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Biography

Quantitative Developer at QuantConnect. Studied Computer Science and Finance at the University of Lethbridge. Competitor in the 2020-1 Rotman International Trading Competitions. See my latest posts at derekmelchin.com.

Activity on QuantConnect

We are pioneering the radical future for open-source quant finance. QuantConnect is the world's largest quant community, empowering 220,000 quants with a framework, data, and infrastructure for their investments.


Public Backtests (2212)

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Creative Yellow Green Salmon

43.419Net Profit

9.285PSR

0.254Sharpe Ratio

-0.021Alpha

0.84Beta

8.337CAR

22.8Drawdown

0Loss Rate

6Parameters

1Security Types

0.302Sortino Ratio

1129Tradeable Dates

3Trades

0.041Treynor Ratio

0Win Rate

Creative Yellow Ant

1.344Net Profit

38.742PSR

-6.068Sharpe Ratio

-0.053Alpha

0.053Beta

0.931CAR

1.2Drawdown

0Loss Rate

4Parameters

1Security Types

-6.225Sortino Ratio

360Tradeable Dates

1Trades

-0.912Treynor Ratio

0Win Rate

Sleepy Yellow Beaver

6.546Net Profit

15.74PSR

-0.191Sharpe Ratio

-0.08Alpha

0.635Beta

4.309CAR

17Drawdown

0Loss Rate

7Parameters

1Security Types

-0.187Sortino Ratio

375Tradeable Dates

3Trades

-0.031Treynor Ratio

0Win Rate

Crawling Sky Blue Pelican

15.702Net Profit

27.574PSR

0.182Sharpe Ratio

-0.048Alpha

0.739Beta

10.19CAR

17.7Drawdown

0Loss Rate

6Parameters

1Security Types

0.197Sortino Ratio

375Tradeable Dates

3Trades

0.03Treynor Ratio

0Win Rate

year_start

43.092Net Profit

37.298PSR

0.646Sharpe Ratio

0.014Alpha

1.54Beta

26.902CAR

31.4Drawdown

25Loss Rate

5Parameters

1Security Types

0.747Sortino Ratio

0Tradeable Dates

21Trades

0.104Treynor Ratio

75Win Rate


Community

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Derek left a comment in the discussion How to pull equity curve/portfolio equity value from backtest

We updated the tutorial here to fix the code:...

20 days ago

Derek left a comment in the discussion Research book not saved

CTRL + S

3 months ago

Derek left a comment in the discussion BTCUSD, Minute The issue starts from Jun 16th, 2024 12:00 AM; and continues until Sep 5th, 2024 12:00 AM

Same issue with ETH, LINK, and DOGE

3 months ago

Derek left a comment in the discussion How to get quantconnect data inside a custom data class?

https://www.quantconnect.com/docs/v2/writing-algorithms/key-concepts/globals-and-statics#03-API-Acce...

4 months ago

Derek left a comment in the discussion Reimagining the 60-40 Portfolio in an Era of AI and Falling Rates

To check the asset classes that each brokerage supports, see this page:...

