Folio - Examples from 'Getting Started'
|
|
|
| Type: | Portfolio optimization |
| Rating: | 3 (intermediate) |
| Description: | Different versions of a portfolio optimization problem. Basic modelling and solving tasks:
|
| File(s): | Folio.java, FolioCB.java, FolioHeuristic.java, FolioIIS.java, FolioInit.java, FolioMip1.java, FolioMip2.java, FolioMipIIS.java, FolioQC.java, FolioQP.java |
|
|
|
| Folio.java |
// (c) 2023-2025 Fair Isaac Corporation
import static com.dashoptimization.objects.Utils.scalarProduct;
import static com.dashoptimization.objects.Utils.sum;
import static java.util.stream.IntStream.range;
// These imports are only for the parser.
import java.io.File;
import java.io.IOException;
import java.nio.file.Files;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Iterator;
import java.util.stream.Stream;
import com.dashoptimization.ColumnType;
import com.dashoptimization.XPRSenumerations;
import com.dashoptimization.objects.Variable;
import com.dashoptimization.objects.XpressProblem;
/**
* Modeling a MIP problem to perform portfolio optimization. <br>
* There are a number of shares available in which to invest. The problem is to
* split the available capital between these shares to maximize return on
* investment, while satisfying certain constraints on the portfolio:
* <ul>
* <li>A maximum of 7 distinct shares can be invest in.</li>
* <li>Each share has an associated industry sector and geographic region, and
* the capital may not be overly concentrated in any one sector or region.</li>
* <li>Some of the shares are considered to be high-risk, and the maximum
* investment in these shares is limited.</li>
* </ul>
*/
public class Folio {
static final String DATAFILE = System.getenv().getOrDefault("EXAMPLE_DATA_DIR", "../../data") + "/folio10.cdat";
static final int MAXNUM = 7; /* Max. number of different assets */
static final double MAXRISK = 1.0 / 3; /* Max. investment into high-risk values */
static final double MINREG = 0.2; /* Min. investment per geogr. region */
static final double MAXREG = 0.5; /* Max. investment per geogr. region */
static final double MAXSEC = 0.25; /* Max. investment per ind. sector */
static final double MAXVAL = 0.2; /* Max. investment per share */
static final double MINVAL = 0.1; /* Min. investment per share */
static double[] RET; /* Estimated return in investment */
static int[] RISK; /* High-risk values among shares */
static boolean[][] LOC; /* Geogr. region of shares */
static boolean[][] SEC; /* Industry sector of shares */
static String[] SHARES;
static String[] REGIONS;
static String[] TYPES;
public static void main(String[] args) throws IOException {
readData(); // Read data from file
try (XpressProblem prob = new XpressProblem()) {
// Create the decision variables
// Fraction of capital used per share
Variable[] frac = prob.addVariables(SHARES.length).withUB(MAXVAL).withName("frac %d").toArray();
// 1 if asset is in portfolio, 0 otherwise
Variable[] buy = prob.addVariables(SHARES.length).withType(ColumnType.Binary).withName("buy %d").toArray();
// Objective: total return
prob.setObjective(scalarProduct(frac, RET), XPRSenumerations.ObjSense.MAXIMIZE);
// Limit the percentage of high-risk values
prob.addConstraint(sum(RISK, v -> frac[v]).leq(MAXRISK));
// Limits on geographical distribution
prob.addConstraints(REGIONS.length,
r -> sum(range(0, SHARES.length).filter(s -> LOC[r][s]).mapToObj(s -> frac[s])).in(MINREG, MAXREG));
// Diversification across industry sectors
prob.addConstraints(TYPES.length,
t -> sum(range(0, SHARES.length).filter(s -> SEC[t][s]).mapToObj(s -> frac[s])).leq(MAXSEC));
// Spend all the capital
prob.addConstraint(sum(frac).eq(1));
// Limit the total number of assets
prob.addConstraint(sum(buy).leq(MAXNUM));
// Linking the variables
for (int s = 0; s < SHARES.length; s++) {
prob.addConstraint(frac[s].leq(buy[s].mul(MAXVAL)));
prob.addConstraint(frac[s].geq(buy[s].mul(MINVAL)));
}
// Set a time limit of 10 seconds
prob.controls().setTimeLimit(10.0);
// Solve the problem
prob.optimize("");
System.out.println("Problem status: " + prob.attributes().getMIPStatus());
if (prob.attributes().getMIPStatus() != XPRSenumerations.MIPStatus.SOLUTION
&& prob.attributes().getMIPStatus() != XPRSenumerations.MIPStatus.OPTIMAL)
throw new RuntimeException("optimization failed with status " + prob.attributes().getMIPStatus());
// Solution printing
System.out.println("Total return: " + prob.attributes().getObjVal());
double[] sol = prob.getSolution();
for (int s = 0; s < SHARES.length; s++)
if (buy[s].getValue(sol) > 0.5)
System.out.println(
" " + s + ": " + frac[s].getValue(sol) * 100 + "% (" + buy[s].getValue(sol) + ")");
}
}
/**
* Read a list of strings. Iterates <code>tokens</code> until a semicolon is
* encountered or the iterator ends.
*
* @param tokens The token sequence to read.
* @return A stream of all tokens before the first semiconlon.
*/
private static <T> Stream<String> readStrings(Iterator<String> tokens) {
ArrayList<String> result = new ArrayList<String>();
while (tokens.hasNext()) {
String token = tokens.next();
if (token.equals(";"))
break;
result.add(token);
}
return result.stream();
}
/**
* Read a sparse table of booleans. Allocates a <code>nrow</code> by
* <code>ncol</code> boolean table and fills it by the sparse data from the
* token sequence. <code>tokens</code> is assumed to hold <code>nrow</code>
* sequences of indices, each of which is terminated by a semicolon. The indices
* in those vectors specify the <code>true</code> entries in the corresponding
* row of the table.
*
* @param tokens Token sequence.
* @param nrow Number of rows in the table.
* @param ncol Number of columns in the table.
* @return The boolean table.
*/
private static boolean[][] readBoolTable(Iterator<String> tokens, int nrow, int ncol) throws IOException {
boolean[][] tbl = new boolean[nrow][ncol];
for (int r = 0; r < nrow; r++) {
while (tokens.hasNext()) {
String token = tokens.next();
if (token.equals(";"))
break;
tbl[r][Integer.valueOf(token)] = true;
}
}
return tbl;
}
private static void readData() throws IOException {
// Convert the input file into a sequence of tokens that are
// separated by whitespace.
Iterator<String> tokens = Files.lines(new File(DATAFILE).toPath()).map(s -> Arrays.stream(s.split("\\s+")))
.flatMap(s -> s)
// Split semicolon off its token.
.map(s -> (s.length() > 0 && s.endsWith(";")) ? Stream.of(s.substring(0, s.length() - 1), ";")
: Stream.of(s))
.flatMap(s -> s)
// Remove empty tokens.
