public override void Run()
{
//========== initialization ==========
StartTime = SubclassedStartTime ?? START_TIME;
EndTime = SubclassedEndTime ?? END_TIME;
Deposit(Globals.INITIAL_CAPITAL);
CommissionPerShare = 0.0; // lazy portfolios w/o commissions
var universe = AddDataSources(ALLOCATION.Select(u => u.Item1));
var bench = AddDataSource(BENCH);
//========== simulation loop ==========
foreach (var s in SimTimes)
{
if (!HasInstruments(universe) || !HasInstrument(bench))
{
continue;
}
//if (SimTime[0].Date.DayOfWeek > NextSimTime.Date.DayOfWeek)
if (SimTime[0].Date.Month != NextSimTime.Date.Month)
{
_alloc.LastUpdate = SimTime[0];
foreach (var a in ALLOCATION)
{
var w = a.Item2 != 0.0 ? a.Item2 : 1.0 / ALLOCATION.Count;
var i = FindInstrument(a.Item1);
_alloc.Allocation[i] = w;
int targetShares = (int)Math.Floor(NetAssetValue[0] * w / i.Close[0]);
i.Trade(targetShares - i.Position);
}
}
AddSubclassedBar(10.0 * NetAssetValue[0] / Globals.INITIAL_CAPITAL);
// plotter output
if (!IsOptimizing && TradingDays > 0)
{
_plotter.AddNavAndBenchmark(this, bench.Instrument);
_plotter.AddStrategyHoldings(this, universe.Select(ds => ds.Instrument));
}
#if false
if (_nav.Count() == 0)
{
Output.WriteLine("First simulation timestamp {0:MM/dd/yyyy}", SimTime[0]);
foreach (var ds in universe)
{
Output.WriteLine(" {0}: start at {1:MM/dd/yyyy}", ds.Instrument.Name, ds.FirstTime);
}
}
_nav.Add(NetAssetValue[0]);
foreach (var d in _cagrPeriods)
{
if (_nav.Count > d)
{
var cagr = Math.Exp(252.0 / d * Math.Log(_nav.Last() / _nav[_nav.Count() - 1 - d])) - 1.0;
if (!_minCagr.ContainsKey(d))
{
_minCagr[d] = cagr;
_maxCagr[d] = cagr;
}
else
{
_minCagr[d] = Math.Min(_minCagr[d], cagr);
_maxCagr[d] = Math.Max(_maxCagr[d], cagr);
}
}
}
#endif
}
//========== post processing ==========
#if false
foreach (var d in _minCagr.Keys)
{
Output.WriteLine("{0}-year return: min = {1:P2}, max = {2:P2}", d / 252, _minCagr[d], _maxCagr[d]);
}
#endif
if (!IsOptimizing)
{
_plotter.AddTargetAllocation(_alloc);
_plotter.AddOrderLog(this);
_plotter.AddPositionLog(this);
_plotter.AddPnLHoldTime(this);
_plotter.AddMfeMae(this);
//_plotter.AddParameters(this);
}
FitnessValue = this.CalcFitness();
}
override public void Run()
{
//---------- initialization
//WarmupStartTime = DateTime.Parse("06/01/2011", CultureInfo.InvariantCulture);
#if FAKE_OPTIONS
// data range for fake data
StartTime = DateTime.Parse("06/01/2011", CultureInfo.InvariantCulture);
EndTime = DateTime.Parse("04/09/2020", CultureInfo.InvariantCulture);
#endif
#if SPX_OPTIONS
// SPX date range
StartTime = DateTime.Parse("02/01/2007", CultureInfo.InvariantCulture);
EndTime = DateTime.Parse("11/28/2018", CultureInfo.InvariantCulture);
#endif
#if XSP_OPTIONS
// XSP date range
//StartTime = DateTime.Parse("08/01/2006", CultureInfo.InvariantCulture);
StartTime = DateTime.Parse("11/19/2007", CultureInfo.InvariantCulture); // availability of monthlies
EndTime = DateTime.Parse("08/01/2018", CultureInfo.InvariantCulture);
#endif
#if SPY_OPTIONS
StartTime = DateTime.Parse("11/19/2007", CultureInfo.InvariantCulture); // availability of monthlies
EndTime = DateTime.Parse("05/31/2020", CultureInfo.InvariantCulture);
#endif
Deposit(Globals.INITIAL_CAPITAL);
CommissionPerShare = Globals.COMMISSION;
var spy = AddDataSource(UNDERLYING_NICK);
AddDataSource(OPTION_NICK);
//var vix = AddDataSource(VIX_1Y);
var bench = AddDataSource(BENCHMARK);
//---------- simulation
foreach (var simTime in SimTimes)
{
if (!HasInstrument(spy) || !HasInstrument(OPTION_NICK) /*|| !HasInstrument(vix)*/ || !HasInstrument(bench))
{
continue;
}
_underlying = _underlying ?? spy.Instrument;
//_vix1y = _vix1y ?? vix.Instrument;
MaintainMainPosition();
MaintainMainHedge();
MaintainIncomePosition();
MaintainIncomeHedge();
if (TradingDays > 0 && !IsOptimizing)
{
_plotter.AddNavAndBenchmark(this, bench.Instrument);
#if true
_plotter.SelectChart("Strikes", "Date");
_plotter.SetX(SimTime[0]);
_plotter.Plot("Underlying", spy.Instrument.Close[0]);
_plotter.Plot("Main Position", _mainPosition != null ? _mainPosition.OptionStrike : 0.0);
_plotter.Plot("Main Hedge", _mainHedge != null ? _mainHedge.OptionStrike : 0.0);
_plotter.Plot("Income Position", _incomePosition != null ? _incomePosition.OptionStrike : 0.0);
_plotter.Plot("Income Hedge", _incomeHedge != null ? _incomeHedge.OptionStrike : 0.0);
#endif
#if false
_plotter.SelectChart("Hedge Strikes", "Date");
_plotter.SetX(SimTime[0]);
_plotter.Plot("Underlying", spy.Instrument.Close[0]);
_plotter.Plot("Main Hedge", _mainHedge != null ? _mainHedge.OptionStrike : 0.0);
_plotter.Plot("Income Hedge", _incomeHedge != null ? _incomeHedge.OptionStrike : 0.0);
#endif
#if true
_plotter.SelectChart("Position Breakdown", "Date");
_plotter.SetX(SimTime[0]);
_plotter.Plot("NAV", NetAssetValue[0]);
_plotter.Plot("Main Position", _mainPosition != null
? (_mainPosition.IsOption
? 100.0 * _mainPosition.Position * _mainPosition.Bid[0]
: _mainPosition.Position * _mainPosition.Close[0])
: 0.0);
_plotter.Plot("Main Hedge", _mainHedge != null ? 100.0 * _mainHedgeCurrentLots * _mainHedge.Bid[0] : 0.0);
_plotter.Plot("Income Position", _incomePosition != null ? 100.0 * _incomePositionCurrentLots * _incomePosition.Ask[0] : 0.0);
_plotter.Plot("Income Hedge", _incomeHedge != null ? 100.0 * _incomeHedgeCurrentLots * _incomeHedge.Bid[0] : 0.0);
_plotter.Plot("Cash", Cash);
#endif
}
}
//---------- post-processing
_plotter.AddOrderLog(this);
_plotter.AddParameters(this);
FitnessValue = this.CalcFitness();
}
public override IEnumerable <Bar> Run(DateTime?startTime, DateTime?endTime)
{
//========== initialization ==========
WarmupStartTime = Globals.WARMUP_START_TIME;
StartTime = Globals.START_TIME;
EndTime = Globals.END_TIME;
Deposit(Globals.INITIAL_CAPITAL);
CommissionPerShare = Globals.COMMISSION;
// our universe consists of risky & safe assets
var riskyAssets = AddDataSources(RISKY_ASSETS);
var safeAssets = AddDataSources(SAFE_ASSETS);
var universe = riskyAssets.Concat(safeAssets);
var bench = AddDataSource(BENCHMARK);
//========== simulation loop ==========
foreach (var simTime in SimTimes)
{
// calculate indicators on overy bar
Dictionary <Instrument, double> momentum = Instruments
.ToDictionary(
i => i,
i => (1.0 * i.Close.Momentum(21)[0]
+ 3.0 * i.Close.Momentum(63)[0]
+ 6.0 * i.Close.Momentum(126)[0]
+ 12.0 * i.Close.Momentum(252)[0]) / 22.0);
// skip if there are any instruments missing from our universe
if (!HasInstruments(universe) || !HasInstrument(bench))
{
continue;
}
// trigger rebalancing
if (SimTime[0].Month != NextSimTime.Month) // monthly
{
// calculate covariance
var covar = new PortfolioSupport.Covariance(Instruments, 12, 21); // 12 monthly bars
// calculate efficient frontier for universe
// note how momentum and covariance are annualized here
var cla = new PortfolioSupport.MarkowitzCLA(
universe.Select(ds => ds.Instrument),
i => 252.0 * momentum[i],
(i, j) => 252.0 / covar.BarSize * covar[i, j],
i => 0.0,
i => safeAssets.Contains(i.DataSource) ? 1.0 : MAX_RISKY_ALLOC);
// find portfolio with specified risk
var pf = cla.TargetVolatility(TVOL);
Output.WriteLine("{0:MM/dd/yyyy}: {1}", SimTime[0], pf.ToString());
// adjust all positions
_alloc.LastUpdate = SimTime[0];
foreach (var i in pf.Weights.Keys)
{
_alloc.Allocation[i] = pf.Weights[i];
int targetShares = (int)Math.Floor(NetAssetValue[0] * pf.Weights[i] / i.Close[0]);
int currentShares = i.Position;
var ticket = i.Trade(targetShares - currentShares);
if (ticket != null)
{
if (i.Position == 0)
{
ticket.Comment = "open";
}
else if (targetShares == 0)
{
ticket.Comment = "close";
}
else
{
ticket.Comment = "rebalance";
}
}
}
}
// plotter output
if (!IsOptimizing && TradingDays > 0)
{
_plotter.AddNavAndBenchmark(this, FindInstrument(BENCHMARK));
_plotter.AddStrategyHoldings(this, universe.Select(ds => ds.Instrument));
if (_alloc.LastUpdate == SimTime[0])
{
_plotter.AddTargetAllocationRow(_alloc);
}
if (IsDataSource)
{
var v = 10.0 * NetAssetValue[0] / Globals.INITIAL_CAPITAL;
yield return(Bar.NewOHLC(
this.GetType().Name, SimTime[0],
v, v, v, v, 0));
}
}
}
//========== post processing ==========
if (!IsOptimizing)
{
_plotter.AddTargetAllocation(_alloc);
_plotter.AddOrderLog(this);
_plotter.AddPositionLog(this);
_plotter.AddPnLHoldTime(this);
_plotter.AddMfeMae(this);
_plotter.AddParameters(this);
}
FitnessValue = this.CalcFitness();
}
public override void Run()
{
//========== initialization ==========
#if USE_BOOK_RANGE
StartTime = SubclassedStartTime ?? DateTime.Parse("01/01/2003", CultureInfo.InvariantCulture);
EndTime = SubclassedEndTime ?? DateTime.Parse("12/31/2018", CultureInfo.InvariantCulture);
#else
StartTime = SubclassedStartTime ?? Globals.START_TIME;
EndTime = SubclassedEndTime ?? Globals.END_TIME;
#endif
WarmupStartTime = StartTime - TimeSpan.FromDays(100);
