Writing Algorithms

Applies CAPM model to rank Dow Jones 30 companies.

Combines momentum and mean reversion techniques in the forex markets.

Applies Copula and Cointergration method to pairs trading.

A demonstration of dynamic breakout II strategy.

A demontration of Dual Thrust Intraday strategy.

Applies regression method to predict the return from the stock market and compare it to the short-term U.S. T-bill rate.

A high frequency pairs trading algorithm based on cointegration.

Applies high frequency filter to the momentum strategy.

MorningStar Fundamental factors universe selection algorithm.

A short term reversal algorithm which gives the opposite signal by analyzing recent period price action.

A basic monthly rebalance long short algorithm based on fundamental factors.

Selects ETFs over ten-month moving average and assigns an equally weighted allocation.

Source: Quantpedia

Selects ETFs in different asset classes with the highest momentum and assigns an equally weighted allocation.

Source: Quantpedia

Constructs a long/short portfolio based on trailing residual momentum normalized by its standard deviation

Source: Quantpedia

Selects ETFs in different sectors with the highest momentum and assigns an equally weighted allocation.

Source: Quantpedia

Buy SPY ETF at its closing price and sell it at the opening each day.

Source: Quantpedia

Goes long the currency with the highest central bank interest rate and goes short the currency with the lowest interest rate.

Source: Quantpedia

Constructs equally weighted portfolios by selecting stocks with the lowest volatility in the past one year.

Source: Quantpedia

Goes long currencies with strongest 12 month momentum against USD and goes short currencies with the lowest 12 month momentum against USD.

Source: Quantpedia

Looks for the security that minimizes the sum of squared deviations and long-short position is opened when pair prices have diverged by multiple of standard deviations.

Source: Quantpedia

Goes long stocks with the lowest return in the previous month and goes short stocks with the greatest return from the previous month.

Source: Quantpedia

Goes long stocks with the best 12-month momentum in the large-cap universe.

Source: Quantpedia

Goes long stocks with the best 12-month momentum in the country equity indexes ETFs.

Source: Quantpedia

Goes long country equity indexes ETFs with the worst 36-month return and short ETFs with the best 36-month return.

Source: Quantpedia

Goes long stocks with the lowest turnover and short on stocks with the highest turnover from the lowest market-cap quartile.

Source: Quantpedia

Sells at-the-money straddle with one month until maturity and buys an offsetting 15% out-of-the-money puts each month.

Source: Quantpedia

Goes long commodity futures with the highest momentum and short on futures with the lowest momentum.

Source: Quantpedia

Goes long stocks with the lowest market capitalization and rebalances the portfolio once a year.

Source: Quantpedia

Goes long asset with better performance over the last period and rebalances portfolio every quarter.

Source: Quantpedia

Buys each month the 20% of commodities with the highest roll-returns and shorts the 20% of commodities with the lowest roll-returns and holds the long-short positions for one month.

Source: Quantpedia

Portfolios are formed based on roll returns and the algorithm goes long and short contracts with the highest and lowest one-month performance.

Source: Quantpedia

Quintile portfolios are formed based on the Book-to-Market ratio and the highest quintile is held for one year.

Source: Quantpedia

Goes long gold when the Fed model shows that the market is undervalued (the earnings yield is higher than the bond yield and their ratio is at least 2).

Source: Quantpedia

Buys SPY the day before the end of the month and liquidates position on 3rd trading day of new month.

Source: Quantpedia

Goes long stocks with the decreasing return from the winner group and short stocks with the increasing return from the loser group.

Source: Quantpedia

Identifies the price divergence from two highly correlated country ETFs and takes a market neutral position.

Source: Quantpedia

Creates long-short positions of growth and value stocks based on the investment sentiment.

Source: Quantpedia

Creates long-short positions of stocks based on the annual change of their total assets.

Source: Quantpedia

Goes long and short stocks with the highest and lowest six-month momentum respectively if the previous 12 months return on the broad market index was positive.

Source: Quantpedia

Decile portfolios are formed based on balance sheet based accruals and highest decile is shorted while lowest decile is bought for a year.

Source: Quantpedia

Forms a long-short portfolio of asset management firms based on trailing rate of change and nearness to trailing high.

Source: Quantpedia

Goes long style index ETF with the highest 12-month momentum and short ETF with the lowest 12-month momentum.

Source: Quantpedia

Goes long the spread if the spread is below 20-day moving average and short if the spread is above 20-day moving average.