5 months ago

Creative Yellow Green Salmon

43.419Net Profit

9.285PSR

0.254Sharpe Ratio

-0.021Alpha

0.84Beta

8.337CAR

22.8Drawdown

0Loss Rate

6Parameters

1Security Types

0.302Sortino Ratio

1129Tradeable Dates

3Trades

0.041Treynor Ratio

0Win Rate

Creative Yellow Ant

1.344Net Profit

38.742PSR

-6.068Sharpe Ratio

-0.053Alpha

0.053Beta

0.931CAR

1.2Drawdown

0Loss Rate

4Parameters

1Security Types

-6.225Sortino Ratio

360Tradeable Dates

1Trades

-0.912Treynor Ratio

0Win Rate

Sleepy Yellow Beaver

6.546Net Profit

15.74PSR

-0.191Sharpe Ratio

-0.08Alpha

0.635Beta

4.309CAR

17Drawdown

0Loss Rate

7Parameters

1Security Types

-0.187Sortino Ratio

375Tradeable Dates

3Trades

-0.031Treynor Ratio

0Win Rate

Crawling Sky Blue Pelican

15.702Net Profit

27.574PSR

0.182Sharpe Ratio

-0.048Alpha

0.739Beta

10.19CAR

17.7Drawdown

0Loss Rate

6Parameters

1Security Types

0.197Sortino Ratio

375Tradeable Dates

3Trades

0.03Treynor Ratio

0Win Rate

year_start

43.092Net Profit

37.298PSR

0.646Sharpe Ratio

0.014Alpha

1.54Beta

26.902CAR

31.4Drawdown

25Loss Rate

5Parameters

1Security Types

0.747Sortino Ratio

0Tradeable Dates

21Trades

0.104Treynor Ratio

75Win Rate

month_start

28.533Net Profit

27.586PSR

0.417Sharpe Ratio

-0.04Alpha

1.458Beta

18.164CAR

31.6Drawdown

34Loss Rate

5Parameters

1Security Types

0.48Sortino Ratio

0Tradeable Dates

147Trades

0.068Treynor Ratio

66Win Rate

week_start

35.191Net Profit

33.118PSR

0.535Sharpe Ratio

-0.008Alpha

1.4Beta

22.199CAR

32Drawdown

33Loss Rate

5Parameters

1Security Types

0.64Sortino Ratio

0Tradeable Dates

574Trades

0.09Treynor Ratio

67Win Rate

every_day

17.104Net Profit

19.876PSR

0.215Sharpe Ratio

-0.078Alpha

1.361Beta

11.069CAR

31.2Drawdown

38Loss Rate

5Parameters

1Security Types

0.245Sortino Ratio

0Tradeable Dates

1819Trades

0.038Treynor Ratio

62Win Rate

Hyper Active Orange Elephant

-7.51Net Profit

0PSR

-1.243Sharpe Ratio

-0.034Alpha

0.066Beta

-0.799CAR

14.3Drawdown

-0.07Loss Rate

12Parameters

0Security Types

2446Tradeable Dates

10686Trades

-0.437Treynor Ratio

0.07Win Rate

Well Dressed Light Brown Leopard

-32.248Net Profit

0.808PSR

-0.867Sharpe Ratio

-0.086Alpha

-1.538Beta

-24.088CAR

37.7Drawdown

100Loss Rate

4Parameters

1Security Types

-1.06Sortino Ratio

354Tradeable Dates

3Trades

0.133Treynor Ratio

0Win Rate

Jumping Fluorescent Orange Rhinoceros

1.241Net Profit

35.991PSR

-6.07Sharpe Ratio

-0.053Alpha

0.053Beta

0.877CAR

1.2Drawdown

0Loss Rate

4Parameters

1Security Types

-6.247Sortino Ratio

354Tradeable Dates

1Trades

-0.92Treynor Ratio

0Win Rate

Jumping Asparagus Lion

4368.38Net Profit

38.76PSR

1.228Sharpe Ratio

0.699Alpha

1.5Beta

80.85CAR

84.3Drawdown

49Loss Rate

55Parameters

2Security Types

1.877Sortino Ratio

1996Tradeable Dates

478Trades

0.561Treynor Ratio

51Win Rate

Virtual Orange Sardine

3464.14Net Profit

33.947PSR

1.164Sharpe Ratio

0.666Alpha

1.514Beta

74.615CAR

84.9Drawdown

51Loss Rate

59Parameters

2Security Types

1.76Sortino Ratio

1996Tradeable Dates

476Trades

0.536Treynor Ratio

49Win Rate

Jumping Orange Giraffe

0.618Net Profit

44.235PSR

0.326Sharpe Ratio