Deposit(Globals.INITIAL_CAPITAL);
//CommissionPerShare = Globals.COMMISSION; // Connors does not consider commissions
var universe = AddDataSources(UNIVERSE.Constituents);
var idle = AddDataSource(IDLE_CASH);
var spx = AddDataSource(SPX);
var benchmark = AddDataSource(BENCHMARK);
//========== simulation loop ==========
var weeklyBars = new Dictionary <Instrument, TimeSeries <double> >();
var entryPrices = new Dictionary <Instrument, double>();
foreach (var s in SimTimes)
{
if (!HasInstrument(benchmark) || !HasInstrument(idle))
{
continue;
}
// determine universe constituents
var constituents = Instruments
.Where(i => UNIVERSE.IsConstituent(i.Nickname, SimTime[0]))
.ToList();
// calculate daily indicators
var dailyIndicators = Instruments
.ToDictionary(
i => i,
i => new
{
volatility = i.Close.Volatility(100)[0],
});
// start with weights representing current positions
const int NUM_POS = 10;
var weights = Instruments
.ToDictionary(
i => i,
i => constituents.Contains(i) && i.Position > 0
? 1.0 / NUM_POS
: 0.0);
// sell, if stock closes 10% below entry price
foreach (var i in Instruments)
{
if (i != idle.Instrument && i.Position > 0.0 && i.Close[0] < 0.90 * entryPrices[i])
{
weights[i] = 0.0;
}
}
// weekly logic on last business day of the week
if (SimTime[0].DayOfWeek > NextSimTime.DayOfWeek)
{
foreach (var i in Instruments)
{
if (!weeklyBars.ContainsKey(i))
{
weeklyBars[i] = new TimeSeries <double>();
}
}
// advance weekly bars
foreach (var i in Instruments)
{
weeklyBars[i].Value = i.Close[0];
}
// calculate weekly indicators
var weeklyIndicators = Instruments
.ToDictionary(
i => i,
i => new
{
rsi = weeklyBars[i].RSI(2)[0],
});
// sell, if RSI is above 80
foreach (var i in Instruments)
{
if (weeklyIndicators[i].rsi > 80)
{
weights[i] = 0.0;
}
}
// determine number of new entries
var numCurrentEntries = weights
.Where(w => w.Value > 0.0)
.Count();
var numNewEntries = NUM_POS - numCurrentEntries;
// buy, if
// - we don't have a position
// - trend filter is positive
// - RSI is below 20
var newEntries = constituents
.Where(i => i.Position == 0)
.Where(i => spx.Instrument.Close[0] > spx.Instrument.Close[126])
.Where(i => weeklyIndicators[i].rsi < 20)
.OrderBy(i => dailyIndicators[i].volatility)
.Take(numNewEntries)
.ToList();
foreach (var i in newEntries)
{
weights[i] = 1.0 / NUM_POS;
entryPrices[i] = i.Close[0];
}
// invest in the idle instrument, if we are not planning to
// fill all slots for mean-reversion instruments
double idleWeight = (numNewEntries - newEntries.Count()) / NUM_POS;
weights[idle.Instrument] = idleWeight;
}
foreach (var i in Instruments)
{
int targetShares = (int)Math.Floor(weights[i] * NetAssetValue[0] / i.Close[0]);
// don't rebalance our mean-reversion instruments
if (i != idle.Instrument && i.Position > 0 && targetShares > 0)
{
targetShares = i.Position;
}
i.Trade(targetShares - i.Position, OrderType.closeThisBar);
}
if (TradingDays > 0 && !IsOptimizing)
{
_plotter.AddNavAndBenchmark(this, benchmark.Instrument);
//_plotter.AddStrategyHoldings(this, universe.Select(u => u.Instrument));
}
AddSubclassedBar(10.0 * NetAssetValue[0] / Globals.INITIAL_CAPITAL);
}
//========== post processing ==========
if (!IsOptimizing)
{
//_plotter.AddTargetAllocation(_alloc);
_plotter.AddOrderLog(this);
_plotter.AddPositionLog(this);
_plotter.AddPnLHoldTime(this);
_plotter.AddMfeMae(this);
//_plotter.AddParameters(this);
}
FitnessValue = this.CalcFitness();
}
public override IEnumerable <Bar> Run(DateTime?startTime, DateTime?endTime)
{
//========== initialization ==========
#if DATE_RANGES_FROM_PAPER
#if DATA_RANG_IS
StartTime = DateTime.Parse("01/03/2005", CultureInfo.InvariantCulture);
EndTime = DateTime.Parse("12/11/2012, 4pm", CultureInfo.InvariantCulture);
#endif
#if DATE_RANGE_OS
StartTime = DateTime.Parse("01/02/1998", CultureInfo.InvariantCulture);
EndTime = DateTime.Parse("12/31/2004, 4pm", CultureInfo.InvariantCulture);
#endif
#if DATE_RANGE_FULL
StartTime = DateTime.Parse("01/02/1998", CultureInfo.InvariantCulture);
EndTime = DateTime.Parse("12/14/2012, 4pm", CultureInfo.InvariantCulture);
#endif
WarmupStartTime = StartTime - TimeSpan.FromDays(126);
#else
WarmupStartTime = Globals.WARMUP_START_TIME;
StartTime = Globals.START_TIME;
EndTime = Globals.END_TIME;
#endif
Deposit(Globals.INITIAL_CAPITAL);
CommissionPerShare = Globals.COMMISSION;
var universe = AddDataSources(U);
var benchmark = AddDataSource(BENCHMARK);
//========== simulation loop ==========
foreach (var simTime in SimTimes)
{
// skip if there are any instruments missing from our universe
if (!HasInstruments(universe) || !HasInstrument(benchmark))
{
continue;
}
// calculate indicators
var indicators = universe
.Select(ds => ds.Instrument)
.ToDictionary(
i => i,
i => new indicatorValues
{
r = i.Close[0] / i.Close[LOOKBACK_R] - 1.0,
a = i.Close[0] / i.Close[LOOKBACK_A] - 1.0,
v = i.Close.Volatility(LOOKBACK_C)[0],
c = universe
.Select(ds => ds.Instrument)
.Where(i2 => i != i2)
// FIXME: how exactly are we calculating correlation here?
.Average(i2 => i.Close.Correlation(i2.Close, LOOKBACK_C)[0])
//.Average(i2 => i.Close.Return().Correlation(i2.Close.Return(), LOOKBACK_C)[0])
//.Average(i2 => i.Close.LogReturn().Correlation(i2.Close.LogReturn(), LOOKBACK_C)[0])
});
// trigger monthly rebalancing
if (SimTime[0].Month != NextSimTime.Month)
{
// calculate loss function for universe
var L = LossFunction(indicators);
// Keller is adamant to filter for absolute momentum
// after ranking for the loss function
var top = L.Keys
.OrderBy(i => L[i])
.Take(N)
.Where(i => indicators[i].a > RMIN / 100.0)
.ToList();
// initialize all weights to zero
var weights = indicators.Keys
.ToDictionary(
i => i,
i => 0.0);
// assign weights for top instruments
for (int n = 0; n < top.Count; n++)
{
// N = 3, a = 0.5: weights = 2.5/6, 2.0/6, 1.5/6
// 0.417 0.333 0.250
weights[top[n]] +=
(1.0 - A / 100.0) / N
+ A / 100.0 * (N - n) / ((N + 1.0) * N / 2.0);
}
// assign any leftover weight to safe instrument
weights[FindInstrument(U_SAFE)] += 1.0 - weights.Sum(kv => kv.Value);
//weights[FindInstrument(U_SAFE)] += (N - top.Count) / (double)N;
// submit orders
foreach (var i in weights.Keys)
{
var shares = (int)Math.Floor(weights[i] * NetAssetValue[0] / i.Close[0]);
i.Trade(shares - i.Position);
}
}
// plotter output
if (!IsOptimizing && TradingDays > 0)
{
_plotter.AddNavAndBenchmark(this, FindInstrument(BENCHMARK));
_plotter.AddStrategyHoldings(this, universe.Select(ds => ds.Instrument));
#if true
// additional plotter output
_plotter.SelectChart("Factor R", "Date");
_plotter.SetX(SimTime[0]);
foreach (var i in indicators.Keys)
{
_plotter.Plot(i.Symbol, indicators[i].r);
}
_plotter.SelectChart("Factor V", "Date");
_plotter.SetX(SimTime[0]);
foreach (var i in indicators.Keys)
{
_plotter.Plot(i.Symbol, indicators[i].v);
}
_plotter.SelectChart("Factor C", "Date");
_plotter.SetX(SimTime[0]);
foreach (var i in indicators.Keys)
{
_plotter.Plot(i.Symbol, indicators[i].c);
}
#endif
if (IsDataSource)
{
var v = 10.0 * NetAssetValue[0] / Globals.INITIAL_CAPITAL;
yield return(Bar.NewOHLC(
this.GetType().Name, SimTime[0],
v, v, v, v, 0));
}
}
}
//========== post processing ==========
if (!IsOptimizing)
{
_plotter.AddTargetAllocation(_alloc);
_plotter.AddOrderLog(this);
_plotter.AddPositionLog(this);
_plotter.AddPnLHoldTime(this);
_plotter.AddMfeMae(this);
_plotter.AddParameters(this);
}
FitnessValue = this.CalcFitness();
}
public override void Run()
{
//========== initialization ==========
#if USE_BENSDORPS_RANGE
// matching range in the book
StartTime = SubclassedStartTime ?? DateTime.Parse("01/02/1995", CultureInfo.InvariantCulture);
EndTime = SubclassedEndTime ?? DateTime.Parse("11/23/2016", CultureInfo.InvariantCulture);
WarmupStartTime = StartTime - TimeSpan.FromDays(365);
#else
StartTime = SubclassedStartTime ?? Globals.START_TIME;
EndTime = SubclassedEndTime ?? Globals.END_TIME;
WarmupStartTime = Globals.WARMUP_START_TIME;
#endif
Deposit(Globals.INITIAL_CAPITAL);
CommissionPerShare = Globals.COMMISSION;
AddDataSources(UNIVERSE.Constituents);
var spx = AddDataSource(SPX);
var benchmark = AddDataSource(BENCHMARK);
//========== simulation loop ==========
double nn = 0.0;
foreach (var s in SimTimes)
{
var universe = Instruments
.Where(i => i.IsConstituent(UNIVERSE))
.ToList();
//----- calculate indicators
// calculate indicators for all known instruments,
// as they might enter the universe any time
var indicators = Instruments
.ToDictionary(
i => i,
i => new
{
rsi = i.Close.RSI(3),
roc = i.Close.Momentum(200),
});
if (!HasInstrument(benchmark))
{
continue;
}
var smaBand = spx.Instrument.Close.SMA(200).Multiply(0.98); // 2% below 200-day SMA
// open positions on Monday
if (NextSimTime.DayOfWeek < SimTime[0].DayOfWeek) // open positions on Monday
{
// we are not entirely sure how Bensdorp wants this strategy to work.