.filter(s -> s.length() > 0).iterator();
while (tokens.hasNext()) {
String token = tokens.next();
if (token.equals("SHARES:"))
SHARES = readStrings(tokens).toArray(String[]::new);
else if (token.equals("REGIONS:"))
REGIONS = readStrings(tokens).toArray(String[]::new);
else if (token.equals("TYPES:"))
TYPES = readStrings(tokens).toArray(String[]::new);
else if (token.equals("RISK:"))
RISK = readStrings(tokens).mapToInt(Integer::valueOf).toArray();
else if (token.equals("RET:"))
RET = readStrings(tokens).mapToDouble(Double::valueOf).toArray();
else if (token.equals("LOC:"))
LOC = readBoolTable(tokens, REGIONS.length, SHARES.length);
else if (token.equals("SEC:"))
SEC = readBoolTable(tokens, TYPES.length, SHARES.length);
}
}
}
|
| FolioCB.java |
// (c) 2023-2025 Fair Isaac Corporation
import static com.dashoptimization.objects.Utils.scalarProduct;
import static com.dashoptimization.objects.Utils.sum;
import static java.util.stream.IntStream.range;
// These imports are only for the parser.
import java.io.File;
import java.io.IOException;
import java.nio.file.Files;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Iterator;
import java.util.stream.Stream;
import com.dashoptimization.ColumnType;
import com.dashoptimization.DefaultMessageListener;
import com.dashoptimization.XPRSenumerations;
import com.dashoptimization.objects.Variable;
import com.dashoptimization.objects.XpressProblem;
/**
* Modeling a MIP problem to perform portfolio optimization. -- Defining an
* integer solution callback --
*/
public class FolioCB {
/* Path to Data file */
private static final String DATAFILE = System.getenv().getOrDefault("EXAMPLE_DATA_DIR", "../../data")
+ "/folio10.cdat";
private static final int MAXNUM = 15; /* Max. number of different assets */
private static final double MAXRISK = 1.0 / 3; /* Max. investment into high-risk values */
private static final double MINREG = 0.2; /* Min. investment per geogr. region */
private static final double MAXREG = 0.5; /* Max. investment per geogr. region */
private static final double MAXSEC = 0.25; /* Max. investment per ind. sector */
private static final double MAXVAL = 0.2; /* Max. investment per share */
private static final double MINVAL = 0.1; /* Min. investment per share */
private static double[] RET; /* Estimated return in investment */
private static int[] RISK; /* High-risk values among shares */
private static boolean[][] LOC; /* Geogr. region of shares */
private static boolean[][] SEC; /* Industry sector of shares */
private static String[] SHARES;
private static String[] REGIONS;
private static String[] TYPES;
/* Fraction of capital used per share */
private static Variable[] frac;
/* 1 if asset is in portfolio, 0 otherwise */
private static Variable[] buy;
private static void printProblemStatus(XpressProblem prob) {
System.out.println(String.format("Problem status:%n\tSolve status: %s%n\tSol status: %s",
prob.attributes().getSolveStatus(), prob.attributes().getSolStatus()));
}
private static void printProblemSolution(XpressProblem prob) {
double[] sol = prob.getSolution();
System.out.println("Total return: " + prob.attributes().getObjVal());
range(0, SHARES.length).forEach(i -> {
if (buy[i].getValue(sol) > 0.5)
System.out.println(String.format("%d: %.2f%s (%.1f)", i, 100.0 * frac[i].getValue(sol), "%",
buy[i].getValue(sol)));
});
}
public static void main(String[] args) throws IOException {
readData();
try (XpressProblem prob = new XpressProblem()) {
// Output all messages.
prob.callbacks.addMessageCallback(DefaultMessageListener::console);
/**** VARIABLES ****/
frac = prob.addVariables(SHARES.length)
/* Fraction of capital used per share */
.withName(i -> String.format("frac_%d", i))
/* Upper bounds on the investment per share */
.withUB(MAXVAL).toArray();
buy = prob.addVariables(SHARES.length).withName(i -> String.format("buy_%d", i)).withType(ColumnType.Binary)
.toArray();
/**** CONSTRAINTS ****/
/* Limit the percentage of high-risk values */
prob.addConstraint(sum(RISK.length, i -> frac[RISK[i]]).leq(MAXRISK).setName("Risk"));
/* Limits on geographical distribution */
prob.addConstraints(REGIONS.length,
r -> sum(range(0, SHARES.length).filter(s -> LOC[r][s]).mapToObj(s -> frac[s])).in(MINREG, MAXREG));
/* Diversification across industry sectors */
prob.addConstraints(TYPES.length,
t -> sum(range(0, SHARES.length).filter(s -> SEC[t][s]).mapToObj(s -> frac[s])).leq(MAXSEC));
/* Spend all the capital */
prob.addConstraint(sum(frac).eq(1.0).setName("Cap"));
/* Limit the total number of assets */
prob.addConstraint(sum(buy).leq(MAXNUM).setName("MaxAssets"));
/* Linking the variables */
prob.addConstraints(SHARES.length,
i -> frac[i].geq(buy[i].mul(MINVAL)).setName(String.format("link_lb_%d", i)));
prob.addConstraints(SHARES.length,
i -> frac[i].leq(buy[i].mul(MAXVAL)).setName(String.format("link_ub_%d", i)));
/* Objective: maximize total return */
prob.setObjective(scalarProduct(frac, RET), XPRSenumerations.ObjSense.MAXIMIZE);
/* Callback for each new integer solution found */
prob.callbacks.addIntSolCallback(p -> {
printProblemSolution(prob);
});
/* Solve */
prob.optimize();
/* Solution printing */
printProblemStatus(prob);
printProblemSolution(prob);
}
}
/**
* Read a list of strings. Iterates <code>tokens</code> until a semicolon is
* encountered or the iterator ends.
*
* @param tokens The token sequence to read.
* @return A stream of all tokens before the first semiconlon.
*/
private static <T> Stream<String> readStrings(Iterator<String> tokens) {
ArrayList<String> result = new ArrayList<String>();
while (tokens.hasNext()) {
String token = tokens.next();
if (token.equals(";"))
break;
result.add(token);
}
return result.stream();
}
/**
* Read a sparse table of booleans. Allocates a <code>nrow</code> by
* <code>ncol</code> boolean table and fills it by the sparse data from the
* token sequence. <code>tokens</code> is assumed to hold <code>nrow</code>
* sequences of indices, each of which is terminated by a semicolon. The indices
* in those vectors specify the <code>true</code> entries in the corresponding
* row of the table.
*
* @param tokens Token sequence.
* @param nrow Number of rows in the table.
* @param ncol Number of columns in the table.
* @return The boolean table.
*/
private static boolean[][] readBoolTable(Iterator<String> tokens, int nrow, int ncol) throws IOException {
boolean[][] tbl = new boolean[nrow][ncol];
for (int r = 0; r < nrow; r++) {
while (tokens.hasNext()) {
String token = tokens.next();
if (token.equals(";"))
break;
tbl[r][Integer.valueOf(token)] = true;
}
}
return tbl;
}
private static void readData() throws IOException {
// Convert the input file into a sequence of tokens that are
// separated by whitespace.
Iterator<String> tokens = Files.lines(new File(DATAFILE).toPath()).map(s -> Arrays.stream(s.split("\\s+")))
.flatMap(s -> s)
// Split semicolon off its token.
.map(s -> (s.length() > 0 && s.endsWith(";")) ? Stream.of(s.substring(0, s.length() - 1), ";")
: Stream.of(s))
.flatMap(s -> s)
// Remove empty tokens.
