Alethea Lin
Quant
Date Joined
5th July, 2019
Bootcamp progress
11% Complete
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2019-07-17 15:14:14
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2019-08-20 20:32:08
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2019-08-06 18:21:32
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2019-07-05 16:34:59
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Receive at least 10 upvotes from different users in the community.
2019-08-30 02:13:48
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2019-07-05 22:06:55
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Public Backtests (19)
View More104.967Net Profit
0.266Sharpe Ratio
0.06Alpha
0.387Beta
3.366CAR
83.3Drawdown
67Loss Rate
0Parameters
1Security Types
-0.0905Sortino Ratio
7914Tradeable Dates
753Trades
0.238Treynor Ratio
33Win Rate
104.967Net Profit
0.266Sharpe Ratio
0.06Alpha
0.387Beta
3.366CAR
83.3Drawdown
67Loss Rate
0Parameters
1Security Types
-0.0905Sortino Ratio
7914Tradeable Dates
753Trades
0.238Treynor Ratio
33Win Rate
0Parameters
1Security Types
7914Tradeable Dates
0Parameters
1Security Types
7914Tradeable Dates
0Net Profit
0Sharpe Ratio
0Alpha
0Beta
0CAR
0Drawdown
0Loss Rate
2Parameters
1Security Types
0Sortino Ratio
127Tradeable Dates
0Trades
0Treynor Ratio
0Win Rate
Community
View MoreAlethea submitted the research Price Earnings Anomaly
Abstract
The Price to Earnings (P/E) ratio is commonly used by investors to determine the valuation of a company's stock. This discussion explores the Price Earnings Anomaly and its impact on portfolio performance. The strategy involves selecting the 10 stocks with the lowest P/E ratio at the beginning of each year and investing an equal amount of capital in each stock. The portfolio significantly outperforms the benchmark, S&P 500, during the three and a half year backtest period. The strategy also considers the size factor, where small market capitalization stocks are found to outperform large market capitalization stocks. This discussion provides insight into the potential benefits of incorporating the P/E ratio and size factor into investment strategies.
Alethea submitted the research Improved Momentum Strategy On Commodities Futures
Abstract
Abstract: This tutorial discusses an improved momentum strategy called TSMOM-CF that addresses weaknesses in traditional time-series momentum strategies. TSMOM-CF incorporates trend strength, uses an efficient volatility estimator, and adds a dynamic leverage mechanism to improve performance. The traditional strategy's oversimplified trading signal, inefficient volatility estimator, and fixed portfolio allocation mechanism are overcome in TSMOM-CF. The paper "Demystifying Time-Series Momentum Strategies: Volatility Estimators, Trading Rules and Pairwise Correlations" by Nick Baltas and Robert Kosowski serves as the basis for the implementation. TSMOM-CF is compared to the basic momentum strategy in the Momentum Effect in Commodities Futures strategy library. The tutorial provides a detailed explanation of the modifications and their impact on performance.
Alethea submitted the research Commodities Futures Trend Following
Abstract
Abstract: This tutorial explores the implementation of a trend following strategy on commodities futures based on a 2014 paper titled "Two Centuries Of Trend Following". The paper highlights the existence of trends in financial markets, which contradicts the efficient market hypothesis. The strategy involves buying when prices go up and selling when prices go down. The paper extends the backtest period of trend following strategies to two centuries and demonstrates statistically significant excess returns on commodities, currencies, stock indices, and bonds. The tutorial focuses on implementing the strategy on a well-balanced commodities pool consisting of 7 representative contracts. The results of the backtest period show a lower Sharpe ratio compared to SPY's Sharpe ratio, indicating potential limitations of the trend following strategy in this context.
Alethea left a comment in the discussion Noob: Struggling to build Lean with MonoDevelop
Hi DaveGilbert,
104.967Net Profit
0.266Sharpe Ratio
0.06Alpha
0.387Beta
3.366CAR
83.3Drawdown
67Loss Rate
0Parameters
1Security Types
-0.0905Sortino Ratio
7914Tradeable Dates
753Trades
0.238Treynor Ratio
33Win Rate
104.967Net Profit
0.266Sharpe Ratio
0.06Alpha
0.387Beta
3.366CAR
83.3Drawdown
67Loss Rate
0Parameters
1Security Types
-0.0905Sortino Ratio
7914Tradeable Dates
753Trades
0.238Treynor Ratio
33Win Rate
0Parameters
1Security Types
7914Tradeable Dates
0Parameters
1Security Types
7914Tradeable Dates
0Net Profit
0Sharpe Ratio
0Alpha
0Beta
0CAR
0Drawdown
0Loss Rate
2Parameters
1Security Types
0Sortino Ratio
127Tradeable Dates
0Trades
0Treynor Ratio
0Win Rate
38.46Net Profit
0.321Sharpe Ratio
0.032Alpha
0Beta
2.827CAR
31Drawdown
46Loss Rate
0Parameters
1Security Types
0.0577Sortino Ratio
4262Tradeable Dates
2149Trades
-98.982Treynor Ratio
54Win Rate
82.864Net Profit
0.62Sharpe Ratio
0.06Alpha
0.004Beta
5.916CAR
28.5Drawdown
43Loss Rate
0Parameters
1Security Types
0.1187Sortino Ratio
3835Tradeable Dates
1875Trades
13.988Treynor Ratio
57Win Rate
0Parameters
1Security Types
5Tradeable Dates
-8.098Net Profit
-8.611Sharpe Ratio