// we see three alternatives
#if false
// solution A
// create one list of 10 stocks, none of which are overbought,
// ranked by momentum
// good: new entries are guaranteed to be on keep-list on day 1
// also, we always hold 10 stocks
// bad: we might exit stocks with top momentum, as soon as they become overbought
// => this strategy seems to never hold stocks longer than 60 days,
// conflicting with the statements made in the book
var nextHoldings = universe
.Where(i => spx.Instrument.Close[0] > smaBand[0])
.Where(i => indicators[i].rsi[0] < MAX_RSI)
.OrderByDescending(i => indicators[i].roc[0])
.Take(MAX_ENTRIES)
.ToList();
#endif
#if false
// solution B
// create separate list for new entries and for keepers
// good: this makes sure that we almost always hold 10 stocks
// bad: a new stock entered might not meet the hold requirements,
// as it might not have top-10 momentum. this adds somewhat of
// a mean-reversion component to the strategy
// => this strategy seems to work very well over the book's backtesting period.
// overall, higher return and higher drawdown than C, worse Sharpe ratio
var keep = universe
.Where(i => spx.Instrument.Close[0] > smaBand[0])
.OrderByDescending(i => indicators[i].roc[0])
.Take(MAX_ENTRIES)
.Where(i => i.Position != 0)
.ToList();
var enter = universe
.Where(i => spx.Instrument.Close[0] > smaBand[0])
.Where(i => i.Position == 0 && indicators[i].rsi[0] < MAX_RSI)
.OrderByDescending(i => indicators[i].roc[0])
.Take(MAX_ENTRIES - keep.Count)
.ToList();
var nextHoldings = keep
.Concat(enter)
.ToList();
#endif
#if true
// solution C
// draw new entries and keeps both from top-10 ranked stocks
// good: new entries are guaranteed to be on the keep list on day 1
// bad: the enter list might be empty, if all top-10 stocks are overbought
// driving down our exposure and therewith return
var top10 = universe
.Where(i => spx.Instrument.Close[0] > smaBand[0])
.OrderByDescending(i => indicators[i].roc[0])
.Take(MAX_ENTRIES)
.ToList();
var keep = top10
.Where(i => i.Position != 0)
.ToList();
var enter = top10
.Where(i => i.Position == 0 && indicators[i].rsi[0] < MAX_RSI)
.ToList();
var nextHoldings = keep
.Concat(enter)
.ToList();
#endif
_alloc.LastUpdate = SimTime[0];
_alloc.Allocation.Clear();
foreach (var i in Instruments)
{
double targetPercentage = nextHoldings.Contains(i)
? 1.0 / MAX_ENTRIES
: 0.0;
int targetShares = (int)Math.Floor(NetAssetValue[0] * targetPercentage / i.Close[0]);
if (targetPercentage != 0.0)
{
_alloc.Allocation[i] = targetPercentage;
}
i.Trade(targetShares - i.Position);
}
nn = nextHoldings.Count / 10.0;
}
//----- output
if (!IsOptimizing && TradingDays > 0)
{
_plotter.AddNavAndBenchmark(this, FindInstrument(BENCHMARK));
//_plotter.AddStrategyHoldings(this, universe);
// plot strategy exposure
_plotter.SelectChart("Exposure Chart", "Date");
_plotter.SetX(SimTime[0]);
_plotter.Plot("Exposure", Instruments.Sum(i => i.Position * i.Close[0]) / NetAssetValue[0]);
//_plotter.Plot("Choices", nn);
if (IsSubclassed)
{
AddSubclassedBar(10.0 * NetAssetValue[0] / Globals.INITIAL_CAPITAL);
}
}
}
//========== post processing ==========
if (!IsOptimizing)
{
_plotter.AddTargetAllocation(_alloc);
_plotter.AddOrderLog(this);
_plotter.AddPositionLog(this);
_plotter.AddPnLHoldTime(this);
_plotter.AddMfeMae(this);
_plotter.AddParameters(this);
}
FitnessValue = this.CalcFitness();
}
public override IEnumerable <Bar> Run(DateTime?startTime, DateTime?endTime)
{
//========== initialization ==========
WarmupStartTime = Globals.WARMUP_START_TIME;
StartTime = Globals.START_TIME;
EndTime = Globals.END_TIME;
Deposit(Globals.INITIAL_CAPITAL);
CommissionPerShare = Globals.COMMISSION; // the book does not deduct commissions
var menu = AddDataSources(ETF_MENU).ToList();
var bench = AddDataSource(BENCHMARK);
//========== simulation loop ==========
foreach (DateTime simTime in SimTimes)
{
// calculate momentum w/ algorithm-specific helper function
var evaluation = Instruments
.ToDictionary(
i => i,
i => MOMENTUM(i));
// skip, if there are any missing instruments
if (!HasInstruments(menu) || !HasInstrument(bench))
{
continue;
}
// rank, and select top-3 instruments
var top3 = menu
.Select(ds => ds.Instrument)
.OrderByDescending(i => evaluation[i])
.Take(NUM_PICKS);
// calculate target percentage and how far we are off
double targetPercentage = 1.0 / NUM_PICKS;
double maxOff = menu
.Select(ds => ds.Instrument)
.Max(i => (top3.Count() > 0 && top3.Contains(i) ? 1.0 : 0.0)
* Math.Abs(i.Position * i.Close[0] / NetAssetValue[0] - targetPercentage) / targetPercentage);
// rebalance once per month, and only if we need adjustments exceeding 20%
if (REBAL_TODAY(maxOff))
{
_alloc.LastUpdate = SimTime[0];
foreach (var i in menu.Select(ds => ds.Instrument))
{
_alloc.Allocation[i] = top3.Contains(i) ? targetPercentage : 0.0;
// determine current and target shares per instrument...
double targetEquity = (top3.Contains(i) ? targetPercentage : 0.0) * NetAssetValue[0];
int targetShares = (int)Math.Floor(targetEquity / i.Close[0]);
int currentShares = i.Position;
// ... and trade the delta
Order newOrder = i.Trade(targetShares - currentShares, ORDER_TYPE);
// add a comment, to make the trading log easier to read
if (newOrder != null)
{
if (currentShares == 0)
{
newOrder.Comment = "Open";
}
else if (targetShares == 0)
{
newOrder.Comment = "Close";
}
else
{
newOrder.Comment = "Rebalance";
}
}
}
}
// plotter output
if (!IsOptimizing && TradingDays > 0)
{
_plotter.AddNavAndBenchmark(this, FindInstrument(BENCHMARK));
_plotter.AddStrategyHoldings(this, ETF_MENU.Select(nick => FindInstrument(nick)));
if (_alloc.LastUpdate == SimTime[0])
{
_plotter.AddTargetAllocationRow(_alloc);
}
if (IsDataSource)
{
var v = 10.0 * NetAssetValue[0] / Globals.INITIAL_CAPITAL;
yield return(Bar.NewOHLC(
this.GetType().Name, SimTime[0],
v, v, v, v, 0));
}
}
}
//========== post processing ==========
if (!IsOptimizing)
{
_plotter.AddTargetAllocation(_alloc);
_plotter.AddOrderLog(this);
_plotter.AddPositionLog(this);
_plotter.AddPnLHoldTime(this);
_plotter.AddMfeMae(this);
_plotter.AddParameters(this);
}
FitnessValue = this.CalcFitness();
}
public override void Run()
{
//========== initialization ==========
WarmupStartTime = Globals.WARMUP_START_TIME;
StartTime = Globals.START_TIME;
EndTime = Globals.END_TIME;
Deposit(Globals.INITIAL_CAPITAL);
CommissionPerShare = Globals.COMMISSION;
var market = AddDataSource(MARKET);
//========== simulation loop ==========
var entryPrices = new Dictionary <Instrument, double>();
foreach (var s in SimTimes)
{
if (!_alloc.Allocation.ContainsKey(market.Instrument))
{
_alloc.Allocation[market.Instrument] = 0.0;
}
double percentToBuySell = Rules(market.Instrument);
_alloc.LastUpdate = SimTime[0];
//----- entries
if (market.Instrument.Position >= 0 && percentToBuySell > 0 ||
market.Instrument.Position <= 0 && percentToBuySell < 0)
{
int sharesToBuySell = (int)(Math.Sign(percentToBuySell) * Math.Floor(
Math.Abs(percentToBuySell) * NetAssetValue[0] / market.Instrument.Close[0]));
_alloc.Allocation[market.Instrument] += percentToBuySell;
market.Instrument.Trade(sharesToBuySell, ORDER_TYPE);
}
//----- exits
if (market.Instrument.Position > 0 && percentToBuySell < 0 ||
market.Instrument.Position < 0 && percentToBuySell > 0)
{
// none of the algorithms attempt to gradually
// exit positions, so this is good enough
_alloc.Allocation[market.Instrument] = 0.0;
market.Instrument.Trade(-market.Instrument.Position, OrderType.closeThisBar);
}
//----- output
if (!IsOptimizing && TradingDays > 0)
{
_plotter.AddNavAndBenchmark(this, market.Instrument);
_plotter.AddStrategyHoldings(this, market.Instrument);
}
}
//========== post processing ==========
if (!IsOptimizing)
{
_plotter.AddTargetAllocation(_alloc);
_plotter.AddOrderLog(this);
_plotter.AddPositionLog(this);
_plotter.AddPnLHoldTime(this);
_plotter.AddMfeMae(this);
_plotter.AddParameters(this);
}
FitnessValue = this.CalcFitness();
}
public override void Run()
{
//========== initialization ==========
WarmupStartTime = Globals.WARMUP_START_TIME;
StartTime = Globals.START_TIME;
EndTime = Globals.END_TIME;
Deposit(Globals.INITIAL_CAPITAL);
CommissionPerShare = Globals.COMMISSION;
var market = AddDataSource(MARKET);
var volatility = AddDataSource(VOLATILITY);
#if INCLUDE_TRIN_STRATEGY
AddDataSource(TRIN);
#endif
//========== simulation loop ==========
foreach (var s in SimTimes)
{
if (!HasInstrument(market) || !HasInstrument(volatility))
{
continue;
}
if (!_alloc.Allocation.ContainsKey(market.Instrument))
{
_alloc.Allocation[market.Instrument] = 0.0;
}
int buySell = Rules(market.Instrument);
_alloc.LastUpdate = SimTime[0];
//----- enter positions
if (market.Instrument.Position == 0 && buySell != 0)
{
int numShares = buySell * (int)Math.Floor(NetAssetValue[0] / market.Instrument.Close[0]);
_alloc.Allocation[market.Instrument] += buySell;
market.Instrument.Trade(numShares, OrderType.closeThisBar);
}
//----- exit positions
else if (market.Instrument.Position != 0 && buySell != 0)
{
_alloc.Allocation[market.Instrument] = 0.0;
market.Instrument.Trade(-market.Instrument.Position, ORDER_TYPE);
}
//----- output
if (!IsOptimizing && TradingDays > 0)
{
_plotter.AddNavAndBenchmark(this, market.Instrument);
_plotter.AddStrategyHoldings(this, market.Instrument);
}
}
//========== post processing ==========
if (!IsOptimizing && TradingDays > 0)
{
_plotter.AddTargetAllocation(_alloc);
_plotter.AddOrderLog(this);
_plotter.AddPositionLog(this);
_plotter.AddPnLHoldTime(this);
_plotter.AddMfeMae(this);
_plotter.AddParameters(this);
}
FitnessValue = this.CalcFitness();
}
public override void Run()
{
//----- initialization
WarmupStartTime = Globals.WARMUP_START_TIME;
StartTime = Globals.START_TIME;
EndTime = Globals.END_TIME;
Deposit(Globals.INITIAL_CAPITAL);
CommissionPerShare = Globals.COMMISSION; // paper does not consider trade commissions
var riskyUniverse = AddDataSources(RISKY_UNIVERSE);
var cashUniverse = AddDataSources(CASH_UNIVERSE);
var protectiveUniverse = AddDataSources(PROTECTIVE_UNIVERSE);
var benchmark = AddDataSource(BENCHMARK);
//----- simulation loop
var monthlyBars = new Dictionary <Instrument, TimeSeries <double> >();
foreach (DateTime simTime in SimTimes)
{
// skip if there are any missing instruments
// we want to make sure our strategy has all instruments available
if (!HasInstruments(riskyUniverse) ||
!HasInstruments(cashUniverse) ||
!HasInstruments(protectiveUniverse) ||
!HasInstrument(benchmark) ||
ASSET_SUB != null && !HasInstruments(ASSET_SUB.Values))
{
continue;
}
// rebalance once per month
// CAUTION: no indicator calculations within this block!