.filter(s -> s.length() > 0).iterator();
while (tokens.hasNext()) {
String token = tokens.next();
if (token.equals("SHARES:"))
SHARES = readStrings(tokens).toArray(String[]::new);
else if (token.equals("REGIONS:"))
REGIONS = readStrings(tokens).toArray(String[]::new);
else if (token.equals("TYPES:"))
TYPES = readStrings(tokens).toArray(String[]::new);
else if (token.equals("RISK:"))
RISK = readStrings(tokens).mapToInt(Integer::valueOf).toArray();
else if (token.equals("RET:"))
RET = readStrings(tokens).mapToDouble(Double::valueOf).toArray();
else if (token.equals("LOC:"))
LOC = readBoolTable(tokens, REGIONS.length, SHARES.length);
else if (token.equals("SEC:"))
SEC = readBoolTable(tokens, TYPES.length, SHARES.length);
}
}
}
|
| FolioHeuristic.java |
// (c) 2023-2025 Fair Isaac Corporation
import static com.dashoptimization.objects.Utils.scalarProduct;
import static com.dashoptimization.objects.Utils.sum;
import static java.util.stream.IntStream.range;
import com.dashoptimization.ColumnType;
import com.dashoptimization.DefaultMessageListener;
import com.dashoptimization.XPRSconstants;
import com.dashoptimization.XPRSenumerations;
import com.dashoptimization.objects.Variable;
import com.dashoptimization.objects.XpressProblem;
/**
* Modeling a small LP problem to perform portfolio optimization. -- Heuristic
* solution --
*/
public class FolioHeuristic {
/* Max. number of different assets */
private static final int MAXNUM = 4;
/* Number of shares */
private static final int NSHARES = 10;
/* Number of high-risk shares */
private static final int NRISK = 5;
/* Number of North-American shares */
private static final int NNA = 4;
/* Estimated return in investment */
private static final double[] RET = new double[] { 5, 17, 26, 12, 8, 9, 7, 6, 31, 21 };
/* High-risk values among shares */
private static final int[] RISK = new int[] { 1, 2, 3, 8, 9 };
/* Shares issued in N.-America */
private static final int[] NA = new int[] { 0, 1, 2, 3 };
public XpressProblem prob;
/* Fraction of capital used per share */
public Variable[] frac;
/* 1 if asset is in portfolio, 0 otherwise */
public Variable[] buy;
public FolioHeuristic(XpressProblem p) {
prob = p;
/**** VARIABLES ****/
frac = prob.addVariables(NSHARES)
/* Fraction of capital used per share */
.withName(i -> String.format("frac_%d", i))
/* Upper bounds on the investment per share */
.withUB(0.3).toArray();
buy = prob.addVariables(NSHARES)
/* Fraction of capital used per share */
.withName(i -> String.format("buy_%d", i)).withType(ColumnType.Binary).toArray();
}
private static void printProblemStatus(XpressProblem prob) {
System.out.println(String.format(
"Problem status:%n\tSolve status: %s%n\tLP status: %s%n\tMIP status: %s%n\tSol status: %s",
prob.attributes().getSolveStatus(), prob.attributes().getLPStatus(), prob.attributes().getMIPStatus(),
prob.attributes().getSolStatus()));
}
private static void printProblemSolution(FolioHeuristic folio, String solveFlag) {
XpressProblem prob = folio.prob;
System.out.println(String.format("Total return (%s): %s", solveFlag, prob.attributes().getObjVal()));
double[] sol = prob.getSolution();
range(0, NSHARES).forEach(i -> System.out.println(String.format("%s: %.2f%s (%.1f)", folio.frac[i].getName(),
100.0 * folio.frac[i].getValue(sol), "%", folio.buy[i].getValue(sol))));
}
private static void model(FolioHeuristic folio) {
XpressProblem prob = folio.prob;
// Output all messages.
prob.callbacks.addMessageCallback(DefaultMessageListener::console);
/**** CONSTRAINTS ****/
/* Limit the percentage of high-risk values */
prob.addConstraint(sum(NRISK, i -> folio.frac[RISK[i]]).leq(1.0 / 3.0).setName("Risk"));
/* Minimum amount of North-American values */
prob.addConstraint(sum(NNA, i -> folio.frac[NA[i]]).geq(0.5).setName("NA"));
/* Spend all the capital */
prob.addConstraint(sum(folio.frac).eq(1.0).setName("Cap"));
/* Limit the total number of assets */
prob.addConstraint(sum(folio.buy).leq(MAXNUM).setName("MaxAssets"));
/* Linking the variables */
prob.addConstraints(NSHARES, i -> folio.frac[i].leq(folio.buy[i]).setName(String.format("link_%d", i)));
/* Objective: maximize total return */
prob.setObjective(scalarProduct(folio.frac, RET), XPRSenumerations.ObjSense.MAXIMIZE);
}
private static void solveHeuristic(FolioHeuristic folio) {
XpressProblem p = folio.prob;
/* Disable automatic cuts */
p.controls().setCutStrategy(XPRSconstants.CUTSTRATEGY_NONE);
// Switch presolve off
p.controls().setPresolve(XPRSconstants.PRESOLVE_NONE);
p.controls().setMIPPresolve(0);
/* Get feasibility tolerance */
double tol = p.controls().getFeasTol();
/* Solve the LP-problem */
p.lpOptimize();
/* Get Solution */
double[] sol = p.getSolution();
/* Basis information */
int[] rowstat = new int[p.attributes().getRows()];
int[] colstat = new int[p.attributes().getCols()];
/* Save the current basis */
p.getBasis(rowstat, colstat);
/*
* Fix all variables `buy' for which `frac' is at 0 or at a relatively large
* value
*/
double[] fsol = new double[NSHARES];
range(0, NSHARES).forEach(i -> {
/* Get the solution values of `frac' */
fsol[i] = folio.frac[i].getValue(sol);
if (fsol[i] < tol)
folio.buy[i].fix(0);
else if (fsol[i] > 0.2 - tol)
folio.buy[i].fix(1);
});
/* Solve with the new bounds on 'buy' */
p.mipOptimize();
printProblemStatus(p);
printProblemSolution(folio, "Heuristic solution");
/* Reset variables to their original bounds */
range(0, NSHARES).forEach(i -> {
if ((fsol[i] < tol) || (fsol[i] > 0.2 - tol)) {
folio.buy[i].setLB(0);
folio.buy[i].setUB(1);
}
});
/* Load basis */
p.loadBasis(rowstat, colstat);
}
public static void main(String[] args) {
try (XpressProblem prob = new XpressProblem()) {
/* Solve with heuristic */
FolioHeuristic folio = new FolioHeuristic(prob);
model(folio);
solveHeuristic(folio);
}
try (XpressProblem prob = new XpressProblem()) {
FolioHeuristic folio = new FolioHeuristic(prob);
model(folio);
/* Solve */
folio.prob.optimize();
/* Solution printing */
printProblemStatus(prob);
printProblemSolution(folio, "Exact Solve");
}
}
}
|
| FolioIIS.java |
// (c) 2023-2025 Fair Isaac Corporation
import static com.dashoptimization.objects.Utils.scalarProduct;
import static com.dashoptimization.objects.Utils.sum;
import static java.util.stream.IntStream.range;
// These imports are only for the parser.
import java.io.File;
import java.io.IOException;
import java.nio.file.Files;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Iterator;
import java.util.stream.Stream;
import com.dashoptimization.ColumnType;
import com.dashoptimization.DefaultMessageListener;
import com.dashoptimization.XPRSenumerations;
import com.dashoptimization.XPRSprob.IISStatusInfo;
import com.dashoptimization.objects.IIS;
import com.dashoptimization.objects.IISConstraint;
import com.dashoptimization.objects.IISVariable;
import com.dashoptimization.objects.LinExpression;
import com.dashoptimization.objects.Variable;
import com.dashoptimization.objects.XpressProblem;
/**
* Modeling a MIP problem to perform portfolio optimization.