Source: Quantpedia

Tercile portfolios are formed based on momentum and the best performing portfolio is held.

Source: Quantpedia

Goes long S&P 100 index ETF during option expiration week and stays in cash during other days.

Source: Quantpedia

Goes long stocks with high earnings quality and short stocks with low earnings quality based on composite factor score.

Source: Quantpedia

Invests into small cap stocks at the beginning of each January and stays invested in large cap stocks for rest of the year.

Source: Quantpedia

Goes long on stocks from the highest performing quintile from the highest volatility group and short on stocks from the lowest performing quintile from the highest volatility group.

Source: Quantpedia

Goes long on stocks with highest ROA and short stocks with the lowest ROA from each market capitalization group.

Source: Quantpedia

Invested in equity market with ETF only if January return is positive otherwise switch investments to T-Bills.

Source: Quantpedia

Goes long in emerging market index ETF 7 days before the new moon and switch to a short position on emerging market index ETF 7 days before the full moon.

Source: Quantpedia

Goes long on equity index ETF if the VIX is in the highest percentile short if VIX is in the lowest percentile in the last two-year history.

Source: Quantpedia

Goes long stocks with the highest volume from the top momentum decile and short stocks with the highest volume from the bottom momentum decile.

Source: Quantpedia

Goes long (short) on futures from the high-volume, low-open interest group with the lowest (greatest) returns in the previous week.

Source: Quantpedia

Invests in equity market 2 days preceding holiday days and stays in cash during the other trading days.

Source: Quantpedia

Goes long stocks with the bottom beta and short stocks with the top beta, securities are weighted by the ranked betas.

Source: Quantpedia

Buys or sells the nearest VIX futures based on the daily roll and hedge against the open positions with E-mini S&P500 futures.

Source: Quantpedia

Reviews the returns from last January, going long on the top 10% winners and short the bottom 10%.

Source: Quantpedia

Goes long in the 10 stocks with the highest performance and goes short in the 10 stocks with the lowest performance in the previous one year.

Source: Quantpedia

Invests in the cheapest 33% of country ETFs according to CAPE ratios.

Source: Quantpedia

Goes long on the low-beta portfolio and short on the high-beta portfolio in country indexes ETFs.

Source: Quantpedia

Invests in stocks with low P/E ratio.

Stock selecting strategy based on Fama-French Five Factors Model.

Source: NYU

Apply statistical arbitrage to take advantage of pricing inefficiencies in stocks.

Source: NYU

Stock selection strategy that calculates expected idiosyncratic skewness using Fama-French three-factor model, sorts stocks based on the calculated skewness, and longs the bottom 5%.

Source: NYU

A strategy based on asymmetric tail risks and excess returns in forex markets.

Source: NYU

A strategy that takes long and short positions based on historical same-calendar month returns

Source: NYU

Stock selection strategy that calculates the unexpected earnings, standardizes the unexpected earnings, goes long on the top 5%, and rebalances the portfolio monthly.

Source: NYU

A momentum strategy based on quarterly returns and earnings growth

Source: NYU

An advanced momentum strategy that modifies the basic momentum strategies by introducing Baltas and Kosowski weights and rebalances the portfolio monthly. The new weighing scheme incorporates trend strength into the trading signal, uses an efficient volatility estimator, and adds a dynamic leverage mechanism.

Source: NYU

A simple trend following strategy on commodities futures.

Source: NYU

Applying a Temporal Convolutional Neural Network to forecasting future stock prices.

Source: Tampere University

We apply Simple Moving Averages to manage the risk of holding leveraged ETFs in an attempt to beat the S&P500

Source: The Lead-Lag Report

A techincal indicator crossover strategy trading the largest energy companies.

Source: SSRN

A momentum strategy based on returns of the market open

Source: NYU

A strategy that tracks the price paths of two correlated ETFs and takes advantage of mis-pricings that arise when the price paths diverge

Source: SSRN

Mathematically Deriving the Optimal Entry and Liquidation Values of a Pairs Trading Process

Source: arXiv

Applying G-Score Investing to Invest in a Portfolio of Technology Stocks

Source: SSRN

Forecasting EURJPY prices with an SVM Wavelet model

Source: Academia

Forecasts future intraday returns with a gradient boosting model trained on technical indicators

Source: arXiv

Analyzes the news releases of drug manufacturers and places intraday trades for the stocks with positive news.

Source: arXiv

Forecasts the next day's return of technology stocks by fitting a gaussian naive bayes model to the historical returns of the technology sector constituents.

Source: Academia