if (SimTime[0].Month != NextSimTime.Month)
{
// calculate 13612W momentum for all instruments
foreach (var i in Instruments)
{
if (!monthlyBars.ContainsKey(i))
{
monthlyBars[i] = new TimeSeries <double>();
}
}
foreach (var i in Instruments)
{
monthlyBars[i].Value = i.Close[0];
}
Dictionary <Instrument, double> momentum13612W = Instruments
.ToDictionary(
i => i,
i => 0.25 *
(12.0 * (monthlyBars[i][0] / monthlyBars[i][1] - 1.0)
+ 4.0 * (monthlyBars[i][0] / monthlyBars[i][3] - 1.0)
+ 2.0 * (monthlyBars[i][0] / monthlyBars[i][6] - 1.0)
+ 1.0 * (monthlyBars[i][0] / monthlyBars[i][12] - 1.0)));
// determine number of bad assets in canary universe
double b = protectiveUniverse
.Select(ds => ds.Instrument)
.Sum(i => momentum13612W[i] < 0.0 ? 1.0 : 0.0);
// calculate cash fraction
//double CF = Math.Min(1.0, b / B) // standard calculation
double CF = Math.Min(1.0, 1.0 / T * Math.Floor(b * T / B)); // Easy Trading
// as part of Easy Trading, we scale back the number of
// top assets as CF increases
int t = (int)Math.Round((1.0 - CF) * T);
// find T top risky assets
IEnumerable <Instrument> topInstruments = riskyUniverse
.Select(ds => ds.Instrument)
.OrderByDescending(i => momentum13612W[i])
.Take(t);
// find single cash/ bond asset
Instrument cashInstrument = cashUniverse
.Select(ds => ds.Instrument)
.OrderByDescending(i => momentum13612W[i])
.First();
// set instrument weights
Dictionary <Instrument, double> weights = Instruments
.ToDictionary(i => i, i => 0.0);
weights[cashInstrument] = CF;
foreach (Instrument i in topInstruments)
{
weights[i] += (1.0 - CF) / t;
}
_alloc.LastUpdate = SimTime[0];
foreach (Instrument i in Instruments)
{
// skip instruments not in our relevant universes
if (!riskyUniverse.Contains(i.DataSource) && !cashUniverse.Contains(i.DataSource))
{
continue;
}
// for the 'on steroids' versions, we run the signals
// as usual, but substitute some assets with leveraged
// counterparts for the actual trading
var i2 = AssetSub(i);
// calculate target allocations
_alloc.Allocation[i2] = weights[i];
int targetShares = (int)Math.Floor(weights[i] * NetAssetValue[0] / i2.Close[0]);
Order newOrder = i2.Trade(targetShares - i2.Position);
if (newOrder != null)
{
if (i.Position == 0)
{
newOrder.Comment = "open";
}
else if (targetShares == 0)
{
newOrder.Comment = "close";
}
else
{
newOrder.Comment = "rebalance";
}
}
}
}
// plotter output
if (!IsOptimizing && TradingDays > 0)
{
_plotter.AddNavAndBenchmark(this, FindInstrument(BENCHMARK));
_plotter.AddStrategyHoldings(this, Instruments
.Where(i => riskyUniverse.Contains(i.DataSource) || cashUniverse.Contains(i.DataSource))
.Select(i => AssetSub(i)));
}
}
//----- post processing
if (!IsOptimizing)
{
_plotter.AddTargetAllocation(_alloc);
_plotter.AddOrderLog(this);
_plotter.AddPositionLog(this);
_plotter.AddPnLHoldTime(this);
_plotter.AddMfeMae(this);
_plotter.AddParameters(this);
}
FitnessValue = this.CalcFitness();
}
public override IEnumerable <Bar> Run(DateTime?startTime, DateTime?endTime)
{
//========== initialization ==========
StartTime = START_TIME;
EndTime = END_TIME;
WarmupStartTime = StartTime - TimeSpan.FromDays(365);
Deposit(Globals.INITIAL_CAPITAL);
CommissionPerShare = Globals.COMMISSION; // it is unclear, if Antonacci considers commissions
// assets we can trade
List <string> ASSETS = ASSET_CLASSES
.SelectMany(c => c.assets)
.Distinct()
.Where(nick => nick != ABS_MOMENTUM)
.ToList();
ASSETS.Add(SAFE_INSTR);
var assets = AddDataSources(ASSETS);
var safe = AddDataSource(SAFE_INSTR); // we just need the data source
var absMom = AddDataSource(ABS_MOMENTUM);
var benchmark = AddDataSource(BENCHMARK);
double totalWeights = ASSET_CLASSES.Sum(a => a.weight);
//========== simulation loop ==========
foreach (DateTime simTime in SimTimes)
{
// skip if there are any missing instruments
if (!HasInstruments(assets) || !HasInstrument(benchmark) || !HasInstrument(absMom))
{
continue;
}
// evaluate momentum for all known instruments
Dictionary <Instrument, double> instrumentMomentum = Instruments
.ToDictionary(i => i, i => MOMENTUM(i));
// execute trades once per month
// CAUTION: do not calculate indicators within this block!
if (SimTime[0].Month != NextSimTime.Month)
{
// create empty structure for instrument weights
Dictionary <Instrument, double> instrumentWeights = Instruments
.ToDictionary(i => i, i => 0.0);
// loop through all asset classes, and find the top-ranked one
Instrument safeInstrument = safe.Instrument;
foreach (AssetClass assetClass in ASSET_CLASSES)
{
// find the instrument with the highest momentum
// in each asset class
var bestInstrument = assetClass.assets
.Select(nick => FindInstrument(nick))
.OrderByDescending(i => instrumentMomentum[i])
.Take(1)
.First();
// sum up the weights (because instrument is duplicated)
instrumentWeights[bestInstrument] += assetClass.weight / totalWeights;
if (assetClass.setSafeInstrument)
{
safeInstrument = bestInstrument;
}
}
// if momentum of any instrument drops below that of a T-Bill,
// we use the safe instrument instead
// therefore, we swap T-Bills for the safe instrument:
double pcntTbill = instrumentWeights[absMom.Instrument];
instrumentWeights[absMom.Instrument] = 0.0;
instrumentWeights[safeInstrument] += pcntTbill;
// submit orders
_alloc.LastUpdate = SimTime[0];
foreach (var ds in assets)
{
_alloc.Allocation[ds.Instrument] = instrumentWeights[ds.Instrument];
int targetShares = (int)Math.Floor(instrumentWeights[ds.Instrument] * NetAssetValue[0] / ds.Instrument.Close[0]);
int currentShares = ds.Instrument.Position;
Order newOrder = ds.Instrument.Trade(targetShares - currentShares);
if (newOrder != null)
{
if (currentShares == 0)
{
newOrder.Comment = "open";
}
else if (targetShares == 0)
{
newOrder.Comment = "close";
}
else
{
newOrder.Comment = "rebalance";
}
}
}
}
// plotter output
if (!IsOptimizing && TradingDays > 0)
{
_plotter.AddNavAndBenchmark(this, benchmark.Instrument);
_plotter.AddStrategyHoldings(this, assets.Select(ds => ds.Instrument));
if (_alloc.LastUpdate == SimTime[0])
{
_plotter.AddTargetAllocationRow(_alloc);
}
if (IsDataSource)
{
var v = 10.0 * NetAssetValue[0] / Globals.INITIAL_CAPITAL;
yield return(Bar.NewOHLC(
this.GetType().Name, SimTime[0],
v, v, v, v, 0));
}
}
}
//========== post processing ==========
if (!IsOptimizing)
{
_plotter.AddTargetAllocation(_alloc);
_plotter.AddOrderLog(this);
_plotter.AddPositionLog(this);
_plotter.AddPnLHoldTime(this);
_plotter.AddMfeMae(this);
//_plotter.AddParameters(this);
}
FitnessValue = this.CalcFitness();
}
public override void Run()
{
//========== initialization ==========
#if USE_BOOK_RANGE
StartTime = SubclassedStartTime ?? DateTime.Parse("01/01/2005", CultureInfo.InvariantCulture);
EndTime = SubclassedEndTime ?? DateTime.Parse("12/31/2018", CultureInfo.InvariantCulture);
#else
StartTime = SubclassedStartTime ?? Globals.START_TIME;
EndTime = SubclassedEndTime ?? Globals.END_TIME;
#endif
WarmupStartTime = StartTime - TimeSpan.FromDays(252);
Deposit(Globals.INITIAL_CAPITAL);
//CommissionPerShare = Globals.COMMISSION; // Connors does not consider commissions
var universe = AddDataSources(UNIVERSE);
var benchmark = AddDataSource(BENCHMARK);
//========== simulation loop ==========
foreach (var s in SimTimes)
{
if (!HasInstruments(universe) || !HasInstrument(benchmark))
{
continue;
}
// calculate momentum and volatility
var indicators = universe
.ToDictionary(
d => d.Instrument,
d => new
{
momentum = MOMENTUM(d.Instrument),
volatility = d.Instrument.Close.Volatility(63)[0],
});
// take the top 5 assets with the highest momentum
var top5 = indicators.Keys
.OrderByDescending(i => indicators[i].momentum)
.Take(5)
.ToList();
// place orders on last business day of the month
if (SimTime[0].Month != NextSimTime.Month)
{
// determine sum of the inverse volatilities
var sumInverseVol = top5
.Sum(i => 1.0 / Math.Max(1e-10, indicators[i].volatility));
foreach (var d in universe)
{
double weight = top5.Contains(d.Instrument)
? 1.0 / indicators[d.Instrument].volatility / sumInverseVol
: 0.0;
int targetShares = (int)Math.Floor(weight * NetAssetValue[0] / d.Instrument.Close[0]);
d.Instrument.Trade(targetShares - d.Instrument.Position);
}
}