* Used infeasible model parameter values and illustrates retrieving IIS.
*/
public class FolioIIS {
/* Path to Data file */
private static final String DATAFILE = System.getenv().getOrDefault("EXAMPLE_DATA_DIR", "../../data")
+ "/folio10.cdat";
private static final int MAXNUM = 5; /* Max. number of different assets */
private static final double MAXRISK = 1.0 / 3; /* Max. investment into high-risk values */
private static final double MINREG = 0.1; /* Min. investment per geogr. region */
private static final double MAXREG = 0.2; /* Max. investment per geogr. region */
private static final double MAXSEC = 0.1; /* Max. investment per ind. sector */
private static final double MAXVAL = 0.2; /* Max. investment per share */
private static final double MINVAL = 0.1; /* Min. investment per share */
private static double[] RET; /* Estimated return in investment */
private static int[] RISK; /* High-risk values among shares */
private static boolean[][] LOC; /* Geogr. region of shares */
private static boolean[][] SEC; /* Industry sector of shares */
private static String[] SHARES;
private static String[] REGIONS;
private static String[] TYPES;
/* Fraction of capital used per share */
private static Variable[] frac;
/* 1 if asset is in portfolio, 0 otherwise */
private static Variable[] buy;
private static void printProblemStatus(XpressProblem prob) {
System.out.println(String.format("Problem status:%n\tSolve status: %s%n\tLP status: %s%n\tSol status: %s",
prob.attributes().getSolveStatus(), prob.attributes().getLPStatus(), prob.attributes().getSolStatus()));
}
public static void main(String[] args) throws IOException {
readData();
try (XpressProblem prob = new XpressProblem()) {
// Output all messages.
prob.callbacks.addMessageCallback(DefaultMessageListener::console);
/**** VARIABLES ****/
frac = prob.addVariables(SHARES.length)
/* Fraction of capital used per share */
.withName(i -> String.format("frac_%s", SHARES[i]))
/* Upper bounds on the investment per share */
.withUB(MAXVAL).toArray();
buy = prob.addVariables(SHARES.length).withName(i -> String.format("buy_%s", SHARES[i]))
.withType(ColumnType.Binary).toArray();
/**** CONSTRAINTS ****/
/* Limit the percentage of high-risk values */
prob.addConstraint(sum(RISK.length, i -> frac[RISK[i]]).leq(MAXRISK).setName("Risk"));
/* Limits on geographical distribution */
range(0, REGIONS.length).forEach(r -> {
LinExpression MinReg = LinExpression.create();
LinExpression MaxReg = LinExpression.create();
range(0, SHARES.length).filter(s -> LOC[r][s]).forEach(s -> MinReg.addTerm(frac[s]));
range(0, SHARES.length).filter(s -> LOC[r][s]).forEach(s -> MaxReg.addTerm(frac[s]));
prob.addConstraint(MinReg.geq(MINREG).setName("MinReg(" + REGIONS[r] + ")"));
prob.addConstraint(MaxReg.leq(MAXREG).setName("MaxReg(" + REGIONS[r] + ")"));
});
/* Diversification across industry sectors */
range(0, TYPES.length).forEach(t -> {
LinExpression LimSec = LinExpression.create();
range(0, SHARES.length).filter(s -> SEC[t][s]).forEach(s -> LimSec.addTerm(frac[s]));
prob.addConstraint(LimSec.leq(MAXSEC).setName("LimSec(" + TYPES[t] + ")"));
});
/* Spend all the capital */
prob.addConstraint(sum(frac).eq(1.0).setName("Cap"));
/* Limit the total number of assets */
prob.addConstraint(sum(buy).leq(MAXNUM).setName("MaxAssets"));
/* Linking the variables */
prob.addConstraints(SHARES.length,
i -> frac[i].geq(buy[i].mul(MINVAL)).setName(String.format("link_lb_%d", i)));
prob.addConstraints(SHARES.length,
i -> frac[i].leq(buy[i].mul(MAXVAL)).setName(String.format("link_ub_%d", i)));
/* Objective: maximize total return */
prob.setObjective(scalarProduct(frac, RET), XPRSenumerations.ObjSense.MAXIMIZE);
/* Solve */
prob.optimize();
/* Solution printing */
printProblemStatus(prob);
if (prob.attributes().getSolStatus() == XPRSenumerations.SolStatus.INFEASIBLE) {
System.out.println("LP infeasible. Retrieving IIS.");
// Check there is at least one IIS
int status = prob.firstIIS(1);
if (status != 0)
throw new RuntimeException("firstIIS() failed with status " + status);
int iisIndex = 1; // First IIS has index 1
do {
IISStatusInfo info = prob.IISStatus();
System.out.println(String.format(
"IIS has %d constraints and %d columns, %d infeasibilities with an infeasibility of %f%n",
info.rowsizes[iisIndex], info.colsizes[iisIndex], info.numinfeas[iisIndex],
info.suminfeas[iisIndex]));
IIS data = prob.getIIS(iisIndex);
System.out.println("Variables in IIS:");
for (IISVariable v : data.getVariables()) {
// Note that the IISVariable class has more fields than
// we print here. See the reference documentation for
// details.
System.out.printf("\t%s %s%n", v.getVariable().getName(), v.getDomain());
}
System.out.println("Constraints in IIS:");
for (IISConstraint c : data.getConstraints()) {
// Note that the IISVariable class has more fields than
// we print here. See the reference documentation for
// details.
System.out.printf("\t%s%n", c.getConstraint().getName());
}
++iisIndex; // Prepare for next IIS (if any)
} while (prob.nextIIS() == 0);
}
}
}
/**
* Read a list of strings. Iterates <code>tokens</code> until a semicolon is
* encountered or the iterator ends.
*
* @param tokens The token sequence to read.
* @return A stream of all tokens before the first semiconlon.
*/
private static <T> Stream<String> readStrings(Iterator<String> tokens) {
ArrayList<String> result = new ArrayList<String>();
while (tokens.hasNext()) {
String token = tokens.next();
if (token.equals(";"))
break;
result.add(token);
}
return result.stream();
}
/**
* Read a sparse table of booleans. Allocates a <code>nrow</code> by
* <code>ncol</code> boolean table and fills it by the sparse data from the
* token sequence. <code>tokens</code> is assumed to hold <code>nrow</code>
* sequences of indices, each of which is terminated by a semicolon. The indices
* in those vectors specify the <code>true</code> entries in the corresponding
* row of the table.
*
* @param tokens Token sequence.
* @param nrow Number of rows in the table.
* @param ncol Number of columns in the table.
* @return The boolean table.
*/
private static boolean[][] readBoolTable(Iterator<String> tokens, int nrow, int ncol) throws IOException {
boolean[][] tbl = new boolean[nrow][ncol];
for (int r = 0; r < nrow; r++) {
while (tokens.hasNext()) {
String token = tokens.next();
if (token.equals(";"))
break;
tbl[r][Integer.valueOf(token)] = true;
}
}
return tbl;
}
private static void readData() throws IOException {
// Convert the input file into a sequence of tokens that are
// separated by whitespace.
