Can You Generate Alpha in US Equities Using Corporate Reputation?

Corporate Reputation Data

The Corporate Reputation Index (CRI), developed by Seldonix and distributed in partnership with Social Market Analytics, allows traders to identify and compare over- and under-priced stocks that are affected by a company’s actions. Corporate Reputation is the controllable portion of a company’s stock price, considered to be an intrinsic driver of company performance, and a major contributor to daily stock price fluctuation.

The Corporate Reputation Index is the first daily business metric for monitoring corporate reputation. Centered on “0”, companies with negative values are deemed undervalued relative to market while those with positive values are overvalued.

The CRI is created after the close of markets and is currently available before markets open the next day at any time after 9:00 PM Eastern US Time the night before.

Each data record features a set of fields:

• The timestamp associated with each field is the market close date of the data used;
• Symbol;
• CRI

Basis of Research using Seldonix data

The purpose of the research described in this paper is to determine if there are opportunities to generate alpha in US equities traded on the NYSE and NASDAQ using Seldonix data as a basis for daily market movement prediction (the holding period is about 6.5 hours).

We show how with the use of simple technical indicators and the popular conception of basket trading, we can exploit the CRI to generate excess returns. An evaluation of the CRI was conducted in the forecasting of stock price. The results of the testing showed a 1 – 8 day lag in the prediction of stock price, depending on the stock. Therefore our purpose is to determine the most appropriate time when the CRI generates the most suitable values for opening a position. As the CRI values change every day and are different for each ticker, we need to construct an approach which will successfully encompass both equally important collations. To identify these situations, we need to:

• Compare short-term values to long-term;
• Compare values within the considered universe of tickers.

The full paper can be accessed here.

Results

This approach gives the following results for S&P 100 tested on the period from 1/5/2010 to 8/18/2014:

Parameter	All Trades	Long Trades	Short Trades
Net Profit/Loss	21,182.82	13,984.97	7,197.85
Total Profit	113,708.71	59,129.80	54,578.91
Total Loss	-92,525.89	-45,144.83	-47,381.06
Cumulated Profit %	21.18 %	13.98 %	7.20 %
Max Drawdown	-2,590.71	-2,774.62	-2,265.55
Max Drawdown %	-2.41 %	-2.66 %	-2.18 %
Max Drawdown Date	9/2/2011	9/30/2011	9/15/2011
Return/Drawdown Ratio	8.18	5.04	3.18
Drawdown Days %	80.96 %	80.36 %	88.29 %
Max Drawdown Duration	119	198	188
CAGR	4.40 %	2.97 %	1.57 %
Sharpe Ratio	1.73	1.37	0.73
Annualized Volatility	2.54	2.16	2.15
Sortino Ratio	2.86	2.15	1.13
UPI	0.39	0.27	0.13
Information Ratio	1.71	1.37	0.72
Optimal f	68.32	63.51	33.96
All Trades #	2308	1166	1142
Profitable Trades Ratio	0.53	0.54	0.52
Winning Trades #	1229	634	595
Losing Trades #	1079	532	547
Average Trade	9.18	11.99	6.30
Average Winning Trade	92.52	93.26	91.73
Average Losing Trade	-85.75	-84.86	-86.62
Avg. Win/ Avg. Loss Ratio	1.08	1.10	1.06
Average Profit per Share	0.04	0.05	0.03
Max Consequent Winners	9	11	9
Max Consequent Losers	10	10	9

 

Rules for closing

The other idea is to exploit the CR trend not only for opening but for closing position. On the figure below you can see the example of position on AAPL chart, blue line on second pad indicates CRI values:

We use the Simple Moving Average (SMA) of the last CRI values (red line on the second pad) to determine whether the instrument gets over or underpriced. Using the model from the paragraph Over/Under Priced, we will close the position for the instrument according to following rule:

1. If CR > SMA (5, CR) (instrument is overpriced at time t, price is likely to return to suggested price at t+1) close Short position on day close;
2. If CR < SMA (5, CR) (instrument is underpriced at time t, price is likely to return to suggested price at t+1) close Long position on day close.