if (TradingDays > 0 && !IsOptimizing)
{
_plotter.AddNavAndBenchmark(this, benchmark.Instrument);
_plotter.AddStrategyHoldings(this, universe.Select(u => u.Instrument));
}
AddSubclassedBar(10.0 * NetAssetValue[0] / Globals.INITIAL_CAPITAL);
}
//========== post processing ==========
if (!IsOptimizing)
{
//_plotter.AddTargetAllocation(_alloc);
_plotter.AddOrderLog(this);
_plotter.AddPositionLog(this);
_plotter.AddPnLHoldTime(this);
_plotter.AddMfeMae(this);
//_plotter.AddParameters(this);
}
FitnessValue = this.CalcFitness();
}
public override void Run()
{
//========== initialization ==========
#if USE_BOOK_RANGE
StartTime = SubclassedStartTime ?? DateTime.Parse("01/01/2007", CultureInfo.InvariantCulture);
EndTime = SubclassedEndTime ?? DateTime.Parse("12/31/2018", CultureInfo.InvariantCulture);
#else
StartTime = SubclassedStartTime ?? Globals.START_TIME;
EndTime = SubclassedEndTime ?? Globals.END_TIME;
#endif
WarmupStartTime = StartTime - TimeSpan.FromDays(252);
Deposit(Globals.INITIAL_CAPITAL);
//CommissionPerShare = Globals.COMMISSION; // Connors does not consider commissions
var universe = AddDataSources(UNIVERSE);
var idle = AddDataSource(IDLE_CASH);
var benchmark = AddDataSource(BENCHMARK);
//========== simulation loop ==========
foreach (var s in SimTimes)
{
if (!HasInstruments(universe) || !HasInstrument(benchmark))
{
continue;
}
var indicators = Instruments
.ToDictionary(
i => i,
i => new
{
longTermTrend = i.Close.Momentum(252)[0],
intermediateTermTrend = i.Close.Momentum(21)[0],
rsi = i.Close.RSI(2)[0],
volatility = i.Close.Volatility(100)[0]
});
// start with weights representing current positions
// note that the idle instrument is not included here
const int NUM_POS = 5;
var weights = Instruments
.ToDictionary(
i => i,
i => universe.Contains(i.DataSource) && i.Position < 0
? -1.0 / NUM_POS
: 0.0);
// exit, if RSI is below 15
foreach (var i in Instruments)
{
if (i.Position < 0.0 && indicators[i].rsi < 15)
{
weights[i] = 0.0;
}
}
// exit, if intermediate-term momentum turns positive
foreach (var i in Instruments)
{
if (i.Position < 0.0 && indicators[i].intermediateTermTrend > 0.0)
{
weights[i] = 0.0;
}
}
// determine number of new entries
var numCurrentEntries = weights
.Where(w => w.Value < 0.0)
.Count();
var numNewEntries = NUM_POS - numCurrentEntries;
// sell short, if
// - we don't have a position
// - trend filters are both negative
// - RSI is above 70
var newEntries = universe
.Select(ds => ds.Instrument)
.Where(i => i.Position == 0)
.Where(i => indicators[i].longTermTrend < 0.0 && indicators[i].intermediateTermTrend < 0.0)
.Where(i => indicators[i].rsi > 70)
.OrderByDescending(i => indicators[i].volatility)
.Take(numNewEntries)
.ToList();
foreach (var i in newEntries)
{
weights[i] = -1.0 / NUM_POS;
}
// invest in the idle instrument, if we are not planning to
// fill all slots for mean-reverting instruments
double idleWeight = ((double)numNewEntries - newEntries.Count()) / NUM_POS;
weights[idle.Instrument] = idleWeight;
// place orders
foreach (var i in Instruments)
{
int targetShares = (int)(Math.Sign(weights[i]) * Math.Floor(Math.Abs(weights[i]) * NetAssetValue[0] / i.Close[0]));
if (i != idle.Instrument)
{
// note: we don't rebalance our mean-reverting instruments
// enter positions w/ limit order
if (i.Position == 0 && targetShares != 0)
{
i.Trade(targetShares, OrderType.limitNextBar, i.Close[0] * 1.03);
}
// exit positions w/ market order
if (i.Position != 0 && targetShares == 0)
{
i.Trade(-i.Position);
}
}
else
{
// idle instrument
i.Trade(targetShares - i.Position);
}
}
if (TradingDays > 0 && !IsOptimizing)
{
_plotter.AddNavAndBenchmark(this, benchmark.Instrument);
_plotter.AddStrategyHoldings(this, universe.Select(u => u.Instrument).Concat(new List <Instrument> {
idle.Instrument
}));
}
AddSubclassedBar(10.0 * NetAssetValue[0] / Globals.INITIAL_CAPITAL);
}
//========== post processing ==========
if (!IsOptimizing)
{
//_plotter.AddTargetAllocation(_alloc);
_plotter.AddOrderLog(this);
_plotter.AddPositionLog(this);
_plotter.AddPnLHoldTime(this);
_plotter.AddMfeMae(this);
//_plotter.AddParameters(this);
}
FitnessValue = this.CalcFitness();
}
public override void Run()
{
//========== initialization ==========
#if USE_BOOK_RANGE
StartTime = SubclassedStartTime ?? DateTime.Parse("01/01/2005", CultureInfo.InvariantCulture);
EndTime = SubclassedEndTime ?? DateTime.Parse("12/31/2018", CultureInfo.InvariantCulture);
#else
StartTime = SubclassedStartTime ?? Globals.START_TIME;
EndTime = SubclassedEndTime ?? Globals.END_TIME;
#endif
WarmupStartTime = StartTime - TimeSpan.FromDays(105);
Deposit(Globals.INITIAL_CAPITAL);
//CommissionPerShare = Globals.COMMISSION; // Connors does not consider commissions
var universe = AddDataSources(UNIVERSE);
var fallback = AddDataSource(FALLBACK);
var benchmark = AddDataSource(BENCHMARK);
//========== simulation loop ==========
foreach (var s in SimTimes)
{
if (!HasInstruments(universe) || !HasInstrument(fallback) || !HasInstrument(benchmark))
{
continue;
}
if (SimTime[0].DayOfWeek > NextSimTime.DayOfWeek)
{
var weights = new Dictionary <Instrument, double>();
foreach (var ds in universe)
{
weights[ds.Instrument] = 0.0;
foreach (var l in LOOKBACKS)
{
weights[ds.Instrument] += ds.Instrument.Close[0] > ds.Instrument.Close[l]
? 0.05
: 0.0;
}
}
weights[fallback.Instrument] = 1.0 - weights.Sum(w => w.Value);
foreach (var i in weights.Keys)
{
int targetShares = (int)Math.Floor(weights[i] * NetAssetValue[0] / i.Close[0]);
i.Trade(targetShares - i.Position);
}
}
if (TradingDays > 0 && !IsOptimizing)
{
_plotter.AddNavAndBenchmark(this, benchmark.Instrument);
_plotter.AddStrategyHoldings(this, Instruments.Where(i => universe.Contains(i.DataSource) || fallback == i.DataSource));
}
AddSubclassedBar(10.0 * NetAssetValue[0] / Globals.INITIAL_CAPITAL);
}
//========== post processing ==========
if (!IsOptimizing)
{
//_plotter.AddTargetAllocation(_alloc);
_plotter.AddOrderLog(this);
_plotter.AddPositionLog(this);
_plotter.AddPnLHoldTime(this);
_plotter.AddMfeMae(this);
//_plotter.AddParameters(this);
}
FitnessValue = this.CalcFitness();
}
public override void Run()
{
//========== initialization ==========
// set simulation time frame
#if USE_CLENOWS_RANGE
// matching Clenow's charts
StartTime = DateTime.Parse("01/01/1999", CultureInfo.InvariantCulture);
WarmupStartTime = StartTime - TimeSpan.FromDays(180);
EndTime = DateTime.Parse("12/31/2014", CultureInfo.InvariantCulture);
#else
WarmupStartTime = Globals.WARMUP_START_TIME;
StartTime = Globals.START_TIME;
EndTime = Globals.END_TIME;
#endif
// set account value
Deposit(Globals.INITIAL_CAPITAL);
CommissionPerShare = Globals.COMMISSION; // Clenow is not considering commissions
// add instruments
AddDataSource(BENCHMARK);
AddDataSources(UNIVERSE.Constituents);
//========== simulation loop ==========
Instrument benchmark = null;
double? benchmark0 = null;
// loop through all bars
foreach (DateTime simTime in SimTimes)
{
benchmark = benchmark ?? FindInstrument(BENCHMARK);
if (benchmark0 == null && TradingDays == 1)
{
benchmark0 = benchmark.Open[0];
}
// calculate indicators
// store to list, to make sure indicators are evaluated
// exactly once per bar
// do this on all available instruments, to make sure we
// have valid data available when instruments become
// constituents of our universe
var instrumentIndicators = Instruments
.Select(i => new
{
instrument = i,
regression = i.Close.LogRegression(MOM_PERIOD),
maxMove = i.TrueRange().Divide(i.Close).Highest(MOM_PERIOD),
avg100 = i.Close.SMA(INSTR_FLT),
atr20 = i.AverageTrueRange(ATR_PERIOD),
})
.ToList();
// index filter: only buy any shares, while S&P-500 is trading above its 200-day moving average
// NOTE: the 10-day SMA on the benchmark is _not_ mentioned in
// the book. We added it here, to compensate for the
// simplified re-balancing schedule.
bool allowNewEntries = FindInstrument(BENCHMARK).Close.SMA(10)[0]
> FindInstrument(BENCHMARK).Close.SMA(INDEX_FLT)[0];
// trade once per week
// this is a slight simplification from Clenow's suggestion to adjust positions
// every week, and adjust position sizes only every other week
// CAUTION: no indicator calculations within this block!