1.445Alpha

-2.461Beta

13.298CAR

7Drawdown

0Loss Rate

9Parameters

0Security Types

12Tradeable Dates

2Trades

-0.043Treynor Ratio

0Win Rate

Formal Magenta Hamster

6.489Net Profit

98.67PSR

11.695Sharpe Ratio

0.994Alpha

0.956Beta

257.866CAR

3Drawdown

0Loss Rate

6Parameters

0Security Types

12Tradeable Dates

2Trades

1.584Treynor Ratio

0Win Rate

Virtual Tan Owlet

4.27Net Profit

100PSR

14.698Sharpe Ratio

0.868Alpha

-0.095Beta

133.461CAR

0.7Drawdown

0Loss Rate

8Parameters

0Security Types

12Tradeable Dates

2Trades

-8.626Treynor Ratio

0Win Rate

Adaptable Fluorescent Orange Giraffe

-7.51Net Profit

0PSR

-1.243Sharpe Ratio

-0.034Alpha

0.066Beta

-0.799CAR

14.3Drawdown

-0.07Loss Rate

12Parameters

0Security Types

2446Tradeable Dates

10686Trades

-0.437Treynor Ratio

0.07Win Rate

Dancing Orange Dinosaur

-7.51Net Profit

0PSR

-1.243Sharpe Ratio

-0.034Alpha

0.066Beta

-0.799CAR

14.3Drawdown

-0.07Loss Rate

12Parameters

0Security Types

2446Tradeable Dates

10686Trades

-0.437Treynor Ratio

0.07Win Rate

Square Black Scorpion

8.419Net Profit

0.637PSR

-1.033Sharpe Ratio

-0.021Alpha

0.049Beta

0.834CAR

3.5Drawdown

-0.08Loss Rate

19Parameters

0Security Types

3552Tradeable Dates

3936Trades

-0.363Treynor Ratio

0.08Win Rate

Virtual Black Beaver

-0.461Net Profit

0.008PSR

-1.015Sharpe Ratio

-0.029Alpha

0.078Beta

-0.047CAR

7.1Drawdown

-0.07Loss Rate

16Parameters

0Security Types

2446Tradeable Dates

10540Trades

-0.302Treynor Ratio

0.06Win Rate

Emotional Tan Cat

-0.461Net Profit

0.008PSR

-1.015Sharpe Ratio

-0.029Alpha

0.078Beta

-0.047CAR

7.1Drawdown

-0.07Loss Rate

16Parameters

0Security Types

2446Tradeable Dates

10540Trades

-0.302Treynor Ratio

0.06Win Rate

Hyper Active Light Brown Armadillo

2.113Net Profit

0.036PSR

-1.32Sharpe Ratio

-0.025Alpha

0.038Beta

0.215CAR

5.9Drawdown

-0.09Loss Rate

17Parameters

0Security Types

3552Tradeable Dates

4060Trades

-0.575Treynor Ratio

0.08Win Rate

Smooth Tan Mosquito

-7.51Net Profit

0PSR

-1.244Sharpe Ratio

-0.034Alpha

0.066Beta

-0.799CAR

14.3Drawdown

-0.07Loss Rate

17Parameters

0Security Types

3552Tradeable Dates

10686Trades

-0.437Treynor Ratio

0.07Win Rate

Alert Green Bear

80.541Net Profit

4.266PSR

0.27Sharpe Ratio

-0.001Alpha

0.326Beta

6.257CAR

18.8Drawdown

-2.86Loss Rate

14Parameters

0Security Types

3552Tradeable Dates

58Trades

0.071Treynor Ratio

5.3Win Rate

Determined Green Bison

757.079Net Profit

67.463PSR

1.179Sharpe Ratio

0.279Alpha

-0.064Beta

42.985CAR

25.2Drawdown

-0.32Loss Rate

45Parameters

0Security Types

1549Tradeable Dates

9128Trades

-4.292Treynor Ratio

0.61Win Rate

Dancing Green Kangaroo

10879.371Net Profit

64.409PSR

1.582Sharpe Ratio

1.031Alpha

-0.192Beta

118.587CAR

59Drawdown

-0.81Loss Rate

28Parameters

0Security Types

1550Tradeable Dates

11198Trades

-5.294Treynor Ratio

1.62Win Rate

Energetic Red Salamander

51.754Net Profit

1.639PSR

0.244Sharpe Ratio

0.116Alpha

-0.155Beta

7.189CAR

43.5Drawdown

-0.94Loss Rate

25Parameters

0Security Types

1549Tradeable Dates

5765Trades

-0.676Treynor Ratio

1.81Win Rate

Hipster Brown Armadillo

3633.461Net Profit

43.031PSR