Iterator<String> tokens = Files.lines(new File(DATAFILE).toPath()).map(s -> Arrays.stream(s.split("\\s+")))
.flatMap(s -> s)
// Split semicolon off its token.
.map(s -> (s.length() > 0 && s.endsWith(";")) ? Stream.of(s.substring(0, s.length() - 1), ";")
: Stream.of(s))
.flatMap(s -> s)
// Remove empty tokens.
.filter(s -> s.length() > 0).iterator();
while (tokens.hasNext()) {
String token = tokens.next();
if (token.equals("SHARES:"))
SHARES = readStrings(tokens).toArray(String[]::new);
else if (token.equals("REGIONS:"))
REGIONS = readStrings(tokens).toArray(String[]::new);
else if (token.equals("TYPES:"))
TYPES = readStrings(tokens).toArray(String[]::new);
else if (token.equals("RISK:"))
RISK = readStrings(tokens).mapToInt(Integer::valueOf).toArray();
else if (token.equals("RET:"))
RET = readStrings(tokens).mapToDouble(Double::valueOf).toArray();
else if (token.equals("LOC:"))
LOC = readBoolTable(tokens, REGIONS.length, SHARES.length);
else if (token.equals("SEC:"))
SEC = readBoolTable(tokens, TYPES.length, SHARES.length);
}
}
}
|
| FolioInit.java |
// (c) 2023-2025 Fair Isaac Corporation
import static com.dashoptimization.objects.Utils.scalarProduct;
import static com.dashoptimization.objects.Utils.sum;
import static java.util.stream.IntStream.range;
import com.dashoptimization.DefaultMessageListener;
import com.dashoptimization.XPRSenumerations;
import com.dashoptimization.objects.Variable;
import com.dashoptimization.objects.XpressProblem;
/** Modeling a small LP problem to perform portfolio optimization. */
public class FolioInit {
/* Number of shares */
private static final int NSHARES = 10;
/* Number of high-risk shares */
private static final int NRISK = 5;
/* Number of North-American shares */
private static final int NNA = 4;
/* Estimated return in investment */
private static final double[] RET = new double[] { 5, 17, 26, 12, 8, 9, 7, 6, 31, 21 };
/* High-risk values among shares */
private static final int[] RISK = new int[] { 1, 2, 3, 8, 9 };
/* Shares issued in N.-America */
private static final int[] NA = new int[] { 0, 1, 2, 3 };
private static void printProblemStatus(XpressProblem prob) {
System.out.println(String.format("Problem status:%n\tSolve status: %s%n\tSol status: %s",
prob.attributes().getSolveStatus(), prob.attributes().getSolStatus()));
}
public static void main(String[] args) {
try (XpressProblem prob = new XpressProblem()) {
// Output all messages.
prob.callbacks.addMessageCallback(DefaultMessageListener::console);
/**** VARIABLES ****/
Variable[] frac = prob.addVariables(NSHARES)
/* Fraction of capital used per share */
.withName(i -> String.format("frac_%d", i))
/* Upper bounds on the investment per share */
.withUB(0.3).toArray();
/**** CONSTRAINTS ****/
/* Limit the percentage of high-risk values */
prob.addConstraint(sum(NRISK, i -> frac[RISK[i]]).leq(1.0 / 3.0).setName("Risk"));
/* Minimum amount of North-American values */
prob.addConstraint(sum(NNA, i -> frac[NA[i]]).geq(0.5).setName("NA"));
/* Spend all the capital */
prob.addConstraint(sum(frac).eq(1.0).setName("Cap"));
/* Objective: maximize total return */
prob.setObjective(scalarProduct(frac, RET), XPRSenumerations.ObjSense.MAXIMIZE);
/* Solve */
prob.optimize();
/* Solution printing */
printProblemStatus(prob);
System.out.println("Total return: " + prob.attributes().getObjVal());
double[] sol = prob.getSolution();
range(0, NSHARES).forEach(i -> System.out
.println(String.format("%s : %.2f%s", frac[i].getName(), 100.0 * frac[i].getValue(sol), "%")));
}
}
}
|
| FolioMip1.java |
// (c) 2023-2025 Fair Isaac Corporation
import static com.dashoptimization.objects.Utils.scalarProduct;
import static com.dashoptimization.objects.Utils.sum;
import static java.util.stream.IntStream.range;
import com.dashoptimization.ColumnType;
import com.dashoptimization.DefaultMessageListener;
import com.dashoptimization.XPRSenumerations;
import com.dashoptimization.objects.Variable;
import com.dashoptimization.objects.XpressProblem;
/**
* Modeling a small LP problem to perform portfolio optimization. -- Limiting
* the total number of assets --
*/
public class FolioMip1 {
/* Max. number of different assets */
private static final int MAXNUM = 4;
/* Number of shares */
private static final int NSHARES = 10;
/* Number of high-risk shares */
private static final int NRISK = 5;
/* Number of North-American shares */
private static final int NNA = 4;
/* Estimated return in investment */
private static final double[] RET = new double[] { 5, 17, 26, 12, 8, 9, 7, 6, 31, 21 };
/* High-risk values among shares */
private static final int[] RISK = new int[] { 1, 2, 3, 8, 9 };
/* Shares issued in N.-America */
private static final int[] NA = new int[] { 0, 1, 2, 3 };
private static void printProblemStatus(XpressProblem prob) {
System.out.println(String.format("Problem status:%n\tSolve status: %s%n\tSol status: %s",
prob.attributes().getSolveStatus(), prob.attributes().getSolStatus()));
}
public static void main(String[] args) {
try (XpressProblem prob = new XpressProblem()) {
// Output all messages.
prob.callbacks.addMessageCallback(DefaultMessageListener::console);
/**** VARIABLES ****/
Variable[] frac = prob.addVariables(NSHARES)
/* Fraction of capital used per share */
.withName(i -> String.format("frac_%d", i))
/* Upper bounds on the investment per share */
.withUB(0.3).toArray();
Variable[] buy = prob.addVariables(NSHARES)
/* Fraction of capital used per share */
.withName(i -> String.format("buy_%d", i)).withType(ColumnType.Binary).toArray();
/**** CONSTRAINTS ****/
/* Limit the percentage of high-risk values */
prob.addConstraint(sum(NRISK, i -> frac[RISK[i]]).leq(1.0 / 3.0).setName("Risk"));
/* Minimum amount of North-American values */
prob.addConstraint(sum(NNA, i -> frac[NA[i]]).geq(0.5).setName("NA"));
/* Spend all the capital */
prob.addConstraint(sum(frac).eq(1.0).setName("Cap"));
/* Limit the total number of assets */
prob.addConstraint(sum(buy).leq(MAXNUM).setName("MaxAssets"));
/* Linking the variables */
/* frac .<= buy */
prob.addConstraints(NSHARES, i -> frac[i].leq(buy[i]).setName(String.format("link_%d", i)));
/* Objective: maximize total return */
prob.setObjective(scalarProduct(frac, RET), XPRSenumerations.ObjSense.MAXIMIZE);
/* Solve */
prob.optimize();
/* Solution printing */
printProblemStatus(prob);
System.out.println("Total return: " + prob.attributes().getObjVal());
double[] sol = prob.getSolution();
range(0, NSHARES).forEach(i -> System.out.println(String.format("%s : %.2f%s (%.1f)", frac[i].getName(),
100.0 * frac[i].getValue(sol), "%", buy[i].getValue(sol))));
}
}
}
|
| FolioMip2.java |
// (c) 2023-2025 Fair Isaac Corporation
import static com.dashoptimization.objects.Utils.scalarProduct;
import static com.dashoptimization.objects.Utils.sum;
import static java.util.stream.IntStream.range;
import com.dashoptimization.ColumnType;
import com.dashoptimization.DefaultMessageListener;
import com.dashoptimization.XPRSenumerations;
import com.dashoptimization.objects.Variable;
import com.dashoptimization.objects.XpressProblem;
/**
* Modeling a small LP problem to perform portfolio optimization. -- Imposing a
* minimum investment per share --
*/
public class FolioMip2 {
/* Number of shares */
private static final int NSHARES = 10;
/* Number of high-risk shares */
private static final int NRISK = 5;
/* Number of North-American shares */
private static final int NNA = 4;
/* Estimated return in investment */
private static final double[] RET = new double[] { 5, 17, 26, 12, 8, 9, 7, 6, 31, 21 };
/* High-risk values among shares */
private static final int[] RISK = new int[] { 1, 2, 3, 8, 9 };
/* Shares issued in N.-America */
private static final int[] NA = new int[] { 0, 1, 2, 3 };
private static void printProblemStatus(XpressProblem prob) {
System.out.println(String.format("Problem status:%n\tSolve status: %s%n\tSol status: %s",
prob.attributes().getSolveStatus(), prob.attributes().getSolStatus()));
}
public static void main(String[] args) {
try (XpressProblem prob = new XpressProblem()) {
// Output all messages.