if (SimTime[0].DayOfWeek <= DayOfWeek.Wednesday && NextSimTime.DayOfWeek > DayOfWeek.Wednesday)
{
// select our universe constituents
var universeConstituents = instrumentIndicators
.Where(e => e.instrument.IsConstituent(UNIVERSE))
.ToList();
// rank by volatility-adjusted momentum and pick top 20%
var topRankedInstruments = universeConstituents
.OrderByDescending(e => (Math.Exp(252.0 * e.regression.Slope[0]) - 1.0) * e.regression.R2[0])
.Take((int)Math.Round(TOP_PCNT / 100.0 * universeConstituents.Count))
.ToList();
// disqualify
// - trading below 100-day moving average
// - maximum move > 15%
var availableInstruments = topRankedInstruments
.Where(e => e.instrument.Close[0] > e.avg100[0] &&
e.maxMove[0] < MAX_MOVE / 100.0)
.ToList();
// calculate position sizes
var positionSizes = availableInstruments
.Select(e => new
{
instrument = e.instrument,
positionSize = RISK_PER_STOCK * 0.0001 / e.atr20[0] * e.instrument.Close[0],
})
.ToList();
// assign equity, until we run out of cash
var instrumentRelativeEquity = Instruments.ToDictionary(i => i, i => 0.0);
double availableEquity = 1.0;
foreach (var i in positionSizes)
{
if (i.positionSize <= availableEquity)
{
instrumentRelativeEquity[i.instrument] = i.positionSize;
availableEquity -= i.positionSize;
}
else
{
break;
}
}
// loop through all instruments and submit trades
_alloc.LastUpdate = SimTime[0];
_alloc.Allocation.Clear();
foreach (Instrument instrument in instrumentRelativeEquity.Keys)
{
if (instrumentRelativeEquity[instrument] > 0.005)
{
_alloc.Allocation[instrument] = instrumentRelativeEquity[instrument];
}
int currentShares = instrument.Position;
int targetSharesPreFilter = (int)Math.Round(NetAssetValue[0] * instrumentRelativeEquity[instrument] / instrument.Close[0]);
int targetShares = allowNewEntries
? targetSharesPreFilter
: Math.Min(currentShares, targetSharesPreFilter);
instrument.Trade(targetShares - currentShares, OrderType.openNextBar);
}
string message = instrumentRelativeEquity
.Where(i => i.Value != 0.0)
.Aggregate(string.Format("{0:MM/dd/yyyy}: ", SimTime[0]),
(prev, next) => prev + string.Format("{0}={1:P2} ", next.Key.Symbol, next.Value));
if (!IsOptimizing && (EndTime - SimTime[0]).TotalDays < 30)
{
Output.WriteLine(message);
}
}
// create plots on Sheet 1
if (TradingDays > 0)
{
#if REPRODUCE_CLENOWS_CHART
_plotter.SelectChart(Name, "date");
_plotter.SetX(SimTime[0]);
_plotter.Plot(Name, NetAssetValue[0] / INITIAL_FUNDS);
_plotter.Plot(benchmark.Name, benchmark.Close[0] / benchmark0);
_plotter.Plot(benchmark.Name + " 200-day moving average", benchmark.Close.SMA(200)[0] / benchmark0);
_plotter.Plot("Cash", Cash / NetAssetValue[0]);
#else
_plotter.AddNavAndBenchmark(this, benchmark);
//_plotter.AddStrategyHoldings(this, universeConstituents);
// plot strategy exposure
_plotter.SelectChart("Strategy Exposure", "Date");
_plotter.SetX(SimTime[0]);
_plotter.Plot("Exposure", Instruments.Sum(i => i.Position * i.Close[0]) / NetAssetValue[0]);
_plotter.Plot("Number of Stocks", (double)Positions.Count);
#endif
}
}
//========== post processing ==========
if (!IsOptimizing)
{
_plotter.AddTargetAllocation(_alloc);
_plotter.AddOrderLog(this);
_plotter.AddPositionLog(this);
_plotter.AddPnLHoldTime(this);
_plotter.AddMfeMae(this);
_plotter.AddParameters(this);
}
FitnessValue = this.CalcFitness();
}
override public void Run()
{
//========== initialization ==========
WarmupStartTime = Globals.WARMUP_START_TIME;
StartTime = Globals.START_TIME;
EndTime = Globals.END_TIME;
Deposit(Globals.INITIAL_CAPITAL);
CommissionPerShare = Globals.COMMISSION; // the book does not deduct commissions
AddDataSource(BENCHMARK);
foreach (string nick in ETF_MENU)
{
AddDataSource(nick);
}
//========== simulation loop ==========
foreach (DateTime simTime in SimTimes)
{
// calculate momentum w/ algorithm-specific helper function
var evaluation = Instruments
.ToDictionary(
i => i,
i => MOMENTUM(i));
// skip, if there are any missing instruments
// we want to make sure our strategy has all instruments available
if (!HasInstruments(ETF_MENU))
{
continue;
}
// find our trading instruments
var instruments = Instruments
.Where(i => ETF_MENU.Contains(i.Nickname));
// rank, and select top-3 instruments
const int numHold = 3;
var top3 = instruments
.OrderByDescending(i => evaluation[i])
.Take(numHold);
// calculate target percentage and how far we are off
double targetPercentage = 1.0 / numHold;
double maxOff = instruments
.Max(i => (top3.Count() > 0 && top3.Contains(i) ? 1.0 : 0.0)
* Math.Abs(i.Position * i.Close[0] / NetAssetValue[0] - targetPercentage) / targetPercentage);
// rebalance once per month, and only if we need adjustments exceeding 20%
if (SimTime[0].Month != SimTime[1].Month &&
maxOff > REBAL_TRIGGER)
{
_alloc.LastUpdate = SimTime[0];
foreach (Instrument i in instruments)
{
_alloc.Allocation[i] = top3.Contains(i) ? targetPercentage : 0.0;
// determine current and target shares per instrument...
double targetEquity = (top3.Contains(i) ? targetPercentage : 0.0) * NetAssetValue[0];
int targetShares = (int)Math.Floor(targetEquity / i.Close[0]);
int currentShares = i.Position;
// ... and trade the delta
Order newOrder = i.Trade(targetShares - currentShares);
// add a comment, to make the trading log easier to read
if (newOrder != null)
{
if (currentShares == 0)
{
newOrder.Comment = "Open";
}
else if (targetShares == 0)
{
newOrder.Comment = "Close";
}
else
{
newOrder.Comment = "Rebalance";
}
}
}
}
// plotter output
if (!IsOptimizing && TradingDays > 0)
{
_plotter.AddNavAndBenchmark(this, FindInstrument(BENCHMARK));
_plotter.AddStrategyHoldings(this, ETF_MENU.Select(nick => FindInstrument(nick)));
if (IsSubclassed)
{
AddSubclassedBar();
}
}
}
//========== post processing ==========
if (!IsOptimizing)
{
_plotter.AddTargetAllocation(_alloc);
_plotter.AddOrderLog(this);
_plotter.AddPositionLog(this);
_plotter.AddPnLHoldTime(this);
_plotter.AddMfeMae(this);
_plotter.AddParameters(this);
}
FitnessValue = this.CalcFitness();
}
public override void Run()
{
//========== initialization ==========
#if USE_BENSDORPS_RANGE
// matching range in the book
StartTime = SubclassedStartTime ?? DateTime.Parse("01/02/1995", CultureInfo.InvariantCulture);
EndTime = SubclassedEndTime ?? DateTime.Parse("11/23/2016", CultureInfo.InvariantCulture);
WarmupStartTime = StartTime - TimeSpan.FromDays(365);
#else
StartTime = SubclassedStartTime ?? Globals.START_TIME;
EndTime = SubclassedEndTime ?? Globals.END_TIME;
WarmupStartTime = Globals.WARMUP_START_TIME;
#endif
AddDataSources(UNIVERSE.Constituents);
AddDataSource(BENCHMARK);
Deposit(Globals.INITIAL_CAPITAL);
CommissionPerShare = 0.015;
var entryParameters = Enumerable.Empty <Instrument>()
.ToDictionary(
i => i,
i => new
{
entryDate = default(DateTime),
entryPrice = default(double),
stopLoss = default(double),
profitTarget = default(double),
});
//========== simulation loop ==========
foreach (var s in SimTimes)
{
//----- find instruments
_benchmark = _benchmark ?? FindInstrument(BENCHMARK);
var universe = Instruments
.Where(i => i.IsConstituent(UNIVERSE))
#if false
// we don't like to have these filter rules here. Instead,
// this should be solved by proper universe selection
.Where(i =>
i.Close[0] > 1.00 &&
i.Volume.ToDouble().SMA(50)[0] > 0.5e6 &&
i.Close.Multiply(i.Volume.ToDouble()).SMA(50)[0] > 2.5e6)
#endif
.ToList();
//----- calculate indicators
// make sure to calculate indicators for all
// known instruments, as they may enter the universe
// at any time
var indicators = Instruments
.ToDictionary(
i => i,
i => new
{
sma150 = i.Close.SMA(SMA_DAYS),
adx7 = i.ADX(7),
atr10 = i.TrueRange().Divide(i.Close).SMA(10),
rsi3 = i.Close.RSI(3),
});
// filter universe to potential candidates
var filtered = ENTRY_DIR > 0
? (universe
.Where(i => // - long -
i.Close[0] > indicators[i].sma150[0] && // close above 150-day SMA
indicators[i].adx7[0] > MIN_ADX && // 7-day ADX above 45
indicators[i].atr10[0] > MIN_ATR / 10000.0 && // 10-day ATR above 4%
indicators[i].rsi3[0] < MINMAX_RSI) // 3-day RSI below 30
.ToList())
: (universe
.Where(i => // - short -
i.Close[0] > i.Close[1] && i.Close[1] > i.Close[2] && // 2 up-days
indicators[i].adx7[0] > MIN_ADX && // 7-day ADX above 50
indicators[i].atr10[0] > MIN_ATR / 10000.0 && // 10-day ATR above 5%
indicators[i].rsi3[0] > MINMAX_RSI) // 3-day RSI above 85
.ToList());
//----- manage existing positions
int numOpenPositions = Positions.Keys.Count();
foreach (var pos in Positions.Keys)
{
// time-based exit
if (entryParameters[pos].entryDate <= SimTime[MAX_HOLD_DAYS - 1])
{
pos.Trade(-pos.Position, OrderType.closeThisBar).Comment = "time exit";
numOpenPositions--;
}
else if (ENTRY_DIR > 0
? pos.Close[0] >= entryParameters[pos].profitTarget // long
: pos.Close[0] <= entryParameters[pos].profitTarget) // short
{
pos.Trade(-pos.Position,
OrderType.openNextBar)
.Comment = "profit target";
numOpenPositions--;
}
else
{
pos.Trade(-pos.Position,
OrderType.stopNextBar,
entryParameters[pos].stopLoss)
.Comment = "stop loss";
}
}
//----- open new positions
// sort candidates by RSI to find entries