1.225Sharpe Ratio

0.767Alpha

-0.329Beta

82.667CAR

58.7Drawdown

-2.2Loss Rate

24Parameters

0Security Types

1549Tradeable Dates

3050Trades

-2.254Treynor Ratio

4.29Win Rate

Well Dressed Black Kangaroo

212.837Net Profit

70.75PSR

1.015Sharpe Ratio

0.123Alpha

-0.043Beta

20.907CAR

14.5Drawdown

-0.47Loss Rate

21Parameters

0Security Types

1510Tradeable Dates

2679Trades

-2.755Treynor Ratio

0.91Win Rate

Formal Green Falcon

3633.461Net Profit

43.031PSR

1.225Sharpe Ratio

0.767Alpha

-0.329Beta

82.667CAR

58.7Drawdown

-2.2Loss Rate

25Parameters

0Security Types

1549Tradeable Dates

3050Trades

-2.254Treynor Ratio

4.29Win Rate

Derek left a comment in the discussion How to pull equity curve/portfolio equity value from backtest

We updated the tutorial here to fix the code:...

20 days ago

Derek left a comment in the discussion Research book not saved

CTRL + S

3 months ago

Derek left a comment in the discussion BTCUSD, Minute The issue starts from Jun 16th, 2024 12:00 AM; and continues until Sep 5th, 2024 12:00 AM

Same issue with ETH, LINK, and DOGE

3 months ago

Derek left a comment in the discussion How to get quantconnect data inside a custom data class?

https://www.quantconnect.com/docs/v2/writing-algorithms/key-concepts/globals-and-statics#03-API-Acce...

4 months ago

Derek left a comment in the discussion Reimagining the 60-40 Portfolio in an Era of AI and Falling Rates

To check the asset classes that each brokerage supports, see this page:...

5 months ago

Derek left a comment in the discussion Opening Range Breakout for Stocks in Play

... and to increase the execution speed.

5 months ago

Derek submitted the research Reimagining the 60-40 Portfolio in an Era of AI and Falling Rates

Abstract

During the initial outbreak of the COVID March 2020 the safety that the 60-40 stock-bonds portfolio offered seemed to break down, leading investors to seek new uncorrelated assets to hedge portfolios in times of crisis. This micro-study aims to determine the new 60-40 portfolio, as the interest from idle cash starts to diminish. It uses machine learning to select and weight portfolio assets based on the magnitude of the predicted returns. The strategy uses machine learning and economic factors to manage a portfolio of risk-on and risk-off assets. The algorithm rebalances the portfolio at the start of every month. During each rebalance, it allocates a portion of the portfolio to each asset the regression model predicts will have a positive return over the following month, scaling the positions based on the magnitude of the predicted returns.

8 months ago

Derek submitted the research Bitcoin as a Leading Indicator

Abstract

This research explores Bitcoin's role as a leading indicator for US Equity market turbulence. Bitcoin, classically a risk-on asset that trades 24/7, can signal crises in other markets due to its liquidity and volatility. The study demonstrates a trading strategy using the LEAN engine, rotating capital between US Equities and cash based on Bitcoin's price action. When Bitcoin drops two standard deviations below its two-year moving average, the strategy shifts to cash, enhancing risk-adjusted returns for long-term investors.