prob.callbacks.addMessageCallback(DefaultMessageListener::console);
/**** VARIABLES ****/
Variable[] frac = prob.addVariables(NSHARES)
/* Fraction of capital used per share */
.withName(i -> String.format("frac_%d", i)).withType(ColumnType.SemiContinuous)
/* Upper bounds on the investment per share */
.withUB(0.3)
/* Investment limit */
.withLimit(0.1).toArray();
/**** CONSTRAINTS ****/
/* Limit the percentage of high-risk values */
prob.addConstraint(sum(NRISK, i -> frac[RISK[i]]).leq(1.0 / 3.0).setName("Risk"));
/* Minimum amount of North-American values */
prob.addConstraint(sum(NNA, i -> frac[NA[i]]).geq(0.5).setName("NA"));
/* Spend all the capital */
prob.addConstraint(sum(frac).eq(1.0).setName("Cap"));
/* Objective: maximize total return */
prob.setObjective(scalarProduct(frac, RET), XPRSenumerations.ObjSense.MAXIMIZE);
/* Solve */
prob.optimize();
/* Solution printing */
printProblemStatus(prob);
System.out.println("Total return: " + prob.attributes().getObjVal());
double[] sol = prob.getSolution();
range(0, NSHARES).forEach(i -> System.out
.println(String.format("%s : %.2f%s", frac[i].getName(), 100.0 * frac[i].getValue(sol), "%")));
}
}
}
|
| FolioMipIIS.java |
// (c) 2023-2025 Fair Isaac Corporation
import static com.dashoptimization.objects.Utils.scalarProduct;
import static com.dashoptimization.objects.Utils.sum;
import static java.util.stream.IntStream.range;
// These imports are only for the parser.
import java.io.File;
import java.io.IOException;
import java.nio.file.Files;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Iterator;
import java.util.stream.Stream;
import com.dashoptimization.ColumnType;
import com.dashoptimization.DefaultMessageListener;
import com.dashoptimization.XPRSenumerations;
import com.dashoptimization.XPRSprob.IISStatusInfo;
import com.dashoptimization.objects.IIS;
import com.dashoptimization.objects.IISConstraint;
import com.dashoptimization.objects.IISVariable;
import com.dashoptimization.objects.Variable;
import com.dashoptimization.objects.XpressProblem;
/**
* Modeling a MIP problem to perform portfolio optimization.
* Same model as in FolioMip3.java.
* Uses infeasible model parameter values and illustrates retrieving MIIS.
*/
public class FolioMipIIS {
/* Path to Data file */
private static final String DATAFILE = System.getenv().getOrDefault("EXAMPLE_DATA_DIR", "../../data")
+ "/folio10.cdat";
private static final int MAXNUM = 5; /* Max. number of different assets */
private static final double MAXRISK = 1.0 / 4; /* Max. investment into high-risk values */
private static final double MINREG = 0.1; /* Min. investment per geogr. region */
private static final double MAXREG = 0.25; /* Max. investment per geogr. region */
private static final double MAXSEC = 0.15; /* Max. investment per ind. sector */
private static final double MAXVAL = 0.225; /* Max. investment per share */
private static final double MINVAL = 0.1; /* Min. investment per share */
private static double[] RET; /* Estimated return in investment */
private static int[] RISK; /* High-risk values among shares */
private static boolean[][] LOC; /* Geogr. region of shares */
private static boolean[][] SEC; /* Industry sector of shares */
private static String[] SHARES;
private static String[] REGIONS;
private static String[] TYPES;
/* Fraction of capital used per share */
private static Variable[] frac;
/* 1 if asset is in portfolio, 0 otherwise */
private static Variable[] buy;
private static void printProblemStatus(XpressProblem prob) {
System.out.println(String.format(
"Problem status:%n\tSolve status: %s%n\tLP status: %s%n\tMIP status: %s%n\tSol status: %s",
prob.attributes().getSolveStatus(), prob.attributes().getLPStatus(), prob.attributes().getMIPStatus(),
prob.attributes().getSolStatus()));
}
public static void main(String[] args) throws IOException {
readData();
try (XpressProblem prob = new XpressProblem()) {
// Output all messages.
prob.callbacks.addMessageCallback(DefaultMessageListener::console);
/**** VARIABLES ****/
frac = prob.addVariables(SHARES.length)
/* Fraction of capital used per share */
.withName(i -> String.format("frac_%s", i))
/* Upper bounds on the investment per share */
.withLB(i -> 0.0).withUB(i -> MAXVAL).toArray();
buy = prob.addVariables(SHARES.length).withName(i -> String.format("buy_%s", i)).withType(ColumnType.Binary)
.toArray();
/**** CONSTRAINTS ****/
/* Limit the percentage of high-risk values */
prob.addConstraint(sum(RISK.length, i -> frac[RISK[i]]).leq(MAXRISK).setName("Risk"));
/* Limits on geographical distribution */
prob.addConstraints(REGIONS.length,
r -> sum(range(0, SHARES.length).filter(s -> LOC[r][s]).mapToObj(v -> frac[v])).in(MINREG, MAXREG)
.setName("MinMaxReg_" + REGIONS[r]));
/* Diversification across industry sectors */
prob.addConstraints(TYPES.length,
t -> sum(range(0, SHARES.length).filter(s -> SEC[t][s]).mapToObj(v -> frac[v])).in(0.0, MAXSEC)
.setName("LimSec(" + TYPES[t] + ")"));
/* Spend all the capital */
prob.addConstraint(sum(frac).eq(1.0).setName("Cap"));
/* Limit the total number of assets */
prob.addConstraint(sum(buy).leq(MAXNUM).setName("MaxAssets"));
/* Linking the variables */
prob.addConstraints(SHARES.length,
i -> frac[i].geq(buy[i].mul(MINVAL)).setName(String.format("link_lb_%d", i)));
prob.addConstraints(SHARES.length,
i -> frac[i].leq(buy[i].mul(MAXVAL)).setName(String.format("link_ub_%d", i)));
/* Objective: maximize total return */
prob.setObjective(scalarProduct(frac, RET), XPRSenumerations.ObjSense.MAXIMIZE);
/* Solve */
prob.optimize();
/* Solution printing */
printProblemStatus(prob);
if (prob.attributes().getSolStatus() == XPRSenumerations.SolStatus.INFEASIBLE) {
System.out.println("MIP infeasible. Retrieving IIS.");
// Check there is at least one IIS
int status = prob.firstIIS(1);
if (status != 0)
throw new RuntimeException("firstIIS() failed with status " + status);
IISStatusInfo info = prob.IISStatus();
System.out.println(String.format(
"IIS has %d constraints and %d columns, %d infeasibilities with an infeasibility of %f%n",
info.rowsizes[1], info.colsizes[1], info.numinfeas[1], info.suminfeas[1]));
IIS data = prob.getIIS(1);
System.out.println("Variables in IIS:");
for (IISVariable v : data.getVariables()) {
// Note that the IISVariable class has more fields than
// we print here. See the reference documentation for
// details.