The same chart with this rule shows better results:

This approach gives the following results for S&P100 tested on the period from 1/5/2010 to 8/18/2014:

Parameter	All Trades	Long Trades	Short Trades
Net Profit/Loss	32,118.49	18,265.41	13,853.08
Total Profit	143,984.75	71,784.79	72,199.96
Total Loss	-111,866.26	-53,519.38	-58,346.88
Cumulated Profit %	32.12 %	18.27 %	13.85 %
Max Drawdown	-3,526.80	-4,508.75	-3,368.95
Max Drawdown %	-3.08 %	-4.22 %	-3.07 %
Max Drawdown Date	9/2/2011	9/30/2011	9/15/2011
Return/Drawdown Ratio	9.11	4.05	4.11
Drawdown Days %	80.45 %	81.83 %	88.63 %
Max Drawdown Duration	95	194	279
CAGR	6.44 %	3.83 %	2.95 %
Sharpe Ratio	1.97	1.31	0.94
Annualized Volatility	3.27	2.93	3.14
Sortino Ratio	3.40	2.06	1.55
UPI	0.58	0.26	0.19
Information Ratio	1.90	1.31	0.91
Optimal f	60.05	44.63	29.93
All Trades #	2190	1103	1087
Profitable Trades Ratio	0.53	0.55	0.51
Winning Trades #	1158	603	555
Losing Trades #	1032	500	532
Average Trade	14.67	16.56	12.74
Average Winning Trade	124.34	119.05	130.09
Average Losing Trade	-108.40	-107.04	-109.67
Avg. Win/ Avg. Loss Ratio	1.15	1.11	1.19
Average Profit per Share	0.06	0.07	0.05
Max Consequent Winners	13	16	16
Max Consequent Losers	11	9	15

 

Filter for stronger signal

One more idea is to filter a stronger signal when CR retains its sign from the previous day, which is a stronger signal indicating overpriced/ underpriced asset. On the chart below you can see two trades on MSFT asset, the second one is unprofitable, when the CR line changes its value from -1 to 1:

Filtering out such unstable situations gets the following results for the S&P 100 tested in the period from 1/5/2010 to 8/18/2014:

Parameter	All Trades	Long Trades	Short Trades
Net Profit/Loss	32,810.12	19,145.45	13,664.67
Total Profit	126,322.99	64,003.72	62,319.27
Total Loss	-93,512.87	-44,858.26	-48,654.61
Cumulated Profit %	32.81 %	19.15 %	13.66 %
Max Drawdown	-2,617.49	-4,409.37	-2,465.16
Max Drawdown %	-2.37 %	-4.18 %	-2.29 %
Max Drawdown Date	9/2/2011	9/30/2011	9/15/2011
Return/Drawdown Ratio	12.53	4.34	5.54
Drawdown Days %	78.38 %	80.02 %	86.74 %
Max Drawdown Duration	89	194	176
CAGR	6.56 %	4.00 %	2.91 %
Sharpe Ratio	2.16	1.49	1.03
Annualized Volatility	3.04	2.68	2.84
Sortino Ratio	3.82	2.45	1.70
UPI	0.67	0.26	0.24
Information Ratio	2.11	1.50	1.01
Optimal f	70.80	55.51	36.20
All Trades #	1839	937	902
Profitable Trades Ratio	0.53	0.55	0.51
Winning Trades #	972	512	460
Losing Trades #	867	425	442
Average Trade	17.84	20.43	15.15
Average Winning Trade	129.96	125.01	135.48
Average Losing Trade	-107.86	-105.55	-110.08
Avg. Win/ Avg. Loss Ratio	1.20	1.18	1.23
Average Profit per Share	0.07	0.08	0.06
Max Consequent Winners	12	12	11
Max Consequent Losers	11	10	16

 

Conclusion

We presented an approach that uses CR indices as a strong predictive factor of price directionality. We developed a trading strategy that implements an algorithm based on this approach. We also constructed two other versions, both based on CRI predictive power, that raise the performance of the main approach.

The main contribution of the paper is back-testing and comparison of the different versions of the strategy. On stocks in the S&P 100, back-testing shows that the first strategy has an average Information Ratio of 1.71 over the period 2010-2014, the second and third versions achieved Information Ratios of 1.90 and 2.11 respectively, which indicates that the CRI is predictive in the forecasting of stock returns.