8 months ago

Derek submitted the research Copying Congress Trades

Abstract

This research explores a trading algorithm that mimics trades made by U.S. Congress members, leveraging their privileged access to market-moving information. The Stop Trading on Congressional Knowledge (STOCK) Act mandates disclosure of such trades, enabling public access. Using the Quiver Quantitative dataset, the algorithm employs an inverse-volatility weighting scheme to balance risk across assets, limiting individual asset exposure to 10% to mitigate concentration risk. By forming a portfolio based on these disclosures, the strategy aims to capitalize on the informational advantage indirectly.

9 months ago

Derek submitted the research Automating the Wheel Strategy

Abstract

The Wheel strategy is a popular options trading approach that generates steady income from equities intended for long-term holding. It involves selling cash-secured puts and covered calls. Initially, out-of-the-money (OTM) puts are sold until shares are assigned. Once shares are held, OTM covered calls are sold until exercised. This strategy generates income through premiums from option sales. The underlying equity should be one the trader is comfortable owning. For implementation, SPY was used as the underlying asset, chosen for its stability and long-term hold potential. The strategy offers built-in risk management and downside protection by effectively managing option assignments and sales.

9 months ago

Derek submitted the research Probabilistic Sharpe Ratio

Abstract

The Probabilistic Sharpe Ratio (PSR) is a method for evaluating investment performance that takes into account the non-normality of returns. The traditional Sharpe ratio assumes that returns are normally distributed, which can lead to misleading results for strategies with non-normal returns. The PSR addresses this limitation by considering the distribution of returns and estimating the probability that a given Sharpe ratio is a result of skill rather than luck. This provides a more accurate measure of a strategy's performance and allows for better comparisons between different strategies. The PSR is particularly useful for strategies with non-normal returns, as it takes into account the impact of skewness and kurtosis on the statistical significance of the observed Sharpe ratio.

10 months ago

Derek submitted the research Head & Shoulders TA Pattern Detection

Abstract

This discussion focuses on the detection of the head and shoulders pattern in technical analysis. While technical analysis traders commonly use graphical patterns to identify trading opportunities, quant traders tend to overlook them due to subjectivity and difficulty in accurate detection. However, this tutorial presents a method to programmatically detect the head and shoulders pattern in an event-driven trading algorithm. The algorithm achieves greater risk-adjusted returns than the benchmarks during the backtesting period. The head and shoulders pattern consists of two shoulders, a tall head, and a neckline. It is believed to signal a bullish-to-bearish trend reversal. Further research can include testing other technical patterns, adjusting algorithm parameters, exploring new position sizing techniques, implementing different exit strategies, and incorporating risk management for corporate actions.

1 years ago

Derek submitted the research Futures Fast Trend Following, with Trend Strength

Abstract

This research focuses on Futures Fast Trend Following strategies that can be applied to both long and short positions, taking into account the strength of the trend. The purpose of the research is to explore the effectiveness of these strategies and their potential implications for trading in the futures market. The research utilizes various methods to analyze historical data and identify trends, and the key findings highlight the profitability and consistency of the trend following strategies. The implications of the research suggest that these strategies can be valuable tools for traders seeking to capitalize on trends in the futures market.

1 years ago

Derek submitted the research Combined Carry and Trend

Abstract

This research is a re-creation of strategy #11 from Advanced Futures Trading Strategies (Carver, 2023) that combines carry and trend strategies in futures trading. The algorithm incorporates exponential moving average crossover (EMAC) trend forecasts and carry forecasts to form a diversified portfolio. The results show that using both styles of strategies can improve risk-adjusted returns. Additionally, the research provides a background on how carry returns are calculated for different asset classes and how the strategy calculates and smooths carry from different future contracts.