System.out.printf("\t%s %s%n", v.getVariable().getName(), v.getDomain());
}
System.out.println("Constraints in IIS:");
for (IISConstraint c : data.getConstraints()) {
// Note that the IISVariable class has more fields than
// we print here. See the reference documentation for
// details.
System.out.printf("\t%s%n", c.getConstraint().getName());
}
}
}
}
/**
* Read a list of strings. Iterates <code>tokens</code> until a semicolon is
* encountered or the iterator ends.
*
* @param tokens The token sequence to read.
* @return A stream of all tokens before the first semiconlon.
*/
private static <T> Stream<String> readStrings(Iterator<String> tokens) {
ArrayList<String> result = new ArrayList<String>();
while (tokens.hasNext()) {
String token = tokens.next();
if (token.equals(";"))
break;
result.add(token);
}
return result.stream();
}
/**
* Read a sparse table of booleans. Allocates a <code>nrow</code> by
* <code>ncol</code> boolean table and fills it by the sparse data from the
* token sequence. <code>tokens</code> is assumed to hold <code>nrow</code>
* sequences of indices, each of which is terminated by a semicolon. The indices
* in those vectors specify the <code>true</code> entries in the corresponding
* row of the table.
*
* @param tokens Token sequence.
* @param nrow Number of rows in the table.
* @param ncol Number of columns in the table.
* @return The boolean table.
*/
private static boolean[][] readBoolTable(Iterator<String> tokens, int nrow, int ncol) throws IOException {
boolean[][] tbl = new boolean[nrow][ncol];
for (int r = 0; r < nrow; r++) {
while (tokens.hasNext()) {
String token = tokens.next();
if (token.equals(";"))
break;
tbl[r][Integer.valueOf(token)] = true;
}
}
return tbl;
}
private static void readData() throws IOException {
// Convert the input file into a sequence of tokens that are
// separated by whitespace.
Iterator<String> tokens = Files.lines(new File(DATAFILE).toPath()).map(s -> Arrays.stream(s.split("\\s+")))
.flatMap(s -> s)
// Split semicolon off its token.
.map(s -> (s.length() > 0 && s.endsWith(";")) ? Stream.of(s.substring(0, s.length() - 1), ";")
: Stream.of(s))
.flatMap(s -> s)
// Remove empty tokens.
.filter(s -> s.length() > 0).iterator();
while (tokens.hasNext()) {
String token = tokens.next();
if (token.equals("SHARES:"))
SHARES = readStrings(tokens).toArray(String[]::new);
else if (token.equals("REGIONS:"))
REGIONS = readStrings(tokens).toArray(String[]::new);
else if (token.equals("TYPES:"))
TYPES = readStrings(tokens).toArray(String[]::new);
else if (token.equals("RISK:"))
RISK = readStrings(tokens).mapToInt(Integer::valueOf).toArray();
else if (token.equals("RET:"))
RET = readStrings(tokens).mapToDouble(Double::valueOf).toArray();
else if (token.equals("LOC:"))
LOC = readBoolTable(tokens, REGIONS.length, SHARES.length);
else if (token.equals("SEC:"))
SEC = readBoolTable(tokens, TYPES.length, SHARES.length);
}
}
}
|
| FolioQC.java |
// (c) 2023-2025 Fair Isaac Corporation
import static com.dashoptimization.objects.Utils.scalarProduct;
import static com.dashoptimization.objects.Utils.sum;
import static java.util.stream.IntStream.range;
import java.io.FileReader;
import java.io.IOException;
import java.io.StreamTokenizer;
import com.dashoptimization.DefaultMessageListener;
import com.dashoptimization.XPRSenumerations;
import com.dashoptimization.objects.QuadExpression;
import com.dashoptimization.objects.Variable;
import com.dashoptimization.objects.XpressProblem;
/**
* Modeling a small QCQP problem to perform portfolio optimization. -- Maximize
* return with limit on variance ---
*/
public class FolioQC {
/* Path to Data file */
private static final String DATAFILE = System.getenv().getOrDefault("EXAMPLE_DATA_DIR", "../../data")
+ "/foliocppqp.dat";
/* Max. allowed variance */
private static final double MAXVAR = 0.55;
/* Number of shares */
private static final int NSHARES = 10;
/* Number of North-American shares */
private static final int NNA = 4;
/* Estimated return in investment */
private static final double[] RET = new double[] { 5, 17, 26, 12, 8, 9, 7, 6, 31, 21 };
/* Shares issued in N.-America */
private static final int[] NA = new int[] { 0, 1, 2, 3 };
/* Variance/covariance matrix of estimated returns */
private static double[][] VAR;
private static void readData() throws IOException {
int s, t;
FileReader datafile = null;
StreamTokenizer st = null;
VAR = new double[NSHARES][NSHARES];
/* Read `VAR' data from file */
datafile = new FileReader(DATAFILE); /* Open the data file */
st = new StreamTokenizer(datafile); /* Initialize the stream tokenizer */
st.commentChar('!'); /* Use the character '!' for comments */
st.eolIsSignificant(true); /* Return end-of-line character */
st.parseNumbers(); /* Read numbers as numbers (not strings) */
for (s = 0; s < NSHARES; s++) {
do {
st.nextToken();
} while (st.ttype == StreamTokenizer.TT_EOL); /* Skip empty lines and comment lines */
for (t = 0; t < NSHARES; t++) {
if (st.ttype != StreamTokenizer.TT_NUMBER)
break;
VAR[s][t] = st.nval;
st.nextToken();
}
}
datafile.close();
}
private static void printProblemStatus(XpressProblem prob) {
System.out.println(String.format(
"Problem status:%n\tSolve status: %s%n\tLP status: %s%n\tMIP status: %s%n\tSol status: %s",
prob.attributes().getSolveStatus(), prob.attributes().getLPStatus(), prob.attributes().getMIPStatus(),
prob.attributes().getSolStatus()));
}
public static void main(String[] args) throws IOException {
readData();
try (XpressProblem prob = new XpressProblem()) {
// Output all messages.
