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Strategies & Market Trends : Technical analysis for shorts & longs -- Ignore unavailable to you. Want to Upgrade?

To: j g cordes who wrote (16067)	5/17/1998 11:16:00 PM
From: Lachesis Atropos	Read Replies (1) \| Respond to of 68426

I was thinking of Stovall's model. What were you thinking when you commented on rank, "a base standard like the SP500"? What I can do is to store the sectors in a directed graph. A node on the graph will represent a sector. The edge leading out of a node and entering a node will represent the direction (sector changes) and the number of times one sector leads to another. In addition, I could order the stocks with in a sector. To see which stocks lead others. This would be quite easy to do. Stocks also migrate across sectors; this could be done also. This seems like a good thing to do! Not too difficult. What are your comments? How would one measure acceleration? By profit? By volume, volume times stock price? Looks like a classic Transport Network problem, a Min-Max flow through a network of sectors. My question is how do we put a numeric value on flow? If we can do this, we can store day to day values. Then get a change vector from the day to day values. Call it DMS (Dynamic Mutating Stovall) model. I run the simulations on an PC. The PC is an over-clocked 166 AMD-K6 running at 275 MHz at an 83 MHz bus speed--a real screamer. The PC runs custom software written in C++ to do market analysis. Lachesis

To: j g cordes who wrote (16067)	5/18/1998 10:43:00 PM
From: Lachesis Atropos	Read Replies (1) \| Respond to of 68426

First Crack at Sector Flow I took the (close-open)* Volume on the last seven days for each stock and rolled them up by sector. Come to think of it (now) I could track the MA's over the (close-open)* Volume values. A the slope of the MA should give us an estimate for velocity going up and down in a sector. Last seven days including todays (May 18) end of day data follows: Table headings are as follow: Sector,Subsector,Day_1,Day_2,Day_3,Day_4,Day_5,Day_6,Day_7,Sum Of Days The Day_n = (Close-Open)*Volume, for the day The last column of is the sum, Sum(Day_1,Day_7). I sorted the "Sum Of Days" and the took out the center values which exposes the most positive and the most negative for a sector. Technology Industry, Computers SubIndustry, 49660.95, -33522.59, 42035.36, 39169.88, 9015.25, -96826.08, 26451.20, 35984.40 Technology Industry, Internet Products & Services SubIndustry, 2226.58, -8187.18, 11893.33, 30545.56, 7664.63, -5454.36, -8755.17, 29933.66 Durables Industry, Appliances SubIndustry, 343.40, -54.01, 47.20, 25168.55, 4454.31, -1278.93, 622.80, 29303.64 Banking Industry, Big-Cap Banks SubIndustry, 205.95, 3414.63, 12402.13, -1145.31, 3456.29, 9264.93, 1462.61, 29061.50 Electronics Industry, Diversified Electronics SubIndustry, 7043.91, 581.80, 3789.68, 13535.18, 424.00, -2009.36, 60.40, 23426.04 Retailers Industry, Department Stores SubIndustry, 1587.37, 228.90, 9079.01, 4382.97, 1149.02, -262.36, 2414.60, 18579.74 Retailers Industry, Bookstores SubIndustry, 1575.20, -5932.53, 9140.92, 8374.22, 1396.82, -1367.12, -2477.62, 10710.42 Financial Industry, Brokerage SubIndustry, 2059.54, 12.79, 3112.34, 143.46, 1145.05, 3328.78, -644.31, 9157.95 Technology Industry, Software & Services SubIndustry, 4990.07, -2429.94, 2914.26, -171.56, 4049.64, -497.42, 103.26, 8864.23 Consumer Products & Services Industry, Personal Products SubIndustry, 1612.88, 30.35, 2025.00, 1153.87, 1745.47, 109.73, 1601.38, 8278.88 Electronics Industry, Semiconductors SubIndustry, 4587.09, -1757.14, 2329.69, 3806.05, 1073.30, -10575.64, -474.79, -1011.10 Travel & Transportation Industry, Car Rental & Sales SubIndustry, 1119.00, -235.02, -311.25, -90.28, 2027.57, -2265.21, -1524.43, -1279.50 Travel & Transportation Industry, Cruise Lines SubIndustry, -2144.33, 53.16, -869.18, 508.63, -42.08, 457.50, -172.10, -2208.36 Consumer Products & Services Industry, Sports SubIndustry, -1066.09, -766.46, -569.31, -305.81, 121.52, 232.40, -110.87, -2354.85 Health Industry, Medical Services SubIndustry, 545.14, 13.75, 209.66, 565.91, 954.57, -3868.55, -1571.56, -3111.14 Auto Industry, Auto Manufacturers SubIndustry, -5129.94, -9819.37, 3823.55, 8698.49, 2528.11, -3042.14, -260.35, -3201.55 Energy Industry, Oilfield Equipment SubIndustry, 1657.20, -2962.43, -440.30, 338.33, 99.69, -1542.12, -1294.15, -4143.58 Media Industry, Music SubIndustry, -5527.80, -1540.12, 1320.41, -102.07, -4300.98, 5405.29, -251.86, -4997.07 Retailers Industry, Office Products SubIndustry, 1435.10, 258.65, 1102.70, 769.48, 1135.77, -595.59, -9271.55, -5165.28 Media Industry, Diversified Media SubIndustry, 4647.30, 9595.33, -7970.46, 1927.01, 3113.20, -14097.20, -5659.48, -8444.02