1 years ago

Derek submitted the research Sector Rotation Based On News Sentiment

Abstract

Abstract: This tutorial explores a sector rotation strategy based on news sentiment using the LEAN algorithmic trading engine and datasets from the QuantConnect Dataset Market. The strategy involves monitoring the news sentiment for 25 different sector Exchange Traded Funds (ETFs) and periodically rebalancing the portfolio to maximize exposure to sectors with the highest public sentiment. Backtesting results demonstrate that the strategy consistently outperforms benchmark approaches. The tutorial provides details on universe selection, implementation, and presents equity curves and Sharpe ratios for different versions of the strategy and benchmarks. To replicate the results, users are encouraged to clone and backtest each algorithm.

2 years ago

Derek submitted the research Country Rotation Based On Regulatory Alerts Sentiment

Abstract

Abstract: This tutorial explores four alternative data strategies that utilize the US Regulatory Alerts dataset to make trading decisions. The strategies include capitalizing on movement in the healthcare sector in response to FDA announcements, capturing momentum in the Bitcoin-USD trading pair based on new Crypto regulations, exploiting trading patterns in the SPY based on specific regulatory alerts, and a country rotation strategy using NLP to detect sentiment in country ETFs. The results show that all four strategies outperform their respective benchmarks. The tutorial also discusses NLP and its role in trading strategies, as well as the implementation of the four strategies using the LEAN algorithmic trading engine.

2 years ago

Derek submitted the research Detecting Impactful News In ETF Constituents

Abstract

Abstract: This tutorial focuses on utilizing natural language processing (NLP) to detect impactful news in ETF constituents. Building upon a previous NLP strategy, we monitor the Tiingo News Feed to determine intraday news sentiment of the largest constituents in the Nasdaq-100 index, while avoiding look-ahead bias. The results indicate that this strategy has experienced lower risk-adjusted returns compared to the QQQ ETF over the past two years. The tutorial discusses the implementation of this strategy as a framework algorithm using the LEAN trading engine, including universe selection and portfolio construction. Backtesting results show a Sharpe ratio of -0.659, with comparisons to other benchmarks provided.

2 years ago

Derek started the discussion Plot Backtest Trade Fills in the Research Environment

Hi everyone!

2 years ago

Derek started the discussion New Insight Manager and Updates for Risk Management Models

Hi everyone,

2 years ago

Derek submitted the research Momentum In Mutual Fund Returns

Abstract

This discussion focuses on the momentum in mutual fund returns and the use of net asset value (NAV) as a predictor of future returns. The study suggests that historical returns and the proximity of NAV to a previous high can provide predictive power. The tutorial uses asset management firms' share prices as a proxy for fund performance and NAV. The performance of this trading strategy is compared to buying-and-holding the S&P 500 index ETF. The strategy generally has a lower Sharpe ratio than the benchmark, except during the 2020 stock market crash where it significantly outperformed with a Sharpe ratio of 9.3. The strategy also demonstrates more consistent returns compared to the benchmark across different testing periods.

4 years ago

Derek submitted the research Intraday ETF Momentum

Abstract

This tutorial implements an intraday momentum strategy for trading actively traded ETFs. The strategy predicts the sign of the last half-hour return based on the return generated in the first half-hour of the trading day. The algorithm is a recreation of the research conducted by Gao, Han, Li, and Zhou (2017), which found that this momentum pattern is statistically and economically significant. The tutorial provides background information on the characteristics of the opening and closing periods of trading, as well as the selection of ETFs for the strategy. The conclusion states that the momentum pattern produces lower returns compared to the S&P 500 benchmark, but outperforms the benchmark during the downfall of the 2020 crash.