prob.callbacks.addMessageCallback(DefaultMessageListener::console);
/**** VARIABLES ****/
Variable[] frac = prob.addVariables(NSHARES)
/* Fraction of capital used per share */
.withName(i -> String.format("frac_%d", i))
/* Upper bounds on the investment per share */
.withUB(0.3).toArray();
/**** CONSTRAINTS ****/
/* Limit variance */
QuadExpression variance = QuadExpression.create();
range(0, NSHARES).forEach(s -> range(0, NSHARES).forEach(
/* v * fs * ft */
t -> variance.addTerm(frac[s], frac[t], VAR[s][t])));
prob.addConstraint(variance.leq(MAXVAR).setName("Variance"));
/* Minimum amount of North-American values */
prob.addConstraint(sum(NNA, i -> frac[NA[i]]).geq(0.5).setName("NA"));
/* Spend all the capital */
prob.addConstraint(sum(frac).eq(1.0).setName("Cap"));
/* Objective: maximize total return */
prob.setObjective(scalarProduct(frac, RET), XPRSenumerations.ObjSense.MAXIMIZE);
/* Solve */
prob.optimize();
/* Solution printing */
printProblemStatus(prob);
System.out
.println("With of max variance of " + MAXVAR + " total return is " + prob.attributes().getObjVal());
double[] sol = prob.getSolution();
range(0, NSHARES).forEach(i -> System.out
.println(String.format("%s : %.2f%s", frac[i].getName(), 100.0 * frac[i].getValue(sol), "%")));
}
}
}
|
| FolioQP.java |
// (c) 2023-2025 Fair Isaac Corporation
import static com.dashoptimization.objects.Utils.scalarProduct;
import static com.dashoptimization.objects.Utils.sum;
import static java.util.stream.IntStream.range;
import java.io.FileReader;
import java.io.IOException;
import java.io.StreamTokenizer;
import com.dashoptimization.ColumnType;
import com.dashoptimization.DefaultMessageListener;
import com.dashoptimization.XPRSenumerations;
import com.dashoptimization.objects.QuadExpression;
import com.dashoptimization.objects.Variable;
import com.dashoptimization.objects.XpressProblem;
/**
* Modeling a small QP problem to perform portfolio optimization. -- 1. QP:
* minimize variance 2. MIQP: limited number of assets ---
*/
public class FolioQP {
/* Path to Data file */
private static final String DATAFILE = System.getenv().getOrDefault("EXAMPLE_DATA_DIR", "../../data")
+ "/foliocppqp.dat";
/* Target yield */
private static final int TARGET = 9;
/* Max. number of different assets */
private static final int MAXNUM = 4;
/* Number of shares */
private static final int NSHARES = 10;
/* Number of North-American shares */
private static final int NNA = 4;
/* Estimated return in investment */
private static final double[] RET = new double[] { 5, 17, 26, 12, 8, 9, 7, 6, 31, 21 };
/* Shares issued in N.-America */
private static final int[] NA = new int[] { 0, 1, 2, 3 };
/* Variance/covariance matrix of estimated returns */
private static double[][] VAR;
private static void readData() throws IOException {
int s, t;
FileReader datafile = null;
StreamTokenizer st = null;
VAR = new double[NSHARES][NSHARES];
/* Read `VAR' data from file */
datafile = new FileReader(DATAFILE); /* Open the data file */
st = new StreamTokenizer(datafile); /* Initialize the stream tokenizer */
st.commentChar('!'); /* Use the character '!' for comments */
st.eolIsSignificant(true); /* Return end-of-line character */
st.parseNumbers(); /* Read numbers as numbers (not strings) */
for (s = 0; s < NSHARES; s++) {
do {
st.nextToken();
} while (st.ttype == StreamTokenizer.TT_EOL); /* Skip empty lines and comment lines */
for (t = 0; t < NSHARES; t++) {
if (st.ttype != StreamTokenizer.TT_NUMBER)
break;
VAR[s][t] = st.nval;
st.nextToken();
}
}
datafile.close();
}
private static void printProblemStatus(XpressProblem prob) {
System.out.println(String.format("Problem status:%n\tSolve status: %s%n\tSol status: %s",
prob.attributes().getSolveStatus(), prob.attributes().getSolStatus()));
}
public static void main(String[] args) throws IOException {
readData();
try (XpressProblem prob = new XpressProblem()) {
// Output all messages.
prob.callbacks.addMessageCallback(DefaultMessageListener::console);
/***** First problem: unlimited number of assets *****/
/**** VARIABLES ****/
Variable[] frac = prob.addVariables(NSHARES)
/* Fraction of capital used per share */
.withName(i -> String.format("frac_%d", i))
/* Upper bounds on the investment per share */
.withUB(0.3).toArray();
/**** CONSTRAINTS ****/
/* Minimum amount of North-American values */
prob.addConstraint(sum(NNA, i -> frac[NA[i]]).geq(0.5).setName("NA"));
/* Spend all the capital */
prob.addConstraint(sum(frac).eq(1.0).setName("Cap"));
/* Target yield */
prob.addConstraint(scalarProduct(frac, RET).geq(TARGET).setName("TargetYield"));
/* Objective: minimize mean variance */
QuadExpression variance = QuadExpression.create();
range(0, NSHARES).forEach(s -> range(0, NSHARES).forEach(
/* v * fs * ft */
t -> variance.addTerm(frac[s], frac[t], VAR[s][t])));
prob.setObjective(variance, XPRSenumerations.ObjSense.MINIMIZE);
/* Solve */
prob.optimize();
/* Solution printing */
printProblemStatus(prob);
System.out.println("With a target of " + TARGET + " minimum variance is " + prob.attributes().getObjVal());
double[] sollp = prob.getSolution();
range(0, NSHARES).forEach(i -> System.out
.println(String.format("%s : %.2f%s", frac[i].getName(), 100.0 * frac[i].getValue(sollp), "%")));
/***** Second problem: limit total number of assets *****/
Variable[] buy = prob.addVariables(NSHARES)
/* Fraction of capital used per share */
.withName(i -> String.format("buy_%d", i)).withType(ColumnType.Binary).toArray();
/* Limit the total number of assets */
prob.addConstraint(sum(buy).leq(MAXNUM).setName("MaxAssets"));
/* Linking the variables */
/* frac .<= buy */
prob.addConstraints(NSHARES, i -> frac[i].leq(buy[i]).setName(String.format("link_%d", i)));
/* Solve */
prob.optimize();
/* Solution printing */
printProblemStatus(prob);
System.out.println("With a target of " + TARGET + " and at most " + MAXNUM + " assets, minimum variance is "
+ prob.attributes().getObjVal());
double[] solmip = prob.getSolution();
range(0, NSHARES).forEach(i -> System.out.println(String.format("%s : %.2f%s (%.1f)", frac[i].getName(),
100.0 * frac[i].getValue(solmip), "%", buy[i].getValue(solmip))));
}
}
}
|
© 2001-2025 Fair Isaac Corporation. All rights reserved. This documentation is the property of Fair Isaac Corporation (“FICO”). Receipt or possession of this documentation does not convey rights to disclose, reproduce, make derivative works, use, or allow others to use it except solely for internal evaluation purposes to determine whether to purchase a license to the software described in this documentation, or as otherwise set forth in a written software license agreement between you and FICO (or a FICO affiliate). Use of this documentation and the software described in it must conform strictly to the foregoing permitted uses, and no other use is permitted.