-3.068Alpha
-0.606Beta
-95.414CAR
10.5Drawdown
0Loss Rate
0Parameters
1Security Types
0Sortino Ratio
5Tradeable Dates
1Trades
3.828Treynor Ratio
0Win Rate
-8.098Net Profit
-8.611Sharpe Ratio
-3.068Alpha
-0.606Beta
-95.414CAR
10.5Drawdown
0Loss Rate
0Parameters
1Security Types
0Sortino Ratio
5Tradeable Dates
1Trades
3.828Treynor Ratio
0Win Rate
3.824Net Profit
1.902Sharpe Ratio
0.611Alpha
-0.367Beta
53.431CAR
8.1Drawdown
50Loss Rate
12Parameters
1Security Types
0.4383Sortino Ratio
22Tradeable Dates
12Trades
-0.966Treynor Ratio
50Win Rate
0Net Profit
0Sharpe Ratio
0Alpha
0Beta
0CAR
0Drawdown
0Loss Rate
7Parameters
1Security Types
0Sortino Ratio
300Tradeable Dates
0Trades
0Treynor Ratio
0Win Rate
0Net Profit
0Sharpe Ratio
0Alpha
0Beta
0CAR
0Drawdown
0Loss Rate
4Parameters
1Security Types
0Sortino Ratio
0Tradeable Dates
0Trades
0Treynor Ratio
0Win Rate
0Net Profit
0Sharpe Ratio
0Alpha
0Beta
0CAR
0Drawdown
0Loss Rate
1Parameters
1Security Types
0Sortino Ratio
9Tradeable Dates
0Trades
0Treynor Ratio
0Win Rate
0Net Profit
0Sharpe Ratio
0Alpha
0Beta
0CAR
0Drawdown
0Loss Rate
1Parameters
1Security Types
0Sortino Ratio
9Tradeable Dates
0Trades
0Treynor Ratio
0Win Rate
0Net Profit
0Sharpe Ratio
0Alpha
0Beta
0CAR
0Drawdown
0Loss Rate
0Parameters
1Security Types
0Sortino Ratio
0Tradeable Dates
0Trades
0Treynor Ratio
0Win Rate
41.78Net Profit
0.529Sharpe Ratio
0.222Alpha
-4.826Beta
10.485CAR
24.8Drawdown
41Loss Rate
6Parameters
1Security Types
0.3219Sortino Ratio
0Tradeable Dates
68Trades
-0.026Treynor Ratio
59Win Rate
41.78Net Profit
0.529Sharpe Ratio
0.222Alpha
-4.826Beta
10.485CAR
24.8Drawdown
41Loss Rate
6Parameters
1Security Types
0.3219Sortino Ratio
0Tradeable Dates
68Trades
-0.026Treynor Ratio
59Win Rate
41.78Net Profit
0.529Sharpe Ratio
0.222Alpha
-4.826Beta
10.485CAR
24.8Drawdown
41Loss Rate
6Parameters
1Security Types
0.3219Sortino Ratio
0Tradeable Dates
68Trades
-0.026Treynor Ratio
59Win Rate
Alethea submitted the research Price Earnings Anomaly
Abstract
The Price to Earnings (P/E) ratio is commonly used by investors to determine the valuation of a company's stock. This discussion explores the Price Earnings Anomaly and its impact on portfolio performance. The strategy involves selecting the 10 stocks with the lowest P/E ratio at the beginning of each year and investing an equal amount of capital in each stock. The portfolio significantly outperforms the benchmark, S&P 500, during the three and a half year backtest period. The strategy also considers the size factor, where small market capitalization stocks are found to outperform large market capitalization stocks. This discussion provides insight into the potential benefits of incorporating the P/E ratio and size factor into investment strategies.
Alethea submitted the research Improved Momentum Strategy On Commodities Futures
Abstract
Abstract: This tutorial discusses an improved momentum strategy called TSMOM-CF that addresses weaknesses in traditional time-series momentum strategies. TSMOM-CF incorporates trend strength, uses an efficient volatility estimator, and adds a dynamic leverage mechanism to improve performance. The traditional strategy's oversimplified trading signal, inefficient volatility estimator, and fixed portfolio allocation mechanism are overcome in TSMOM-CF. The paper "Demystifying Time-Series Momentum Strategies: Volatility Estimators, Trading Rules and Pairwise Correlations" by Nick Baltas and Robert Kosowski serves as the basis for the implementation. TSMOM-CF is compared to the basic momentum strategy in the Momentum Effect in Commodities Futures strategy library. The tutorial provides a detailed explanation of the modifications and their impact on performance.
Alethea submitted the research Commodities Futures Trend Following
Abstract
Abstract: This tutorial explores the implementation of a trend following strategy on commodities futures based on a 2014 paper titled "Two Centuries Of Trend Following". The paper highlights the existence of trends in financial markets, which contradicts the efficient market hypothesis. The strategy involves buying when prices go up and selling when prices go down. The paper extends the backtest period of trend following strategies to two centuries and demonstrates statistically significant excess returns on commodities, currencies, stock indices, and bonds. The tutorial focuses on implementing the strategy on a well-balanced commodities pool consisting of 7 representative contracts. The results of the backtest period show a lower Sharpe ratio compared to SPY's Sharpe ratio, indicating potential limitations of the trend following strategy in this context.
Alethea left a comment in the discussion Business days till expiration
Hi Gil,
Alethea left a comment in the discussion Noob: Struggling to build Lean with MonoDevelop
Hi DaveGilbert,
Alethea left a comment in the discussion Collaboration
Hi Joe,
Alethea left a comment in the discussion 'ForexHolding' object has no attribute 'TotalMargin'
Hi Brent,
Alethea left a comment in the discussion Extending Backtesting Data Range
Hi Frost,
Alethea left a comment in the discussion Extending Historical Data
Hi Frost,
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Alethea left a comment in the discussion Business days till expiration
Hi Gil,
5 years ago