We present the performance of five well-known factors on an annual basis for the last 10 years. We only present factors where academic research supports the existence of positive

Quantocracy’s Daily Wrap for 07/05/2020

This is a summary of links featured on Quantocracy on Sunday, 07/05/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • R + Python = Rython [Eran Raviv]

    Enough! Enough with that pointless R versus Python debate. I find it almost as pointless as the Bayesian vs Frequentist dispute. I advocate here what I advocated there (..dont be a Bayesian, nor be a Frequenist, be opportunist). Nowadays even marginally tedious computation is being sent to faster, minimum-overhead languages like C++. So its mainly syntax administration we insist