4 years ago

Derek submitted the research Ichimoku Clouds In The Energy Sector

Abstract

4 years ago

Derek submitted the research Intraday Arbitrage Between Index ETFs

Abstract

4 years ago

Derek submitted the research Gradient Boosting Model

Abstract

This tutorial focuses on training a Gradient Boosting Model (GBM) to forecast intraday price movements of the SPY ETF using technical indicators. The implementation is based on research by Zhou et al (2013), who found that a GBM produced a high annualized Sharpe ratio. However, the tutorial's research shows that the model underperforms the SPY with its current parameter set during a 5-year backtest. The tutorial concludes by suggesting potential areas of further research to improve the model's performance. The GBM is trained by iteratively building regression trees to predict pseudo-residuals and making predictions based on the learning rate and regression tree outputs. Technical indicator values are used as inputs, and the mean squared error loss function is used to assess the model's performance.

4 years ago

Derek submitted the research Using News Sentiment To Predict Price Direction Of Drug Manufacturers

Abstract

Abstract: This tutorial explores the use of news sentiment to predict the price direction of drug manufacturers. By implementing an intraday strategy, we aim to capitalize on the upward drift in stock prices following positive news releases. Our findings show that combining this effect with the day-of-the-week anomaly can lead to profitable trading during the 2020 stock market crash. However, our algorithm underperforms the S&P 500 market index ETF, SPY, during the same period. The algorithm is inspired by the work of Isah, Shah, & Zulkernine (2018). We conclude that while the sentiment analysis strategy may not provide accurate results in the US drug manufacturing industry, profitability can be achieved by restricting trading to the most profitable day of the week. The strategy produces a negative Sharpe ratio of -1.

4 years ago

Derek submitted the research Gaussian Naive Bayes Model

Abstract

Abstract: This discussion focuses on the Gaussian Naïve Bayes (GNB) model and its application in forecasting the daily returns of stocks in the technology sector. The GNB model is trained using historical returns of the sector and compared to the performance of the SPY ETF over a 5-year backtest and during the 2020 stock market crash. The implementation of the GNB model shows a higher Sharpe ratio and lower variance compared to the SPY ETF. The algorithm used in this discussion is based on previous research and follows the principles of Naïve Bayes models. The GNB model assumes independence and normal distribution of feature vectors.

4 years ago

Derek submitted the research Sortino Portfolio Optimization with Alpha Streams Algorithms

Abstract

QuantConnect provides trading infrastructure and data for quants to develop and deploy algorithmic trading strategies. They offer the Alpha Streams platform for quants to license their proprietary signals to investors. To assist investors in analyzing the performance of these signals, QuantConnect has released a new notebook that determines the optimal portfolio weights for each alpha, maximizing the portfolio's Sortino ratio. The Sortino ratio measures the strategy's average daily return in excess of a risk-free rate, divided by the standard deviation of negative daily returns. The notebook uses a walk-forward approach to avoid bias and overfitting, and the optimization is done on a rolling monthly basis.

4 years ago

Derek started the discussion Strategy Library Addition: Intraday ETF Momentum

Hi everyone,

4 years ago

Derek started the discussion Strategy Library Addition: Momentum in Mutual Fund Returns

Hi everyone,

4 years ago

Derek started the discussion Strategy Library Addition: Gaussian Naive Bayes Model

Hi everyone,

4 years ago

Derek submitted the research Residual Momentum

Abstract

Residual momentum is a strategy where stocks with higher monthly residual returns outperform those with lower returns. It has been found to have less exposure to Fama-French factors, higher Sharpe ratios, and better out-of-sample performance compared to total return momentum strategies. Residual momentum is also more stable throughout the business cycle and tends to underperform during trending periods but outperform during reverting periods. This strategy is less concentrated in small-cap stocks, leading to lower trading costs and minimizing the impact of tax-loss selling. The algorithm imports custom data, selects a universe of stocks based on fundamental data and market cap, and rebalances the portfolio monthly by longing the top 10% and shorting the bottom 10% of stocks based on their scores.

5 years ago

QuantConnect Boot Camp

QuantConnect Boot Camp is a comprehensive educational program designed to help individuals learn algorithmic trading and quantitative finance using the QuantConnect platform.

Get this certificate by completing QuantConnect Boot Camp Courses