var entries = ENTRY_DIR > 0
? filtered // long
.Where(i => i.Position == 0)
.OrderBy(i => indicators[i].rsi3[0])
.Take(MAX_ENTRIES - numOpenPositions)
.ToList()
: filtered // short
.Where(i => i.Position == 0)
.OrderByDescending(i => indicators[i].rsi3[0])
.Take(MAX_ENTRIES - numOpenPositions)
.ToList();
foreach (var i in entries)
{
// save our entry parameters, so that we may access
// them later to manage exits
double entryPrice = ENTRY_DIR > 0
? i.Close[0] * (1.0 - MIN_ATR / 10000.0) // long
: i.Close[0]; // short
double stopLoss = ENTRY_DIR > 0
? entryPrice * (1.0 - STOP_LOSS / 100.0 * indicators[i].atr10[0]) // long
: entryPrice * (1.0 + STOP_LOSS / 100.0 * indicators[i].atr10[0]); // short
double profitTarget = ENTRY_DIR > 0
? entryPrice * (1.0 + PROFIT_TARGET / 10000.0) // long
: entryPrice * (1.0 - PROFIT_TARGET / 10000.0); // short
entryParameters[i] = new
{
entryDate = NextSimTime,
entryPrice,
stopLoss,
profitTarget,
};
// calculate target shares in two ways:
// * fixed-fractional risk (with entry - stop-loss = "risk"), and
// * fixed percentage of total equity
double riskPerShare = ENTRY_DIR > 0
? Math.Max(0.10, entryPrice - stopLoss) // long
: Math.Max(0.10, stopLoss - entryPrice); // short
int sharesRiskLimited = (int)Math.Floor(MAX_RISK / 100.0 / MAX_ENTRIES * NetAssetValue[0] / riskPerShare);
int sharesCapLimited = (int)Math.Floor(MAX_CAP / 100.0 / MAX_ENTRIES * NetAssetValue[0] / entryParameters[i].entryPrice);
int targetShares = (ENTRY_DIR > 0 ? 1 : -1) * Math.Min(sharesRiskLimited, sharesCapLimited);
// enter positions with limit order
i.Trade(targetShares,
OrderType.limitNextBar,
entryParameters[i].entryPrice);
}
//----- output
if (!IsOptimizing && TradingDays > 0)
{
_plotter.AddNavAndBenchmark(this, FindInstrument(BENCHMARK));
//_plotter.AddStrategyHoldings(this, universe);
// plot strategy exposure
_plotter.SelectChart("Exposure Chart", "Date");
_plotter.SetX(SimTime[0]);
_plotter.Plot("Exposure", Instruments.Sum(i => i.Position * i.Close[0]) / NetAssetValue[0]);
if (IsSubclassed)
{
AddSubclassedBar(10.0 * NetAssetValue[0] / Globals.INITIAL_CAPITAL);
}
}
}
//========== post processing ==========
if (!IsOptimizing)
{
//_plotter.AddTargetAllocation(_alloc);
//_plotter.AddOrderLog(this);
//_plotter.AddPositionLog(this);
//_plotter.AddPnLHoldTime(this);
//_plotter.AddMfeMae(this);
_plotter.AddParameters(this);
}
FitnessValue = this.CalcFitness();
}
public override void Run()
{
//----- initialization
WarmupStartTime = Globals.WARMUP_START_TIME;
StartTime = Globals.START_TIME;
EndTime = Globals.END_TIME;
Deposit(Globals.INITIAL_CAPITAL);
CommissionPerShare = Globals.COMMISSION; // paper does not consider trade commissions
AddDataSources(riskyUniverse);
AddDataSources(cashUniverse);
AddDataSources(protectiveUniverse);
AddDataSource(BENCHMARK);
//----- simulation loop
foreach (DateTime simTime in SimTimes)
{
// calculate 13612W momentum for all instruments
Dictionary <Instrument, double> momentum13612W = Instruments
.ToDictionary(
i => i,
i => 0.25 *
(12.0 * (i.Close[0] / i.Close[21] - 1.0)
+ 4.0 * (i.Close[0] / i.Close[63] - 1.0)
+ 2.0 * (i.Close[0] / i.Close[126] - 1.0)
+ 1.0 * (i.Close[0] / i.Close[252] - 1.0)));
// skip if there are any missing instruments
// we want to make sure our strategy has all instruments available
if (!HasInstruments(riskyUniverse) ||
!HasInstruments(cashUniverse) ||
!HasInstruments(protectiveUniverse))
{
continue;
}
// rebalance once per month
// CAUTION: no indicator calculations within this block!
if (SimTime[0].Month != SimTime[1].Month)
{
// find T top risky assets
IEnumerable <Instrument> topInstruments = Instruments
.Where(i => riskyUniverse.Contains(i.Nickname))
.OrderByDescending(i => momentum13612W[i])
.Take(T);
// find single cash/ bond asset
Instrument cashInstrument = Instruments
.Where(i => cashUniverse.Contains(i.Nickname))
.OrderByDescending(i => momentum13612W[i])
.First();
// determine number of bad assets in canary universe
double b = Instruments
.Where(i => protectiveUniverse.Contains(i.Nickname))
.Sum(i => momentum13612W[i] < 0.0 ? 1.0 : 0.0);
// calculate cash fraction
//double CF = Math.Min(1.0, b / B) // standard calculation
double CF = Math.Min(1.0, 1.0 / T * Math.Floor(b * T / B)); // Easy Trading
// set instrument weights
Dictionary <Instrument, double> weights = Instruments
.ToDictionary(i => i, i => 0.0);
weights[cashInstrument] = CF;
foreach (Instrument i in topInstruments)
{
weights[i] += (1.0 - CF) / T;
}
_alloc.LastUpdate = SimTime[0];
foreach (Instrument i in Instruments)
{
if (riskyUniverse.Contains(i.Nickname) || cashUniverse.Contains(i.Nickname))
{
_alloc.Allocation[i] = weights[i];
}
int targetShares = (int)Math.Floor(weights[i] * NetAssetValue[0] / i.Close[0]);
Order newOrder = i.Trade(targetShares - i.Position);
if (newOrder != null)
{
if (i.Position == 0)
{
newOrder.Comment = "open";
}
else if (targetShares == 0)
{
newOrder.Comment = "close";
}
else
{
newOrder.Comment = "rebalance";
}
}
}
}
// plotter output
if (!IsOptimizing && TradingDays > 0)
{
_plotter.AddNavAndBenchmark(this, FindInstrument(BENCHMARK));
_plotter.AddStrategyHoldings(this, Instruments
.Where(i => riskyUniverse.Contains(i.Nickname) || cashUniverse.Contains(i.Nickname)));
}
}
//----- post processing
if (!IsOptimizing)
{
_plotter.AddTargetAllocation(_alloc);
_plotter.AddOrderLog(this);
_plotter.AddPositionLog(this);
_plotter.AddPnLHoldTime(this);
_plotter.AddMfeMae(this);
_plotter.AddParameters(this);
}
FitnessValue = this.CalcFitness();
}
public override void Run()
{
//========== initialization ==========
WarmupStartTime = Globals.WARMUP_START_TIME;
StartTime = Globals.START_TIME;
EndTime = Globals.END_TIME;
Deposit(Globals.INITIAL_CAPITAL);
CommissionPerShare = Globals.COMMISSION;
var risky = RISKY_PORTFOLIO
.Select(a => Tuple.Create(AddDataSource(a.Item1), a.Item2))
.ToList();
var cash = CASH_PORTFOLIO
.Select(a => Tuple.Create(AddDataSource(a.Item1), a.Item2))
.ToList();
var universe = risky
.Select(a => a.Item1)
.Concat(cash
.Select(a => a.Item1))
.Distinct()
.ToList();
var economy = AddDataSource(ECONOMY);
var market = AddDataSource(MARKET);
var benchmark = AddDataSource(BENCHMARK);
//========== simulation loop ==========
foreach (var simTime in SimTimes)
{
// skip if there are any instruments missing from our universe
if (!HasInstruments(universe) || !HasInstrument(benchmark) || !HasInstrument(economy))
{
continue;
}
// calculate indicators
var economyLagged = economy.Instrument.Close.Delay(25); // 1 month publication lag: March observation published April 03
var economySMA = economyLagged.SMA(252);
var economyGrowing = economyLagged[0] < economySMA[0];
var marketSMA = market.Instrument.Close.SMA(200); // 10-months moving average
var marketRising = market.Instrument.Close[0] > marketSMA[0];
// trigger monthly rebalancing
if (SimTime[0].Month != NextSimTime.Month)
{
// determine target allocation: cash, if economy shrinking _and_ markets declining
var allocation = economyGrowing || marketRising
? risky
: cash;
// determine weights
var weights = universe
.Select(ds => ds.Instrument)
.ToDictionary(
i => i,
i => allocation
.Where(a => a.Item1 == i.DataSource)
.Sum(a => a.Item2));
// submit orders
_alloc.LastUpdate = SimTime[0];
foreach (var i in weights.Keys)
{
_alloc.Allocation[i] = weights[i];
var shares = (int)Math.Floor(weights[i] * NetAssetValue[0] / i.Close[0]);
i.Trade(shares - i.Position);
}
}
// plotter output
if (!IsOptimizing && TradingDays > 0)
{
_plotter.AddNavAndBenchmark(this, FindInstrument(BENCHMARK));
_plotter.AddStrategyHoldings(this, universe.Select(ds => ds.Instrument));
if (_alloc.LastUpdate == SimTime[0])
{
_plotter.AddTargetAllocationRow(_alloc);
}
#if true
// additional plotter output
_plotter.SelectChart("Unemployment Trend", "Date");
_plotter.SetX(SimTime[0]);
_plotter.Plot(economy.Instrument.Name, economyLagged[0]);
_plotter.Plot(economy.Instrument.Name + "-SMA", economySMA[0]);
_plotter.SelectChart("Market Trend", "Date");
_plotter.SetX(SimTime[0]);
_plotter.Plot(market.Instrument.Name, market.Instrument.Close[0]);
_plotter.Plot(market.Instrument.Name + "-SMA", marketSMA[0]);
#endif
}
}
//========== post processing ==========
if (!IsOptimizing)
{
_plotter.AddTargetAllocation(_alloc);
_plotter.AddOrderLog(this);
_plotter.AddPositionLog(this);
_plotter.AddPnLHoldTime(this);
_plotter.AddMfeMae(this);
_plotter.AddParameters(this);
}
FitnessValue = this.CalcFitness();
}
public override void Run()
{
//========== initialization ==========
WarmupStartTime = Globals.WARMUP_START_TIME;
StartTime = Globals.START_TIME;
EndTime = Globals.END_TIME;
Deposit(Globals.INITIAL_CAPITAL);
CommissionPerShare = Globals.COMMISSION; // Faber does not consider commissions
var assets = ASSET_CLASSES
.SelectMany(c => c.assets)
.Distinct()
.ToList();
AddDataSource(BENCHMARK);
AddDataSources(assets);
//========== simulation loop ==========
foreach (DateTime simTime in SimTimes)
{
// evaluate instrument momentum for all known instruments,
// we need to make sure to evaluate every instrument only once!
Dictionary <Instrument, double> instrumentMomentum = Instruments
.ToDictionary(i => i,
i => SCORING_FUNC(i));
// skip if there are any missing instruments,
// we want to make sure our strategy has all instruemnts available
if (!HasInstruments(assets) || !HasInstrument(BENCHMARK))
{
continue;
}
// create empty structure for instrument weights
Dictionary <Instrument, double> instrumentWeights = assets
.ToDictionary(nick => FindInstrument(nick), nick => 0.0);
// loop through all asset classes
foreach (AssetClass assetClass in ASSET_CLASSES)
{
List <Instrument> assetClassInstruments = assetClass.assets
.Select(n => FindInstrument(n))
.ToList();
var bestInstruments = assetClassInstruments
.OrderByDescending(i => instrumentMomentum[i])
.Take(assetClass.numpicks);
foreach (Instrument bestInstrument in bestInstruments)
{
instrumentWeights[bestInstrument] += assetClass.weight / assetClass.numpicks;
}
}
// execute trades once per month
if (SimTime[0].Month != SimTime[1].Month)
{
double totalWeight = ASSET_CLASSES
.Sum(a => a.weight);
double equityUnit = NetAssetValue[0] / totalWeight;
_alloc.LastUpdate = SimTime[0];
string message = string.Format("{0:MM/dd/yyyy}: ", SimTime[0]);
foreach (var i in instrumentWeights.Keys)
{
_alloc.Allocation[i] = instrumentWeights[i] / totalWeight;
message += string.Format("{0} = {1:P2}, ", i.Symbol, instrumentWeights[i]);
int targetShares = (int)Math.Floor(instrumentWeights[i] * equityUnit / i.Close[0]);
int currentShares = i.Position;
Order newOrder = i.Trade(targetShares - currentShares);
if (newOrder != null)
{
if (currentShares == 0)
{
newOrder.Comment = "open";
}
else if (targetShares == 0)
{
newOrder.Comment = "close";
}
else
{
newOrder.Comment = "rebalance";
}
}
}
if (TradingDays > 0 && !IsOptimizing && (EndTime - SimTime[0]).TotalDays < 31)
{
Output.WriteLine(message);
}
}
// plotter output
if (TradingDays > 0)
{
_plotter.AddNavAndBenchmark(this, FindInstrument(BENCHMARK));
_plotter.AddStrategyHoldings(this, assets.Select(nick => FindInstrument(nick)));
}
}
//========== post processing ==========
if (!IsOptimizing)
{
_plotter.AddTargetAllocation(_alloc);
_plotter.AddOrderLog(this);
_plotter.AddPositionLog(this);
_plotter.AddPnLHoldTime(this);
_plotter.AddMfeMae(this);
_plotter.AddParameters(this);
}
FitnessValue = this.CalcFitness();
}
public override void Run()
{
//========== initialization ==========
StartTime = Globals.START_TIME;
EndTime = Globals.END_TIME;
var universe = AddDataSources(UNIVERSE);
var safeInstrument = AddDataSource(SAFE_INSTRUMENT);
var benchmark = AddDataSource(BENCHMARK);
Deposit(Globals.INITIAL_CAPITAL);
CommissionPerShare = Globals.COMMISSION;
//========== simulation loop ==========
foreach (var s in SimTimes)
{
//----- skip until all required instruments are valid
if (!HasInstruments(universe) ||
!HasInstrument(safeInstrument) ||
!HasInstrument(benchmark))
{
continue;
}
//----- memorize our momentum
// its good practice to do this, to make sure
// indicators are only evaluated once
var momentum1 = universe
.ToDictionary(
ds => ds.Instrument,
ds => ds.Instrument.Close.Momentum(RANK1_DAYS)[0]);
var momentum2 = universe
.ToDictionary(
ds => ds.Instrument,
ds => ds.Instrument.Close.Momentum(RANK2_DAYS)[0]);
//----- rank universe by momentum
var rank1 = universe
.OrderByDescending(ds => momentum1[ds.Instrument])
.Select((ds, n) => new { instr = ds.Instrument, rank = n, mom = momentum1[ds.Instrument] })
.ToDictionary(
i => i.instr,
i => i);
var rank2 = universe
.OrderByDescending(ds => momentum2[ds.Instrument])
.Select((ds, n) => new { instr = ds.Instrument, rank = n, mom = momentum2[ds.Instrument] })
.ToDictionary(
i => i.instr,
i => i);
var rank3 = universe
.OrderBy(ds => 1.001 * rank1[ds.Instrument].rank + rank2[ds.Instrument].rank) // use rank1 as tie break
.Select((ds, n) => new { instr = ds.Instrument, rank = n, sum = 1.001 * rank1[ds.Instrument].rank + rank2[ds.Instrument].rank })
.ToDictionary(
i => i.instr,
i => i);
//----- select our 2 top ranking instruments
#if true
// this is what Cesar Alvarez seems to be describing
// in his blog post. however, the results are nowhere close
// to what he published.
var top2 = rank3
.OrderBy(i => i.Value.rank)
.Take(2)
.ToDictionary(
i => i.Key,
i => i.Value);
#else
// this is probably what Cesar Alvarez has simulated,
// as the results seem to match those published
// on the blog closely.
// this is chosing the 2 _worst_ ranked sectors,
// making this a mean-reversion strategy
var top2 = rank3
.OrderByDescending(i => i.Value.rank)
.Take(2)
.ToDictionary(
i => i.Key,
i => i.Value);
#endif
//----- assign weights
var weights = universe
.ToDictionary(
ds => ds.Instrument,
ds => top2.ContainsKey(ds.Instrument)
? (ds.Instrument.Close[0] > ds.Instrument.Close[252] ? 0.5 : 0.0)
: 0.0);
weights[safeInstrument.Instrument] = 1.0 - weights.Sum(i => i.Value);
//----- trade instruments
if (SimTime[0].Month != SimTime[1].Month)
{
foreach (var i in weights.Keys)
{
var targetShares = (int)Math.Floor(weights[i] * NetAssetValue[0] / i.Close[0]);
i.Trade(targetShares - i.Position);
}
}
//---- plot output
_plotter.AddNavAndBenchmark(this, benchmark.Instrument);
_plotter.AddStrategyHoldings(this, universe.Select(ds => ds.Instrument));
}
//========== post processing ==========
if (!IsOptimizing)
{
//_plotter.AddTargetAllocation(_alloc);
_plotter.AddOrderLog(this);
_plotter.AddPositionLog(this);
_plotter.AddPnLHoldTime(this);
_plotter.AddMfeMae(this);
//_plotter.AddParameters(this);
}
FitnessValue = this.CalcFitness();
}
public override void Run()
{
//========== initialization ==========
#if USE_BENSDORPS_RANGE
// matching range in the book
StartTime = DateTime.Parse("01/02/1995", CultureInfo.InvariantCulture);
WarmupStartTime = StartTime - TimeSpan.FromDays(365);
EndTime = DateTime.Parse("11/23/2016", CultureInfo.InvariantCulture);
#else
WarmupStartTime = Globals.WARMUP_START_TIME;
StartTime = Globals.START_TIME;
EndTime = Globals.END_TIME;
#endif
Deposit(Globals.INITIAL_CAPITAL);
CommissionPerShare = Globals.COMMISSION;
AddDataSources(UNIVERSE.Constituents);
AddDataSource(BENCHMARK);
//========== simulation loop ==========
foreach (var s in SimTimes)
{
//----- find instruments
_benchmark = _benchmark ?? FindInstrument(BENCHMARK);
var universe = Instruments
.Where(i => i.IsConstituent(UNIVERSE))
.ToList();
//----- calculate indicators
// calculate indicators for all known instruments,
// as they might enter the universe any time
var indicators = Instruments
.ToDictionary(
i => i,
i => new
{
rsi = i.Close.RSI(3),
roc = i.Close.Momentum(200),
});
var smaBand = _benchmark.Close.SMA(200).Multiply(0.98); // 2% below 200-day SMA
// filter universe to potential candidates
var filtered = universe
.Where(i => _benchmark.Close[0] > smaBand[0] &&
indicators[i].rsi[0] < MAX_RSI)
.ToList();
if (NextSimTime.DayOfWeek < SimTime[0].DayOfWeek) // open positions on Monday
{
// sort by momentum
var ranked = universe
.Where(i => _benchmark.Close[0] > smaBand[0])
.OrderByDescending(i => indicators[i].roc[0])
.ToList();
// enter: top-ranked momentum and low RSI
var entry = ranked
.Where(i => indicators[i].rsi[0] < MAX_RSI)
.Take(MAX_ENTRIES)
.ToList();
// hold: top-ranked momentum
var hold = ranked
.Take(MAX_ENTRIES)
.ToList();
// keep those we have identified as 'hold'
var nextHoldings = Instruments
.Where(i => i.Position != 0 &&
hold.Contains(i))
.ToList();
// fill up, until we reach MAX_ENTRIES
nextHoldings = nextHoldings
//.Concat(entry.Take(MAX_ENTRIES - nextHoldings.Count))
.Concat(entry.Where(i => !nextHoldings.Contains(i)).Take(MAX_ENTRIES - nextHoldings.Count))
.ToList();
_alloc.LastUpdate = SimTime[0];
_alloc.Allocation.Clear();
foreach (var i in Instruments)
{
double targetPercentage = nextHoldings.Contains(i)
? 1.0 / MAX_ENTRIES
: 0.0;
int targetShares = (int)Math.Floor(NetAssetValue[0] * targetPercentage / i.Close[0]);
if (targetPercentage != 0.0)
{
_alloc.Allocation[i] = targetPercentage;
}
i.Trade(targetShares - i.Position);
}
}
//----- output
if (!IsOptimizing && TradingDays > 0)
{
_plotter.AddNavAndBenchmark(this, FindInstrument(BENCHMARK));
//_plotter.AddStrategyHoldings(this, universe);
// plot strategy exposure
_plotter.SelectChart("Exposure Chart", "Date");
_plotter.SetX(SimTime[0]);
_plotter.Plot("Exposure", Instruments.Sum(i => i.Position * i.Close[0]) / NetAssetValue[0]);
if (IsSubclassed)
{
AddSubclassedBar();
}
}
}
//========== post processing ==========
if (!IsOptimizing)
{
_plotter.AddTargetAllocation(_alloc);
_plotter.AddOrderLog(this);
_plotter.AddPositionLog(this);
_plotter.AddPnLHoldTime(this);
_plotter.AddMfeMae(this);
_plotter.AddParameters(this);
}
FitnessValue = this.CalcFitness();
}